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} | s2 | Generation of Wheat Transcription Factor FOX Rice Lines and Systematic Screening for Salt and Osmotic Stress Tolerance
Transcription factors (TFs) play important roles in plant growth, development, and responses to environmental stress. In this study, we collected 1,455 full-length (FL) cDNAs of TFs, representing 45 families, from wheat and its relatives Triticum urartu, Aegilops speltoides, Aegilops tauschii, Triticum carthlicum, and Triticum aestivum. More than 15,000 T0 TF FOX (Full-length cDNA Over-eXpressing) rice lines were generated; of these, 10,496 lines set seeds. About 14.88% of the T0 plants showed obvious phenotypic changes. T1 lines (5,232 lines) were screened for salt and osmotic stress tolerance using 150 mM NaCl and 20% (v/v) PEG-4000, respectively. Among them, five lines (591, 746, 1647, 1812, and J4065) showed enhanced salt stress tolerance, five lines (591, 746, 898, 1078, and 1647) showed enhanced osmotic stress tolerance, and three lines (591, 746, and 1647) showed both salt and osmotic stress tolerance. Further analysis of the T-DNA flanking sequences showed that line 746 over-expressed TaEREB1, line 898 over-expressed TabZIPD, and lines 1812 and J4065 over-expressed TaOBF1a and TaOBF1b, respectively. The enhanced salt and osmotic stress tolerance of lines 898 and 1812 was confirmed by retransformation of the respective genes. Our results demonstrate that a heterologous FOX system may be used as an alternative genetic resource for the systematic functional analysis of the wheat genome.
Introduction
With a global output of 681 million tons in 2011, bread wheat (Triticum aestivum; AABBDD) accounts for 20% of the calories consumed by humans and is an important source of proteins, vitamins, and minerals [1]. Bread wheat is thought to have originated as a result of hybridization between the wild diploid grass Aegilops tauschii (DD) and the cultivated tetraploid wheat Triticum dicoccoides (AABB) [1]. The large size and complexity of the wheat genome have been substantial barriers to functional analyses of its genes. Recently, scientists published draft sequences of the AABBDD genome of the hexaploid wheat variety Chinese Spring (CS42) [1], the genome of the wheat A-genome progenitor Triticum urartu accession G1812, and the DD genome of Ae. tauschii accession AL8/78 [2,3]. The estimated relative genome sizes are about 17,4.94, and 4.36 gigabase pairs (Gb), respectively, and they contain an estimated 94,000-96,000, 34,879, and 43,150 genes [1][2][3]. These studies have also shown that more than half of the bread wheat genome is composed of transposable elements belonging to different families [2,3].
Considering the large size and complexity of the wheat genome and its recalcitrant nature to genetic transformation, systematic functional genomic analyses using EMS, irradiation, and T-DNA or transposon insertion mutants are unrealistic at present. A system for the identification of gene function by screening for transgenic plants ectopically expressing full-length (FL) cDNAs, named FOX hunting, was recently developed [4][5][6][7]. This system can be applied to almost any plant species without prior knowledge of its genome sequence because only FL cDNAs are required. Rice FOX hunting systems have been developed by transferring FL cDNAs into plants using Agrobacterium libraries [7][8][9]. Rice FOX Arabidopsis mutant lines have been demonstrated to be important materials for functional analyses of the rice genome [6,7,[10][11][12]. Because of the high level of synteny between the genomes of wheat and rice, heterologous over-expression of wheat FL cDNAs in rice may provide a fast and ideal approach for functional analyses of the wheat genome.
Transcription factors (TFs) play important roles in plant responses to environmental stress; they can activate the expression of stress-related genes and the synthesis of diverse functional proteins, leading to various physiological and biochemical responses [13]. Several TF genes have been implicated in the response of wheat to abiotic stresses, including TaBTF3, TabZIP60, TaMBF1, TaWRKYs, TaMYBs, and TaNACs [14][15][16][17]. Moreover, over-expression of the TF genes TaERF3 and TaNAC67 can enhance the tolerance of wheat to different stresses [18,19].
In this study, 1,455 FL cDNAs of TFs, belonging to 45 families, from bread wheat and its relatives were introduced and over-expressed in rice. About 15,000 T 0 plants were carefully examined for phenotypic changes, and 5,232 lines were screened for salt and osmotic stress tolerance. Seven TFs that function in stress tolerance were identified. Among them, the function of two putative salt and osmotic stress tolerance genes (TabZIPD and TaOBF1a) corresponding to lines 898 and 1812 were validated by retransformation.
The resulting fragments were separated by 1.0% agarose gel electrophoresis then cut from the gels according to size (<1 kb, 1-2 kb, and >2 kb in length) and purified using a MinElute PCR Purification Kit (Qiagen, Hilden, Germany). The collected TF FL cDNAs were divided into three groups according to their size for FOX library construction: I, <1 kb; II, 1-2 kb; and III, >2 kb.
Gateway expression vector construction
The binary vector pCUbi1390 was digested with SpeI then blunted with T4 DNA polymerase and ligated with the Gateway Vector Conversion System Reading Frame Cassette B (RfB) fragment (Invitrogen, Carlsbad, CA) to construct a binary destination vector. The ligation reactions were performed in 10 μl containing 1 μl of lined pCUbi1390 (10 ng), 1 μl of Cassette B (RfB) fragment (50 ng), 1 μl of T4 ligase buffer, and 1 μl of T4 ligase (Takara Bio Inc., Otsu, Japan) overnight at 16°C. Next, the ligation reaction was transformed into E. coli cells (http:// tools.invitrogen.com/content/sfs/manuals/gatewayvectorconversion_ccdbsurvival2_man.pdf). The plasmids of surviving clones were isolated and the direction of the RfB fragment was verified using restriction digests to obtain the binary destination vector pCUbi1390RfB.
Gateway LR Clonase II was used to catalyze the reaction of the entry vector pENTR Gus (https://tools.invitrogen.com/content/sfs/vectors/pentr_gus_map.pdf) with the destination vector pCUbi1390RfB to generate the expression vector pCUbiGus; pCUbiGus was then transformed into E. coli strain DH5α cells, and plasmid DNA was isolated using a Qiagen Plasmid Mini Kit. Transient GUS expression was assayed by the bombardment of rice calli and subsequent GUS staining as described previously [20].
Construction of a TF FL cDNA library in Agrobacterium
A TF FOX library was produced as described by Ichikawa et al. [4] except that the TF FL cDNAs were amplified before the Gateway reaction. TF FL cDNAs from wheat and its relatives were amplified using a high-fidelity DNA polymerase (KOD -Plus-; Toyobo Co. Ltd., Osaka, Japan) using the primers Enter-PF (5'-GGGGACAAGTTTGTACAAAAAAGCAGGCTAC CCTCACTAAAGGGAACAAAAG-3') and Enter-PR (5'-GGGGACCACTTTGTACAAGAA AGCTGGGTGACTCACTATAGGGCGAATT-3'; the underlining at the 5' end indicates the attB1 and attB2 sequences necessary for the Gateway BP reaction). The products were purified using a MinElute PCR Purification Kit (Qiagen) and then reacted with the donor vector pDONR/Zeo (https://tools.invitrogen.com/content/sfs/manuals/gateway_pdoner_vectors.pdf) using Gateway BP Clonase II (Invitrogen) to generate entry vectors. The reactions were transformed into E. coli DH5α cells by the heat shock method, and surviving clones were collected for isolation of the entry vector plasmid using a Qiagen Plasmid Mini Kit. The entry vector plasmid was reacted with the destination vector pCUbi1390RfB using Gateway LR Clonase II (Invitrogen) to generate the binary expression vector pCUbi1390FOX containing the TF FL cDNAs. The products of the LR reaction were transformed into E. coli strain DH5α. The surviving clones from each library were collected and plasmid DNA was isolated using a Qiagen Plasmid Mini Kit. The rescued plasmids were transformed into Agrobacterium tumefaciens strain AGL1 by electroporation at 2,000 clones per Petri dish (150 mm in diameter) on solid YEP medium containing 50 mg/L of kanamycin and 20 mg/L of rifampin according to the manufacturer's instructions (Gene Pulser Xcell; Bio-Rad, Hercules, CA). After 24 h of incubation at 27°C in the dark, 96 clones from each library were randomly selected to test the recombination efficiency and PCR amplification fidelity of the TF FL cDNAs. About 1 mL of a single clone-derived suspension was used for plasmid extraction and subjected to amplification by PCR and sequencing. The pCUbi1390FOX-specific primers flanking the cDNA insert (Test-PF [5'-GAATTCTAAGAGGAGTCCACCATG-3'] and Test-PR [5'-GAAATTCGAGCTGGTC ACCTG-3']) were used for amplification. The remaining Agrobacterium clones from each plate were collected and combined in 50 mL of AAM medium containing 50 mg/L of kanamycin and 20 mg/L of rifampin and cultured at 27°C in the dark until the OD 600 reached 0.5-0.6 [21]. A total of 1 mL of Agrobacterium cells was used for plasmid extraction and PCR amplification to test for the representation of specific wheat TF FL cDNAs using gene-specific primers. The remaining Agrobacterium cell suspensions were used for rice callus transformation.
Generation and characterization of wheat TF FOX rice lines
The Japonica rice cultivar Nipponbare was used in this study. Rice transformation and transformant verification were carried out using a well-established protocol [22]. In brief, calli derived from mature seeds were inoculated with A. tumefaciens strain AGL1 carrying the binary vector pCUbi1390FOX with TF FL cDNAs from wheat and its relatives as described previously. After two rounds of selection and pre-differentiation culture, hygromycin-resistant calli were transferred to differentiation medium. Regenerated plants were verified by PCR using HPT (hygromycin resistance gene)-specific primers (HPT-F [5'-AAGTTCGACAGCGTC TCCGAC-3'] and HPT-R [5'-TCTACACAGCCATCGGTCCAG-3']) and the pCUbi1390FOX Test primers described above.
To further identify the stress tolerance function of the TFs over-expressed in lines 898 and 1812, over-expression vectors for the specific TF FL cDNAs were retransformed into rice. The two over-expression vector clones were obtained by screening of the FOX Agrobacterium plates using PCR with the corresponding specific primers (lines 898 and 1812) listed in Table 2.
T 0 plants that were about 15 cm tall were transferred to an experimental paddy field designed specifically for transgenic plants during a suitable planting season (with 15 cm between plants and 30 cm between rows). At least 20 T 1 seeds were germinated during the proper season in a greenhouse, transferred, and planted in the paddy field as described previously [23]. Mutants with visible phenotypic changes were scored and marked for further analysis. The remaining seeds were dried to a water content of 5.0-6.0% and stored in vacuumsealed aluminum foil bags at 4°C.
DNA extraction and PCR amplification of FL cDNA inserts from the FOX lines
Young leaves (approximately 500 mg per line) from 100 randomly selected T 0 lines were collected for DNA extraction using the modified CTAB method [24]. DNA samples were quantified using a DU 800 Spectrophotometer (Beckman, Fullerton, CA) and verified by gel electrophoresis. PCR amplification was carried out using Takara PCR mix (Takara Bio Inc.; http://www.takara.com.cn) with the pCUbi1390RfB Test primers described above.
Southern blot analysis of the FL cDNA copy number in the transgenic rice plants
Approximately 40 μg of genomic DNA from each line was digested with EcoRI and separated on a 0.8% agarose gel. Following electrophoresis, the fragments were blotted onto a nylon membrane (Hybond-N+; Amersham Pharmacia Biotech, Piscataway, NJ) using standard methods. Subsequent DNA hybridization and immunological detection were performed using a DIG High Prime DNA Labeling and Detection Starter Kit II (Roche, Basel, Switzerland) according to the manufacturer's protocol. The primers used for labeling were HPT-specific primers (described above). Because HPT was located outside the EcoRI cutting region in pCU-bi1390RfB, the number of hybridized bands reflects the T-DNA insertion copy number, which indicates the wheat FL cDNA copy number in the transgenic rice plants.
Systematic screening for salt and osmotic stress-tolerant plants
Screening for salt and osmotic stress-tolerant plants was carried out as described by Huang et al. [25] with the following modifications. T 1 seeds from Nipponbare carrying empty vector (CK) and the FOX lines were kept for at least 1 week at 42°C to break any possible dormancy, soaked in water at room temperature for 3 days, and then germinated for 1 day at 37°C. About 40 uniformly germinated seedlings were sown in a 96-well plate from which the bottom had been removed. The plate was floated on water for 1 day at 37°C in the dark to promote root growth then transferred to a growth chamber under a 13-h light (24°C)/11-h dark (20°C) photoperiod. Five days later, the seedlings were cultured with Yoshida's culture solution. For salt or osmotic stress treatment, 15-day-old seedlings were transferred to a culture solution containing 150 mM NaCl or 20% (w/v) PEG-4000 (to simulate drought stress), respectively. Putative stress-tolerant lines obtained in the first round of screening were subjected to an additional two rounds of screening.
Semi-quantitative RT-PCR analysis
Total RNA from wild-type and stress-tolerant FOX plants (both roots and shoots were included) was isolated using Trizol reagent (Invitrogen) and reverse-transcribed using a Fas-tQuant RT Kit (with gDNase; Tiangen Biotech, Beijing, China). The RNA was quantified using a UV spectrophotometer (DU 800; Beckman). First-strand cDNA was synthesized by reverse transcription using a cDNA synthesis kit (Takara Bio Inc.; http://www.takara.com.cn) in 20 μl containing 1 μg of total RNA, 10 ng of oligo(dT) 14 primer, 2.5 mM dNTPs, 1 μl of AMV, and 0.5 μl of RNAsin. PCR was performed in a 20-μl volume containing a 1/20 aliquot of the cDNA reaction, 0.5 μM gene-specific primers, 10 mM dNTPs, 1 U of rTaq DNA polymerase, and 2 μl of 10× reaction buffer. The reaction protocol was as follows: denaturation at 94°C for 3 min followed by 25 cycles of 94°C for 30 s, 60°C for 45 s, and 72°C for 1 min, with a final step at 72°C for 10 min. A 1-μl aliquot of the reaction was loaded on a 1.0% agarose gel (regular; BioWest, Castropol, Spain) and analyzed by electrophoresis. The PCR products were extracted using a gel extraction kit (Qiagen) after gel analysis and sequenced with the original PCR primers to verify that the products were correct. Semi-quantitative RT-PCR was used to analyze the expression of putative salt and osmotic stress tolerance-related genes in the FOX lines. OsAC-TIN1 was used as an internal control to normalize the data (using the primers ActinF [5'-TGTATGCCAGTGGTCGTACCA-3'] and ActinR [5'-CCAGCAAGGTCGAGACGAA-3']). The gene-specific primers used for RT-PCR are listed in Table 2.
Efficiency of Agrobacterium FOX vector construction
To test the efficiency of the Gateway system for constructing over-expression libraries, we assayed for transient GUS expression 24 and 72 h after bombardment. As shown in S1 Fig, among 119 (24 h) and 163 (72 h) randomly selected pieces of callus, 73 (24 h) and 102 (72 h) were stained dark blue, respectively, whereas no positive staining was observed in any of the 259 calli bombarded with the control vector (without the GUS gene). These results indicate that the binary destination vector, pCUbi1390FOX, and the Gateway system worked well for the construction of wheat TF FOX vectors. The TF FL cDNAs were divided into three groups according to their size: I, <1 kb; II, 1-2 kb; and III, >2 kb. FOX libraries were successfully constructed using the Gateway system. PCR amplification showed that more than 95% of the Agrobacterium clones carried cDNAs of the expected size in all of the sub-libraries (Fig 1). Sequencing of twelve plasmids (four from each sub-library) confirmed that the PCR products used for construction of the FOX library exhibited high fidelity (data not shown).
Eleven genes of different sizes from GenBank were selected to test for the representation of specific genes in the wheat TF Agrobacterium libraries. Gene-specific primers were used to screen the libraries (Table 3). For most of the genes tested, PCR products were produced from a pool of 2,000 clones. In only one case, a gene was not amplified from a pool of 2,000 clones but was successfully amplified from a pool of 4,000 clones (Table 3). These data indicate that the Agrobacterium libraries were of sufficient quality for use in rice transformation. Generation and characterization of the FOX rice plants More than 15,000 T 0 plants were obtained and grown in a paddy field designed specifically for transgenic plants, and 10,496 plants successfully set seeds. Phenotyping was carefully carried out, and plants with visible phenotypic changes in the T 0 generation were marked and harvested separately. Among the 10,496 T 0 plants, 1,562 (14.88%) showed obvious phenotypic changes, including changes in plant height, fertility and flowering time, leaf morphology and color, tiller number, and grain shape and size (Fig 2). About 100 T 0 plants with obvious phenotypic changes were selected for Southern blot analysis and PCR amplification. As shown in Fig 3, about 31.8% of the plants carried a single copy of the T-DNA, 31.8% carried two copies of the T-DNA, and about 36.4% carried 3-5 copies. The average T-DNA copy number was 1.95 per line, according to a statistical analysis of our Southern blot results (data not shown). PCR amplification and sequencing showed that only one PCR product could be amplified from about 57% of the lines, and 23% of the lines had two or more different T-DNA inserts (Fig 4; S2 and S3 Tables.).
Systematic screening for salt and osmotic stress-tolerant FOX rice lines
To verify the feasibility of this system, we screened for stress-related wheat TFs from among our TF FOX rice lines. For salt or osmotic stress tolerance screening, T 1 plants of 5,232 FOX lines were systematically treated with liquid Yoshida's culture medium supplemented with 150 mM NaCl or 20% PEG-4000, respectively. More than 100 putative stress-tolerant lines were obtained in the first round of screening. A total of 15 lines were identified in the second round of screening from these putative stress-tolerant lines, and 7 stress-tolerant lines were verified in the third round of screening. Of the seven lines, five (591, 746, 1647, 1812, and J4065) were tolerant to NaCl stress, five (591, 746, 898, 1078, and 1647) were tolerant to osmotic stress, and three (591, 746, and 1647) were tolerant to both NaCl and osmotic stress (Figs 5 and 6). The wheat TF FL cDNAs in the respective lines were amplified, and the PCR products were sequenced (Table 2 and S4 Table). Sequencing revealed that line 746 over-expressed TaEREB1, line 898 over-expressed TabZIPD, and lines 1812 and J4065 over-expressed TaOBF1a and TaOBF1b, respectively (Table 2). RT-PCR showed that a specific gene was expressed in the respective stress-tolerant plants but not in stress-sensitive wild-type plants (Fig 7).
To further verify the stress tolerance function of the TFs, two lines (898 and 1812) with a single T-DNA insertion were selected for retransformation based on our Southern blot results (data not shown). As shown in Fig 8, the stress tolerance observed in lines 898 (osmotic) and 1812 (NaCl) was confirmed by retransformation of the respective genes (TaZIPD and TaOBF1a) and screening of the Agrobacterium library using primers specific for lines 898 and 1812, as described in Table 2.
Discussion
The most direct approach for dissecting gene function is to characterize the phenotypic changes in specific gene mutants. Rice has become a model plant for genetic research in monocots because of its small genome size (466 megabases), publicly available genome sequence, saturated mutant populations with different characters, adequate number of molecular markers, segregating populations for gene mapping, and an efficient transformation system using A. tumefaciens [21,26,27]. In contrast, for wheat, there is currently no efficient system for studying gene function because of its large and complex genome, redundancy of gene families, and its recalcitrant nature to genetic transformation.
FOX gene hunting enables the systematic dissection of gene function without knowing the complete genome sequence of the organism of interest. Rice and Arabidopsis FOX systems have been established, and over-expression lines have been successfully used for systematic phenomic characterization and gene function validation. The heterologous rice FOX Arabidopsis system has also been confirmed to be an efficient tool for analyses of gene function. The heterologous FOX system can be used to analyze the function of genes from any plant species, regardless of the availability of genome sequence information, gene redundancy, and the ability of the species to be transformed. FL cDNAs and over-expression constructs can be obtained using routine molecular biological techniques and transferred to host plants such as Arabidopsis and rice [4,28,29]. Moreover, the dominant nature of FOX lines is an advantage for the characterization of conditional phenotypes (e.g., stress responses).
Wheat is an important staple crop with a genome size of about 17 Gb and 94,000-96,000 genes. Most of the bread wheat genome is composed of retroelements and several classes of plant DNA transposons [1]. Gene loss in wheat may be rapid; most functional classes show equal gene loss in the three genomes, but TF families show a clear tendency to be retained as functional genes. These genes may maintain transcriptional networks in each genome and contribute to non-additive gene expression and genome plasticity [1]. More than 1,000 TFs are present in each genome (1,489 members belonging to 56 families exist in Ae. tauschii), and these TFs play important roles in plant growth, development, and defense [2]. In the present study, a wheat TF FOX rice system was established. In total, 10,496 rice lines transgenic for 1,455 wheat TF FL cDNAs driven by the maize ubiquitin promoter were generated.
Among these 10,496 T 0 plants, 1,562 (14.88%) showed obvious phenotypic changes, including changes in plant height, fertility and flowering time, leaf morphology and color, tiller number, and grain shape and size (condition-dependent traits such as stress tolerance were excluded). The toxic and even lethal effects of high and constitutive expression, especially for TF genes in host cells, may be considered a disadvantage of the FOX system. Constitutive overexpression of the TaDREB3 gene in barley leads to a stunted phenotype in addition to improved frost tolerance [30]. Thus, stress-inducible promoters may be preferable for use in FOX vector construction [31].
In the wheat FOX rice lines described in this study, multiple insertions existed in a single transgenic line. As shown in Fig 3, about 68% of the lines tested had multiple copies of cDNA integrated into the genome (the average copy number was 1.95 based on a statistical analysis of our Southern blot results). However, PCR amplification produced only one band in about 57% of the lines tested. That only one product was amplified in most FOX lines may be due to the insertion of T-DNAs carrying the same cDNA into different sites of the rice genome, or the preferable amplification of a specific cDNA when different cDNAs coexisted in a single line. The GC content of a genome also has strong effects on the amplification efficiency of target cDNAs, and the wheat genome possesses a high GC content and/or secondary structure [1,5]. Overall, about 20% of the lines did not produce a band by PCR (Fig 4). The coexistence of multiple cDNAs in a single line increases the complexity of phenotype-genotype co-segregation analyses. This problem could be solved by using the T 1 population, in which cDNAs will have segregated from each other. In addition, the number of wheat TFs used to construct the FOX libraries and the number of lines screened for abiotic stress tolerance were limited in this study. Indeed, 1,489 TFs belonging to 56 families have been identified in the D genome of Ae. tauschii, and the overall number of TFs in the A, B, and D genomes of common wheat is estimated to be >4,000 [2].
In this study, seven lines over-expressing different TFs were identified through stress screening. Most of them were related with or identified as reported stress-related TFs ( Table 2). TaEREB1 belongs to the APETALA2/Ethylene-Responsive Element Binding Protein (AP2/ EERBP) TF superfamily, which includes APETALA2/Ethylene-Responsive Factor (AP2/ERF) TFs; these proteins activate the cis-elements present in the promoters of stress-inducible genes [32]. The AP2/EREBP superfamily is composed of the AP2, ERF, and RAV families, and the ERF family includes the ERF and CBF/DREB subfamilies. The CBF/DREB subfamily is reportedly involved in plant responses to abiotic stress (e.g., water deficit) [33,34]. TaOBF1 (lines 1812 and J4065) is a bZIP TF and the wheat homolog of rice OBF1 [35]; it has been reported to interact with a wheat lip19 homolog (Wlip19) to convey abiotic stress tolerance in common wheat [35]. The cDNA sequence of the TF in line 898 had 94% identity with the cDNA sequence of TabZIPD and 88% identity with the cDNA sequence of LeABF6, a Lophopyrum elongatum stress-related bZIP TF that has been found to enhance the drought and salt tolerance of transgenic tobacco (unpublished data from the NCBI). These results indicate that the heterologous FOX system described in this paper could be an important alternative genetic resource for the systematic functional analysis of wheat TFs.
Supporting Information S1 Table. Characteristics of nine full-length cDNA libraries from wheat and its relatives. | v3-fos |
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} | s2 | Data in support of proteomic and comparative genomic analysis reveal adaptability of Brassica napus to phosphorus-deficient stress
This data article contains data related to the research article titled proteomic and comparative genomic analysis reveal adaptability of Brassica napus to phosphorus-deficient stress [1]. Proteome alterations of roots and leaves in two B. napus contrasting genotypes, P-efficient ‘Eyou Changjia’ and P-inefficient ‘B104-2’, under long-term low phosphorus (P) and short-term P-free starvation was investigated, and then comparative gnomic analysis was conducted to interpret the interrelation of the differential abundance protein species responding to P deficiency with quantitative trait loci (QTLs) for P deficiency tolerance. The report concluded with the results that nearly 50% of the identified protein species was mapped in the confidence intervals of QTLs for P efficiency related traits. The tables presented here represented the detail information of protein spots detected, as well as protein species identified.
Subject area
Biology More specific subject area
Plant proteomics
Type of data Tables How data was Total protein was extracted from roots and leaves of 'Eyou Changjia' and 'B104-2', respectively. 2-DE was performed to discover protein spots with abundance altered at least 7 2-fold (T-test Po 0.05).
Data source location N/A Data accessibility
Data is provided in Supplementary materials directly with this article
Value of the data
The data further validate the information presented in Chen et al. [1].
The data provide the detail information of spots detection.
The data provide the detail information of identified protein species.
Experimental design
Two Brassica napus genotype under two kinds of P treatments, long-term low P stress and shortterm P-free starvation, were conducted, and three time points were used in each P treatment. Total protein was extracted from roots or leaves respectively of two B. napus by triplicate. 2-DE images were generated and compared to gain spots with abundance altered at least 72-fold (T-test p o0.05). Then protein spots were identified by MALDI-TOF MS.
Plant materials and growth conditions
P-efficient 'Eyou Changjia' and P-inefficient 'B104-2' that used in the present study were selected from 194 rapeseed (B. napus) cultivars by Duan et al. [2]. Seeds were surface sterilized with 10% (w/v) sodium hypochlorite for 5 min and then washed 3 times in deionized water (dH 2 O). The surfacesterilized seeds were germinated on moistened gauze until root length about 2 cm. For long-term low P stress experiment, half of the seedlings were grown in a nutrient solution containing 1.4 mM Na 2 HPO 4 and 3.6 mM NaH 2 PO 4 (LP, 5 mM P) for 18 days after transplanting, then the seedlings were shifted to nutrient solution containing 36 mM Na 2 HPO 4 and 144 mM NaH 2 PO 4 (HP, 200 mM P) for additional 2 to 5 days. The remaining seedlings were grown in HP solution, which was used as the control. In addition to the P, the basal complete nutrient solution contained: 0.24 g/L NH 4 NO 3 , 0.50 g/L MgSO 4 , 0.15 g/L KCl, 0.36 g/L CaCl 2 , 0.05 mM EDTA-Fe and Arnon microelement solution [3]. Roots and leaves of both genotypes were harvested separately on the 18th, 20th and 23rd day after transplanting, which were marked as 18, 18 þR2 and 18 þR5, respectively. For short-term P-free starvation, all of the seedlings were grown under þP (200 mM P) for 15 days, then half the seedlings were shifted to the P-free solution ( À P, 0 mM P) and the remaining seedlings were maintained under þP conditions as the control. The roots and leaves were harvested at 0, 1, 3 and 5 days after the P was removed. For proteomic analysis, the 1st and 2nd euphylla next to the cotyledon from three seedlings were collected as one leaf sample, and the corresponding three roots of the seedling were collected as one root sample. Each sample was replicated biologically three times ( Supplementary Fig. S3). Seedlings were grown in an illuminated culture room (300-320 μmol/m 2 /s, 24 1C day/22 1C night, 16 h photoperiod). The nutrient solution was refreshed every 5 days, which was supplied initially with 1/4 full-strength nutrient solution, then 1/2 and full-strength in turn. After the fresh weights were measured, both root and leaf samples were immediately chilled in liquid nitrogen and stored at À80 1C for further using.
Extraction and quantification of total protein
The root protein was extracted as described in our previous study [4]. And the leaf protein was extracted using TCA/acetone method as described by Wang et al. [5]. The proteins (control and treated) were extracted from three independent biological replicates, respectively. Then each biological replicate was used as an independent sample for protein content determination using Bradford method [6] with series of concentration gradient of BSA as a standard before 2-DE, in which 2 mL and 4 mL of the extracted protein solutions were used, respectively. And the protein yield was calculated for each sample (Table S2).
2-DE and images analysis
For 2-DE, 17 cm IPG strip (Bio-Rad, USA) with liner gradient pH range (pH 5-8) was selected. For each strip 1000 mg root protein or 1500 mg leaf protein extracts were loaded to each IPG strip in first dimension, and then 12% polyacrylamide gels were used in the second dimension as previously described [4]. The gels were stained by coomassie brilliant blue and scanned using a GS-800 densitometer (Bio-Rad, USA), then the image analysis software PDQuest 8.0 (Bio-Rad, USA) were used for spots detecting. Local regression method (LOESS) normalization was selected to correct the differences between the gels. Spots abundance showing at least two-fold alteration and the P o0.05 based on Student's T-test were considered as DAPs. Qualitative difference and quantitative differences were showed in Supplementary Table S2.
MALDI-TOF/TOF MS and protein identification
The selected spots were manually excised from the gels. After alkylated and reduced, the trypsindigested protein spots were automatically transferred to MALDI-TOF/TOF analyzer (Applied Biosystems, USA). Both the MS and MS/MS data were submitted to Mascot (Version 2.2, Mtrix Science Ltd, London, UK) for protein species identification. The search results were evaluated by protein score confidence interval (C.I.%) calculated in GPS Explorer software (Applied Biosystems), which is based on the MASCOT score. Only those identified protein species with a C.I.%499% were accepted (Table S1) [1]. | v3-fos |
2022-11-19T15:23:37.331Z | {
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} | s2 | Common genetic basis for canopy temperature depression under heat and drought stress associated with optimized root distribution in bread wheat
QTL related to cooler canopy temperatures are associated with optimal root distribution whereby roots proliferate at depth under drought or near to surface under hot, irrigated conditions. Previous research using a bread wheat RIL population of the Seri/Babax cross showed that common QTL were associated with cooler canopies under both drought and heat-stressed conditions. A subset of RIL was grown under water-limited and hot-irrigated field environments to test how cooler canopies are related to root development. Eight sisters and the two parents were used in the study with genotypes grouped as COOL or HOT according to their respective QTL for canopy temperature and previous phenotypic data. Root mass production and residual available soil moisture were measured around anthesis at four depth profiles (from 0 to 120 cm depth). When considering different root profiles, there was a clear interaction of QTL with environment. Under water stress, the COOL genotypes showed a deeper root system allowing the extraction of 35 % more water from the 30–90 cm soil profile. The strategy under heat was to concentrate more roots at the surface, in the 0–60 cm soil layer where water was more available from surface irrigation. Since COOL genotypes showed better agronomic performance, it can be concluded that their QTL are associated with more optimal root distribution in accordance with water availability under the respective stresses. The study demonstrates the importance of root development under both water-limited and hot-irrigated environments, and shows a common genetic basis for adaptation to both stresses that appears to be associated with sensitivity of roots to proliferate where water is available in the soil profile.
Introduction
While the focus of most research in plants is on the above ground organs, the radicular system represents a high proportion of the total plant's mass and energy requirement. Nonetheless, a comprehensive understanding of root mechanisms involved in, for example, drought and heat response, are imperative to the effort of increasing adaptation of crops to harsher environments under climate change. Roots have a range of functions including anchorage, mechanical support, nutrient and water uptake, and signaling. Roots are also extremely sensitive to water deficit and high temperatures; for example, they show a narrow range of optimum growth temperature compared to other organs (Porter and Gawith 1999).
Under high temperature field experiments, root growth was observed to be diminished due to a reduction in the carbon partitioned below ground, and the number, length and diameter of roots are especially affected if the heat occurs during the reproductive stage (Batts et al. 1998). Drought has different effects depending on the severity. If a moderate drought occurs root development can be promoted because an increased amount of carbon assimilates is sent to the roots; primary root development is increased while lateral roots are repressed (Smith and De Smet 2012). Under drought, high concentrations of 1 3 ABA can be detected in the roots which have been linked to plant signaling, resulting in stomatal closure and even seed abortion (Prasad et al. 2008). Drought and heat stress symptoms above ground -such as smaller organs and tissue chlorosis-are relatively easy to detect. Nonetheless, relatively few studies have considered the role roots play in stress response mainly because precise, well-controlled, field experimental procedures are not straightforward. As a result many researchers opt for studies in controlled environments where rooting volume and temperatures are generally poorly representative of field growing conditions (Anderson 1986). Molecular control of root development has been studied in Arabidopsis (Larkindale et al. 2005) but in cereals relatively little is known. In maize and rice, mutants have been used to study the lateral root development and crown root elongation. The proteomics of the roots of two Agrostis grass species exposed to moderated (30 °C) and intense (40 °C) heat stress were studied by Xu and Huang (2008) showing more proteins associated with stress response mechanisms were up-regulated in the thermotolerant species.
In the field, it has been shown that bread wheat genotypes that invest significant resources in deep root development are capable of extracting residual moisture when drought stress occurs Lopes and Reynolds 2010). Under heat stress, well-watered plants increase their transpiration rate due to high vapor pressure deficit which permits evaporative canopy cooling. To match evaporative demand requires increased stomatal conductance (Amani et al. 1996) and adequate vascular capacity including in the roots. Some traits can be used as surrogates for the analysis of root development, for example, the measurement of the canopy temperature. Cool canopy temperatures have been associated with increased plant access to water as a result of deeper roots (Lopes and Reynolds 2010). These authors found that genotypes with cooler canopy temperatures reported 30 % more yield associated with an increase of 40 % in root dry weight at 60-120 cm. Genomic regions (QTL) associated with canopy temperature have been co-located with regions controlling other drought adaptive traits including kernel number, grain yield and chlorophyll content (Pinto et al. 2010;Diab et al. 2008;Olivares-Villegas et al. 2008). In a previous study, Pinto et al. (2010) identified 15 QTL for canopy temperature (CT) in the Seri/Babax bread wheat population grown under drought, hot-irrigated and non-stressed conditions. The authors demonstrated five consistent QTL (1Ba, 2Ba, 3Bb, 4Aa, 7Aa) associated with cooler canopies that were common to both drought and heat environments. Three of the QTL were specific only for drought and heat stress, and the other two were also found under non-stressed conditions. The five QTL for CT explained an average of 7 and 14 % of variance under drought and heat, respectively, with maximum of 27.6 % under the heat environment in the 4A-a linkage group. On the same linkage group, a QTL explained a maximum of 27.4 and 17.1 % of yield variation under drought and heat, respectively. The involvement of roots was inferred since cooler canopies are a result of higher transpiration rates which require adequate access to water. For the current study, lines showing contrast in these five QTL for CT were used for the selection of the sisters together with phenotypic data for CT and yield. These five QTL overlapped with QTL for traits previously associated with drought and heat tolerance including water soluble carbohydrates (WSC), kernel number, yield and plant greenness (Kuchel et al. 2007;Marza et al. 2006;Rebetzke et al. 2008).
The importance of roots in determining yield under stressed environments was highlighted by the recent release of rice varieties with improved performance under drought as a result of deep root development achieved through MAS for QTL associated with root length (Steele et al. 2006). The five QTL used in the current study are regions reported in the literature to be associated with root-related traits. A number of QTL for early root length have been mapped in the 1B region of wheat and in its homoeologous region in rice, both crops grown in hydroponic culture (Price and Tomos 1997;Ren et al. 2012). Chromosome 2 was found to be associated with one or more architectural characteristics of seminal roots of durum wheat grown in gel chamber, including length, number and thickness (Sanguineti et al. 2007) and up to 68 % of variance for root length of bread wheat was explained by a QTL identified in this region (Ren et al. 2012). Also, in field grown rice a QTL located in the homoeologous chromosome (Chromosome 8, Ahn et al. 1993) to 2B explained more than 30 % of variance for root thickness under drought stress (Champoux et al. 1995). It seems that the 2B chromosome might contain genes for evapotranspiration efficiency since wheat experiments in pots under controlled conditions (Ehdaie and Waines 1997) showed several QTL in the long arm of the chromosome 2B of bread wheat associated with biomass production-including roots, shoots and spikes. Similarly, chromosomes 3 and 7 of wheat are associated with deep root development and root thickness and Champoux et al. (1995) report QTL in homoeologous regions of rice controlling these traits under field drought-stressed conditions. Up 30 % of the root length variance (Price and Tomos 1997) was explained by a QTL located in chromosome 11 of rice that was hydroponically grown, which maps with segments of chromosomes 4, 5 and 7 of wheat where QTL for CT, NDVI, yield and grain number were previously mapped in field experiments with the Seri/Babax population (Pinto et al. 2010). The genomic region of chromosome 7 seems to contain several genes associated with drought tolerance in wheat, rice and barley where QTL have been identified for osmotic adjustment 1 3 and related traits in wheat (Morgan and Tan 1996) and it homoeologues in rice (Zhang et al. 2001;Lilley et al. 1996) and barley (Teulat et al. 1998). Using the subset of sisters grouped according to their phenotype and genotypic data in COOL and HOT canopies, the current study was established with the following objectives: (i) to characterize a subset of contrasting Seri/Babax sisters in their agronomic and physiological performance when grown under drought and heat stresses, (ii) to verify the potential of the previously identified QTL in marker assisted selection, and (iii) to test the hypothesis that optimal root distribution provides a common physiological response for adaptation under both drought and heat stress.
Germplasm
The recombinant inbred lines used in this study came from the cross of parents, Seri M82 and Babax (also named Baviacora M 92 or Bav 92), both spring wheat (Triticum aestivum L.) semi-dwarf lines with moderate tolerance to drought and heat stress (Olivares-Villegas et al. 2007) and high-yield potential. Only Seri M82 carries the T1BL.1RS (rye) translocation from Kavkaz (Villarreal et al. 1998). The population was constructed for mapping of complex traits and therefore shows a relatively narrow range in phenology and height which is useful to avoid the confounding effect of major flowering and Rht genes (Pinto et al. 2010). Ten genotypes were included in this study and classified in two groups: COOL and HOT. The list of eight sisters and two parents is presented on Table 1, including their group (COOL/HOT) and the CT QTL used for the classification.
The HOT genotypes generally carried the Seri allele on those regions where any of the five QTL for CT was identified. The allele from Seri accounted for the undesirable expression of high CT and decreased yield (Pinto et al. 2010). In contrast, the COOL genotypes generally carried the Babax allele on the selected QTL for CT, allele responsible for lower canopy temperatures and high yields. For the QTL × E analyses a factorial design was applied using SAS Proc Mixed. Table 2. Drought trials received approximately 200 ≤ 300 mm of water during the whole cycle, including irrigations and precipitation. Genotypes were sown in November and most water was received before the booting stage. Subsequently, there was moderate drought stress during booting/heading and gradually intensifying stress during grainfilling. To establish the heat experiments, the sowing date was delayed by approximately, 3 months. The air temperature became higher as the cycle progressed, reaching average daily maxima of nearly 37 °C during grainfilling. The heat-stressed trials were fully irrigated every 2 weeks to minimize water limitations that could confound the results. Additionally, the sisters were sown during 2 years under high yielding conditions with minimal water and temperature limitations as control trials. Pest and diseases were controlled during the season in all the experiments. The four trials were established in a complete randomized block design with four replications. Each experiment consisted of ten genotypes sown in double raised beds of 3.5 × 0.8 m using a seed density of 13 g/m 2 . The soil at the Yaqui Valley is classified as sandy-clay and hyposodic vertisol, smectitic chromic haplotorrert according to the World Reference Base (Verhulst et al. 2009). Table 1 List of eight sisters and the two parents (Genotypes 9 and 10) selected from the Seri/Babax bread wheat population for their contrasting phenotypic and genotypic performance under drought and heat stress a Indicates the linkage group where the QTL for CT was identified by Pinto et al. (2010) Genotype Cross Selection History Group QTL for which was selected a
Description of the environments and experiments
Measurements Agronomic and physiological measurements were performed on all ten genotypes sown in each environment. For the residual available soil moisture (RASM) and root biomass analyses at heading stage, a subset of four genotypes were selected, two of them COOL and two HOT. Only genotypes number three, four, five and six (Table 1) were included in the root and soil analyses. Traits recorded in the complete pool of genotypes were: yield (g/m 2 ), aboveground biomass at maturity (g/m 2 ), stem number at anthesis and maturity (stems/m 2 ), phenology, water soluble carbohydrates content in the stems at heading ±7 days (%) and canopy temperature during grainfilling (CTg) and vegetative stage (CTv). These measurements were performed using standard protocols cited by Reynolds et al. (2007). Days to heading and days to maturity were determined when 50 % of the plot exhibited 50 % of the spike (Zadoks 5.5) and when 50 % of the plot lost greenness, respectively. For the residual available soil moisture and root biomass analyses, an hydraulic soil corer (Giddings Corp. Co., Fort Collins, CO, USA) as cited by Lopes and Reynolds et al. (2010) was used to extract the soil sample from 0 to 120 cm depth. Sampling was done exactly above the row of plants to obtain soil and root biomass. Soil sampling was performed at heading time plus 10 days (±2 days). On each plot two and four points were sampled in the 2009 and 2011 seasons, respectively. Soil samples were separated into four depth profiles: 0-30, 30-60, 60-90 and 90-120 cm using plastic bags to avoid soil moisture losses before weighing. In the same plot the two/four subsamples were bulked in a single plastic bag according to the corresponding profile. Samples were kept in the field in a cool box. At the research station, the soil was mixed, then, a weighed sample about 100 g (fresh weight) was dried in the oven at 75 °C for 24 h to determine residual soil moisture. The remaining soil was washed and sieved to obtain root tissue. Roots were dried and weighed to determine root biomass production by soil profile. A student's T test was used to compare the two groups of genotypes and determine differences between COOL and HOT genotypes. The statistical analyses were performed using SAS v9.0. Root biomass and RASM data was standardized by the yearly average (SMean). These relative values for root and RASM used to compare between groups were calculated dividing individual data point by the trial mean.
Results
Agronomic and physiological performance of two contrasting groups of sisters Means for agronomic and physiological traits are presented on Table 3. Differences in CTv and CTg from a previous study (Pinto et al. 2010) were used together with QTL data, to group the lines in two contrasting sets of COOL and HOT genotypes (Table 1). Under drought the two groups reported significant differences of 1.4 and 0.6 °C in CTv and CTg, respectively. In the heat experiments the differences between the two groups were 1.0 and 0.8 °C for CTv and CTg (Table 3). The COOL Table 2 Weather conditions for each drought (Drt) and Heat trial sown during 2008-2009 and 2010-2011 crop seasons in the Yaqui Valley, NW Mexico Weather data by stage is summarized using the average of daily records for maximum air temperature (T max ), minimum air temperature (T min ), sum of precipitation (Rain) and sum of evapotranspiration (Eto), according to data from the Mexican National Water Commission (CNA) The "Irrigation" column indicates the estimated total millimeters of water applied in the whole cycle genotypes yielded 19 and 12 % more than the HOT genotypes under drought and heat, respectively, which was in agreement with 20 % higher biomass production at maturity under drought and 12 % higher biomass under heat. The number of stems was around 20 % higher in the group of COOL genotypes (data not shown). While the growing cycles for drought and heat were on average 112 and 83 days, respectively, the differences in days to heading and maturity between COOL and HOT groups was no more than 3 days in any environment (Table 3). Under drought, the COOL genotypes had 65 % more grains per square meter and 15 % less WSC in the stems but no differences were found for kernel weight in any environment (data not shown); when grown under heat stress the difference in grain number was 20 % more grains produced by the COOL and 40 % less WSC. High and significant correlation with yield was found for canopy temperature measured during the grainfilling stage, biomass at maturity, and grain number in the two environments (Table 3). Under non-stressed conditions both groups of genotypes reported statistically equal plant height differing only in four cm (data not shown).
Differences in radicular biomass and residual available soil moisture of the COOL and HOT genotypes Significant differences were found between COOL and HOT genotypes for root biomass production and residual soil moisture (Table 4), under both drought and heat stresses, with smaller amounts of residual moisture and more extensive roots generally associated with cooler, higher biomass plants (Figs. 1, 2).
Drought
Root mass measured shortly after anthesis and plotted against residual moisture at the same stage (Fig. 1) shows that COOL genotypes used more of the available water in deeper soil profiles (Table 4, p = 0.02 for RASM at 30-90 cm and p = 0.04 for RAMS at 30-120 cm), and that root mass was also higher in these two regions (p = 0.0018 for both, 30-90 and 30-120 cm). It was observed that the moisture at 0-30 cm was close to zero as a result of the larger concentration of roots in this region and soil exposure that allowed evaporative losses. The total residual soil Table 3 Means for COOL and HOT genotypes for 2 years of experiments (2008-2009 and 2010-2011) with Seri/Babax bread wheat grown under drought and heat stress Data for the canopy temperature during vegetative and grainfilling stages was taken from: Pinto et al. (2010) and used for the selection of sister lines included in the current study. Statistically significant values according to Student's t test at levels * α = 0.1, ** α = 0.05 and *** α = 0.01. All traits were recorded in the complete set of ten genotypes except by those indicated by ( †) which were measured in the subset selected for root and RASM analyses. ( ‡) Data for 1 year under Drt. Phenotypic correlation (Pearson) is shown as r for all the traits with yield using raw data for two replications and 2 years in each environment
Heat
Measurements of root development and RASM shortly after anthesis in the heat experiments showed that the HOT genotypes left more residual soil moisture across the whole soil profile (Table 4, p = 0.04) down to 120 cm (Fig. 2). The strongest contrast was found nearer the surface at profiles 0-30 and 30-60 cm (Fig. 2) where the COOL genotypes left 60 % (p = 0.001) and 30 % (p = 0.032) less moisture than the HOT genotypes, respectively. This result was consistent with the COOL genotypes having relatively more superficial roots than deep roots compared to the HOT genotypes. For example, in the 30-60 cm region the COOL genotypes developed 35 % more roots (p = 0.0003) than the HOT genotypes.
Roots and RASM partitioning under heat and drought
Comparing the total amount of roots (0-120 cm profile), it was found that the COOL genotypes produced only about 10 % more root tissue than the HOT genotypes under both heat and drought (Fig. 3). However, the analysis of the distribution showed that greater differences were found below 30 cm. Both COOL and HOT genotypes concentrated most of their radicular development (˜ 80 %) in the 0-30 cm profile when grown under heat stress, while under drought they tended to be more equally distributed across the 0-30 and 30-120 regions (Fig. 3). Under drought 54 % of the total root biomass of the COOL genotypes was located in the 30-120 cm profile (Fig. 3), while the remaining 46 % was superficial (0-30 cm). The HOT genotypes showed a smaller proportion (44 %) of roots in the 30-120 cm under drought. The amount of roots found at 0-30 cm under heat, was four times greater than roots from 30-90 and 30-120 cm. Combined analyses across environments and years (QTL × E) showed highly significant interactions between QTL (i.e., COOL v HOT) and the relative distribution of roots across the soil profile which is consistent with the observation that under drought the COOL-QTL favor deeper roots, while under heat stress the COOL-QTL favor more superficial roots (data not shown).
Discussion
Notwithstanding the well-documented adaptive value of phenological escape (earliness) from drought and heat stress (Barnabás et al. 2008), the potential confounding effect of phenology was avoided in this study by pre-selecting lines of similar heading time (heading range for 2 years averaged 7 and 5 days for drought and hot-irrigated environments, respectively), with contrasting agronomic performance and CT.
Drought
Phenotypic differences between the COOL and HOT genotypes were consistent with their agronomic performance and root mass and distribution profiles. The results showed that under drought, cooler canopy temperatures were associated with genetic gains of 19 % in yield, 20 % in biomass, and 40 % in deep roots, at 30-90 cm and 30-120 cm (Table 3; Fig. 1). Similar results were found by Lopes and Reynolds (2010) who reported that genotypes with lower canopy temperatures developed 40 % more root mass at 60-120 cm and 30 % higher yields. In the current study, the differences in the root architecture of the two groups were further supported by the amount of residual soil moisture (RASM) at depth. In the superficial layers both groups of genotypes left similar amounts of moisture. However, the analysis of the deeper section from 30-90 and 30-120 cm showed that in these regions the COOL genotypes were able to extract more water leaving 35 and 25 % less residual available moisture than the HOT genotypes (Fig. 1). The capacity of COOL genotypes to extract extra water in the 60-90 cm profile was also associated with an increase of 115 % of root biomass in the same profile under drought (Fig. 1). Lopes and Reynolds (2010) reported that genotypes with greater root development in the deep regions had lower amounts of WSC in the stems, perhaps as a result of more WSC being translocated to the roots to support deep root development. The current study obtained similar results, showing that the WSC content of the COOL genotypes was 15 % lower (Table 3) than the WSC of the HOT genotypes when grown under drought, and 40 % lower under heat. The later was supported by phenotypic correlations with the root distribution under drought, which showed that root biomass in the 60-90 (r = −0.54, p = 0.057), 60-120 (r = −0.68, p = 0.015) and 90-120 (r = −0.72, p = 0.006) soil layers was negatively associated with the percentage of WSC (using raw data) in the stems measured at around anthesis.
Mechanisms that may be determined by the "COOL QTL" Drought stress usually promotes hormone signaling; in particular, ABA concentrations are increased in the roots, helping in the maintenance of root growth and water uptake (Prasad et al. 2008). Manschadi et al. (2006) compared two wheat genotypes with different root architecture in root chambers, finding that the root length density below 90 cm in the drought-tolerant variety was almost four times greater than in a standard Australian variety. These authors found that the former showed more compact horizontal root architecture with a narrow angle but greater vertical development. This root pattern allowed superior water extraction capacities of the drought-tolerant variety (~ 25 % more water uptake from 60 to 90 cm). They proved that post anthesis, a drought-adapted variety was able to continue development, focusing in the central and deepest soil layers, in contrast with the standard variety which equally extended its roots horizontally and vertically.
Heat
Several studies discuss the relevance of the root development as a key trait for drought tolerance, but scarce information regarding its role under heat stress is available. Deep root development at high temperatures has been associated with higher leaf transpiration rates. Plants with a strong radicular system are able to satisfy the high evaporative demand through elevated transpiration rates under hot irrigated conditions and thus maintain cooler canopies (Amani et al. 1996;Bonos and Murphy 1999). While studies with tall fescue and ryegrass showed that high temperatures generally decreased root dry weight and photosynthetic rate, tall fescue, considered heat-tolerant, exhibited greater root mass at 0-40 cm (Jiang et al. 2001) and a faster depletion of soil water (%). The current study found that the group of COOL genotypes had higher amounts of radicular tissue in all soil profiles down to 120 cm depth, but especially in the 30-60 cm profile. These results showed that under heat stress, cooler canopy temperatures were associated with genetic gains of 12 % in yield, 12 % in biomass and 35 % in root development in the 30-60 cm layer (Fig. 3). When water uptake was studied, the COOL genotypes were more effective in removing soil moisture, resulting in 30 % less RASM at 30-60 cm than the HOT genotypes (Fig. 2). Studies with Kentucky bluegrass showed that the maintenance of transpiration under heat stress was an important attribute for performance under stress. Comparison between heattolerant and susceptible cultivars showed that those with canopy temperatures 5 °C cooler had 65 % more roots at 30-45 cm (Bonos and Murphy 1999). At the cellular level, it has been observed that the thermal stability of the plasma membrane of wheat roots is affected by high temperatures (Zhao et al. 2011). Structural analyses of proteins located in the root membranes have shown that above 25 °C the proportion of α-helix and β-sheet changed due to unfolding and disordering of structures. This change in the structure of plasma membrane proteins resulted in the reduction of H + -ATPase activity, an enzyme responsible for multiple physiological functions such as nutrient uptake and cell growth, especially under stress conditions (Janicka-Russak 2011).
Significance of these results to breeding
Genetic confirmation that CT is associated with effective root development
Root growth measurement is challenging and usually involves intensive and destructive techniques to obtain root tissue, however, canopy temperature, which is much easier to measure, is associated with the plant's ability to extract deep water Lopes and Reynolds 2010) and can be easily measured using infrared technology. Data from a previous study using these lines showed that the genotypes exhibited genetic variation for canopy temperature under heat-stressed growing conditions and that the COOL group had lower temperatures; this was supported by the identification of QTL associated with this trait (Pinto et al. 2010). For example, the QTL for CT at chromosome 2B was classified as stress exclusive (drought and heat) and was also reported as the main QTL responsible for root developmental pattern in wheat, namely the maximum root length of lateral and primary roots (Ren et al. 2010;Sanguineti et al. 2007). Studies with rice and barley reinforced the importance of the QTL utilized herein as regions that might contain genes affecting root architectural characteristic and physiological attributes that determine plant performance (Zhang et al. 2001;Teulat et al. 1998;Champoux et al. 1995). Both parents from the experimental population of this study were identified as differing significantly in yield performance under drought while showing high-yield potential (Reynolds et al. 2000). Their breeding value--as genetic sources of numerous varieties and cultivars--is recognized by breeding programs elsewhere (Fox et al. 1996 (Mathews et al. 2008). This allele has been reported as responsible for the cool canopies and increased yield in previous studies with the same population (Pinto et al. 2010;Olivares et al. 2007) and other studies have associated the short arm of the 1B chromosome with traits related to transpiration efficiency (Rebetzke et al. 2008). In the subset of RIL included herein, the Seri allele associated with the T1BL.1RS (rye) translocation resulted in negative effects on yield and in warmer canopy temperatures which was in agreement with previous studies involving Seri crosses grown under drought stress and irrigated conditions (Pinto et al. 2008;Mathews et al. 2008;Peake 2003). However, the effect of the T1BL.1RS translocation seems to be environmentdependent (Rattey et al. 2009) since it also has been found to be advantageous for drought adaptation in earlier studies (Villareal et al. 1995). In the 4A chromosome, unfavorable effects from the Seri allele were observed on canopy temperature in a previous study; the presence of the Babax allele in the 4A chromosome of the RIL resulted in cooler canopy temperatures which were apparently associated to larger aboveground biomass and yield increments where as much as 27 % of genetic variance for these traits have been linked to the Babax parental (Pinto et al. 2010). Results from the current study indicated that the COOL genotypes (which generally possessed the Babax allele in the 4A region) showed significantly higher aboveground biomass production as well as higher radicular development.
Common QTL for heat and drought Pinto et al. (2010) showed for the first time common QTL associated with adaptation of wheat to both drought-and hot-irrigated conditions in the Seri/Babax population, and inferred the involvement of roots since cooler canopies were associated with better performance in both environments. The current study, by measuring root growth in subsets of iso-QTL lines from the same population has provided definitive evidence for the involvement of roots. However, the response of roots was not simply to grow deeper or more extensively, but rather to adapt to the specific needs of the environment. Namely, under drought, the roots of the cooler lines showed a greater distribution at depth. On the other hand, under heat stress, the roots of the cooler lines showed a relatively greater proportion of roots at the surface where access to water was more reliable given frequent gravity irrigations in this treatment. This would suggest that the QTL of COOL lines may be exerting their influence at a relatively high level of integration and be involved in determining root distribution pattern in response to environmental cues. This is backed up by work that linked CT to plant growth regulation (Tang et al. 2008;Wardlaw 1974). This selective root performance observed in bread wheat RIL is supported by results from a recent study with Arabidopsis which revealed that water availability determines root development, influencing the position of lateral branches and root hairs. The authors indicate that roots can distinguish between soil areas containing air or humidity and are able to respond according to the environment. This kind of response is known as hydropatterning, a conserved process not exclusive to Arabidopsis but present also in cereals like Maize and Rice (Bao et al. 2014). In addition, the specificity of the CT QTL previously reported by Pinto et al. (2010) was supported by an interesting trade off observed between stem water soluble carbohydrates (WSC) content and root growth under both stresses. Under drought, root development in the deep soil layers (60-120 cm) was negatively and significantly associated with WSC, while under heat, the negative association with WSC was found in the upper soil region at 30-60 cm. These results were consistent with the findings from Lopes and Reynolds (2010) regarding the possible contribution of stored stem WSC to the development of deeper roots under drought.
Conclusions
QTL conferring tolerance to both heat and drought stress provide useful opportunities for adapting wheat to climate change, under which both stresses are expected to increase. If one or more of the QTL can be used to derive close markers, they would be especially useful in molecular breeding since heat and drought are both challenging targets separately, and are expected to increasingly occur together (Sanderson 2011). The result also confirms the value of using CT as a proxy for favorable expression of root traits under both heat and drought stress by putting it on a firmer genetic basis. In addition, the observation that these QTL affect adaptive root response gives a useful lead into understanding the genetic basis of how root growth may be regulated.
Author contribution statement RSP: Conducted all of the experiments that were based on an earlier study she also published. She performed all data analysis and led the write-up. MPR: Designed the experiment and participated in all aspects of data analysis and writing of the paper. | v3-fos |
2018-04-03T05:52:42.569Z | {
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} | s2 | Variations in chemical fingerprints and major flavonoid contents from the leaves of thirty‐one accessions of Hibiscus sabdariffa L.
Abstract The leaves of Hibiscus sabdariffa L. have been used as traditional folk medicines for treating high blood pressure and fever. There are many accessions of H. sabdariffa L. throughout the world. To assess the chemical variations of 31 different accessions of H. sabdariffa L., fingerprinting analysis and quantitation of major flavonoids were performed by high‐performance liquid chromatography (HPLC). The HPLC method was validated for linearity, sensitivity, precision, repeatability and accuracy. A quadrupole‐time‐of‐flight mass spectrometry (Q‐TOF‐MS) was applied for the characterization of major compounds. A total of 9 compounds were identified, including 6 flavonoids and 3 phenolic acids. In the fingerprint analysis, similarity analysis (SA) and principal component analysis (PCA) were used to differentiate the 31 accessions of H. sabdariffa L. Based on the results of PCA and SA, the samples No. 15 and 19 appeared much different from the main group. The total content of five flavonoids varied greatly among different accessions, ranging from 3.35 to 23.30 mg/g. Rutin was found to be the dominant compound and the content of rutin could contribute to chemical variations among different accessions. This study was helpful to understand the chemical variations between different accessions of H. sabdariffa L., which could be used for quality control. © 2015 The Authors Biomedical Chromatography Published by John Wiley & Sons Ltd.
Introduction
Hibiscus sabdariffa L. (family: Malvaceae) is used for both food and traditional medicine (Da-Costa-Rocha et al., 2014). It is most popular for its calyces used as sour tea (Ali et al., 2005). In India, Africa and Mexico, infusions of the leaves or calyces are traditionally used for their diuretic, cholerectic, febrifugal and hypotensive effects (Kuo et al., 2012;Guardiola and Mach, 2014). Research has shown that H. sabdariffa L. leaves have multiple biological activities, such as antiatherosclerotic effect (Chen et al., 2013), anticancer activity (Lin et al., 2012), antioxidant and antihyperlipidemic activities (Ochani and D'Mello, 2009;Gosain et al., 2010;Sindi et al., 2014). Flavonoids and phenolic acids are considered as the major bioactive compounds in the leaves of H. sabdariffa L. (Chen et al., 2013).
Many accessions (samples of a crop variety collected at a specific location and time) of H. sabdariffa L. are widely cultivated in Africa, Asia, and America (Patel, 2014). The H. sabdariffa L. leaves from different countries and accessions could have different chemical constituents, which may result in the improper clinical usage under the same name. Most of the research about H. sabdariffa L. does not specify the origin of the variety and the crop site, making it difficult to make comparisons between the chemical profile and bioactivities of extracts obtained in different studies (Borrás-Linares et al., 2015). Furthermore, the amount of bioactive compounds in H. sabdariffa L. leaves is an important aspect that influences their therapeutic effects. Therefore, to evaluate chemical variations of different accessions of H. sabdariffa L. is needed.
A strategy for clarifying the chemical variations of different accessions of H. sabdariffa L. consist of two aspects. One is the qualitative and quantitative analysis of several bioactive components ( Jin et al., 2008). The other is chemical fingerprint analysis, which has been accepted by World Health Organization (WHO) (Kong et al., 2009;World Health Organization, 1991). At present, fingerprint analysis, based on multivariate statistical analysis, such as similarity analysis (SA) and principal component analysis (PCA), is widely applied to discriminate the medicinal plants (Tian et al., 2009;Xu et al., 2011), and fruits (Sârbu et al., 2012).
Flavonoids in edible and medicinal plants possess wide range of biochemical and pharmacological effects. Rutin, quercetin and its derivatives, and kaempferol and its derivatives are identified as major flavonoids in H. sabdariffa L. leaves (Zhen et al., 2016). The flavonoid content is an important factor in plant foods, which has been archived in the United States Department of Agriculture (USDA) database (U.S. Department of Agriculture, Agricultural Research Service, 2013). Therefore, flavonoids could be used as marker compounds to evaluate chemical consistency among 31 H. sabdariffa L. leaves. In our previous studies, high radical scavenging activity was observed in the leaves of H. sabdariffa L. The activity varied among different accessions (Wang et al., 2014). Therefore, this study was designed to profile the chemical fingerprint in the leaves of 31 H. sabdariffa L. accessions cultivated in United States. A Q-TOF-MS was carried out to identify the major fingerprint peaks. The chemical profiles of H. sabdariffa L. leaves were investigated by chemometric methods. Moreover, a reliable HPLC method was developed and validated for simultaneous determination of five flavonoids in the leaves of 31 H. sabdariffa L. accessions.
Plant materials
A total of 31 accessions of H. sabdariffa L. were included in this study. Their sample identity numbers, country origins, and accession labels are listed in the Table 1
Preparation of standard and sample solutions
Dried H. sabdariffa L. leaves powder (0.20 g) were accurately weighed and extracted with 70% aqueous methanol (20 mL) by ultrasonic-assisted extraction (44 KHz, 70 W, Branson Ultrasonic Corporation, Danbury, CT, USA) for 30 min at room temperature Zu et al., 2006). Each sample was prepared in triplicate for quantification of analytes. The sample solutions were filtered through 0.45-μm membrane.
Stock solutions of the five analytes were prepared in methanol. The stock solution was diluted with 70% methanol to yield a series of appropriate concentrations. All the prepared samples were stored at -10°C till their analysis. HPLC and Q-TOF-MS analysis conditions HPLC analysis was carried out on an Agilent 1200 series equipped with a diode array detector (Agilent Technologies, USA). Chromatographic separation was performed on a C 18 column (4.6 × 150 mm, 3.5 μm, Zorbax eclipse plus, Agilent USA) at 30°C with a guard column (4.6 × 12.5 mm, 5 μm, Zorbax eclipse plus). The mobile phase consisted of H 2 O (solvent A) and ACN (solvent B) with 0.1% (v/v) formic acid, respectively. The gradient program was as follows: 0-19 min, 10-46% B; 19-20 min, 46-10% B. A post-run equilibrium time of 3 min was used for all samples. The flow rate was set at 1 mL/min with ultraviolet (UV) detection at 350 nm. The T splitter gave a flow rate of 0.25 mL/min toward the MS detector.
Mass spectrometry was performed using an Agilent 6540 Q-TOF-MS system (Agilent Corp., USA) equipped with a jet stream ESI interface. The TOF/MS system was operated in both negative and positive ion modes. Mass spectra were recorded over the mass range m/z 50-1100. The mass analysis conditions were set as follows: drying gas (N 2 ) flow rate, 10 L/min; nebulizer, 40 psi; drying gas temperature, 350°C; sheath gas temperature, 350°C; capillary voltage, 3500 V; fragmentor voltage, 120 V.
Method validation for the determination of five flavonoids
The linearity, precision (inter-day and intra-day), repeatability, and recovery were carried out to validate the HPLC method according to ICH guideline (Validation of Analytical Procedures: Text and Methodology Q2 (R1), 2005) Six working solutions were analyzed for the construction of calibration curves. Linearity was evaluated by the calculation of a regression line by the method of least squares. The limits of detection (LOD) and quantification (LOQ) were estimated experimentally by injecting a series of dilute solutions with known concentrations until the signal-to-noise ratio (S/N) for the standards reached a 3:1 ratio for LOD and 10:1 for LOQ, respectively. Intraand inter-day variations were applied to determine the precision of the developed method. The repeatability of the proposed HPLC method was studied at three levels (0.10 g, 0.20 g, 0.25 g) of the sample No.15 (Senegal). The samples of each level were extracted and analyzed triplicates. The accuracy of the method was tested by detecting the recovery, which was evaluated by adding three concentration levels (low, middle and high) of standard solutions into certain amount (0.10 g) of sample No.15 (Senegal) (Peng et al., 2013). The samples were extracted and analyzed for quantitative analysis as the developed method mentioned above.
Data analysis
Accurate mass data were recorded and processed by MassHunter B.04.00 software (Agilent Technologies, USA). Principal components analysis (PCA) and similarity analysis (SA) were performed to analyze the 31 samples of H. sabdariffa L. based on the common characteristic peaks. PCA and SA were calculated and generated using a professional software named "ChemPattern 1.0.1.0" (fingerprint chromatography processing software, ChemMind Technologies (Beijing) Co., Ltd., China). All the data were pretreated including data normalization and chromatograms alignment before PCA and SA.
Optimization of sample extraction and chromatographic conditions
According to the previous studies, methanol-water (70:30) has a higher efficiency in extracting flavonoids than ethanol-water (70:30) . Ultrasonic extraction is considered a simpler and more effective method for extraction of flavonoids in the plant leaves. Moreover, ultrasonication for 30 min gave a similar result as the soxhlet for 240 min (Zu et al., 2006). The ultrasonic extraction method in this study was also optimized including extraction times (30 min, 45 min and 60 min), extraction temperatures (room temperature, 35°C and 45°C) and times of extraction (once and twice). The peak areas of the five flavonoids were used as a marker for evaluation of extraction efficiency. There were no significant differences in the peak areas of the five flavonoids among different extraction conditions as described above. Therefore, the simple and convenient extraction method was selected as follows: solvent, 70% methanol; extraction temperature, room temperature; ultrasonic extraction time, 30 min.
HPLC conditions including chromatographic column, mobile phase and detection wavelength were optimized. The best results were obtained using an Agilent zorbax eclipse plus C 18 (150 × 4.6 mm i.d., 3.5 μm) column at 30°C, with gradient elution of 0.1 % aqueous formic acid and ACN with 0.1% formic acid (v/v) as the mobile phase. According to the peak area of principal peaks, 350 nm was chosen as the detection wavelength. Under the optimized conditions, the separation of five marker compounds can be easily achieved in 20 min. Typical HPLC-DAD chromatograms are shown in Fig. 2A.
HPLC fingerprint analysis
The fingerprints of 31 samples of H. sabdariffa L. were obtained under the optimal HPLC conditions and are shown in Fig. 3. Peaks that existed in all the samples were assigned as "common pattern", which was generated based on all chromatograms by the professional software of ChemPattern 1.0.1.0 (Fig. 2B).
HPLC fingerprint method precision and reproducibility were evaluated by the analysis of five runs of the same sample solution and five replicates from the same sample, respectively. The relative standard deviations (RSD) of retention time (RT) and peak area (PA) of 9 characteristic peaks in the precision test were found in the range of 0.15-3.27%, whereas in the reproducibility test the RSDs of RT and PA were also below 0.75 and 4.26%, respectively. The stability of sample solution was evaluated at different time points (0, 2, 4, 8, 12 and 24 h), and the RSDs of RT and PA were less than 0.32 and 3.90%, respectively. All of these results indicated that the HPLC fingerprint method was reliable.
Identification of major compounds in H. sabdariffa L.
The structural identification of 9 characteristic peaks was performed by the LC-Q-TOF-MS. Both negative and positive ion modes were used because they provided more information about chemical structure. Some phenolic acids, flavonoids and ascorbic acid have been reported in the leaves of H. sabdariffa L. (Rodriguez-Medina et al., 2009;Wang et al., 2014;Kumar et al., 2015). In this study, the nine characteristic peaks were identified by comparison of their retention time and accurate MS with those of reference standards. The MS data are shown in Table 2. Of these 9 compounds identified, the 5 flavonoids (rutin, kaempferol-3-orutinoside, kaempferol-3-o-glucoside, quercetin and kaempferol) were chosen as the marked components.
Method validation for the determination of five flavonoids
The linear ranges, regression equations, LODs and LOQs of the five analytes were detected using the developed HPLC method. As shown in Table 3, the calibration curves of the analytes showed good linearity (r 2 ≥ 0.9996) with given concentration ranges. LOD and LOQ values were less than 0.10 μg/mL and 0.35 μg/mL, respectively, and showed the adequate sensitivity of the proposed method. The intra-and inter-day variations (RSD) of five analytes peak areas were less than 0.67% and 0.90%, while retention time were less than 0.26% and 0.26%, respectively (Table 4). The average recoveries obtained in this study ranged from 86.80% to 103.50% (Table 5). The repeatability of the developed method was evaluated at three levels ( Table 6). The results showed that the repeatability (RSD, n = 3) was less than 1.05% (0.10 g), 0.81% (0.20 g), 1.29% (0.25 g), respectively. Therefore, the proposed HPLC method could be considered accurate for quantitative determination of the five investigated compounds.
Quantitative analysis of five analytes in 31 H. sabdariffa L. accessions
The developed HPLC method was successfully applied to the simultaneous quantification of the five marker compounds in 31 accessions of H. sabdariffa L. The results are shown in Table 7. The quantitative analysis results showed that the content ranges (mg/g) were 0.47-19.16 (rutin), 0.66-8.65 (kaempferol-3-orutinoside), 0.18-1.94 (kaempferol-3-o-glucoside), 0.18-0.82 (quercetin), and 0.03-0.22 (kaempferol), respectively. The total content of the five flavonoids showed great variations among different accessions, ranging from 3.35 to 23.30 mg/g. Among the tested samples, the sample No. 2 from Cuba had the highest contents of five flavonoids, while the sample No. 19 from USA had the lowest total amount (Table 7). Based on the previous studies, it is found that both the total flavonoid content and antioxidant activity of H. sabdariffa L. leaves were higher than those of H. sabdariffa L. flowers (Chen et al., 2013;Mohd-Esa et al., 2010). Variations in antioxidant activity may be due to different phenolic, flavonoid and ascorbic acid contents (Kumar et al., 2015). Therefore the total antioxidant activities of samples could vary greatly among different accessions of H. sabdariffa L.
Principal component analysis (PCA)
To evaluate the variations among the 31 accessions, PCA was performed. The data of chromatographic fingerprints were imported into the ChemPattern 1.0.1.0 software. The score plot of the first two principal components (PC1-PC2) is shown in Fig. 4.
The first two principal components (PC1-PC2) were accounted for 85.9% of the total variance of the samples. The PCA analysis showed that the differences observed in the H. sabdariffa L. accessions were derived from the concentration of rutin. PC1, which explained 63.4% of the variance, was positively correlated with rutin content. For PC2 significant variables were flavonoid content and kaempferol-3-o-rutinoside content.
PCA analysis revealed clearly the relationships among the tested samples. As shown in Fig. 4, the two samples No. 21 and 22 were clustered in one group, which were from Sudan. Except the sample No. 15 from Senegal and No. 19 from USA, the other samples can be clustered in one main group. The main group may be considered as rutin-rich chemotype, which contains much more rutin than others. The results also indicated that samples No.15 and 19 produced greater variations in their chemical compositions and content. Recovery (%) = (amount found-original amount)/spiked amount × 100. c RSD (%) = (recovery SD/mean) × 100. Because all the leaf samples were obtained from the accessions grown in the same place and under the same cultivation conditions, such variations may result from the inherent variability of the accessions. No. 19 could be a low quality accession in terms of its major flavonoid contents.
Similarity analysis (SA)
Similarity analysis is a conventional method describing the similarity among the fingerprints. In this study, cosine similarity algorism was applied for the similarity analysis. By comparison with the fingerprint common pattern of H. sabdariffa L., the similarity index of 31 samples was not less than 0.983 except those of samples No. 15,19,21 and 22 (Fig. 5).
As shown in Fig. 5, taking 0.98 as the threshold, the samples with the correlation coefficients above it should be clustered to a group, which has been properly proved by the previous results from PCA. The different similarity values of samples means the different internal quality of these samples. Therefore, the developed HPLC fingerprint common pattern could be as a quality assessment model for classifying H. sabdariffa L. accessions. Generally, the climatic and edaphic conditions are important environmental factors that can affect chemical composition of the leaf samples. In order to eliminate the environmental effect, we collected the seeds from 31 accessions and germinated and grew them in the same environment. The leaves were collected at the same time for quantitative and chemical fingerprint analyses. We assume the chemical variations among the accessions could be attributed to the variations of the seed sources where these individual accessions may have adapted to their original climatic and edaphic conditions. Therefore, the resulting genetic variations could be one of the key factors affecting the contents of bioactive compounds and quality of H. sabdariffa L. Many of these accessions could also be called ecotypes of the species. This study is a first comprehensive evaluation of the chemical variations among 31 H. sabdariffa L. accessions based on the combination of quantitative and chromatographic fingerprint analyses. Because of the tremendous potential of utilizing the leaves of this species for food, nutrition, and medicine, as well as value added products for human health, this research would be helpful for the quality control of H. sabdariffa L. in the future.
Conclusion
A strategy for clarifying the chemical variations of different accessions of H. sabdariffa L. was developed. Firstly, chemical fingerprint analysis was performed based on the multivariate analysis methods (PCA and SA). Secondly, a simple HPLC method was developed and validated for simultaneously quantitative analysis of major flavonoids in 31 accessions of H. sabdariffa L. The samples were clustered in one group except four accessions (No.15,19,21 and 22). The chemical differences could be due to the inherent variability of the accessions. The proposed HPLC and fingerprint method were validated and proved to be reliable. The chemical fingerprint analysis is helpful to clarify the relationship among different accessions of H. sabdariffa L. and useful for quality control. Table 1. | v3-fos |
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} | s2 | Expert Opinion on the Perceived Effectiveness and Importance of On-Farm Biosecurity Measures for Cattle and Swine Farms in Switzerland
Biosecurity is crucial for safeguarding livestock from infectious diseases. Despite the plethora of biosecurity recommendations, published scientific evidence on the effectiveness of individual biosecurity measures is limited. The objective of this study was to assess the perception of Swiss experts about the effectiveness and importance of individual on-farm biosecurity measures for cattle and swine farms (31 and 30 measures, respectively). Using a modified Delphi method, 16 Swiss livestock disease specialists (8 for each species) were interviewed. The experts were asked to rank biosecurity measures that were written on cards, by allocating a score from 0 (lowest) to 5 (highest). Experts ranked biosecurity measures based on their importance related to Swiss legislation, feasibility, as well as the effort required for implementation and the benefit of each biosecurity measure. The experts also ranked biosecurity measures based on their effectiveness in preventing an infectious agent from entering and spreading on a farm, solely based on transmission characteristics of specific pathogens. The pathogens considered by cattle experts were those causing Bluetongue (BT), Bovine Viral Diarrhea (BVD), Foot and Mouth Disease (FMD) and Infectious Bovine Rhinotracheitis (IBR). Swine experts expressed their opinion on the pathogens causing African Swine Fever (ASF), Enzootic Pneumonia (EP), Porcine Reproductive and Respiratory Syndrome (PRRS), as well as FMD. For cattle farms, biosecurity measures that improve disease awareness of farmers were ranked as both most important and most effective. For swine farms, the most important and effective measures identified were those related to animal movements. Among all single measures evaluated, education of farmers was perceived by the experts to be the most important and effective for protecting both Swiss cattle and swine farms from disease. The findings of this study provide an important basis for recommendation to farmers and policy makers.
Introduction
Within the context of livestock production, biosecurity is defined as management activities that reduce the opportunities for infectious agents to gain access to, or spread within, a production unit [1]. In Switzerland and other European countries, biosecurity is achieved through a combination of nationally legislated and voluntary on-farm measures. The significance of onfarm biosecurity has been emphasized in the European Union Animal Health Strategy 2007-2013 "Prevention is Better than Cure". Within the first draft of the new Animal Health Law of the European Union, an attempt was made to focus on on-farm biosecurity in order to allow free trade across the borders of different European countries [2]. This strategy therefore commits farmers to maintaining high on-farm biosecurity standards.
Biosecurity practices might differ among and within countries for reasons such as differences in production types, diseases present, legislation on disease control, and available resources. The Swiss approach to maintaining a disease-free livestock population is dominated largely by governmental control measures, with the compulsory Bluetongue (BT) vaccination in 2008-2010 and the ongoing Bovine Virus Diarrhea (BVD) eradication program being notable examples [3,4]. In contrast, the implementation of on-farm biosecurity measures in Switzerland is relatively poor. This may be associated with the fact that Swiss livestock herds are still small, despite the global trend towards fewer and bigger enterprises. In 2011, the average herd size of a Swiss cattle farm was 39 (33 in 2001), and that of a Swiss swine farm 190 (105 in 2001) [5]. Larger holdings are more likely to suffer greater economic losses in the event of a disease outbreak. This may be one reason why larger enterprises apply a stricter biosecurity management than small and backyard holdings [6][7][8]. Despite the poor implementation of on-farm biosecurity measures, Switzerland has maintained a favorable animal disease status [9]. This favorable status might further contribute to a more relaxed biosecurity attitude of farmers [10].
There are many studies reporting biosecurity measures commonly implemented, as well as the factors that influence implementation of biosecurity measures by farmers and veterinarians [7,[10][11][12][13][14][15][16][17][18]. Also many studies exist that describe which measures should be applied in order to keep disease risk at a minimum [19][20][21][22]. However, these studies are often only based on general knowledge about infectious diseases. Furthermore, it has been suggested that the large variety of published recommendations, might confuse and thus discourage farmers from implementing biosecurity measures [23,24]. This may explain why there is a great deal of variation in, and even absence of on-farm biosecurity practices as observed in some studies [8,23]. The limited examples of proven efficacies, combined with the lack of relevant education are potential reasons for infrequent or non-compliance to biosecurity measures [23]. All these factors may contribute to the negative attitude farmers often have towards biosecurity [8,25]. Educating farmers about biosecurity is an important factor influencing the implementation of biosecurity measures [11,26,27]. When communicating to farmers, it is essential to describe the protective effect and potential benefit of various biosecurity measures. This allows farmers to focus on biosecurity measures that are relevant to their production type, and the disease risks they face, thus optimizing time and resource expenditures. The effectiveness of biosecurity measures has been reported in an observational study that investigated disease spread relative to recommended biosecurity measures during an outbreak [28]. However, this is difficult to demonstrate in the field in the absence of a disease outbreak in a region. Controlled, experimental settings are not an optimal approach, because it is a challenge to extrapolate the results to field conditions. Metrics for quantifying the effectiveness of biosecurity measures in field settings include calculating the basic reproductive rate of an infection (R0) for different scenarios [29] or estimating the population attributable fraction (PAF) of disease for each biosecurity measure. The latter is defined as the fraction of disease in the population that could be prevented through elimination of a risk factor, i.e. the implementation of a biosecurity measure [30]. These methods are rarely used because of the challenge of correlating different measures among themselves and with external factors in field studies [31].
Expert opinions are a valuable option for gathering knowledge in a field where accurate and unbiased field data is unavailable [32]. The Delphi technique in particular, is commonly used to generate consensus amongst experts, and has also found application in veterinary epidemiology [33,34]. The Delphi technique has been criticized for generating subtle pressure to conform with group consensus, which may lead to a watered-down best opinion [35]. In addition, the method can sometimes be time consuming [35,36]. Nevertheless, if planned and implemented carefully, the Delphi technique can be very useful for capturing information upon which to base policy decisions. One of the advantages of the Delphi method is that experts can be questioned independently allowing each expert opinion to be weighted equally [37]. Furthermore, the feedback of the group consensus and re-evaluation of the experts own answer reduces the overall variance while avoiding the social and personality influences that may arise in group discussions.
The aim of this study was to assess the perception of Swiss experts about the effectiveness and importance of individual on-farm biosecurity measures for cattle and swine farms (31 and 30 measures, respectively), using a modified Delphi method. The study results will have value for developing biosecurity recommendations for farmers and informing risk based surveillance and disease control policy.
Expert opinion
A modified Delphi method was used in this study [37,38]. The expert opinion consisted of face-to-face interviews, followed by a report with the initial findings, and telephone calls for the discussion and revision of the results.
Selection of experts
Our goal for selecting experts was to include a broad range of veterinary expertise from the field of animal disease control in Switzerland. Experts were employed in public veterinary services (n = 6), universities (n = 6), or animal health institutions (n = 4) in Switzerland. These were the experts most likely to be consulted in the event of an infectious disease outbreak in livestock within Switzerland. All cattle and swine experts that were contacted (eight for each species) agreed to participate in the study. Each expert was interviewed at a location of his choice and all interviews were conducted by the same interviewer, namely the first author.
Selection of on-farm biosecurity measures
Based on a thorough review of literature, measures aimed at preventing transmission of infectious agents with varying transmission characteristics were selected and a list of on-farm biosecurity measures was created. Biosecurity measures were grouped into 11 categories on the basis of common vehicles and modes of transmission or prevention of infectious agents. A final list of 32 on-farm biosecurity measures, of which 31 were applicable to cattle farms (Table 1) and 30 to swine farms (Table 2) were selected. "Vaccination", which fits in the category "reduction of infection pressure" was included as a separate category and was evaluated for those diseases where vaccination can be applied.
Selection of diseases
As some routes of transmission are more relevant for one disease than for another, we focused the evaluation of the perceived effectiveness on specific diseases. This would allow the prioritization of biosecurity measures for specific or related diseases. Furthermore, this would also facilitate a more precise evaluation by the experts. Individual diseases were selected to be representative of: diseases with vector-borne transmission (Bluetongue, BT), (re-) emerging diseases (African Swine Fever, ASF), those having a high economic impact (Foot and Mouth Disease, FMD), and diseases that are particularly relevant for Switzerland. The latter, are either officially eradicated, and only appear sporadically (Enzootic Pneumonia, EP; Porcine Reproductive and Respiratory Syndrome, PRRS; Infectious Bovine Rhinotracheitis, IBR), or are subject to an ongoing eradication program (Bovine Viral Diarrhea, BVD). Cattle experts were asked to rank the effectiveness of biosecurity measures for dealing with the pathogens causing BT, BVD, IBR and FMD, while swine experts were asked to rank those related to ASF, EP, PRRS and FMD.
Category: Contact to the outside world
Closed housing Geographical barriers (mountains, rivers,. . .) Low animal density in the area No breeding animals, transport vehicles and equipment shared with other farms 2.
Category: Animal contacts
Prevention of contact with wild animals Prevention of contact with pets 2.5 (0-4) Median Score 3 2.5 3 2 2
Category: Visitors
Access restriction for visitors In-house or clean boots and clothes for non-professional visitors Personal working hygiene of professional visitors (boots, clothes, hands,. . .) Median Score 4 4 3 4 4
Category: Stable
Cleaning and disinfection of the compartments following animal replacement Median Score 4 2.75 2 2 3
Category: Feedstuff
Treatment of feedstuff (chemically, physically) Storage of feedstuff dry and protected 1.
Category: Disease awareness
The set-up was designed based on the experience of four pilot interviews to minimize question ambiguity and generally refine the opinion process. The face-to-face interviews of the Swiss experts were conducted from February to April 2012. According to Swiss legislation, no ethical approval was required for this study since no sensitive data were collected. The research objectives of the study were communicated to all participants and their agreement to participate was obtained through a written consent. All experts were assured anonymity. Interviews were audiotaped for documentation. During these interviews, experts were given the task of ranking biosecurity measures based on their perceived effectiveness and importance of each measure in preventing infectious agents from entering and spreading within, a farm. The diseases to be evaluated for the perceived effectiveness were assigned to the experts in random order. Each biosecurity measure was written on a card. For some measures, a brief explanation of the measure was included on the back of the card, to ensure that all experts used the same definition for each measure. As an example, for the biosecurity measure "animal health monitoring by the farmer", the explanation "farmer observes and knows his/her animals; he/she keeps records of disease occurrence and treatments" was provided. During the interview, the cards were shuffled and handed over to the experts for ranking. Experts were first asked to sort the biosecurity measure cards along an arrow, from "no importance" to "of utmost importance". In a second step, the experts were asked to allocate a score from 0-5 to each biosecurity measure card. This approach was intended to assist experts by helping them focus on ranking the measures first, and then assign a semi-quantitative value to the ranked measures. A 6-point scale was used to necessitate the experts to lean towards one of the given scale extremities and not to remain in neutral position. For the assessment of the perceived effectiveness, it was left up to the expert to choose whether to use the scale from 0-5 immediately, or in a second step.
The first task given to the experts was to rank the cards based on their perceived importance of each measure in preventing an infectious agent from entering and spreading within a farm. For this, the experts were asked to consider the feasibility, effort required, and benefit of each measure, as well as Swiss legislation. With the definition of "importance", we intended to collect the opinion of the experts on the biosecurity measures that should be promoted within Switzerland. The second task was to rank the perceived effectiveness of the measures in preventing specific infectious agents from entering and spreading within a farm. Experts were asked to base this ranking solely on the transmission characteristics of the particular agents, irrespective of the feasibility of the measure and the prevalence of the disease. The experts were allowed to write down and rank additional biosecurity measures if they thought the list was incomplete or not sufficiently precise. They were also allowed to ask questions at any time during the interview. In order to get an impression of how experts perceive their knowledge, they were asked to assess their knowledge about each disease, using a score from 1 (poorest) to 6 (best). The results of the self-evaluation were not considered in the analysis.
Following the completion of all 16 interviews, a report was sent to each expert per mail. Each report contained five bar charts (one for the perceived importance, and one for the perceived effectiveness towards each of the four diseases), showing the individual experts' scores and the median and range of the scores from all experts for the same species. In a second round of the expert opinion, each expert was given the opportunity to revise his scores during a pre-arranged phone call. Changes were documented, and the revised scores were used in the final analysis.
Statistical analysis
Expert scores were reported as medians, quartiles and ranges. Perceived effectiveness of each biosecurity measure was first described for each individual disease. In addition, the median of the perceived effectiveness scores of all 4 diseases was calculated for each biosecurity measure and expert to describe its overall perceived effectiveness. Spearman's rank correlation coefficient (r s ) was used to assess the association between scores for perceived importance and effectiveness of different biosecurity measures.
To assess agreement among the different experts, the absolute value of the difference between scores was calculated for each pair of experts and each biosecurity measure. This resulted in 28 individual comparisons per biosecurity measure, up to 868 comparisons per disease for the perceived effectiveness of biosecurity measures and up to 952 comparisons for the perceived importance of biosecurity measures. Percent of comparisons with total agreement between 2 experts (difference of 0), and deviation by different amounts between 2 experts (difference from 0.5 to 5) were used to describe the raw agreement among experts. The proportion of the total variance in scores that could be attributed to individual experts was estimated with Intraclass Correlation Coefficients (ICC) from nonparametric repeated measures ANOVA models. In these models, the outcomes were the scores on perceived importance and effectiveness for the different diseases and animal species. For the calculation of ICC expert, the individual biosecurity measures were entered as a subject variable, and the experts were entered as a random effect. The ICC for contribution of experts to the total variance of scores was calculated from the model output [39]:
ICC ¼
Mean Square ðExpertÞ À Mean Square ðResidualÞ Mean Square ðExpertÞ þ ðk À 1Þ Mean Square ðResidualÞ k-1 represents the degrees of freedom for the model. The Wilcoxon-Mann-Whitney-test was applied to investigate differences in the median scores for the perceived importance of biosecurity measures between cattle and swine. All statistical analyses were performed with the software NCSS 8 [40]. Results were recorded in a Microsoft Access 2010 file (Microsoft Corp, Redmond, Washington USA).
Results
The individual interviews lasted from 25 to 98 min (overall mean 53 min, 47 min for cattle experts, and 59 min for swine experts). Some experts commented that the modified Delphi method used in the study was convenient for capturing their opinions. Most experts (14/16) agreed that the list of biosecurity measures was exhaustive. Two swine experts provided the following additional biosecurity measures: "prevention of contact with birds", "no attendance at markets/shows or no return from there", "chronology of animal transports", "big distance between farm and road", "restrictions to workers having been abroad" and "buying semen only from males with health certificate". Since these measures were evaluated only by the experts who suggested them, they were not included in the second round of opinion or in the final study results. In the second round of the opinion process, all the experts reassessed their scores. The reassessment however did not result in any changes in the median values.
The most important and effective biosecurity measures for cattle farms where considered those related to "disease awareness". For swine farms, biosecurity measures related to "animal movements" received the highest scores for their perceived importance and effectiveness. For both species, the least important and effective measures as perceived by the experts where those in the category "feedstuff". Furthermore, vaccination was rated as being of low importance for both species. The overall assessment of the perceived effectiveness and importance of biosecurity measures is presented in Tables 1 and 2. The degree of agreement among experts ranged from complete agreement to a strong disagreement (scores ranging from 0-5). For cattle farms, experts were in almost complete agreement on the perceived effectiveness of the measure "prevention of contact with pets", and on measures related to "feedstuff". On the other hand, their opinions on the importance of measures related to feedstuff were divided. Cattle experts disagreed strongly on the biosecurity measures: "no breeding animals, transport vehicles and equipment shared with other farms" and "limitation of number of animals". Swine experts agreed in their assessment of "quarantine animals after market/show" and of "no breeding animals, transport vehicles and equipment shared with other farms". On the other hand, "geographical barriers", "limitation of number of animals" and "vehicle access restriction", were assessed dissimilarly. The overall differences in the assessment are shown in Figs 1 and 2. Differences of half points were not common since the instruction for the opinion was to provide scores from zero to five, and only some experts gave half points. Of all individual Expert Opinion on the Perceived Effectiveness and Importance of On-Farm Biosecurity Measures assessments per species, 69% for cattle and 67% for pigs differed by a maximum of one point and, 88% for cattle and 87% for pigs differed by a maximum of two points. The agreement in the assessments was comparable for the individual diseases, which indicates that one disease was not discussed more controversially than another.
The comparison of the same biosecurity measures for cattle and swine farms revealed a statistically significant difference between the perceived importance of the following biosecurity measures: "quarantine animals after market/show", "prevention of contact with wild animals", rodent control", "low animal density in the area", "geographical barriers" and "no breeding animals, transport vehicles and equipment shared with other farms" (all Wilcoxon-Mann-Whitney-test P-value < 0.05).
For cattle biosecurity measures, there was a strong correlation between the assessment of the perceived effectiveness of measures for BVD and IBR (r s = 0.8). There was a moderate correlation between the perceived importance and the perceived effectiveness of measures for BVD (r s = 0.6), IBR (r s = 0.6) and the overall disease median (r s = 0.5). The assessment of the perceived effectiveness of the measures for FMD was also moderately correlated to those for IBR (r s = 0.6) and BVD (r s = 0.6).
For swine biosecurity measures, there was a strong correlation between the perceived effectiveness of measures for FMD and ASF (r s = 0.8). There was a moderate correlation between the perceived importance and the perceived effectiveness of measures for ASF (r s = 0.6) and for PRRS (r s = 0.6).
The assessment of reliability revealed a weak dependency of the opinion results on the individual expert (ICC expert: 0.05-0.36), and a stronger dependency on the individual measures (ICC measure: 0.46-0.73) ( Table 3).
Discussion
This study was conducted to assess the perceptions of veterinary experts on the effectiveness and importance of individual on-farm biosecurity measures, using a modified Delphi method. For cattle farms, biosecurity measures in the category "disease awareness" of farmers were rated as being the most important (score: 5) and among the most effective (scores: 4-4.5) measures. Farmers are often the first to recognize and report disease outbreaks, and education of Expert Opinion on the Perceived Effectiveness and Importance of On-Farm Biosecurity Measures farmers is a fundamental tool in disease eradication [41]. For highly contagious diseases in particular, early detection and notification by farmers may have an enormous impact on disease mitigation. Other measures perceived as important (and effective for individual diseases) for cattle farms included "vehicle cleaning and disinfection", measures on "personal working hygiene" for both, farmers and visitors, "quarantine of sick and new animals" and ensuring that only healthy animals are brought to common pastures. The latter is especially relevant for Switzerland, since alpine pasturing has been implicated in the spread of diseases such as BVD [42,43], which also explains the high perceived effectiveness score this measure has received for this particular disease.
Vaccination was rated as being of no or low importance for all cattle diseases. This was to be expected since Switzerland generally implements a non-vaccination policy. However, for BT virus this was surprising as vaccination led to a notable reduction of BT outbreaks from 2008 on, following the introduction of the disease in 2007 [3]. Since at the time of the expert opinion BT was already eradicated in Switzerland, one might assume that the experts downgraded the importance of vaccination against this disease. Nevertheless, vaccination against BT virus was still rated as effective, which might reflect that the experts are aware of the protective potential of the vaccine, but do not wish to vaccinate at all. The biosecurity category "contact to the outside world" was also rated as being of low importance for cattle farms. This is not surprising since free ranging is a common practice for cattle farming in Switzerland. Nevertheless, maximum disagreement was observed on the perception of the effectiveness of individual measures within this category, especially for FMD, which might have resulted from differences in expert knowledge.
For swine farms, measures relating to animal movements were perceived as being the most important and effective. In a country like Switzerland, where movements and mixing of pigs are generally very intensive, this was to be expected. Indeed, movements of domestic and wild animals play a central role in the spread of diseases [44]. As for cattle diseases, vaccination of pigs was rated as not being important. Prevention of contact with wild animals was rated as very effective for ASF and EP, which can be explained by the role wild boars might play in the transmission of these two diseases; however, the role of wild boars in the persistence of these pathogens in pigs is being questioned [45,46]. The perceived importance of some biosecurity measures differed significantly between cattle and swine experts; in all of these cases, higher scores were given by the swine experts. This, in turn, might reflect the stronger focus on biosecurity for swine farms. As an example, for the measure "quarantine animals after market/show", this is possibly related to the fact that, at least in Switzerland, it is considered unacceptably risky to bring back to the farm pigs that have been to exhibitions; in the rare cases that this is done, strict quarantine measures have to be applied. The measure "prevention of contact with wild animals" is again more relevant to swine biosecurity because of the risks imposed by the increasing number of wild boars in Switzerland [47]. The same could indirectly be true for "geographical barriers", which can restrict movements of wild boars. "Rodent control" might reflect the risk for transmission by rodents of Salmonella species, Yersinia species and other important zoonotic pathogens [48]. The measure "low animal density in the area" could be linked to the potential for disease outbreaks in areas of high livestock density, as was the case with CSF in The Netherlands [49]. The recent outbreak of PRRS caused by the import of boar semen from Germany into Switzerland might account for the high scoring of the perceived importance of the measure "no breeding animals, transport vehicles and equipment shared with other farms" by swine experts [50].
Despite some, mostly disease specific differences, the overall tendency of the experts was to rate the majority of the measures as being rather effective. Of all diseases, FMD in cattle, as well as PRRS and FMD in pigs, have received the highest values on the effectiveness of individual measures, whereas biosecurity appears according to the experts not to be very effective for vector-borne diseases such as BT. The strong correlation between the assessment of the perceived effectiveness for BVD and IBR in cattle, as well as for ASF and FMD in pigs (both with r s = 0.8) might reflect the similarities in the epidemiology of these diseases. The estimation of the effectiveness of biosecurity measures has been reported to be negatively correlated to the potential for aerosol transmission [18]. This was not observed in the present study, in which measures were perceived as being the most effective on FMD virus, a pathogen that can readily be transmitted through the air over great distances [51]. Since FMD is a highly contagious and a muchfeared disease, countermeasures are very important, but some might not be very effective in preventing aerosol spread. A possible explanation for the high scoring of the perceived effectiveness of biosecurity measures by the Swiss experts is that, people who have never experienced a particular disease and do not feel endangered thereof, tend to assess the effectiveness of biosecurity measures higher than people who have experienced an outbreak [18]. Switzerland is officially declared free from five (BT, FMD, ASF, PRRS, IBR) of the seven diseases investigated in this study.
Expert opinions are an established method for gathering knowledge in the absence of data. In our study, it was not surprising to observe that, recently emerged or endemic diseases in Switzerland such as BT and EP were perceived by the experts as best known, whereas exotic diseases such as ASF were perceived as the least well known. In other studies, the results of the self-evaluation have been used to weight the assessment scores [52]. We decided against it, in the belief that the subjectivity of a self-evaluation outweighs its information content. In addition, self-evaluation might not be a reliable predictor of expert performance [32].
We decided not to include any weighting in this study however, for several biosecurity scoring systems assigning weight to individual measures was a key point [53][54][55][56]. For most biosecurity measures, deciding on a logical weighting principle is hampered by the lack of data, whereas equal weighting poses the risk of under-or overestimating the contribution of certain biosecurity measures in reducing disease transmission.
A greater number of experts would have increased the study power, however this was difficult to achieve in a small country like Switzerland, with a limited number of animal health experts. In order to capture biosecurity knowledge in Switzerland, we included veterinary experts covering a wide range of expertise within the interdisciplinary field of livestock production [32]. Broadly defined expert groups have been reported to increase the accuracy of expert advice [57] however it may also have contributed to the wide range of answers, as it was observed in this study. Furthermore, because of the limited sample size, the estimation of the perceived importance and effectiveness of the measures is not exact and the ranking of biosecurity measures is not absolute.
We calculated ICC, to investigate the influence of each expert on the variance in scores. With the ICC values for the measures being consistently larger, it can be concluded that the variance in scores was influenced more by the question itself (importance/effectiveness of a particular biosecurity measure), rather than by the personal opinion of the expert.
Inconsistency in the definition and application of the term biosecurity may also have contributed to the rather wide range of expert scores for certain measures. For some experts, the inclusion of both prevention of introduction and spread in a single definition of biosecurity, may have caused some confusion and therefore inconsistency in their answers. Some biosecurity measures were probably ranked by the experts only with regards to prevention of introduction, such as for "access restriction for visitors" or, with a stronger focus on the prevention of spread, such as for "quarantine animals after market/show". This may have been avoided by differentiating between internal biosecurity (the prevention of spread within a herd; sometimes referred to as biocontainment) [58] and external biosecurity (the prevention of introduction of pathogens into a herd) [59]. Although both, internal and external biosecurity measures were included in our study, the distinction between the two concepts was not addressed explicitly. It was our opinion that leaving these definitions out would make the opinion process shorter, less complex and more attractive to experts and that this would outweigh potential imprecision in the study results. For the same reason, the number of measures was kept at a minimum by consolidating related measures into single measures. For example, the measure: "minimize purchase and sale of animals", is a consolidation of two measures, one referring to "purchase" and another to "sale". For some measures, this may have caused some confusion and introduced variability. For example, the measure "disposal of carcasses and manure" left some experts (3/ 16) unsatisfied as they saw a greater risk associated with carcasses than with manure. Asking experts to evaluate these two measures as one, may have resulted in the perceived importance or effectiveness of carcass disposal being underestimated, and, that of manure disposal being overestimated.
Most experts (14/16) agreed that the list of biosecurity measures was exhaustive. Additional measures were proposed by only two swine experts. Measures concerning artificial insemination were not listed, with the idea that the risk of transmitting disease when using a bull or boar for mating is even higher than with artificial insemination. Bringing new genetics into a herd always carries the risk of pathogen introduction and for this reason, reproduction is included in the categories of "animal movement", "animal contacts" and "contact to the outside world". The measure "quarantine animals after market/show" was especially difficult to assess for swine experts (3/8 skipped this measure) since it is uncommon in Switzerland to bring pigs back to the holding after attending markets/shows, and for biosecurity reasons it would be preferable not to attend markets/shows at all.
Another challenge arose from the lack of a common agreement about the definition of individual biosecurity measures. "Geographical barriers" is not commonly considered to be a biosecurity measure, but geographical barriers can contribute to preventing infectious agents from spreading. Similarly, "minimize purchase and sale of animals" is not always classified as a biosecurity measure; however, it is known to be of major importance for disease introduction. Quarantine is defined as the isolation of animals that are either infected or suspected of being so, or of non-infected animals that are at risk [1]. Recommendations for implementation of quarantine as a biosecurity measure vary in duration and degree of separation, making a general assessment of quarantine difficult. Some experts (2/16) in this study suggested that quarantine should be extended to include periparturient animals in addition to sick and newly introduced animals. Harmonized definitions of (on-farm) biosecurity measures would facilitate future research and the development of standardized, evidence-based recommendations.
Differentiating between perceived importance and effectiveness of measures was essential for gaining a clear understanding of the biosecurity measures that should be promoted within Switzerland. The term "importance" was introduced in order to include aspects that are country specific. For example, vaccination against FMD is effective for preventing or controlling an outbreak, but it is not considered an important measure in Switzerland, as current Swiss legislation prohibits its application. In an attempt to prevent confusion, both the definitions of importance and effectiveness, and the expert opinion process were explained to experts and provided in written form. Furthermore, experts were allowed to ask questions, and were given as much time as needed to complete their opinion. Nonetheless, the distinction between "importance" and "effectiveness" proved to be challenging to some experts, and may have contributed to the variability in some of the answers.
Conclusion
This study provided some valuable information on the perceptions of veterinary experts on the importance and effectiveness of biosecurity measures for cattle and swine farms in Switzerland. Farmers' disease awareness and animal movements were identified as core components for safeguarding cattle and swine farms from infectious disease. While the perceived importance of biosecurity measures is specific for Switzerland, the perceived effectiveness of these measures could also be useful to other countries since it relates to the nature of the disease and is thus not country specific. Moreover, this study has also identified some important points that need to be considered when planning an expert opinion on this field. One of the greatest challenges for the experts was the distinction between the terms "importance" and "effectiveness" of biosecurity measures. Furthermore, the study has highlighted the need for more precise and commonly accepted definitions of biosecurity measures. The partially broad range of the expert opinions also raises the demand for further research on the effectiveness of biosecurity measures. This would facilitate communication to farmers and policy makers on the value of onfarm biosecurity. | v3-fos |
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} | s2 | Kiwi fruit (Actinidia chinensis) quality determination based on surface acoustic wave resonator combined with electronic nose
In this study, electronic nose (EN) combined with a 433 MHz surface acoustic wave resonator (SAWR) was used to determine Kiwi fruit quality under 12-day storage. EN responses to Kiwi samples were measured and analyzed by principal component analysis (PCA) and stochastic resonance (SR) methods. SAWR frequency eigen values were also measured to predict freshness. Kiwi fruit sample's weight loss index and human sensory evaluation were examined to characteristic its quality and freshness. Kiwi fruit's quality predictive models based on EN, SAWR, and EN combined with SAWR were developed, respectively. Weight loss and human sensory evaluation results demonstrated that Kiwi fruit's quality decline and overall acceptance decrease during the storage. Experiment result indicated that the PCA method could qualitatively discriminate all Kiwi fruit samples with different storage time. Both SR and SAWR frequency analysis methods could successfully discriminate samples with high regression coefficients (R = 0.98093 and R = 0.99014, respectively). The validation experiment results showed that the mixed predictive model developed using EN combined with SAWR present higher quality prediction accuracy than the model developed either by EN or by SAWR. This method exhibits some advantages including high accuracy, non-destructive, low cost, etc. It provides an effective way for fruit quality rapid analysis.
Introduction
Kiwi fruit (Actinidia chinensis) is a valuable source of vitamins, 1,2 fats, proteins, amino acids, dietary fibers and rich minerals (such as calcium, iron, pectin, etc). It is widely cultured in south Asia and Southeast Asia and China is its main producing area. Apart from its edible and medicinal values, the emodin extracted from its root has broad applications in medicine, health care, and other fields. 3 The leaching solution extracted from its branches is a good source of adhesive colloid. 2,[4][5][6] Moreover, due to its unique ability for human to regulate emotion and enhance appetite, Kiwi fruit is very suitable for patients suffering from gastric, hypertension and other diseases.
Ripe Kiwi and other fruits are more vulnerable to many factors from both environment and itself. As a result, fruit quality decline or even rot occurs during the storage. 7,8 Human sensory evaluation method can directly discriminate Kiwi fruits with different qualities. However, its result is often affected by various factors, such as individual preference, health situation, physiological age, etc. Physical/chemical examining method, such as firmness, microbial, etc, effectively reveals fruit's quality condition. Nevertheless, these measurements cover some drawbacks including fuzzy operation, low repeatability, high cost, and too much time consuming, etc, which makes it unsuitable for rapid quality analysis. [9][10][11] Instrument analysis method, such as gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS), presents food quality with precise analysis abilities. However, some disadvantages exist in these methods, such as high cost, time consuming, etc. In addition, only skilled operators are required to perform the instrumental analytical experiments. 12 So, there is an urgent demand for developing a rapid quality analysis method with quick response, high accuracy, and low cost in fruit area.
Surface acoustic wave (SAW) is first proposed in 1970s and it provides the basis for making highly integrated devices with small size and high sensitivity. [13][14][15][16][17][18] So far, there are many reports about detection applications about SAW in terms of many fields especially in food analysis, such as monitoring of the growth of bacteria, detection of pancreatic lipase, and biomedical analysis, etc. [19][20][21][22] Currently, more and more researches focus on the chemical/biological modification about surface acoustic wave resonator (SAWR). If specific reaction (such as antigen-antibody, receptor-ligand interaction, etc) occurs during the processing, some information about wave (velocity, for example) will change accordingly when SAW passes the piezoelectric substrate resonator, which realizes the characterization about test sample's species and concentration. However, there are also some defects within this technique, to illustrate, SAW devices are often used only one time after modifying, which results in high testing cost. [23][24][25] EN technique, simulating human's olfactory system, is a method regarding odor fingerprint detection. 26 A traditional EN system consists of 3 main functional parts: gas sensor array, signal preprocessing and pattern recognition. It chooses gas as analysis object and obtains characteristic signal. It could real-time capture and examine aromatic substances from specific positions, so it is called EN figuratively. Because of its particular functions, it has applied to food, makeup, petrochemicals, packaging material, environmental inspection, clinic, chemistry, etc. [27][28][29] In this study, EN combined with a 433 MHz SAWR was utilized to examine the responding signals of Kiwi fruit with different storage time. Human sensory evaluation and weight loss examinations were performed to characteristic Kiwi fruit's freshness. The PCA method could qualitatively discriminate Kiwi samples with different storage days. Both SR and SAWR frequency analysis methods could discriminate all samples with high regression coefficients. The validation experiment result demonstrated that the built predictive model based on EN combined with SAWR present higher prediction accuracy than the model built based on EN or SAWR. The proposed method in this research takes some unique advantages including fast response, non-destruction, high accuracy, etc. The proposed method is promising in fruit quality analysis.
Results and Discussion
Human sensory evaluation Kiwi fruit's human evaluation result is shown in Figure 1a. Kiwi fruit sample's initial score is set at score of 5 and score of 3 is regarded as the limit of overall acceptance. There is no obvious change observed in Kiwi fruit samples within the first 4 days. After that, it exhibits a significant quality decline trend in the following days. In day 8, the preference score is 2.98 § 0.13, which indicates that Kiwi fruit is severely spoiled and it loses commercial and edible values. Owing to the influences of microbial infection and self-physiological metabolism, Kiwi fruit's quality changes significantly with the increase of storage time, including increasing losses of moisture, color, roughness and glossiness, softer touch, severer rot degree and much more cracks. Therefore, human sensory evaluation can classify Kiwi fruits with different qualities.
Weight loss
Kiwi fruit's weight loss result is shown in Figure 1b. There is no significant change can be seen within the first 2 days. After that, it shows a continuous increase trend and reaches approximate 5% in day 12. During the storage, living cells in Kiwi fruit still precedes strong respiration along with some internal physical/chemical reactions. As a result, considerable moisture loses in Kiwi fruits, which results in Kiwi fruit's weight loss increase with the increase of storage days. Some researches have also reported similar results in other fruits. [30][31][32] Freshness predictive model based on SAWR measurement result SAWR frequency measurement is performed by following processing: first, connect Kiwi sample with SAWR system, then use frequency meter to collect its frequency value, next, transfer the data to a computer through a RS-232 communication interface. The data can be read real-time by self-PC software. The SAWR frequency detecting result is shown in Figure 2a.With the increase of storage time, Kiwi fruit's SAWR frequency increases continuously. The initial frequency value is about 260 MHz, while it reaches about 440 MHz in day 9. Different frequency values are obtained, corresponding to different storage days. The result shows that the SAWR detecting system has high sensitivity toward Kiwi fruit samples with different storage time.
Due to the different dielectric characteristics of Kiwi fruits with different qualities, samples would significantly influence SAWR current frequency when it is in serial with SAWR circuit. According to equation (1), SAWR's frequency value finally rises due to the significant increase of Re and decrease of conductivity (G e D 1=R e ). Although the dynamic capacitor parameter (Ce) also changes during the whole processing, it has weak impact on SAWR frequency responses than Re. So it can be neglected.
According to the result shown in Figure 2a, the relationship between output frequency (Freq) and storage time (Time) is obtained after linear-fitting and shown as equation (1): After one-time conversion to equation (1), Kiwi fruit's freshness predictive model is acquired based on SAWR and expressed as equation (2): With the help of equation (2), it can realize the prediction about Kiwi fruit's storage time based on SAWR system.
To validate the robustness of the predictive model, a batch of Kiwi fruit samples with unknown storage time was examined using SAWR system and the detected frequency value was set as true value. The predicting values were obtained by inputting the detected values into equation (2). The linear fitting result between predicting value and true value is shown in Figure 2b with regression coefficient R 2 D 0.865, which demonstrates that SAWR cannot efficiently discriminate Kiwi fruit samples and partial samples bring about major errors.
The PCA result, freshness predictive model, and the validation experiment results based on EN EN original responses to Kiwi fruit samples are shown in Figure 3a. The volatile gases existing in the headspace of samples are inhaled into EN gas chambers and sensed by the functional materials settled in gas sensors. The specific absorption of function materials for specific gas species induces materials' changes in their electrical characteristics. And the responses rise accordingly with the growth of gas concentration. So signals induced by electrical changes can be used to characterize gas concentrations. What's more, 8 gas sensors give different responses due to their different sensing abilities for specific gas species. So EN sensor array forms different responding pattern for Kiwi fruits with different storage days. EN system's unique functions have been confirmed such as analysis of aroma compounds of commercial cider vinegars, 33 composition of commercial truffle flavored oils, 34 detection of adulteration in cherry tomato juices, 35 etc.
All sensors' initiative responses to Kiwi fruit are close to zero. All sensors' response values increase gradually and finally reach individual stable value. Sensor S4 presents the maximal stable value (about 0.095 V). The final stable value of S1, S5, S7 and S6 is about 0.058, 0.028, 0.020 and 0.010 V, respectively, while the rest 3 sensors (S3, S8, and S2) present weak responses to all samples.
Kiwi fruit's PCA result is shown in Figure 3b. The first principal components (PC1) and the second principal components (PC2) capture 91.06 % of data variance. Five sensors' response values (S1, S4, S5, S6 and S7) to Kiwi fruit are chosen as sample's whole freshness eigen values. Kiwi fruit samples with different storage days can be well distinguished by the PCA method. However, this method is not suitable for quantitative discrimination. 36,37 Kiwi fruit's SNR spectrum calculated by SR as function of external noise intensity is shown in Figure 3c. Derivative vales arise before the formation of eigen peaks for Kiwi fruit samples with different storage days. After that, SNR value increases gradually with the increase of stimulating noise intensity. Each eigen peak appears at noise intensity of 208 or so. Sample' SNR-Max Furthermore, a batch of Kiwi samples with unknown storage time was examined using EN system. Kiwi fruit's SNR spectrum calculated by SR was input into equation (4) and the predicting values were calculated. The result is shown in Figure 3e with regression coefficient R 2 D 0.939, which indicates that the SNR spectrum can achieve the goal of freshness prediction about Kiwi fruits, but partial samples present low predicting accuracy.
Freshness predictive model and the validation experiment results based on EN combined with SAWR
Based on above 2 model's properties, a new predictive model was proposed to predict Kiwi fruit's storage time combining EN with SAWR system. Two confidence coefficients (P 1 andP 2 ) were preset. By inputtingFreq,SNR and Time values into equation (5), the result is that P 1 D 0:5153; P 2 D 0:4726. By inputting P 1 and P 2 values into equation (5), a mixed predictive model based on EN combined with SAWR is built and the result is shown in equation (6) Next, a batch of Kiwi fruit samples with unknown storage time was examined using EN and SAWR system. A series of SNR and SAWR frequency eigen values were recorded and input into equation (6). The linear fitting relationship between predicting value and true value is shown in Figure 4. The regression coefficient RD0.998, which suggests that EN in combination with SAWR system could better predict Kiwi fruit's quality and freshness. In addition, the combination of EN and SAWR technique applied in many other areas also exhibits some significant benefits. 38,39 From the aspect of non-destructive detection, 3 predictive models were built to predict Kiwi fruit's quality. SAWR detection result reflects Kiwi fruit's internal information, while EN analysis result reveals Kiwi fruit's external message, thus this combination could better deliver Kiwi fruit sample's whole change during storage. This technique is promisingly used to guide fruit's optimal harvest time, which is of great use to reduce economic loss due to fruit's nutrition decreases. What's more, we decide to conduct further research work in the near future and apply this technique for fruit's best picking period judgment.
Materials and Methods
Kiwi fruit samples Kiwi fruit samples were purchased from Gouzhuang wholesale fruit market (China, Hangzhou province). The samples were nearly in the same level of quality (such as size, weight, and
Human sensory evaluation
As the method previously described, 40 Kiwi fruit sensory evaluation was evaluated by 6 experienced panelists in our lab. Voting number is set at k, k 2 (1,10). Kiwi fruit's quality is divided into m levels, and the score of a specific level is set at h, j 2 (1, m). Kiwi fruit attributes are divided into n elements, and a specific element is set at u, i 2 (1,n). The contributory weight is determined by pairwise comparison of contribution weight of attributes is set at x( P x i D 1). If there is a specific relationship between 2 objects of hand u, the relation set (matrix) of f is calculated as follows: Thus, the overall acceptability of Kiwi fruit is calculated by the weight grade method as follows: Kiwi fruit's sensory evaluation method is shown in Table 1.
SAWR series of testing device SAWR system and its load circuit were self-developed in our lab. As it shown in Figure 5a, ST cut type quartz was taken as the piezoeletric base material. And precision photolithographic process was conducted to make a 433 MHz high-frequency and single-ended SAWR. It's outer size was 4.5mm£11mm. Vacuum pack was adopted to package SAWR. Figure 5b is a schematic diagram of detecting system, which consists of SAWR and its load circuit, stabilized power supply (DF1741SB3A, Ningbo CSI Electronics Co., Ltd), and universal counter (EE 3386, Jiangsu New Union Technology Co., Ltd). The experiment was performed as following process: connecting Kiwi samples to SAWR circuit, putting them into a metal shield box, then capture the load frequency from SAWR by the universal counter and transfer it to the computer via RS232 communication interface for subsequent analysis. Figure 5c, where Co is a static capacitor, Ls, Cs and Rs represent dynamic inductance, capacitance and resistance of SAWR, respectively. When Kiwi frit sample connect to SAWR, Ce is an equivalent dynamic capacitor and Re is an equivalent dynamic resistance of sample. The frequency of SAWR loaded with Kiwi fruit sample can be calculated by following formula:
Equivalent circuit model of SAWR in serial with Kiwi fruit samples is shown in
In equation (9), SAWR's unloaded frequency F 0 D 1=2p ffiffiffiffiffiffiffiffiffi L s C s p , Y is amplification circuit's phase parameter, analyte's conductivity G e D 1=R e , electrode capacitance C e D ke C C p , where e is a permittivity, and C p is parasitic capacitance between wires. These parameters keep highly stable, so R e , C e and e become decisive factors to oscillation frequency. So, if Kiwi fruit samples with different quality are connected to the circuit, the changeable parameters (including R e , C e and e) will directly lead to the differences of SAWR's working condition and frequency.
With the rapid development of SAW technique, it has been widely employed including the distinct detection of ammonia, 41 high-speed gap measurement, 42 hydrogen detection, 43 etc.
EN detection system
In recent years, EN detection technique has aroused increasing research interest, especially in food, such as vinegars, 44,45 truffle flavored oils, 34 cherry tomato juices, 46 Chinese green tea. 47 As it shown in Figure 6, EN system's structure consists of 3 main components: signal control and its collection (U1), sensory arrays (U2) and gas supply device (U3). The experiment was performed as following processing: first, open clean pump and valve 2 to absorb clean air for washing all sensors. Next, close the clean pump and valve 2 when all sensors' responses stabilize at baseline. Then put Kiwi fruit sample into a clean vial and seal them with parafilm. After standing for 30 min, sampling probe and pneumatic balancer were simultaneously inserted. Then turning on EN system, the sampling time lasted for 45 s. Pneumatic balancer insulated impurity gas and absorbed clean gas into the vial via active carbon, which realized pressure balance. Eight metal oxide semiconductor (M.O.S) gas sensors were adopted to constitute array units. And their detailed parameters are shown in Table 2.
Weight measurement A Mettler Toledo AL104 electronic balance was used to measure Kiwi fruit sample's weight during 12-day experiment. And sample's weight loss percentage (%) was reported with respect to the initial weight.
PCA
Principal component analysis (PCA), as a pattern recognition technique, has proved to be effective for discriminating between the responses of e-nose to complex gases. [48][49][50][51] So PCA method was used to analyze the EN data.
SR
Stochastic resonance (SR) is a non-intuitive phenomenon, which provides enhancement in a nonlinear noise system and attracts more and more attention in the field of signal processing. 52-54 SNR from the output signal is used to describe SR usually. There are 3 factors existing in SR system: a bistable system, an input signal and an extra noise source. Currently, overdamped Brownian motion particle driven by cycle power in a bistable potential well is used to represent the characteristics of the system.
www.tandfonline.com real parameter, V .x/ D 0:25ax 4 ¡ 0:5bx 2 (11) Thus, equation (10) can be rewritten as: Nowadays, what can reflect SR's characteristics most commonly is SNR, and here we define SNR as: S.v/ and S N .V/ represent signal spectra's density and noise intensity within the extent of signal frequency, respectively.
Conclusions
A rapid freshness predictive model for forecasting Kiwi fruit's storage comes up in this study. Kiwi fruit's weight loss percentage increases with the increase of storage time, which indicates moisture loss in samples is significant. Human sensory evaluation also demonstrates that Kiwi fruit's overall acceptance declines significantly during the whole experiment. Three freshness predictive models about Kiwi fruit based on SAWR, EN, and EN combined with SAWR, correspond to Time SAWR D Freq (R 2 D0.998), respectively. Compared with 3 models' prediction accuracy, it is clear that the mixed predictive model presents higher prediction accuracy than the model developed based on EN or SAWR and the validation experiments also validate this fact.
Furthermore, the proposed technique lowers the detection cost for SAWR. The SAWR detection method proposed in this study has following advantages: test sample works as a SAWR load, while SAWR device works as a stable frequency supply, which reduces one-time use waste. From another aspect, the variations of working frequencies must exist in most SAWR devices even produced in the same bath. Therefore, this method eliminates some basic errors due to the replacement of SAWR, which contributes to improving experiment accuracy. SAWR detection result reflects Kiwi fruit's internal information, while EN analysis result reveals sample's external message, so this combination could real-time monitor and deliver Kiwi fruit real change during storage. This method is promising for judging fruit's best harvest time including rapid response, good repeatability, low cost, etc.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed. | v3-fos |
2019-04-25T13:10:37.957Z | {
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} | s2 | Efficiency of Atmospheric Pressure Nitrogen Gas Remote Plasma Sterilization and the Clarification of Sterilization Major Factors
Experiments reported here were conducted using atmospheric nitrogen gas remote plasma with a pulsed power source. The sterilization efficiency, major sterilization factors and most appropriate sterilization conditions were determined. By varying several factors such as hotplate temperature, relative humidity, water vapor supply location, etc., the most appropriate sterilization conditions were identified. The temperature of the hotplate was varied from 55°C to 75°C and with this 20°C increase in temperature, sterilization was completed in half the time. In this experiment, it was confirmed that the combined effect of a relative humidity (RH) of 0.5% and nitrogen gas was superior to the use of nitrogen gas alone. Furthermore, it was clarified that the optimal humidity was in the range of 0-5 % RH. When RHs of 0, 0.5 and 5% were tested, 0.5% RH was found to be optimal for sterilization. The location of the water vapor supply was changed relative to the hotplate, and use of the most remote port upstream of the reactor resulted in the most efficient sterilization. In addition, the results correlated with the amount of NO radicals generated. The NO radical is the precursor of OONO・(peroxynitrite anion radical). The sterilization factors associated with this experiment were NO radicals, H2O2, OH radicals, O2 ・(superoxide anion radicals) and OONO・only OONO・production correlated with sterilization efficiency. Therefore, OONO・is thought to be the major factor for nitrogen gas plasma sterilization. In addition, as already described, the highest sterilization efficiency was with 0.5% RH and the amount of OONO・produced correlated with the RH. These data support the idea that OONO・is the major contributing factor for nitrogen gas plasma sterilization. The D values for this experiment were approximately 10 min. *Corresponding author: Hideharu Shintani, Department of Science and Engineering, Chuo University, Kasuga Bunkyo 112-0003, Tokyo, Japan, Tel: +81338171733; E-mail: shintani@mail.hinocatv.ne.jp; hshintani@jcom.zaq.ne.jp Citation: Shintani, H., et al. Efficiency of Atmospheric Pressure Nitrogen Gas Remote Plasma Sterilization and the Clarification of Sterilization Major Factors. (2015) J Pharm Pharmaceutics 2(1): 2228. Efficiency of Atmospheric Pressure Nitrogen Gas Remote Plasma Sterilization and the Clarification of Sterilization Major Factors Hideharu Shintani1*, Naohiro Shimizu2, Shouji Tange2, Nobuo Takahashi2, Akikazu Sakudo3, Akira Mizuno4, Eiki Hotta5 Received date: April 17, 2015 Accepted date: November 18, 2015 Published date: November 24, 2015 DOI: 10.15436/2377-1313.15.004 Journal of Pharmacy &
Introduction
Several papers have been published on gas plasma sterilization [14,11,19,20]. The definition of sterilization can be found in the book published from NOVA [11]. The advantages of gas plasma are that sterilization with a sterility assurance level (SAL) of 10 -6 and material/functional compatibility can be attained without any difficulty. This is because the penetration depth of gas plasma sterilization is quite shallow (10-20 nm, [19]) and therefore only one layer of bioburden can be sterilized. The bioburden represents the type and number of viable microorganisms existing in/ on products. Most of the bioburden exists as one layer; therefore, deeper penetration capability is unnecessary for efficient sterilization.
In contrast, existing sterilization procedures including gamma-ray irradiation sterilization, electron-beam sterilization, moist heat sterilization, dry heat sterilization, ethylene oxide gas sterilization, hydrogen peroxide gas sterilization and so on, have the ability to penetrate deeper. Therefore, materials are easily sterilized using these methods and a SAL of 10 -6 can be attained; however, the sterilized products are useless due to degradation of the product material during the sterilization process, a phenomenon called failure to attain material/functional compatibility [16,17]. Good manufacturing practice (GMP) and sterilization guidelines require simultaneous attainment of both a SAL of 10 -6 and material/ functional compatibility, but this requirement is difficult to attain with the existing sterilization procedures. Therefore, sterilization procedures using stable gases that are safe to handle and that have shallow penetration depths are needed. As described previously, gas plasma sterilization has the characteristics necessary to meet these requirements [14,11,19,20] .
For the studies reported here, we used a remote type of nitrogen gas plasma sterilization procedure using a pulsed power supply of SIThy [13]. Several factors associated with the sterilization procedure were determined, and the main factors associated with sterilization were identified. In addition, appropriate sterilization conditions were identified and are reported herein.
Experimental
In Figure 1, the schema of the experimental system is shown.
Remote gas plasma was utilized. The experimental system consists mainly of a humidity control device, plasma producer, and exhaust gas analyzer.
In Figure 2, a photograph of the plasma generator parts is presented and the experimental conditions are presented in Table 1. A detailed explanation of the experimental conditions can be found in the Master's thesis of Takuya Uyama (TISTech, 2015). Figure 3 presents the typical waveforms obtained when using the experimental conditions in Table 1.
The relative humidity (RH) was measured at the upper and lower sites of the reactor with BKPRECISION Ltd., 725 digital temperature/humidity sensors. Exhaust NOx gases were determined using a Shimadzu NOA-7000 analyzer and exhaust ozone gas was determined by using an EG-700EIII ozone monitor from Ebara Ltd. Table 1. Samples to be sterilized, including a biological indicator (BI), were placed on a hotplate (Figures 1 and 4). The distance between the reactor and hotplate was kept constant at 100 mm ( Figure 1). The temperature of the hotplate was varied from 55-75°C ( Figure 8).
Nitrogen gas was chosen for use in these sterilization studies because of its higher dissociation energy, which makes it relatively stable compared with other gases, and therefore it is inert and safe to handle ( Table 2).
The need for humidity in gas plasma sterilization has been reported [2,21]. A supply of water vapor was introduced at three locations as shown in Figures 4 and 5. The site of water vapor introduction was varied because water vapor can play a role in generating various reactive oxygen species that may function in the sterilization process. Location was at the upper part of the reactor, location was just below the reactor, and location was just before the site of sample treatment. At location , NO radicals, which are actively involved in the sterilization process, may be produced [15,18]. In location , it can be speculated that N metastables or other reactive oxygen species (ROS) may be generated by reactions with water vapor. In location , short-lived OH radical may attack the biological indicator (BI) and result in its sterilization. The actual experimental set up with the different positions of water vapor introduction is shown in Figure 5.
Sterilization evaluation was confirmed by using a BI of Geobacillus stearothermophilus ATCC 7953 with 10 6 CFU (colony forming unit)/carrier, which was obtained from MESA Lab. The D value (decimal reduction value) was obtained by two methods, the fraction negative method and survivor curve method [3,4]. In the case of the fraction negative method, the BI was incubated using SCDB (soybean casein digest broth) liquid medium at 58°C for 2 days. The result was confirmed using a chemical indicator (CI, Figure 6). When the BI survived, the color changed to yellow, whereas when sterilization was successful, the color remained unchanged (purple). This is due to the production of organic acids (mostly citric acid) from the TCA cycle ( Figure 6). To generate the survivor curve, we used SCDA (soybean casein digest agar) solid medium. Ten-fold serial dilutions using SCDB were carried to achieve final plate counts of 30-300 CFU/plate as required in ISO 14161. Spores were retrieved from the BI carrier by using the procedures described in ISO 11737-1. According to ISO 11138-1, the D value must be obtained using both the fraction negative method and the survivor curve method, so we carried out both methods following the ISO 11138-1 requirement.
Surfaces of spores were observed by using scanning electron microscopy (SEM; S-5500 Hitachi technologies Ltd).
Several reactive oxygen species (ROSs) were analyzed by using emission spectrophotometric analyzers from Maya 2000 Pro (Ocean Optics Ltd.) ( Figure 7). A quartz window was incorporated into the reactor and analyses were conducted under the following conditions. The determination wavelength was 200-650 nm, grating was 600 lines/mm, entrance slit width was 10 μm, exposure time was 100 ms and analyses were repeated 5 times. Production of one type of ROS, H 2 O 2 , has been reported by nitrogen gas plasma sterilization [7,9,10], So we measured H 2 O 2 by using a chemical indicator (CI). The CI for H 2 O 2 analysis was from Quantofix Peroxide 25 (MACHEREY-NAGEL Ltd.) and the analysis range was 0-25 μg/mL.
All analyses described above are presented and explained in the Results and Discussion.
Relationship between Sterilization Efficiency and Hotplate Temperature
As shown in Figure 8, it was determined that the higher the temperature, the greater the sterilization efficiency. From Figure 8, it is seen that sterilization can be completed in 240 min, 150 min and 120 min at 55°C, 65°C and 75°C, respectively. These results indicate that 75°C is the best temperature for sterilization because an increase of 20°C from 55°C to 75°C resulted in a sterilization time that was half as long, and it is expected that the target materials including the BI are tolerant to this temperature.
Relationship between Sterilization Efficiency and Relative Humidity
As shown in Figure 9, the optimum relative humidity (RH) was determined. A RH of 0.5% was the most appropriate for sterilization. This result has been confirmed in another experiments with consistent results.
Determination of NOx and O 3 (ozone) as exhaust gases
NOx and ozone were determined and their amounts were less than 0.6 ppm and 0.04 ppm, respectively. Since the amounts generated were so low, it can be concluded that these ROSs do not contribute to nitrogen gas plasma sterilization.
Relationship between Sterilization Efficiency and Water Vapor Supply Location
As shown in Figure 10, water vapor supply locations and in The tube on the left indicates survival of the BI (acid produced) and that on the right is sterilized (color is unchanged). Figure 4 were superior to that of with respect to sterilization efficiency. The reason in Figure 4 was inferior to the others was likely due to N metastables or OH radicals being inactivated before reaching the BI target. Location in Figure 4 represents the shortest distance between the water vapor supply and the site of sterilization, whereas location in Figure 4 was the most remote, but the abundantly produced NO radicals are the precursors of OONO • -(peroxynitrite anion radicals), which are the real sterilization factors described later. Measurement of NO radicals was conducted using Figures 7 and 14. NO radical detection using CI was also reported by Shintani et al., 2014. Additional results supported the conclusion that water vapor supply location , rather than location resulted in the best sterilization efficiency.
D Value (Decimal Reduction Value) Determination by the Fraction Negative Method
The D value was determined by the Stumbo Murphy Cochran Procedure, one of the fraction negative methods (ISO 14161).
The results are summarized in Table 3. The D value was the lowest at a RH of 0.5% (~ 8.7 min). The others were approximately 10 min, indicating that a RH of 0.5% resulted in the most efficient sterilization. The D value was determined under the following conditions: hotplate temperature, 75°C, RH, 0.5% or 0%, and water vapor supply location or as shown in Figures 11 and 12.
From data in Figure 11, it can be concluded that the use of a RH of 0.5% was superior to 0% RH, as the D was approximately 10 min. Results presented in Figure 12 indicate that water vapor supply location was superior to location , and the D value was approximately 10 min. These data are consistent with the D values obtained by the fraction negative method. The D value from the survivor curve method was determined using a regression line with a coefficient of correlation of greater than 0.8 as required in ISO 11138-1. Figure 13 shows the SEM observation of spores. Compared with the untreated control (left), sterilized spores showed no shrinkage, but some roughness of the surface was observed for spores that were treated for 30 min (middle). However, roughness did not always increase with increasing treatment time up to 90 min (right), indicating that roughness is a temporary rather than permanent phenomenon. It therefore appears that SEM observation does not provide any useful information regarding the success of the sterilization process. Nitrogen gas plasma does not cause any etching in contrast to O 2 gas plasma [20,21].
Emission spectrum analysis
In Figure 14, the emission spectrum at a RH of 0.5% is shown. By using the equipment shown in Figure 7, the emission spectrum can be obtained. NO radicals, N 2 second positives and N 2 + were detected. However, no OH radicals were detected at 310 nm, indicating that OH radicals are not major contributors to nitrogen gas plasma sterilization.
Emission intensity depending on RH at 258.55 nm
A wavelength of 258.55 nm was used for the detection of NO radicals as shown in Figure 14. In Figure 15, the relationship between emission intensity at 258.55 nm and relative humidity is presented. As shown in Table 3, sterilization efficiency was optimal at a RH of 0.5%, indicating that the NO radical itself does not function as a sterilization factor because results in Figure 15 do not indicate that 0.5% RH was optimal. In addition, 258.55 nm is in the UV-C range and UV-C is thought to be effective for sterilization of microorganisms by causing thymine dimer formation. However, no role for UV-C in sterilization could be demonstrated in previous studies using E. coli and Bacillus atrophaeus ATCC 9372 [6,1].
H 2 O 2 (hydrogen peroxide) determination
H 2 O 2 formation was analyzed using a CI from Macherey-Nagel Ltd., and the relationship between H 2 O 2 concentration and humidity is presented in Figure 16. As shown in Table 3, sterilization efficiency was optimal at a RH of 0.5%, indicating that H 2 O 2 or OH radicals from H 2 O 2 do not correlate with the RH tendency; therefore H 2 O 2 or OH radicals do not appear to be major contributors in nitrogen gas plasma sterilization.
Formation of superoxide anion radicals (O 2 • -)
Superoxide anion radicals (O 2 • -) were speculated to be produced at the reactor site and reach the treatment location as shown in Figure 17. NO• and O 2 •were also speculated to be produced even when the water vapor was introduced at location 3, the lowest part in Figure 4, because sterilization was successful at this location.
Measurement of O 2 •was not successful; therefore, its effect on gas plasma sterilization remains uncertain, but it can be speculated that O 2 •supports the production of peroxynitrite anion radicals (ONOO• -) as shown in Figure 18.
Formation of OH radicals (HO •)
OH radicals may be formed by the reaction shown in Figure 18 and/or from H 2 O 2 . However, as shown in Figure 14 and mentioned in section of 8, OH radicals were not detected and therefore OH radicals do not appear to be major contributors to nitrogen gas plasma sterilization.
Evaluation of peroxynitrite anion radical (ONOO • -) Formation
Peroxynitrite anion radicals (ONOO• -) can be formed from NO radicals + superoxide anion radicals (O 2 • -) (Figure 18, Nova E and Parola M, 2008). The reaction in Figure 18 will occur just at the upper layer of bacteria (Figure 19), indicating that NO radicals and O 2 •migrate from the reactor site to the treatment site and react as shown in Figure 18 to produce OONO• -. Figure 12. Relationship between exposure time and colony forming unit at water vapor supply locations and , with a RH of 0.5% and a temperature of 75 o C Location was found to be the most appropriate. The left panel is the control, the middle is after a 30 min treatment and the right is after a 90 min treatment. Roughness did not always increase with increasing treated time, indicating roughness is not always a permanent factor. Reactor O 2 •-produced in the reactor migrates to the treatment location and reacts with NO•, producing ONOO•-just before reaching the BI (Figures 18 and 19).
www.scidoc.org/IJCPT.php
Peroxynitrite anion radicals were detected by using aminophenyl fluorescein (APF) reagent as shown in Figure 20 [12]. The relationship between the peroxynitrite anion radical (ONOO• -) concentration and relative humidity is presented in Figure 21. As shown in Table 3, sterilization efficiency was optimal at a RH of 0.5%, indicating that the peroxynitrite anion radical concentration correlates with the RH level. Based on this finding it can be speculated that peroxynitrite anion radicals function as a major sterilization factor in nitrogen gas plasma sterilization. In addition, please refer to the footnote of Figure 20 for further clarification of ONOO•as a major sterilization factor.
Relation between sterilization efficiency (%) and relative humidity (RH%)
The relationship between sterilization efficiency and relative humidity combined with several ROSs is presented in Figure 22.
The results indicate that sterilization efficiency coincides with the tendency of peroxynitrite anion radical (ONOO• -) formation; therefore, peroxynitrite anion radicals (ONOO• -) are thought to be the major factor of nitrogen gas plasma sterilization. Other factors such as NO radicals, H 2 O 2 , OH radicals or O 2 •-do not co-incide with the % RH (Figures 14-16). Peroxynitrite anion radicals (ONOO• -) react with tyrosine, causing nitration at the p site and with DNA bases, especially guanine, causing nitration (-NO 2 ) and hydroxylation (-OH), which results in transcription failure.
Conclusion
The experiments reported here were conducted to identify the nitrogen gas plasma sterilization factor(s) and the appropriate sterilization conditions. By varying hotplate temperature, relative humidity (RH) and water vapor supply location, sterilization efficiency was confirmed. In addition, SEM observation of spore surfaces, emission spectrophotometric analysis, and determination and evaluation of peroxynitrite anion radicals (ONOO• -) were conducted to determine which ROSs contribute to nitrogen gas plasma sterilization.
The sterilization times at 55°C, 65°C and 75°C were 240 min, 150 min, and 120 min, respectively, indicating that at higher hotplate temperatures, the sterilization periods were shorter. Increasing the temperature by 20°C reduced the sterilization period by half. The sterilization efficiency was improved by using a combination of water vapor and nitrogen gas. Relative humidity (RH) was changed from 0.0% RH, 0.5% RH and 5% RH and the D values under these conditions were 10.71 min, 8.66 min and 10.07 min, respectively, indicating that the optimum RH is 0.5%. In order to identify the sterilization factors, the water vapor supply location was varied. The results indicate that the active species were relatively long-lived because the most efficient location was the most remote from the reactor.
SEM observation indicated that there was no significant difference in the appearance of control and treated spores, and no etching occurred. Treated spores seemed to have increased roughness compared with control spores, but this roughness did not always increase with increasing sterilization time, so roughness is not always an indication of sterilization. The reason has not been clarified, so no ROSs can be confirmed from SEM observation.
By attaching a quartz window to the reactor, it was possible to carry out emission spectrophotometric analysis. Based on the emission spectrum at a RH of 0.5%, NO radicals, N 2 second positives and N 2 + were detected ( Figure 14). In this experiment, NO radicals, which are detected at 258.55 nm in the UV-C range, increased with increasing relative humidity ( Figure 15). This indicates that the tendency of NO radical formation does not coincide with that of the sterilization tendency as shown in Figure 22. This result indicates that NO radicals do not participate directly as a major factor in nitrogen gas plasma sterilization. ROSs such as NO radicals, H 2 O 2 , OH radicals, O 2 • -(super oxide anion radicals) or ONOO• -(peroxynitrite anion radicals) were compared for their contribution to sterilization ( Figure 22). The RH tendency coincided with that of OONO• - (Figures 21 and 22); therefore, we conclude that OONO•may be the major sterilization factor in nitrogen gas plasma sterilization.
Based on the experimental conditions for nitrogen gas plasma sterilization, the water vapor supply position was best at location (furthest from the reactor; Figure 4) and the humidity was optimal at 0.5% RH (Figure 9). Hotplate temperature was optimal at 75°C ( Figure 8). Together these results indicate that higher temperature and optimum RH at 0.5% were the best when using position for the water vapor supply (Figures 10, 11 and 12). All results support the concluding data summarized in Figure 22.
We reported the original description of ONOO• -(peroxynitrite anion radical), and demonstrated that ONOO•is the major factor in nitrogen gas plasma sterilization. In contrast to ONOO• - (Figures 21 and 22), other ROSs do not have identical tendencies with respect to RH (Figure 9, 15 and 16) and only ONOO• presents an identical tendency to the RH. Therefore, ONOO• can be defined as the major sterilization factor in nitrogen gas plasma sterilization. Normalized values [-] | v3-fos |
2019-04-04T13:06:12.426Z | {
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} | s2 | Quality losses in virgin olive oil due to washing and short-term storage before olive milling
To identify critical points during olive mill pre-processing operations, the effect of the closed circuit washing stage on olive microbiological contamination, and the influence of the successive short-term storage on olives and virgin olive oil (VOO) quality were evaluated. Microbiological, physical, and chemical parameters were assessed in olives and oils at three mill pre-processing stages: reception, washing, and short-term storage. Olive washing in closed loop systems was shown to be a critical control point at the olive mill due to microbiological cross-contamination and fruit physical damage. Moreover, when the olives were short-term stored before oil extraction, positive VOO sensory attributes decreased by as much as one point of intensity, as justified by the changes observed in phenolic and lipoxygenase derived volatile compounds. These results confirm the high risk of fruit cross-contamination due to the poor hygiene of the water used in olives mills to wash olives, and point out the effect on VOO quality of a common practice such as short term silo storage of olives.
Practical applications: The identification of new critical control points within pre-processing operations in ordinary usage, and commonly accepted as good production practices, will contribute to enhance virgin olive oil quality. Preventive actions can be undertaken on the basis of the reported results, such as the control of water hygiene and short term storage conditions.
The figure shows the microbiological contamination of olives during washing with recycled water and during short-term silo storage, and the loss of sensory quality in the correspondent virgin olive oils.
INTRODUCTION 33
The concept of critical production steps has recently been applied to virgin olive oil (VOO) 34 production as a tool to ensure the quality of the product [1]. Several critical points, which must 35 be monitored to allow control of the sensory attributes of the olive oil, have been identified 36 from harvesting to VOO storage. Among post-harvest operations prior to oil extraction, 37 storage of the olives is the step that has been most considered. In the past years, several 38 studies have been carried out to evaluate the effect of long time storage on olive oil quality on 39 the quality of the olives and the oils extracted from them [2][3][4][5][6][7]. The storage periods evaluated 40 range from three days to three weeks at temperatures from 4ºC to 20ºC. The conclusion to be 41 drawn is that storage conditions are crucial for the quality of VOO. However, in most cases, 42 storage for several days could not usually be considered an option; in order to preserve olive 43 quality until processing for oil extraction, it is recommended that storage be short-term (<24h) 44 [8], in keeping with the mill processing capacity. Although short-term silo storage is a common 45 practice adopted to optimize the processing capacity of mills, little information is available on 46 its effect on olive and oil quality. 47 In addition to the effects of storage conditions, recent reports indicate that there is a risk of 48 microbiological cross-contamination at olive mills during washing in closed circuits [9][10][11] and 49 Mac Conkey agar and Pseudomonas on Cetrimide agar supplemented with 100 mg/L 110 cycloheximide (Cetrimide-C). The plates were incubated at 30 °C during 3-5 days and viable 111 counts were expressed as log cfu/g olive. Analyses were performed in triplicate. 112
Virgin olive oils quality indices and sensory analysis 113
Free acidity, coefficients of specific extinction at 232 and 270 nm (K 232 and K 270 ), and peroxide 114 value (PV) of VOO samples obtained from the assay were determined in analytical duplicate 115 according to regulation (EU) No 1348/2013 [16]. Vichi et al. [18]. Briefly, 2 g of oil spiked with 4-methyl-2-pentanol (internal standard; final 126 concentration 1.5 mg/kg), was weighed into a 10 mL vial fitted with a silicone septum. The vial 127 was placed into a water or bath fixed at 40 ºC, where the sample was maintained under 128 magnetic stirring (700 rpm). After 10 minutes of sample conditioning, a DVB/CAR/PDMS fiber 129 was exposed during 30 min to the oil headspace and immediately desorbed in the gas 130 chromatograph injector. Each extraction was performed in duplicate.
Olive quality parameters 174
Olive mill pre-processing operations had a remarkable influence on the physical and hygienic 175 conditions of the olives. First, the integrity of the olives ( Table 2) was assessed by visual 176 examination (n=100 for each sampling) and computing bruised, squashed and fermented 177 fruits. The initial incidence of injured fruit, corresponding to real conditions of handpicking and 178 transport, is relatively high because it comprises also injuries of very low intensity. The is given by the initial differences between olive batches, and it is in turn explained by the 181 differences in the maturity of olives from the different batches. The incidence of damaged 182 fruits progressively increased through the pre-processing steps from reception to silo exit, 183 prior to milling. The loss of integrity due to blows during unloading and throughout the 184 washing circuit is especially important if the olives are stored before milling, because rupture 185 of the tissues provides a foothold for microbial growth. During silo storage, healthy olives 186 undergo further damage caused by the weight of olives in the silo and fermentation processes. 187 From the point of view of hygiene, microbiological assays showed that on delivery to the mill, 188 fresh olives intended for oil production presented spontaneous microbiota composed by fungi, 189 lactic bacteria, enterobacteria and Pseudomonas (Table 2), in agreement with previous reports 190 [5,11,12]. At this point, considerable batch-to-batch variability was observed in contamination 191 by Pseudomonas, enteric and acetic bacteria, as evidenced by the high standard deviation. 192 Despite the heterogeneous microbiological profile of the olive batches on reception, the stage 193 of passing through the olive mill washing tank resulted in a significant increase of 194 microbiological contamination, also as previously reported [11]. This additional contamination 195 was fairly similar for the different olive batches, and it remained after short-term silo storage. 196 During this last step, a further increase of lactic acid bacteria was observed. 197 It should be considered that these silo are usually not washed during the harvesting season, 198 with heavy risks for the hygienic aspects of stored fruits. The surfaces of silo can be covered 199 by molds, so the risk of cross-contamination with mycotoxins should be considered in future 200
research. 201
These results confirm the high risk of cross-contamination due to the use of recycled water to 202 wash the olives [9][10][11], and the need to establish critical hygiene control points in olive oil 203 production process 204 Finally, no significant differences in the VOO yield have been found after the distinct 205 treatments ( Table 2), so we can conclude that possible losses of quality would not be 206 compensated by an increase in the production of VOO. 207
Virgin olive oil quality parameters 208
Analysis of the VOOs obtained from olives collected at each pre-processing step did not 209 produce any evidence that olive deterioration had substantial effects on the official VOO 210 quality parameters ( Table 3): all the oils corresponded to the EVOO category, according to EU 211 regulations [16,17]. Indices of oxidative status such as K 270 and PV were lower in the oils 212 obtained after the olives were washed and stored in the silo; in the case of the stored olives, 213 this could be explained by the reducing anaerobic conditions in the silo. 214 Although no sensory defects arose after any of the pre-processing steps, VOO sensory 215 attributes were influenced by the different operations evaluated ( Table 2). In particular, short-216 term silo storage negatively influenced VOO sensory quality by reducing the intensity of the 217 positive attributes, as established in EU regulation [4,17]: fruity, bitter and pungent; as well as 218 other secondary attributes, such as astringency and greenness ( Table 3). In contrast, the ripe 219 fruit (banana, kiwi, strawberry) note significantly increased after this stage. It is worth 220 mentioning that pre-processing operations carried out according to overall accepted practices, 221 caused a decrease of one point of fruity note intensity, which represents a remarkable loss of 222 sensory quality. Although this loss did not determine the declassing the EVOO to lower 223 categories, it would have commercial repercussions. In fact, according to the EU and the IOC 224 Regulations [17,20], some samples of the study passed from a "intense fruity" (fruity>6) to a 225 "medium fruity" (3<fruity<6) classification after olives short-term storage. As far as we know, 226 this is the first report showing the effect of short term silo storage of olives on the quality of 227 VOO. The global fruity attribute, which is the sum of all the fruity notes perceived by the 228 panelists, not only became weaker after short-term storage, but also turned into a ripe fruit note, as evidenced by the increase of this secondary attribute ( Table 2). These results indicate 230 that during fruit storage, at the very beginning of the olive fruit degradation, and before 231 sensory defects or chemical alterations appear, the fruity note decrease and turns into a ripe 232 fruit note. This modification could be induced by several factors including microbiological 233 activity and the slight over-ripening caused by the storage conditions. 234 The reduction of VOO bitterness after olives storage had been previously described and 235 proposed to increase the acceptability of oils with high bitter intensities [4,21]. In the present 236 work, a slight but significant decrease of bitterness, as well as of puncency and astringency, 237 was observed even storing olives during less than 12h ( Table 3). In contrast to experimental 238 findings at the laboratory scale [11], the intensity of the fruity but not of the bitter descriptor 239 was reduced in oils obtained from olives contaminated during the washing step, due to the 240 activity of olive microbiota during the oil extraction process. This could be explained by the 241 fact that in the present study on reception at the mill the olive batches presented a higher 242 microbiological charge than in the assay cited above, so modifications in the microbiological 243 activity induced during the washing stage were less discernible in the extracted VOO. 244
Volatile and phenolic compounds in VOO 245
The alterations of the VOO sensory profile induced by the pre-processing steps can be 246 explained by modification in the VOO volatile and phenolic fractions. Figure 1 illustrates the 247 modifications induced by the pre-processing steps on C6 compounds from the lipoxygenase 248 pathway. It is worth mentioning that not only the short-term silo storage, but also the washing 249 of olives with contaminated water had a significant effect on VOO C6 volatiles, confirming that 250 the activity of olive microbiota influences VOO chemical composition even during the 251 extraction process [11], and justifying the loss of fruity note reported in VOOs from washed 252 olives [12,13]. In agreement with previous results [11], the C6 alcohols hexanol and (E)-2-253 hexenol were more abundant in the oils obtained after olive washing and silo storage, respectively, while (Z)-3-hexenol progressively increased over both stages. C6 acetate esters 255 showed behavior analogous to that of the corresponding C6 alcohols. In contrast, through the 256 pre-processing steps considered in the present study, and in particular after short-term silo 257 storage of the olives, C6 aldehydes hexanal, (Z)-3-hexenal and (E)-2-hexenal showed a 258 progressive and significant decrease. C5 compounds and pentene dimers from the 259 lipoxygenase pathway were also negatively affected both by microbiological contamination 260 during washing and by microbiological activity during storage (Figure 2). Out of these LOX 261 derivatives, 1-penten-3-one, (Z)-2-pentenol and all the C6 compounds were present at 262 concentrations above their perception thresholds [21], excepting (E)-2-hexanol, which was 263 always below the threshold of 5 mg/kg [22]. Interestingly, hexyl acetate, and (Z)-3-hexenol 264 reached their perception threshold (1 mg/kg) [22] just after the olive washing and storage 265 steps, respectively. On this basis, the changes in the proportion of C6 alcohols and esters 266 versus C6 aldehydes and C5 compounds could explain the change of VOO sensory notes 267 without the appearance of sensory defects. In fact, the green, herbaceous, leafy note has 268 previously been reported to be positively related to some LOX C5 compounds and negatively 269 related to LOX C6 alcohols such as (E)-2-hexenol [22]. Conversely, the ripe fruit note could be 270 associated to the increase of LOX esters (Figure 1), although no previous references about this 271 correlation are available. 272 Among the typical fermentative compounds (Table S1, supplementary information), acetoin 273 and methylbutyl acetate were observed to increase slightly during the storage stage; however, 274 the short duration of the storage meant that their concentrations did not reach those 275 necessary to cause a defect [24]. 276 Meanwhile, the changes in the phenolic fraction induced by the pre-processing operations 277 explained the observed decrease of the related sensory attributes such as bitter, astringent compounds were influenced by the pre-processing steps, including apigenin, the levels of 281 which dropped after the olive washing stage; while the concentration of simple phenol tyrosol 282 was observed to increase in oil after short-term olive storage, probably due to hydrolysis of 283 ligstroside aglycon promoted by microbiological activity, in agreement with previous results 284 [11]. Finally, the progressive decrease of VOO o-diphenols after each olive processing step 285 could explain the observed reduction of the VOO oxidative stability, as measured by the 286 rancimat test ( Table 2). 287 In conclusion, of the post-harvest operations olive washing in closed loop systems, where the 288 water is not renewed in a continuous process, and it is only periodically replaced, was shown 289 to be a critical control point at the olive mill due to microbiological cross-contamination. At the 290 olive mill scale, the volatile composition and the fruity attribute of VOOs were influenced by 291 olive microbiota during oil extraction, while the relatively high initial microbiological charge of 292 some batches on reception hindered the identification of further effects of contamination on 293 VOO sensory and phenolic profiles. Moreover, the common practice of short-term silo storage 294 of olives after washing was shown to influence VOO sensory quality. Although no sensory 295 defects arose from this step, some positive VOO sensory attributes decreased by as much as 296 one point of intensity. The reduction of the green and fruity attributes can be explained by the 297 changes observed in lipoxygenase derived compounds, specifically the reduction in C6 298 aldehydes, pentene dimers and C5 compounds, and the increase in C6 alcohols. Short-term silo 299 storage was also accompanied by the appraisal of a ripe fruit note. Moreover, bitter, pungent 300 and astringent attributes were reduced in oils after olive silo storage, due to the decrease in 301 phenolic compounds. 302 These results confirm the high risk of fruit cross-contamination due to the microbiologically control points for olive oil production process. Moreover, the effect of short term (<12h) olives 305 storage on VOO quality parameters was pointed out. Table 2. Microbiological profile a , characteristics, and damage of olive fruits b through the preprocessing steps. Differences between groups were assessed by one-way ANOVA. Different letters in the same row indicate significant Fisher's LSDs (least significant differences) (p < 0.05).
Step c (n=5) short-term silo storage. [16] (median of the intensity sensory attribute); c : secondary positive attributes (median of the intensity sensory attribute). Table 4. Concentration a (mg/kg) of phenols in virgin olive oils obtained from fruits collected after each pre-processing step. Differences between groups were assessed by one-way ANOVA.
Different letters in the same row indicate significant Fisher's LSDs (least significant differences) (p < 0.05). | v3-fos |
2019-04-02T13:08:31.521Z | {
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} | s2 | Pollen Dispersal and Pollination Patterns Studies in Pati Kopyor Coconut using Molecular Markers
Parentage analysis has been used to evaluate pollen dispersal in Kopyor coconut (Cocos nucifera L.). Investigations were undertaken to elucidate (i) the dispersal of pollen, (ii) the rate of self and outcrossing pollination, and (iii) the distance of pollen travel in Pati kopyor coconut population. The finding of this activities should be beneficial to kopyor coconut farmers to increase their kopyor fruit harvest and to support breeding of this unique coconut mutant. As many as 84 progenies were harvested from 15 female parents. As many as 95 adults coconut provenances surrounding the female parents were analyses as the potential male parents for the progenies. The adult coconut palms were mapped according to their GPS position. All samples were genotyped using six SSR and four SNAP marker loci. Parentage analysis was done using CERVUS version 2.0 software. Results of the analysis indicated that evaluated markers were effective for assigning candidate male parents to all evaluated seedlings. There is no specific direction of donated pollen movement from assigned donor parents to the female ones. The donated pollens could come from assigned male parents in any directions relative to the female parent positions. Cross pollination occured in as many as 82.1% of the progenies analyzed. Outcrossing among tall by tall (TxT), dwarf by dwarf (DxD), hybrid by hybrid (HxH), TxD, DxT, TxH, DxH, and HxD were observed. Self-pollination (TxT and DxD) occurred in as many as 17.9% of the progenies. The dwarf coconut was not always self pollinated. The presence of DxD, TxD, and HxD outcrossing was also observed. The donated pollens could come from pollen donor in a range of at least 0-58 m apart from the evaluated female recipients. Therefore, in addition to the wind, insect pollinators may have played an important role in Kopyor coconut pollination.
Introduction
Kopyor coconuts are natural coconut mutants having abnormal endosperm and only exist in Indonesia. The endosperm is soft, crumbly and detached from the shell, forming flakes filling up the shell (Maskromo et al. 2007;Novarianto et al. 2014). The Makapuno coconut grown in the Philipines and other Asian countries is another example of coconut mutant exhibiting endosperm abnormality (Samonthe et al. 1989;Wattanayothin, 2010). This mutant has been used as parent for hybridizations in coconut breeding (Wattanayothin, 2005). The Macapuno coconut exhibits a soft and jelly-like endosperm (Santos, 1999) that is phenotypically different to Indonesian Kopyor coconut.
The kopyor coconut mutant phenotype is genetically inherited from parents to their progenies (Sukendah 2009) and most probably is controlled by a single locus (K locus) regulating the endosperm development of coconut . However, the identity of the regulatory locus has not yet been resolved.
The abnormal endosperm phenotype in kopyor coconut is controlled by the recessive k allele; therefore, the genotype of kopyor fruit of coconut would be homozygous kk for the zygotic embryos and homozygous kkk for the endosperm. On the other hand, the genotype of the normal fruit of coconut would either be a homozygous KK or a heterozygous Kk for the zygotic embryo and either a homozygous KKK, heterozygous KKk, or heterozygous Kkk, respectively.
The origin of Kopyor coconut mutant is not well documented; however, currently the kopyor palms are found in a number of areas in Java and southern part of Sumatera (Novarianto and Miftahorrachman 2000). The district of Pati, Central Java Province is recognized as one of the Kopyor coconut production centers. Kopyor coconuts have existed in this region for generations, especially the dwarf type of Kopyor coconuts. Although only in a limited numbers, Kopyor Tall and Kopyor Hybrid coconut types also exist along side of the dwarf one.
The tall and dwarf coconut have different morphological characters and pollination strategy. Tall coconuts are generally outcrossing since male flower mature earlier than the female counterpart in the same inflorescence. Dwarf coconut tends to self-pollinate because of an overlapping maturation period between male and female flowers (Deb Mandal and Shyamapada 2011).
Pollination in coconut most probably is assisted by insect pollinators or by the wind (Ramirez et. al. 2004). The family of Diptera, Coleoptera and Hymenoptera are reported as effective pollinators of coconut (Ramirez et al. 2004). Distances of pollen transfer between male and female parents may be used to predict the type of pollinator assisting pollination in coconut. Such question may be answerred by studying pollen dispersal.
Evaluating pollen dispersal in various plant species usually use an approach based on the parentprogeny genotype genotype (Austerlitz et al. 2004). Evaluations have been done in pines (Schuster and Mitoon 2000), Dinizia excels -Fabaceae (Dick et al. 2003), Quercus garryana -Fagaceae (Marsico et al. 2009) and teak (Prabha et al. 2011). Availability of molecular markers capable of identifying genotype of parents and their progenies should assist the pollen dispersal studies. Using such markers, it should also be possible to estimate the self-pollination and outcrossing rates in a certain population (Milleron et al. 2012).
To our understanding, pollen dispersal analysis has not been evaluated in coconuts. With the development of kopyor coconut in Indonesia, availability of information associated with pollen dispersal should be beneficial considering the recessive nature of the kopyor character. Such coconut pollen dispersal evaluation requires availability of some coconut progeny arrays and polymorphic loci for molecular markers of coconut genome.
Co-dominant markers, such as SSR and SNAP markers for coconut have been developed and routinely evaluated at PMB Lab, Department of Agronomy and Horticulture, Faculty of Agriculture, Bogor Agricultural University (IPB), Bogor, Indonesia for a number of plant species. These include coconut , cacao (Kurniasih 2012), and nut meg -Myristica sp. (Soenarsih 2012). Moreover, the gene specific SNAP markers have also been developed and used successfully in coconut (Sudarsono el al. 2014).
The SSR markers have successfully been used in gene flow analysis of pines (Lian et al. 2001;Burczyk and Koralewski. 2005). SNAP marker have also been reported as an effective co-dominant marker for plant analysis (Morin et al. 2004, Sutanto et al. 2013) and proven to generate better data quality for the majority of samples on plant genetic studies (Brumfield et al. 2003) and population structure analysis (Herrera et al. 2007).
The objectives of this research were is to evaluate (i) the dispersal of pollen, (ii) the rate of self and out-crossing pollination, and (iii) the distance of pollen travel in Pati kopyor coconut population. The finding of these activities should be beneficial to kopyor coconut farmers to increase their kopyor fruit yield and to support breeding and cultivar development of this unique mutant.
Time and Location of Research
This research was conducted during the period of July 2012 up to January 2014. The field activities were at the Kopyor coconut plantation belonging to local farmer's at Sambiroto, Pati District, Central Java, Indonesia. The research site was at the following GPS location: S 6 32.182 E 11 03.354. The soil in the evaluated Kopyor coconut plantation is sandy soil. The laboratory activities were done at Plant Molecular Biology Laboratory (PMB Lab), Department of Agronomy and Horticulture, Faculty of Agriculture, Bogor Agricultural University, Bogor, Indonesia.
Selection of Parents and Progeny Arrays
There were 164 adult coconut trees in the field research site, consisted of a mixture of both kopyor heterozygous Kk and normal homozygous KK coconut trees. Only 95 out of 164 adult coconut trees in one block of 100x100 m 2 were sampled in this evaluation. Based on the coconut type, the sampled population consisted of 68 dwarf, 14 tall and 13 hybrid coconuts. Moreover, based on their phenotype, they were recognized as 22 normal homozygous KK and 73 kopyor heterozygous Kk coconuts. Map of the existing coconuts in the research site was generated using the GPS position of all individuals.
Six dwarf, seven tall, and two hybrid coconuts among the kopyor heterozygous Kk trees were selected as female parents. They were selected using purposive random sampling to represent different sites in the sampled population. A single fruit bunch from each female parent containing 2-10 fruits/bunch was harvested 10-11 months after pollination. The total harvested fruits were collected and identified as either kopyor or normal fruits. The identified normal fruits were germinated and DNA was isolated from leaf tissue of the germinated seedlings (63 seedlings of normal fruits). The kopyor fruits are not able to naturally germinate since this character is lethal. Zygotic embryos were isolated from the identified kopyor fruits and DNA was isolated directly from the whole zygotic embryo tissues (21 zygotic embryos). Among the 84 DNA samples, 26 samples were from tall, 45 from dwarf, and 13 from hybrid female parents.
Genotyping of Parents and Progenies
DNA isolation was conducted using the CTAB method (Rohde et al. 1995). Either young coconut leaf or zygotic embryo (0.3-0.4 g) was homogenized in 2 ml of lysis buffer, containing 0.007 g PVP and 10 μl2-mercaptoetanol. The homogenized tissues were then incubated in 65°C waterbath for 60 minutes and the mixtures were centrifuged at 11000 rpm for 10 minutes using using the Eppendorf 5416 centrifuge. Supernatant was then transferred to an Eppendorf tube and an equal volume of chloroform:isoamyl-alcohol (24:1) was added. The mixtures were mixed well; centrifuged at 11000 rpm for 10 minutes and the supernatant was transferred into new microtube.
Cold isopropanol (0.8 volume of supernatant) and sodium acetate (0.1 volume of supernatant) were added into the supernatant.
After overnight incubation, the mixture was centrifuged at 11000 rpm for 10 minutes and DNA pellet was retained. The DNA pellet was washed using 500 μl of cold 70% ethanol, centrifuged and air dried before it was diluted into100 μl aquabidest. RNA contaminants were remove using RNase treatment following standard procedures (Sambrook and Russel 2001).
SSR marker at 37 loci (Lebrun et al. 2001) were evaluated for their polymorphism 6 polimorphic loci were selected. In addition, four SNAP marker loci developed based on nucleotide sequence variabilities of both SUS and WRKY genes were also used to genotype all of the parents and progeny arrays. To generate markers, PCR amplifications were conducted using the following reaction mixtures: 2µl of DNA; 0.625µl of primers, 6.25µl PCR mix (KAPA Biosystem), and 3µl ddH20. Amplifications were conducted using the following steps: one cycle of pre-amplification at 95°C for 3 minutes, 35 cycles of amplification steps at 95°C for 15 seconds (template denaturation), annealing temperature for 15 seconds (primer annealing), and 72°C for 5 seconds (primer extension), and one cycle of final extention at 72°C for 10 minutes as suggested by KAPA Biosystem kit.
The generated SSR markers were separated using vertical 6% polyacrilamide gel electrophoresis (PAGE) using SB 1x buffer (Brody and Kern 2004) and stained using silver staining. The silver staining was done following methods developed by Creste et al. (2001). Electrophoregrams were visualized over the light table and used to determine the genotype of the evaluated samples.
The generated SNAP markers were separated using 1% agarose gel electrophoresis using TBE 1x buffer and stained using standard DNA staining procedures (Sambrook and Russel 2001). The electrophoregrams were visualized over the UV transluminescence table and recorded using digital camera. The recorded pictures were used to determine the genotype of the evaluated samples.
Identification of the Candidate Male Parents
Each sample of the progeny arrays has a known female parent but unknown pollen donor (the male parent). The candidate male parents could be any one of the sampled adult population including the female parents. Studies were conducted to determine the assigned male parent donating pollen to generate any fruit in the progeny arrays.
Identification of the assigned male parent was done by analyzing genotype of progeny and the respective female parent versus the genotype of all adult trees in the selected samples. The ID of the potential male parent for any progeny was determine based on the results of parentage analysis. Simulation was conducted to determine the threshold level for confidence interval of 80% (relax) and 95% (strict) levels before the final parentage analysis steps. Parentage analysis using the genotype of progenies, female parents, and potential male parents was done using CERVUS version 2.0 software (Marshall et al. 1998). Most likely approach (potential male parent with the highest LOD score) based on the matching genotype of progeny, female parent and potential male parent were used as the basis for assigning certain adult individual as the potential male parent or pollen donor of a progeny. The progeny and female parent genotype were compared with those of other adult trees and the assigned male parent was selected based on the output of CERVUS version 2.0 analysis results (Marshall et al. 1998).
Pattern of Pollen Dispersal
The location of the female and the assigned male parents were plotted in the map of adult individuals generated by Garmin MapSource GPS mapping software version 76C5x. The distance between the known female parent and the assigned male parent was calculated using the same software. The distances and positions of both female and male parents in the generated map was then used to ilustrate pattern of pollen dispersal in the location. Self pollination was defined if the assigned male parent was the same as the female parent. Otherwise, they were assigned as outcrossing. The outcrossing were further grouped as outcrossing between either dwarf (dwarf parent pollinated other dwarf), tall (tall parent pollinated other tall), or hybrid (hybrid parent pollinated other hybrid); outcrossing between dwarf and either tall or hybrid (either tall or hybrid parent pollinated by dwarf); outcrossing between tall by hybrid coconuts (tall parent pollinated hybrid) or vice versa. The numbers of both self pollination and the respective cross pollination were calculated.
The Parents and Progeny Arrays
Map of the existing coconut palms in the research site are presented in Fig. 1. As indicated, the sample coconut population consists of a mixture of normal homozygous KK and kopyor heterozygous Kk individuals and a mixture of dwarf, tall and hybrid coconuts. All of these adult trees were used as potential male parents capable of donating pollens to and pollinating the selected female parents and generating the evaluated progeny arrays. The position of the selected female parents (6 dwarf, 7 tall, and 2 hybrid kopyor heterozygous Kk coconuts) are indicated in Fig. 1. The harvested progenies from selected female parents ranged from 2-10 progenies per female parent. Out of 84 selected progenies, 21 were kopyor nuts and 63 were normal ones. They were harvested from tall (26 progenies), dwarf (45 progenies), and hybrid (13 progenies) female parents, respectively.
Genotyping of Parents and Progeny Arrays
The selected SSR and SNAP marker loci generated polymorphic markers in the evaluated coconut population. An example of the polymorphic marker generated by either the selected SSR (CnCir_56 locus) and SNAP (SUS 1_3 locus) primer pairs producing polimorphic markers is presented in Fig. 2. and 3. In Fig. 2, the evaluated individuals are either homozygous cc (sample #1), bb (sample #7-10), heterozygous bc (sample # 2-6, and 11), or heterozygous ab (sample # 12) for the CnCir_56 SSR locus. On the other hand, the evaluated individuals (sample # 1, 3, 4, 6) are heterozygous for reference and alternate SNAP alleles and the other two (sample # 2 and 5) are homozygous for the reference allele (Fig. 3). All individuals were genotyped using the same approaches. The summary of genotping results for a total of 179 individuals using six SSR and four SNAP marker loci are presented in Table 1. The marker loci generated a range of 2-4 alleles per locus (Table 1).
Mean number of alleles per locus is 3.4 and mean PIC for all marker loci was 0.47. The polymorphic information content (PIC) for SSR marker loci ranges from 0.31-0.68 while that of SNAP markers ranges from 0.28-0.37 (Table 1).
The PIC values represents measures of polimorphism between genotypes in a locus using information of the allele numbers (Sajib et al. 2012). Total exclusionary power using the ten marker loci is either 0.85 (first parent) or 0.97 (second parent), indicating the SSR and SNAP markers should be informative enough for analyzing the evaluated coconut population. Note: T -tall coconut, D -dwarf coconut, and H -hybrid coconut
Identification of the Candidate Male Parents
Results of simulation analysis using 10.000 iterations, 95 candidate male parents, and the known female parent for each progeny, predicted the rate of success in identifying male parents at 95% (strict) was 32% and at 80% (relax) confidence interval was 62%. Parentage analysis was able to resolve the identity of the male parent for every individual in the 84 progeny arrays using the most likely parent approach. Moreover, the results of analysis also indicated that assignment of the predicted male parents for the 20% (17 individuals) progenies are at least in the minimum of 95% confidence and 43% (36 individuals) were at least in the minimum of 80% confidence. The assignment for the male parents of other 57% (48 individuals) progenies were at the level of less than 80 % confidence. Although the confidence level was below 80 %, the male parent assignment for these progenies shows LOD (likelihood of odds) value higher than 0. A positive LOD value indicates the suspected male parent might be the true parents. According to Marshall et al. (1998), the higher the LOD value the higher the possibility for the assigned male parent to be the actual parent (Marshal et al. 1998).
Cross pollination is pollination of female flower by male pollen from different parents. Cross pollination produces half-sib progenies. The tall, dwarf and hybrid coconuts could reciprocally donate their pollens. Based on the assigned male parent of the 84 progeny arrays, cross pollination occured in as many as 69 events (82.1 %). Among those identified as outcrossing, 4 events are cross pollination between tall x tall (TxT), 16 tall by dwarf (TxD), and 4 tall by hybrid (TxH) parents. Moreover, outcrossing among DxD (15 events), DxT (6 events), DxH (11 events), HxH (2 event) and HxD coconuts (11 events) were also observed. Complete scheme and pollination types identified based on results of pollen dispersal analysis are presented in Table 2.
The general understanding stated that because of the open flower morphology and the differences in flower maturation, tall coconut is probably always cross pollinated (Ramirez et al. 2004;Maskromo et al. 2011). However, our data indicated there are at least 2.38% of self pollination among the tall coconut (Table 2). Self pollination is characterized by the pollination of female flower by male pollen of the same parent. Self pollination produces fullsib progenies. Total numbers of self pollination are observed in as many as 15 events (17.9 %) in the evaluated progeny arrays (Table 2). They consist of two self pollination events in the tall kopyor coconut (2.38 %) and 13 self pollination events in the dwarf kopyor one (15.48%). Based on 13 progeny arrays harvested from the hybrid parents, no self pollination in the hybrid coconut is recorded ( Table 2).
The general understanding stated that because of the overlapping period between male and female flower maturation, dwarf coconut is always self pollinated (Maskromo et al. 2011). However, our data indicated the dwarf coconut is not always self pollinated. Contrary to the basic understanding, our data indicated the presence of more dwarf to dwarf (15 events, 17.86%), dwarf to tall (6 events, 7.14%) and dwarf to hybrid (11 events, 13.1%) outcrossing (Table 2).
Finding by Rajesh et al. (2008) has previously indicated that cross pollination did occur in dwarf coconuts. Availability of new tools, such as molecular markers, for analyzing outcrossing rate may change the previous understanding. Such changes have been shown in Hymenaea coubaril which was previously reported as more cross pollinated because of self incompatibility (Dunphy et al. 2004). However, more recent pollen dispersal studies indicated that H. coubaril is more self pollinated (Carneiro et al. 2011).
Other alternative explanation for this findings is that it is just a special case in the evaluated site. In the study site, coconut palms were planted in high density. Moreover, population of honey bees exist in the coconut plantation. Honey bees are known to roam around the male and female flowers and function as effective pollinators for coconuts. The high density planting and the availability of pollinators may have caused the unexpected One assigned male parent may donate one or more pollens to the evaluated female coconut parent, with a range of 1-5 pollens per assigned male one. Number of assigned male parents donating certain numbers of pollen to the evaluated female parents is presented in Fig. 4. The data indicate that most of the assigned male parents contribute only one pollen to the evaluated female parents. Only three assigned male parents (two dwarf, and one hybrid coconuts) donated 4 or 5 pollens to the surrounding female parents.
The same female parents may receive donated pollens from different numbers of assigned male parents, with a ranged of 1-7 assigned male parents donated pollen to the same female one. The numbers female parents receiving donated pollens from different number of assigned male parent iss presented in Fig. 5. The data indicated a single female parent most frequently received pollens from 2, 4 or 5 different assigned male parents. Only three female parents evaluated in this experiment (two dwarf and one hybrid coconuts) are found receiving pollens from at least 6 assigned male parents (Fig. 5).
Pattern of Pollen Dispersal
The distances between female to the assigned male parents have been determined based on their GPS positions. The distance of pollen travel between assigned male to female parents as measured in this evaluation ranged from 0 -58 m. Numbers of pollination events of each distance class from the assigned male to the female coconut parents are presented in Fig. 6. The assigned male parents are distributed almost evenly in the different class distances from the female parents. The 0 m distance between parents indicates self pollination events.
To evaluate pattern of pollen dispersal among the assigned male parent to the female, the positions of assigned male parents as pollen donors to one female parent are plotted to a map using their GPS positions. Representative samples of the assigned male parent positions to a single female recipient parent are presented in Figures 7-11.
As the female parent, Hybrid kopyor # 059 (Fig. 7) received 6 donated pollens from six different assigned pollen donors. The pollen contributors to the progeny array harvested from Hybrid kopyor # 059 female parent were all kopyor heterozygous Kk coconuts. However, the seven progenies harvested from this female parent were all phenotypically normal, i.e. genetically either a normal heterozygous Kk or homozygous KK. The positions of the assigned male parents relative to the female parent # 059 in the study site are presented in Fig. 7. Figure 7. Pattern of pollen movement to female parent #059 inferred from parentage analysis. The mark indicates position of ( ) Dwarf kopyor, ( ) Hybrid kopyor as the assigned male (pollen donor) parents, and ( ) hybrid kopyor #59 as the female recipient, respectively The Dwarf kopyor # 067 (Fig. 8) received 10 donated pollens from eight different assigned male parents. The assigned pollen contributors to the Dwarf kopyor # 067 female parent were all kopyor heterozygous Kk coconuts. Only one out of the 10 progenies harvested from this female parent was phenotypically kopyor. The assigned male parent for the harvested kopyor fruit was the tall kopyor # 089. The positions of the assigned male parents relative to the female parent # 067 are presented in Fig. 8. Dwarf kopyor # 068 ( Fig. 9) received 9 donated pollens from four assigned male parents. The four progenies were the result of outcross with either hybrid (# 59) or dwarf (#87 or # 90) and from self pollination. The assigned pollen contributors to the Dwarf kopyor # 068 were all kopyor heterozygous Kk coconuts. Three out of the 9 progenies harvested from Dwarf kopyor # 069 were phenotypically kopyor. These kopyor fruits received one donated pollen from either the tall kopyor # 059, dwarf kopyor # 68 or # 87. The positions of the assigned male parents relative to the female parent # 68 are presented in Fig. 9. Dwarf kopyor # 084 (Fig. 10) received 8 donated pollens from surrounding pollen donors. The pollen contributors to the Dwarf kopyor # 084 female parent were all kopyor coconuts. Only two out of the 8 progenies harvested from Dwarf kopyor # 084 were phenotypically kopyor. These two kopyor fruits received donated pollens from either The two assigned male parents, either dwarf kopyor # 056 (one pollen) and hybrid kopyor # 057 (one pollen), each contributed a one pollen to the evaluated progenies. Moreover, assigned male parent # 32 is the most distance pollen contributor among the evaluated trees. The positions of the assigned male parents (pollen contributors) relative to the female parent # 084 are presented in Fig. 10. Dwarf kopyor # 089 (Fig. 11) received 7 donated pollens from surrounding pollen donors. The pollen contributors to the Dwarf kopyor # 089 female parent were all kopyor coconuts. None of the 7 progenies harvested from Dwarf kopyor # 089 was phenotypically kopyor. The positions of the assigned male parents relative to the female parent # 089 are presented in Fig. 11. In the reseach location, wind blows from left to right during the night and from right to left during the day. If the wind is the major pollinators, there should be a specific pattern of pollen movement. Moreover, the distance of pollen dispersals should be close to the pollen donors. Our data did not support the wind as the only major pollinator in Kopyor coconut since pollens disperse in random directions and the assigned male parents are as far as 58 m apart from the evaluated female recipients. Our data also indicated that insect pollinators may play an important role in Kopyor coconut pollination. Numbers of insects are associated with inflorescence of kopyor coconuts. Such insects may aid pollination and promote cross pollination in kopyor coconuts, as it happens to other plant species (Bown 1988). These findings, however, do not rule out the role of wind in the Kopyor coconut pollination, especially from closely spacing male pollen donors. This might have been the first report of using molecular marker to study pollen dispersal in coconut. Results of this study point to new finding about pollen dispersal and pollination, selfing and out-crossing rates among dwarf, hybrid, and tall coconuts, respectively. However, further research and evaluation are necessary to generalize the finding since the present study is specific for the current study site.
Conclusion
The evaluated markers were effective for assigning candidate male parents to all evaluated seedlings. There is no specific direction of donated pollen movement from assigned donor parents to the female ones. The donated pollens could come from assigned male parents in any directions relative to the female parent positions. Based on the assigned male parent of the 84 progeny arrays, cross pollination occured in as many as 69 events (82.1%) including one among tall by tall (TxT), dwarf by dwarf (DxD) and hybrid by hybrid (HxH) cross pollination events. Moreover, outcrossing among TxD, TxH, DxH and vice-versa were also observed. This finding also indicated the dwarf coconut is not always self pollinated. The presence of 17.86 DxD, 19.05% TxD and 13.10% HxD were also observed. In Kopyor coconut, the pollens could travel from pollen donors as far as 58 m apart from the evaluated female recipients. Therefore, insect pollinators may have played an important role in long distance pollen dispersal in Kopyor coconut. | v3-fos |
2017-07-06T21:26:06.519Z | {
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} | s2 | MAGIC maize: a new resource for plant genetics
A multiparent advanced-generation intercross population of maize has been developed to help plant geneticists identify sequence variants affecting important agricultural traits.
Introduction
Maize is a staple crop worldwide, and its cultivated forms vary dramatically in their environmental adaptation and visible appearance. Underlying the incredible phenotypic diversity is a very high level of genome sequence variationthe average rate of single-nucleotide polymorphism (SNP) variation in maize is ten times greater than it is in humans [1]. In addition to SNP variation, maize varieties exhibit substantial structural differencesnamely, copy-number variations and a range of structural variations, which include the presence or absence of expressed genes in different maize genomes [2].
It is likely that any two maize lines from different geographic regions have at least one type of sequence difference in most of their genes. Given this high level of sequence-level variation between maize varieties, how can we know which particular sequence differences contribute to the observed phenotypic differences?
Maize geneticists have attacked this problem by using various techniques, including mutant analysis, linkage mapping and transposon tagging, with notable success in identifying genes with large-effect mutations, such as the components of seed-color pathways. Identifying genes that have smaller effects on quantitatively measured traits is more difficultmany quantitative trait locus (QTL) mapping studies have been conducted in maize, but few have pinpointed causal genes. This is because many of the typical approaches use populations that are too small and have insufficient recombination events.
As the resolution of linkage mapping in modestly sized populations derived from two-parent crosses is usually insufficient to identify precisely the causal variants underlying QTLs, the creation of inbred lines derived from multi-parent cross designs has been used to address these problems. These alternative genetic mapping strategies with higher resolution include association analysis [3], advanced intermated lines [4] and multiple biparental family sets, such as the maize nested association mapping (NAM) panel [5]. These designs require trade-offs among the amount of genetic variation sampled, the resolution of genetic mapping, the confounding effects of population substructure, and the effort required to generate the mapping population. Now a paper by Della' Aqua and colleagues published in Genome Biology presents an analysis of the first multipleparent advanced-generation inter-cross ('MAGIC maize' or 'MM') population in maize [6]. The resulting population offers some unique properties to facilitate the genetic analysis of complex traits, and this design, combined with the genetics resources available in maize, provides a powerful genetic resource. Other plant MAGIC populations have been developed for analysis of complex traits in Arabidopsis, wheat and rice [7][8][9].
The advantages of mapping with MAGIC Diversity panels often have substantial sub-population genetic structure resulting from gathering together geographically distinct lines with varying levels of pedigree relationships [3]. Subgroups within the diversity panel can differ for mean trait values and also for allele frequencies at many loci, leading to false-positive markertrait associations due to population sub-structure instead of close linkage of markers to causal variations. Statistical methods help to remove the confounding effects of population structure on association tests, but at a cost of reduced power of association testing in some cases.
MAGIC populations eliminate this population substructure, producing stable, homozygous mapping lines by employing several generations of inter-mating following the initial crosses of the founder lines, and by avoiding selection during self-fertilization. The multiple intermating generations have the added useful effect of introducing more recombinations along the chromosomes within the population, meaning that the chromosome blocks inherited by each individual mapping line are reduced in size compared with those of the parent genomes, thus allowing geneticists to better uncouple the effects of linked genes.
The MM population that has been developed currently comprises 529 inbred lines, which were derived from intercrossing eight inbred founder lines to produce a maize population whose genomes represent reshuffled combinations of all eight founders; as genotyping continues, the authors plan to release approximately 1000 more lines.
Although an eight-founder population does not sample as much allelic diversity as a diversity panel, MM ensures that the sampled alleles are sufficiently replicated to allow the statistical estimation of their effects. A diversity panel will capture many more rare alleles, but their rarity makes accurately measuring their effects much more difficult. At the other extreme, NAM uses a common reference parent for all of the crosses, resulting in the reference parent alleles being sampled many more times than those of other founders, which is less statistically efficient (although it provides the substantial advantage of conferring better adaptation on the resulting crosses with unadapted parents). Furthermore, QTLs that contribute to the differences among biparental families can be more difficult to detect in designs such as NAM, whereas the MAGIC design avoids the confounding effect of family structure on QTL inheritance. Finally, a wider range of epistatic interactions can be tested in the MAGIC design because a particular haplotype of a founder in one genomic location occurs in combination with the haplotypes of many other founders at different genomic regions.
Resolving QTL to genes
Della' Aqua and colleagues developed this MAGIC maize population and directly genotyped all of the progeny lines using a moderate-density SNP array with approximately 50,000 markers. In addition, they sequenced the parental lines to generate approximately an additional 30 million SNPs. Using statistical methods originally developed for similar mouse studies, the authors identified the inherited founder haplotype of each mapping line at each genomic window defined by a set of informative markers. This allowed them to impute very accurately the additional SNPs within those intervals, and to supplement QTL mapping based on founder haplotype inheritance (in which each founder is modeled with a unique QTL effect at each local genome region) with mapping based on identity-in-state at the individual SNPs (which assumes biallelic effects shared between founders if they carry the same SNP at a particular site). The authors performed the SNP association tests within intervals of interest defined by the haplotypebased QTLs, providing a sufficiently high resolution to dissect each QTL and identify those candidate genes most likely to contribute to the observed effect. In principle, these tests could also be conducted genomewide in follow-up studies.
A major goal of complex-trait genetics is to resolve QTLs to underlying causal genes (or sequence variants, not all of which are coding genes). Besides the SNP association tests within QTL intervals, Della' Aqua and colleagues also used a novel approach of searching for genes whose transcription patterns matched the founder allele QTL effects. QTL mapping estimates the haplotypeto-phenotype relationship, whereas the transcription data are used to estimate the expression level of each gene within each founder haplotypethe gene-withinhaplotype-to-transcriptome relationship. By hypothesizing that the cis-effects of the local haplotypic region of each founder on the expression of genes within the same region might cause some part of the phenotypic variation, the authors use the correlation between gene expression within each founder haplotype and the haplotype effect on the trait to identify genes following this pattern. This approach can miss genes that affect the trait by means other than by direct expression variation, but it is useful in narrowing down to the more likely causal genes within a QTL interval.
In addition to identifying expression variation related to QTL effects, Della' Aqua and colleagues also demonstrated at least one instance in which structural variation appeared to be related to a QTL effect on grain yield. They identified a QTL in which two founders contributed a low-yield QTL effect; within this interval, a cluster of 24 genes in a 2.5-Mbp region had low expression within those same two founder haplotypes, and finally both of those founders (but no others) entirely lacked sequence reads within this region. This suggests that a large sequence deletion involving numerous genes carried by these two founders results in reduced yield. The authors did not directly confirm the sequence deletion, but, if this result holds, it will support other evidence that large-scale structural variants in maize can affect yield and perhaps that the complementation of such variants in crosses between distinct lines contributes to hybrid vigor [10]. | v3-fos |
2018-04-03T03:19:04.897Z | {
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} | s2 | Proteomic analysis of symbiotic proteins of Glomus mosseae and Amorpha fruticosa.
Arbuscular mycorrhiza fungi (AMF) can colonize the roots of Amorpha fruticosa, a perennial leguminous woody shrub, and form arbuscular mycorrhiza (AM). AMF have significant promoting effects on A. fruticosa growth as the intensity of fungal colonization increases. Taking AMF-A. fruticosa symbionts as the experimental material, gel-free isobaric tags for relative and absolute quantification (iTRAQ) coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used to investigate the expression of A. fruticosa mycorrhizal proteins at the maturation stage. A total of 3,473 proteins were identified, of which 77 showed dramatic changes in their root expression levels; 33 increased, and 44 decreased. We also found nine AMF proteins that were expressed with AMF treatment. The 77 proteins were classified according to function. Plant proteins were assigned into 11 categories: metabolism-related (32%), protein folding and degradation-related (22%), energy-related (10%), protein synthesis-related (8%), stress and defense-related (24%), transcription-related (6%), membrane and transport-related (4%), cellular structure-related (2.5%), signaling transduction-related (11%) and unknown proteins (5%). The results of the study provide a foundation for further investigation of the metabolic characteristics and molecular mechanisms of AM.
and the results reveal 21 differentially expressed gel spots in maize leaves. Among them, 8 proteins were successfully identified. With the development of molecular biology techniques, quantitative analysis of the differences in protein expression profiles during the colonization process of pathogenic or symbiotic microorganisms has become possible; these techniques have played a critical role in analyzing pathogenic mechanisms. Isobaric tags for relative and absolute quantification (iTRAQ) represents one of the new and powerful techniques for simultaneous analysis of multiple samples and provide relative quantification of hundreds of proteins. iTRAQ reagents produce high-quality, reproducible results from complex samples, and iTRAQ has thus become widely used. However, iTRAQ-based studies on the symbiotic mechanisms of AMF and host plants have rarely been reported. Our group has studied the symbiotic relationship between plants and fungi at the mRNA level, Zhang xingxing identified 30 symbiosis-related genes expressed in Amorpha fruticosa roots colonized by GM at different stages by using mRNA differential-display PCR (DDRT-PCR). The expressed genes were confirmed by reverse Northern blotting. Eleven fragments were sequenced and putatively identified by homologous alignment, and these genes were found to relate to defense and signal transduction 10 . Kong xiangshi also has found 47 symbiosis-related unigenes during AMF treatment by using suppression subtractive hybridization (SSH) and subsequent Gene Ontology (GO) database, BLAST annotation and literature searches to categorize each of the identified genes. Among the expressed genes, those related to plant metabolism and stress and defense show important roles during the symbiotic process of AMF-A. fruticosa 11 . Based on our previous work, we have continued to use A. fruticosa, a perennial leguminous woody shrub plant, as a host. Using AMF-A. fruticosa symbionts as the experimental materials, we used iTRAQ combined with 2-D LC-MS/MS to investigate the expression of A. fruticosa mycorrhizal proteins at the maturation stage. The results of the study provide a theoretical basis for the further analysis of the metabolic characteristics and molecular mechanisms of symbiosis between AMF and A. fruticosa. Fig. 1. At day 5, the roots were relatively small, and only a few hyphae were detected. Most of the spores were not in contact with the host roots and were mainly in their vegetative growth stage 12,13 . The infection rate began to increase at day 10, and the growth status of GM-inoculated seedlings was significantly better than that of non-inoculated plants. The colonization percentage increased rapidly at day 15. At that time, there was a large quantity of mycelium-infected roots that increased over time. The colonization percentage reached its peak at the vigorous phase (i.e., 30 days), and a large number of vesicles and arbuscules were observed within the roots. At 40 days, we observed that the hyphae had extended from the plant root surface and had infected neighboring roots. No colonization by AM was observed in the non-inoculated plants, because the mixed soil used for culture had been autoclaved thoroughly.
Identification of Symbiosis-Related Proteins using iTRAQ LC-MS/MS. The roots of A. fruticosa
changed their protein levels when colonized by GM, and mutualistic symbionts formed. Using an iTRAQ approach, 86 differentially expressed symbiosis-related proteins were successfully identified. Among them, 77 were plant proteins, with 33 proteins showing increases and 44 showing decreases (Table 1), and 9 were fungal proteins ( Table 2). More detailed information in supplementary information. AMF proteins play an import role in symbiotic systems, but they show high expression in only the AMF themselves. The low overall concentration of AMF proteins, and the limitations of the technology, resulted in few AMF proteins being detected 14 . Classification of Symbiosis-Related Proteins. The GO database, BLAST annotations and information reported in the literature were used to categorize each of the identified proteins 11 . The 77 differentially expressed proteins in A. fruticosa were categorized into different functional classes and assigned to 11 categories. The functional categories are shown in Fig. 2; they include metabolism-related (32%), protein folding and degradation-related (22%), energy-related (10%), protein synthesis-related (8%), stress and defense-related (24%), transcription-related (6%), membrane and transport-related (4%), cellular structure-related (2.5%), signaling transduction-related (11%) and unknown (5%). Among these classes, proteins related to plant metabolism, protein folding and degradation, and energy (totaling 64% of the identified proteins) play important roles during the symbiotic process of AMF-A. fruticosa.
Discussion
Previous studies have demonstrated that colonization is a multi-step, genetically regulated process under the control of specific loci 15,16 . AMF interact with host plants as cell walls, cell membranes and cellular components undergo dramatic changes 17 . During the colonization process, functional proteins are induced to express and regulate this process, ultimately forming stable mutualistic symbionts.
Signaling-related proteins. Mutualistic symbionts are the result of a mutual recognition and interaction process between AMF and plant signaling molecules. During the colonization process, signal transduction occurs so that the symbiotic partners recognize each other and the host plants decrease their defense responses. At the same time, AMF are prepared to colonize and to form appressoria and, subsequently, to form arbuscules, vesicles and spores. Because of their mutual nutritional relationship, a real-time dynamic signal dialogue between fungi and host plants is continually present. In this study, we found that the protein levels of Rho GDP-dissociation inhibitor 1 and somatic embryogenesis receptor-like kinase were significantly increased in the symbiotic roots. Rho GDP-dissociation inhibitor 1, a regulator of Rho GTPase, regulates the balance of Rho GTPase bound to GTP or GDP. There are 2 conformational states of Rho GTPase: the GTP-bound 'active' state, and the GDP-bound 'inactive' state, in which GTP has been hydrolyzed to GDP 18 . As a member of the subfamily of small G proteins, Rho GTPase regulates a number of important signal-transduction pathways in eukaryotic cells. Rho GTPase, called Rop (Rho-related GTPase) in plants, has different isomers in animals and fungi 19 . Rho GTPases are widely distributed in plants, and the corresponding genes in Arabidopsis, maize, barley, rice, peas and alfalfa have been cloned [20][21][22] . Rho GTPases participate in the regulation of a variety of cellular processes, e.g., gene expression, cell wall synthesis, H 2 O 2 production, actin rearrangement processes, signal transduction pathways of MAP kinase 23,24 , and cytoskeletal assembly and reassembly, to produce a variety of cellular responses. As a regulatory factor, RhoGDI1 was significantly increased in A. fruticosa AM. Clearly, this protein is closely related to signal transduction between A. fruticosa and GM.
Multiple somatic embryogenesis receptor-like kinases (SERKs) have been defined, including the leucine-rich repeat receptor-like kinase (LRR-RLK) subfamily members and a family of transmembrane signal-transduction proteins 25 . They are characterized by a predicted signal sequence, a single transmembrane region, and a cytoplasmic kinase domain. These features suggest that some SERK family protein kinases may play pivotal roles in communication between cells and the environment or in cell-cell interactions. Currently, SERK genes have been cloned from various plant species. The AtSERK3 gene participates in the brassinolide (brassinosteroid, BR) signal-transduction pathway. BR is an important hormone that regulates plant growth and development. Functional analysis has shown that the Arabidopsis thaliana mutant became a dwarf when the AtSERK3 gene is knocked out 26 . The overexpression of the OsSERK1 gene in rice cultivars leads to an increase in host resistance to blast fungus 27 ; in contrast, transcripts of the lettuce LsSERK gene not only are decreased in in vitro somatic embryonic structures but also easily infect Sclerotinia 28 . Studies have also shown that the SERK gene is closely related to antibiotic stress. Plant root colonization by AMF results in increased levels of somatic embryogenesis receptor-like kinase, which plays a major role in promoting plant growth and enhancing plant disease resistance.
Stress and defense-related proteins. Inoculation with AMF has strong growth-promoting effects on
A. fruticosa, especially at the mature stage of symbiont formation. These effects are mediated by increased action of SERK in BR signal-transduction pathways, which have a key role in the regulation of autoimmune responses and of plant root cell elongation and division. However, such regulation is not determined by a single factor. At an early stage of symbiosis, a weak defense response emerges when roots are stimulated by AMF colonization. Lectin plays a crucial role in this defense response by recognizing and binding to the sugar molecules of intruders and interfering with their function on plants. Many plant lectins can bind to glucose, mannitol, galactose or other monosaccharides, and they exhibit high affinity to the oligosaccharides of alien plants. Studies have shown that lectins on leguminous tree surfaces can gather rhizobia around the roots 29 . As AMF infect the roots of A. fruticosa, plant defense responses are initiated, resulting in agglutinin-2 accumulation. Agglutinin-2 is an important factor for the identification of AMF, similarly to rhizobia. When A. fruticosa is colonized by AMF, the abscisic acid (ABA) content increases rapidly, leading to the closing of plant stomata and decreased transpiration; this response also activates the genes encoding soluble osmolytes, thus decreasing stress injuries and the impact of stress-induced reactive oxygen and ethylene 30 . Therefore, ABA accumulation may stimulate metabolic enzymes to produce a feedback effect 31 . The major ABA catabolic route is decomposition via ABA 8′ -hydroxylase to form phaseic acid. Therefore, ABA 8′ -hydroxylase accumulation in A. fruticosa may represent a mechanism for regulating ABA levels.
In multiple rice mapping populations, germin-like protein (GLP) markers have been associated with quantitative trait loci (QTL) for resistance to rice blast pathogens. At the early stage of rice blast fungus infection or mechanical damage, some OsGLPs are transiently induced and expressed. Varying 5′ regulatory regions and the differential expression of some protein family members between resistant and susceptible cultivars correspond with differential hydrogen peroxide (H 2 O 2 ) accumulation levels after fungal infection 32 . Wang discovered a new wheat germin-like protein 33 that is up-regulated in both resistant and susceptible plants. It has been speculated to be involved in wheat defense responses. GLP is significantly increased at the early stage of AMF infection in roots of A. fruticosa, and it may participate in biotic stress responses.
Protein folding and degradation-related proteins. During the symbiosis process, the modification and degradation of peptides and proteins are critical for maintaining cell function. Protein disulfide isomerase, bi-ubiquitin, serine carboxypeptidase, proteasome subunit beta type-6 and subtilisin-like protease SDD1 accumulate in plant roots to ensure proper cell function.
Plants use the proteasome pathway for selective protein degradation, and the proteasome plays pivotal roles in removing abnormally modified proteins and non-targeted proteins. Interactions between bi-ubiquitin and proteasome subunit beta type-6 provide an effective way to degrade proteins. Bi-ubiquitin is highly conserved in eukaryotes, and it is covalently bound to target proteins through post-translational modification to mediate degradation.
Serine carboxypeptidase (SCP), an enzyme that catalyzes the hydrolysis of proteins in eukaryotes, has been found in rice, Arabidopsis and peas. It has been shown that SCP has broad functions in plants, including protein turnover and secondary metabolism synthesis, and it plays an important role in improving plant stress resistance. Liu showed that the expression of OsBISCPL1 was induced by rice blast fungi and antiviral signaling molecules (salicylic acid and jasmonic acid) 34 and that overexpression of OsBISCPL1 could enhance disease resistance, oxidative stress tolerance and ABA sensitivity in transgenic Arabidopsis plants. OsBISCPL1 is expressed ubiquitously and differentially in rice, and it is induced by antiviral signaling molecules (BTH, JA, SA and ACC) and is up-regulated by incompatible interactions between rice and the blast fungus. Liu has shown that the expression of the ZmSCP gene in corn is up-regulated under induction by Rhizoctonia solani and that the ZmSCP protein are associated with various abiotic stresses 35 .
The subtilisin-like protease SDD1 is a member of the processing-type proteases in eukaryotes. As a preproprotein, it can direct peptides for transport to the cytoplasm. SDD1 is a crucial gene that regulates stomatal development and encodes a subtilisin-like serine protease. As a processive enzyme, it may activate a protein molecule or a signal that directs receptors into contact with epidermal cells during stomatal development processes. Liang has shown that the serine protease-encoding gene SDD1 is widely expressed acts on the development of stomata and is also necessary for normal root development 36 .
Protein disulfide isomerase (PDI), a multifunctional protein, is distributed widely in eukaryotic organisms and is involved in modifying/folding newly synthesized proteins. The catalytic thiol-disulfide exchange reaction to form disulfide is involved in many physiological processes, such as auxiliary protein folding in the endoplasmic reticulum, reconstruction of misfolded proteins, and the repair and refolding of damaged proteins under stress 37 . Additionally, as a chaperone, PDI can assemble heterogeneous protein peptides and regulate disulfide bonds in an ATP-dependent manner, and it may also be closely related to sugar transport, protein synthesis and other metabolic processes in eukaryotic organisms.
Energy-related Proteins. During the symbiosis process, dihydrolipoyl dehydrogenase, aldehyde dehydrogenase and isocitrate dehydrogenase [NAD] regulatory subunit 1 accumulated in plant roots. AMF colonization significantly enhances the energy metabolism of plants. The Krebs cycle provides more energy than glycolysis, and it is an important pathway not only an important for sugar metabolism but also for the metabolism of lipids, proteins and nucleic acids, which are eventually oxidized to carbon dioxide and water. Isocitrate dehydrogenase (IDH) is considered to be the rate-limiting enzyme of the Krebs cycle; it catalyzes decarboxylation to ketoglutarate while reducing NAD + to NADH 38 . Therefore, the activity of NAD-IDH has a significant impact on cellular metabolism. Isocitrate dehydrogenase [NAD] regulatory subunit 1, a regulatory factor, controls the activity of NAD-IDH and thus affects metabolic activity.
Kuhlemeier has explored the energy metabolism of tobacco pollen and has found that, in vegetative tissues 39 , pyruvate enters the Krebs cycle by pyruvate dehydrogenase (PDH); however, in reproductive organs, it is converted to acetaldehyde by pyruvate decarboxylase (PDC) and then enters the Krebs cycle via aldehyde dehydrogenase (ALDH) and acetyl coenzyme A synthetase (ACS). Thus, ALDH plays an important role in the pyruvate metabolism pathway of PDC/ALDH/ACS. Under stress conditions, plant cells quickly accumulate excessive reactive oxygen species (ROS), which cause oxidative stress and result in the accumulation of large amounts of toxic substance and eventually in plant death 40 . Aldehydes are an important component of peroxidation reaction products, and they play a crucial role in the oxidation of carboxylic aldehydes, the removal of toxic aldehydes, and the reduction of lipid peroxidation, thereby improving plant tolerance 41 . As an important member of the pyruvate dehydrogenase family, dihydrolipoyl dehydrogenases ensure the production of oxidatively decarboxylated pyruvate CoA, and CoA then enters the Krebs cycle to produce large amounts of energy for plant growth.
Scientific RepoRts | 5:18031 | DOI: 10.1038/srep18031 Cellular structure-related proteins. Dramatic changes in plant morphology and in the penetrating mycelium, dynamic reorganization of cytoskeletal elements and organelle transformation occur when arbuscular vesicles develop 42 . Tubulin is an important component of the cytoskeleton, and it plays an important role in maintaining intracellular structural order and cell morphology. Meanwhile, tubulin is closely related to cellular transport, cell differentiation, cell motility, signal recognition, cell division and other developmental activities. Mills has revealed dramatic changes in both microtubules and actin arrangement in the host cell, and further studies have found that microtubules and actin rearrangement in the host cell are necessary for expression in non-host plants 43 . Studies on plant tubulin have primarily been focused on annual plants, such as Arabidopsis, tobacco, and rice, but study of the tubulin gene in perennial trees has been rare 44 . Membrane and transport-related proteins. A K + efflux antiporter and coatomer, which are membrane and transport-related proteins, respectively, were found in the A. fruticosa mycorrhizea. The K + efflux antiporter is mainly responsible for maintaining the intracellular ion balance and regulating the cells' osmotic pressure. During AMF colonization, AMF invasion affects the ion balance of plant root cells, and plants maintain the intracellular ion balance to stimulate K + increases. Coatomer, a coat protein, transports vesicles, and vesicle-mediated non-selective transport ensures the accurate transport of proteins and lipids.
Lipid metabolism is one of the basic metabolic pathways in plants. The β -ketoacyl-acyl carrier protein synthase (KASI)-mediated acyl chain extension is important in the de novo synthesis of fatty acids. Ceramides, which are central molecules in the sphingolipid signaling pathway, play important roles as second messengers in plants and participate in many significant plant signaling pathways, such as cell growth, proliferation, differentiation, senescence and apoptosis 45 . Neuraminidase is a key enzyme that regulates ceramide. Neutral neuraminidase hydrolyzes ceramide to form sphingosine (ref). Liu has found that AtCER is involved in H 2 O 2 -induced oxidative stress 46 .
During cell morphogenesis, lignin plays an important role in the growth and development of vascular tissues and is involved in cell wall lignification, which increases the hardness or compressive strength of the cell wall. It also promotes the formation of mechanical tissues while also having a major impact on plant lodging, disease and stress resistance 47 . There are 3 types of monomeric lignin biosynthesis pathways,: the shikimate pathway, the phenylketonuria pathway and the lignin biosynthesis-specific pathway 48 . COMT is a key enzyme in the specific lignin pathway and is involved in the synthesis of S-lignin 49 . AMF colonization enhanced the synthesis of woody amorpha lignin, thus affecting the growth and development of plants.
Transcription and protein synthesis-related proteins. Ribosomal proteins are important components of the ribosome, and they have important roles in translation efficiency and ribosome stability. They also participate in important cellular processes, such as DNA repair, apoptosis and regulation of gene expression; e.g., 40S ribosomal proteins showed significant accumulation in plant roots after AMF invasion.
Nascent polypeptide-associated complex subunit alpha (NAC), which is located at the top of the newly synthesized polypeptide, can reversibly bind to eukaryotic ribosomes and guide the correct distribution and translocation of newly synthesized polypeptides in the cell. The observed increases in 40S ribosomal protein and NAC levels, combined with folding-and degradation-associated proteins, ensure the fast and accurate synthesis and distribution of AM symbiosis-related proteins.
Transcriptional regulation is an important aspect of the regulation of gene expression. The results show significant accumulation of histone H3 and histone H4 in the host plant roots. Nucleosomes constitute the basic unit of chromatin in eukaryotes. Histones, which are structural proteins of chromosomes, play important roles in DNA folding and packing, protecting DNA from digestive enzymes, and gene regulation, tumor formation, and apoptosis. The N-terminal amino acids of histones participate in acetylation, methylation, phosphorylation, ubiquitination and other covalent modifications. Studies have shown that histones may change the structure of chromatin via post-translational modifications, thus modulating gene expression 50 .
Unknown proteins. During AMF symbiosis, the expression levels of proteins within A. fruticosa roots were changed; some proteins disappeared, and new symbiosis proteins arose. The functional analysis of symbiotic proteins in A. fruticosa, a non-model plant, is not difficult. Because these proteins were differentially expressed in the symbiotic system, they are targets for future studies.
AM-A. fruticosa molecular regulation model. By using bioinformatics analysis, we found that mycorrhizal proteins were involved in several biological processes and cellular activities (Fig. 3), and we verified that the symbiosis formed between AMF and A. fruticosa is a uniform and harmonious result of symbiotic interactions.
Methods
G. mosseae (GM) was harvested from sorghum, which was supplied by the Ecology Laboratory of Heilongjiang University, by co-culturing for longer than 40 days. Inocula contained a mixture of the rhizosphere that consisted of AM fungal spores, hyphae and mycorrhizal fragments. The inocula contained approximately 500 spores per 20 g.
Seedling culture. Seeds soaking for 24 h. The growing medium was 50% peat soil, 30% vermiculite and 20% sand. It was sterilized in an autoclave at 121°C for 2 h and then air dried for 1 week before the start of the experiments 10,11 . Mycorrhizal colonization percentage determination. The germinated seeds were then planted in a pre-sterilized mixed matrix and grown under a 16-h photoperiod at temperatures of 25/18 °C (day/night) with 60% relative humidity. One group was inoculated with GM inoculum, and the other was inoculated with sterilized inoculum as a control (CK). Each treatment was repeated 10 times. A total of 20 pots were arranged randomly and watered every 2 days. The mycorrhizal colonization percentage of the seedlings was determined using the Phillip and Hayman staining method (KOH bleaching-acid fuchsin stain) with some modifications (Phillips J M, 1970) 51 .
Protein extraction, protein quantification and SDS-PAGE. At the maturation stage, A. fruticosa roots were harvested, and total root protein was precipitated with 10% (w/v) trichloroacetic acid (TCA) in acetone at − 20 °C overnight. After centrifugation at 40,000 × g at 4 °C for 1 h, the pellets were washed 3 times with cold 80% acetone. A 2-D Quant kit (GE Healthcare, USA) was used to determine the protein concentrations. SDS-polyacrylamide gel (12%) electrophoresis was performed with 30-μ g samples at 120-V constant voltage for 2 h. The gel was stained with Coomassie blue and visualized 52,53 . iTRAQ labeling. The CK group and the GM group each included 3 biological replicates. After digesting with trypsin, the proteins from the non-infected and infected samples were labeled with iTRAQ reagents 115 (CK1), 116 (CK2), 117 (CK3), 118 (GM1), 119 (GM2), and 121 (GM3) and were then combined following the manufacturer's protocol at a ratio of 1:1:1:1:1:1 for LC-MS/MS analysis 54,55 . LC-MS/MS measurements. The labeled samples were pooled and purified using a strong cation-exchange chromatography (SCX) column and were then separated on an analytical column (1.7 μ m, 100 μ m × 100 mm) at a flow rate of 300 nL/min using a linear gradient of 5-35% acetonitrile (ACN) over 40 min. The ion spray voltage was 4.5 kV, and nitrogen was used as a nebulizing gas (30 psi) and a curtain gas (15 psi). From each MS scan, the 30 most intense precursor ions were selected for MS/MS fragmentation and were detected at a mass resolution of 30,000 at m/z 400 56 . Data analysis was performed with a Triple TOF 5600 System, and then the iTRAQ data were compared with the protein sequences of homologous species after genome annotation.
Protein identification. Protein Pilot 4.0 (AB Sciex Inc., USA) was used to simultaneously identify and quantify proteins 57,58 . Differentially expressed proteins were required to satisfy 3 conditions for identification: (1) each confident protein identification involved at least 1 unique peptide; (2) the P-value was less than 0.05; and (3) changes of greater than 1.2-fold or less than 0.8 fold were considered significant. All of the identified proteins were classified according to the annotations acquired by using the UniProt knowledge base and the GO database. | v3-fos |
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} | s2 | Nutritive Evaluation of the Bambara Groundnut Ci12 Landrace [Vigna subterranea (L.) Verdc. (Fabaceae)] Produced in Côte d’Ivoire
The nutritional evaluation of the Bambara groundnut Ci12 landrace (Vigna subterranea (L.) Verdc.) seeds produced in Côte d’Ivoire shows a 19% content of protein, containing all the essential amino acids with tryptophan as the limiting amino acid, a total dietary fiber level of 10%, with a low soluble fraction content, and a fat content of 1.4%, with a high proportion of total unsaturated fatty acids (61%) of which 36% were n-6 fatty acids. This legume contains phosphorus, as the major mineral, followed by magnesium and calcium, and trace elements (iron, copper and zinc). It is characterized by the same amount of α-tocopherol and antioxidant capacity as common legumes. The high concentration of essential amino acids, n-6 fatty acids and minerals, mainly Fe, in the Ci12 landrace of Bambara groundnut indicates that this local legume has the potentiality to improve the nutritional status in Côte d’Ivoire and it could be regarded as a nutrient dense food.
Introduction
Legume seeds are the most important sources of macronutrients, such as protein, carbohydrates and dietary fiber, in the diet of many populations, especially in developing countries. One of these legumes is the Bambara groundnut, its name is derived from the name of a Mali tribe called "Bambara" [1]. The Bambara groundnut, or round beans, is widespread in Africa where it is known by various names, according to different local language: for instance, among the Akan tribes of Côte d'Ivoire, it is commonly named Clô-Nglô, while in literature the name Bambara groundnut is preferred. This bean is related to cowpeas and it is botanically known as Vigna subterranea (L.) Verdc., a member of the Fabaceae family.
There are two botanical varieties namely Vigna subterranea var. spontanea, which includes the wild varieties, and Vigna subterranea var. subterranea, which includes the cultivated varieties. Although it represents a common food staple in semi-arid area of Africa, the Bambara groundnut remains one of the crops less investigated [2] but one with a great nutritional potential. Unfortunately, the Bambara groundnut has become less important in many parts of Africa because of the expansion of other crop productions. In the recent years, however, there has been renewed interest in such a crop for cultivation in the arid savannah zones. Actually, the Bambara groundnut is known for its resistance to drought and the reasonable yield when grown on poor soils. The Bambara groundnut is the second most important food legume and the third food crop, after maize and groundnut, grown by the small-scale farmers in many African countries. It is also cultivated both as an intercrop with maize, cowpeas and melon and as a sole crop [3].
In all the developing countries, due to the high price of meat and fish, the interest is focused on grain legumes as a source of protein. Legumes are rich not only in proteins, but in other nutrients such as starch and fat [1]. Notwithstanding this, the nutritional value of legume seeds is restricted by the presence of anti-nutrients such as tannin, phytic acid and enzyme inhibitors [1]. Different processing methods such as cooking, roasting and autoclaving, significantly affects the tannin content in Bambara groundnut: in particular, dehulling, soaking and boiling-discarding cooking water-have been shown to be effective in reducing the tannin content [4].
The cultivation of the Bambara groundnut is located in the western and northern areas of Africa characterized by contrasting environments, including tropical rain forests and dry savannas. In these zones, the Bambara groundnut plays a key role in both the diet, used as flour with an improvement of its digestibility [5], and the local culture: for instance, in Côte d'Ivoire, the Bambara groundnut is mainly cultivated by women, and represents a source of income for the household.
Ten landraces of the Bambara groundnut (Ci1, Ci2, Ci3, Ci4, Ci5, Ci7, Ci8, Ci9, Ci10, Ci12) are cultivated according to their areas of origin, their colours and their shapes [6]. However, in order to set up better collecting and conservation strategies their morphological diversities were initially evaluated [7], and only recently agronomic and genetic data have been implemented [6]. Despite the increasing number of scientific reports on the Bambara groundnut in Africa [5,8] only one study [9] is currently available on the overall nutritional quality of seeds from Côte d'Ivoire. Among the available Bambara groundnuts, the Ci12 landrace has a high yield [6] and is the most consumed variety [5] in the north of Côte d'Ivoire. Due to the limited data available in literature on the nutritional quality of the Bambara groundnut, the aim of this study was to investigate the chemical composition and the nutritional potential of this African legume.
Results and Discussion
The proximate composition, minerals and phytic acid contents of the Bambara groundnut are shown in Table 1. Moisture (11.7 ± 0.1 g/100 g fresh weight, fw) was slightly higher than that reported in literature, a result that could be attributed to its preparation steps and to the environmental condition, while protein and carbohydrate content appears in line with those reported by Falade and Nwajei [8]. In order to assess the nutritional quality of the protein fraction, we evaluated the amino acid content of Bambara groundnut flour and calculated the amino acid score (AAS) ( Table 2). The amino acid content is in agreement with that reported by Ihekoronye and Ngoddy [10] showing that the Bambara groundnut is rich in essential amino acids, such as isoleucine, leucine, lysine, methionine, phenylalanine, threonine and valine. In accordance with literature data on African samples [11], glutamic (209.5 mg/g crude protein) and aspartic acids (146.1 mg/g crude protein) are the major non-essential amino acids, while leucine (102.1 mg/g crude protein) and lysine (80.2 mg/g crude protein) are the principal essential amino acids, thus indicating a protein quality very similar to that assessed for different legumes [12]. In accordance with data on Voadzeiia subterranea reported by Glew et al. [13], the Bambara groundnut Ci12 landrace contains all the essential amino acids, but it does not meet the recommended amino acid patterns specified by FAO/WHO Expert Consultation [14] because of the limited amount of tryptophan. Despite this fact, it could play an important role in meeting the people's protein needs in combined meals, especially in developing countries. [14]. SAA: sum of sulphur amino acids (methionine + cysteine); AAA: sum of aromatic amino acids (phenylalanine + tyrosine); AAS: mg of essential amino acid in test protein/mg of essential amino acid in recommended amino acid scoring patterns in FAO report [14].
The fat content was in line with that reported for pulses (Table 1); from a qualitative point of view, the main fatty acids assessed in analyzed Bambara groundnut flour were palmitic (16:0), oleic (18:1 n-9) and linoleic acids (18:2 n-6), representing 21%, 23% and 36% of the total fatty acids content, respectively (Table 3). These data are in agreement with those reported by Minka and Bruneteau [15] for linoleic and palmitic acids but inconsistent for oleic acid, found only in our sample, and linolenic acid found in a great amount in other Bambara seeds (21% vs. 1.3% of our sample) as reported by Minka and Bruneteau [15]. The content of carotenoids, tocopherols, total polyphenols and the values of total antioxidant capacity in the analyzed Bambara seeds are shown in Table 4. To the best knowledge of the authors, the content of carotenoids and tocopherols in the Bambara groundnut has not been measured yet. Referring to the results of 30 Brazilian genotypes of cowpea (Vigna unguiculata L. Walp) [16] and in agreement with such data, the cowpea analyzed in the present study does not contain a detectable amount of carotenoids. Regarding tocopherols, the only isomer found is α-tocopherol in an amount comparable to common legumes [17], whereas a major amount the δ-isomer has been reported in Vigna unguiculata L. Walp genotypes [16]. As formerly observed [18], the Trolox equivalent antioxidant capacity (TEAC) value (2.2 mmol of Trolox/100 g) measured by the direct procedure was greater than the ferric reducing antioxidant power (FRAP) one (0.62 mmol of Fe 2+ /100 g) likely due to a low yield of extraction and/or a loss of antioxidants during the hydrolysis treatments applied in this extraction based measurement. However, the values of FRAP and of TEAC were consistent with the data previously determined for common pulses [18,19], even though extremely lower than those recently reported for two varieties of Bambara groundnut [20]. These differences could be likely attributable to several factors, such as different genotype, growing conditions, season, and maturity of the seeds. Nevertheless, the present results demonstrate that the analyzed Bambara groundnut, an underutilized legume, exhibits a comparable antioxidant capacity to commonly consumed legumes, such as chickpea, bean and pea. Starch is the major and most important energy source in cereals, legumes, and tubers. The structure and functional properties of starch and flour from the Bambara groundnut have been evaluated in different works: the starch granules of the Bambara groundnut are generally more round and smaller than those present in legumes and tend to show a low amylose content for a legume (21.7%) [21]. In the Bambara groundnut Ci12 landrace, we assessed a rough 50% of the nutrients as starch, of which about 35% was amylose (Table 1). This high amylose content could be an interesting trait both in a functional and in a technological point of view. Amylose, in fact, is considered one of the main determinants for a favorable glycemic response [22] and for resistant starch formation, with consequent health benefits on glucose metabolism, energy intake and colonic health [23].
The total dietary fiber content (Table 1) assessed in our samples is almost double when compared to that observed in other Bambara groundnut varieties [8], but appears lower than that reported for legumes such as bean, chickpea, etc. The high fiber content evaluated in our samples could probably relate to the thick and hard peel of seeds, not eliminated prior to the flour preparation, or to a stage of over-maturity of the seeds as previously shown for forages [24]. Moreover, the ratio of insoluble to soluble fiber in legumes ranged from 5:1 to 5:19 [25], while, in our Ci12 landrace, it resulted to about 20:1.
The nutritional value of legume seeds is often limited by the presence of anti-nutrients, such as tannins, phytic acid and enzyme inhibitors [1]; tannins reduce the protein digestibility by inhibiting the proteolytic activity and/or by forming indigestible complexes with dietary protein. Our data on total phenol content (707 ± 1.4 mg CE/100 g) was in line with those already reported in the Bambara groundnut [26]. Different studies evidenced that tannins, the principal anti-nutritional fraction of total polyphenols, represent about half of the total phenol content present in these seeds [26] and correlate visually with seed-coat color. However, a recent study shows that kaempferol-3-O-glucoside-7-rhamnoside appears to be the most prevalent flavonoid in V. subterranea and that, among 11 analysed species of Vigna, V. subterranea varieties do not contain proanthocyanidins [27], which are known as condensed tannins. Due to the mounting evidence of several beneficial effects towards the human health of these compounds, it would be interesting to investigate, in the future, the specific phenolic compounds present in our samples as well as the best cooking techniques in order to preserve their characteristics.
The content of phytic acid (inositol hexaphosphate) assessed in our samples is higher (1.1 ± 0.1 g/100 g fw) compared to that reported in literature [28]. In several seeds, most of the phosphorus is present as phytic acid and in this structure, due to dissociation of phosphate groups at human intestinal physiological pH, it can bind cations, like calcium, iron or zinc. This binding forms insoluble salts that are not available for absorption, thereby decreasing mineral bioavailability [29]. On the other hand, phytic acid could have several beneficial effects, particularly as a natural antioxidant or as an inhibitor of the cancerous process, despite the fact that the mechanism is still not completely clear [29].
It is now common knowledge that various food-processing methods can reduce and/or destroy most of these anti-nutritional factors. Soaking, cooking, pressure-cooking or germinating induce a variety of physical and biochemical changes in seeds/flours, which could improve their nutritional value [4,26]. In addition, the fermentation, achieved by indigenous microbiota or by the addition of fermented material from a previous production through back slopping, plays an important role in removing anti-nutritional factors. For the Bambara groundnut in particular, isolates from fermenting cotyledons (dawadawa-type product) showed Bacillus subtilis and Bacillus licheniformis as the major fermenting microorganisms [30]. Some studies emphasized that the fermentation process reduces tannins and trypsin inhibitor activity (by 24% and 40%, respectively) [4] or increases the phenolic content and antioxidant capacity of the fermented Bambara groundnut [31]. Moreover, the fermentation of Bambara seeds has been recently suggested with the aim of producing a vegetable milk, with better sensory properties and suitable as a potential probiotic carrier [1]. In this contest, it would be interesting to carry out "tailored" fermentation processes in order to improve Bambara flours from both nutritional and technological points of view.
The mineral analyses (Table 1) showed that P is the major mineral, as already observed by Amarteifio et al. [32], followed by Mg and Ca; their levels (335.8 ± 5.9, 136.0 ± 2.0 and 30.2 ± 1.6 mg/100 g fw, respectively) are generally consistent with those of other varieties grown in Southern Africa, when expressed on dry basis [32]. The Ci12 landrace of Bambara groundnut contains also trace elements like Fe, Cu and Zn (8.8 ± 0.6, 0.5 ± 0.0 and 1.9 ± 0.1 mg/100 g fw, respectively); their contents resulted lower than some varieties of Bambara [11,32], but higher than others [28]. Moreover, considering the amount of phytic acid present in flour, it is conceivable that the bioavailability of these elements, and especially of Fe, is quite low. In this regard, it should be of interest to investigate the effect of the above mentioned processing procedure, such as fermentation, to decrease phytate and thereby improve the potential role of the Bambara flour for producing food items rich in Fe in geographic areas with a high prevalence of iron deficiency.
Samples
The Bambara groundnut of the Ci12 landrace (red and grey mottles on cream background, small shape), originated in Sinematialie (north of Côte d'Ivoire), was purchased from several local markets of Abidjan. Samples (n = 10) were immediately transferred to the laboratory of Food Biochemical and Tropical Products Technology (Abidjan, Côte d'Ivoire) for the flour preparation. The seeds were cleaned manually to remove all foreign materials, mixed and grinded into fine flour with a laboratory blender (Bimby mod. 2200, Vorwerk, Wuppertal, Germany) prior to analysis. All the analyses were done, in triplicate on flour obtained by pooling all the samples in the same amount, at the Department of Food Science, University of Parma, and at the Department of Food, Environmental and Nutritional Sciences (DeFENS), University of Milan, Italy.
Proximate Composition
The moisture and ash (925.10; 945.38), crude protein (925.31) and lipid (963.15) content were determined in accordance with AACC standard methods [33]. Carbohydrates were evaluated as total starch [34] and simple sugars [35]; the starch fraction was also characterized in terms of amylose content by means of a commercial kit (K-AMYL, Megazyme Int., Wicklow, Ireland). Soluble and insoluble dietary fibre was assessed by the enzymatic gravimetric procedure [36].
Determination of Minerals
The sample was accurately weighted and dry-ashed (550 °C, one night; method 40-70.01) [33] in a muffle furnace (Cavallo Srl, Buccinasco, Italy). Grey ashes were treated with high purity hydrogen peroxide (H2O2 30%, Suprapur Merck, Darmstadt, Germany) to obtain white ashes, that were dissolved with acid solution (2 mL HCl 30%, Suprapur Merck) and diluted with distilled water in volumetric flasks. Mineral concentrations (Zn, Fe, Cu, Ca and Mg) were determined by Atomic Absorption (Analyst 800 Perkin Elmer, Waltham, MA, USA), while phosphorous (P) was determined by a colorimetric method using Cary 3E UV-VIS Spectrophotometer (Varian, Mulgrave, Australia) [37]. All analyses were carried out in triplicate and reported as mean and standard deviation; data are expressed as mg/100 g fw.
Determination of Phytic Acid
The phytic acid content was determined by HPLC with post-column sulfosalicylic acid reaction, by using a spectrophotometric detector as described by Oberleas and Harland [38], and quantified in relation to an external standard curve of phytic acid. Before HPLC analysis, suitable aliquots of sample were extracted with 10 mL of 0.66 M HCl for 3 h, centrifuged and filtered (0.45 μm). Results are expressed as g/100 g fw.
Determination of Amino Acids
Five hundred mg of the sample were weighted into a 18 mL Pyrex glass tube fitted with Teflon-lined screw caps and 6 mL of 6 N HCl were added and mixed. The tube was flushed with nitrogen for 1 min in order to remove air. Hydrolysis was then carried out at 110 °C for 23 h. After cooling the tubes at room temperature, the internal standard (7.5 mL of D,L nor-leucine 5 mM in water) was added; the mixture was filtered through paper filter and collected into a 250 mL volumetric flask. Acid hydrolysis was used for the determination of all amino acids except tryptophan, cysteine and methionine. For cysteine and methionine performic acid oxidation followed by acid hydrolysis was used. In this case, 500 mg of the sample was weighed in an 18 mL Pyrex glass tube fitted with a Teflon-lined screwcap. After adding 2 mL of neat performic acid freshly prepared, samples were kept in an ice bath for 16 h at 0 °C. Then 0.3 mL of hydrobromic acid was added in order to remove excess performic acid. The bromine formed during the reaction was removed by drying with nitrogen flow. The acid hydrolysis procedure using 6 N HCl as described above was then performed.
In order to prepare a calibration standard solution, 40 μL of D,L nor-leucine (2.5 mM in HCl 0.1 N), 40 μL of cysteic acid (2.5 mM in HCl 0.1 N), 40 μL of Amino Acid Hydrolyzate Standard Mixture (EC Number 231-791-2, SIGMA-Aldrich, Stockholm, Sweden) and 880 μL of deionized water were mixed. Then 10 μL of hydrolyzate sample or standard solution were transferred into a 1.5 mL tube, 70 μL of borate buffer were added, in order to keep the optimal pH range for derivatization (8.2-9.7), and the solution was briefly vortexed. Twenty μL of reconstituted AccQ. Fluor reagent was finally added and the mixture was immediately vortexed for several seconds. The tube was closed and left to stand for one minute at room temperature, then heated in a heating bath at 55 °C for 10 min. The resulting derivatized standard solution was diluted with 400 μL of deionized water before injecting in the HPLC system.
The sample and standard solutions were analysed as previously described [39].
Determination of Total Tryptophan by Derivative Spectrophotometry
The sample was prepared by homogenizing 200 mg of the sample with 15 mL NaOH 0.1 N. The sample was centrifuged and the supernatant was collected and diluted 1:5 with NaOH 0.1 N only before the spectrophotometric analysis. The calibration standard solution was prepared with N-Acetyl-L-Tryptophanamide 0.2 mM in NaOH 0.1 M (stock solution), then diluted with NaOH 0.1 M to obtain working calibration standard solutions of 0.02, 0.05, 0.08, 0.11, 0.14, 0.17 and 0.20 mM. Quantification of total tryptophan was carried out as previously described by Fletouris et al. [40].
Determination of Fatty Acid Composition
The samples were extracted according to the method of Folch et al. [41] using a chloroform/methanol mixture in the ratio of 2:1 (v/v). Methyl esters were prepared from the total lipids by the method of Ackman [42]. Fatty acid methyl esters were analyzed by a Varian 3400 CX gas liquid chromatography equipped with a OMEGAWAX AX 320 column (Supelco, Bellefonte, PA, USA) and a flame ionization detector. Injector and detector temperatures were 250 and 260 °C, respectively. The initial oven temperature was 140 °C and was increased by 2 °C/min to 200 °C and held at this temperature for 25 min; hydrogen at a flow rate of 2.0 mL·min −1 was used as carrier gas. A standard fatty acid methyl ester mixture (Omegawax Column test Mix 4-8476 Supelco) was run and retention times were used in identifying the sample peaks; nitrogen at a flow rate of 2.0 mL·min −1 was used as carrier gas. A response factor was calculated to correct the GC response of each fatty acid ester to bring them to a common baseline. The methyl ester of pentadecanoic acid (C15:0) was used as an internal standard. Fatty acid levels were estimated on the basis of peak areas of the standards.
Determination of Carotenoids
Carotenoids were extracted according to the method reported by Panfili et al. [43], slightly modified as follows: a sample (2 g) was saponified under nitrogen in a screw-capped tube by adding 5 mL of ethanolic butylated hydroxytoluene (BHT, 60 g/L) as antioxidant, 2 mL of ethanol (95% v/v), 2 mL of sodium chloride (10 g/L), and 2 mL of sodium hydroxide (600 g/L); β-apo-8-carotenal (SIGMA-Aldrich, cod. 10810, Stockholm, Sweden) was added as the internal standard. The tubes were placed in a 70 °C water bath and mixed every 5-10 min. After alkaline digestion at 70 °C for 45 min, the tubes were cooled in an ice bath and samples extracted with 15 mL of THF stabilized with BHT (1 g/L), centrifuged for 5 min at 840× g, the supernatant recovered, and the solid material extracted again with 15 mL portions of THF (with BHT). The combined THF extracts were then extracted twice with 40 mL portions of n-hexane/ethyl acetate (9:1 v/v) and 40 mL of NaCl solution (10 g/L). The combined organic layers were collected and evaporated to a dry state and the residue dissolved in 2 mL of methanol: THF (95:5, v/v). The chromatographic separation of the compounds was achieved by means of a 250 mm × 4.6 mm i.d., 5 μm particle Size C18 polymeric reversed-phase, VYDAC 201TP™ column. The mobile phase was acetonitrile/methanol/dichloromethane (84:15:1, v/v) at a flow rate of 1.2 mL/min. Spectrophotometric detection was achieved by a diode array detector (Photodiode array 2996-Waters, Milford, MA, USA) set in the range of 200-600 nm. Carotenoids were identified through their characteristic spectra and retention times in comparison with standards.
Determination of Tocopherols
For this research, 10 g of a sample was saponified with 40 mL KOH (50%, w/v) plus 120 mL of ethanol (96%, v/v) in a Soxhlet apparatus for 30 min and then extracted with 100 mL of diethyl ether (adding 10 g of BHT as antioxidant). The organic phase was repeatedly washed with water saturated with ethyl ether to neutral pH and then recovered. The volume was corrected to 250 mL with ethyl ether and 100 mL aliquot evaporated to a dry state; the residue was dissolved in 25 mL of n-hexane. HPLC analysis was achieved by means of a 250 mm × 3.3 Lichrosorb Si60 column (Merck) and fluorimetric detection (λexc: 290 nm; λem: 330 nm) with Perkin Elmer LC 24 detector. The mobile phase was n-hexane/ethyl acetate (100/7.5, v/v) at a flow rate of 2 mL/min. Tocopherols were identified through comparison of their retention times with known standard solutions [44].
Determination of Total Antioxidant Capacity
The total antioxidant capacity of the sample was measured by two procedures: (i) a direct procedure based on the TEAC assay and previously described by Açar et al. [18]; and (ii) an extraction/hydrolysis procedure. For the latter procedure, the sample was extracted as previously described [19] and analyzed in triplicate for antioxidant capacity by FRAP assay [45]. The antioxidant capacity was expressed as mmol of Trolox equivalents per 100 g fw and mmol of Fe 2+ equivalents per 100 g fw for the TEAC and FRAP assays, respectively.
Determination of Polyphenols
The phenolic compounds were extracted following the procedure described by Crozier et al. [46], and determined by the Folin-Ciocalteu assay using the method described by Adom and Liu [47]. Briefly, the extracts were oxidized with Folin-Ciocalteu reagent, the reaction was neutralized with sodium carbonate and the absorbance was measured at 760 nm. Data were reported as mean ± SD for at least three replications and were expressed as mg catechin equivalents per 100 g fw.
Conclusions
Our results showed that the Bambara groundnut seed of Ci12 landrace of Côte d'Ivoire is a good source of essential amino acid, n-6 fatty acids and minerals, mainly Fe. With a high yield even when grown on poor soils, the Bambara groundnuts landrace C12 has the potential to improve the nutritional status and could be regarded as a nutrient dense food. Moreover, a tailored fermentation process could be optimized in an attempt to reduce anti-nutrients and, in turn, to improve the bioavailability of minerals and the overall nutritional quality. | v3-fos |
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} | s2 | Evaluation of Two PCR Tests for Coxiella burnetii Detection in Dairy Cattle Farms Using Latent Class Analysis
Different tests performed on bulk tank milk samples (BTM) are available to determine the C. burnetii status of herds. However, these tests, which are based on the detection of either antibodies directed against C. burnetii (ELISA) or bacterial DNA (PCR), have limitations. A currently disease-free herd infected in the past may continue to test positive with ELISA due to the persistence of antibodies in animals that were infected and that subsequently cleared the infection. Infectious herds can also be misclassified using PCR because of the absence of bacteria in the BTM when the test is performed. Recently, PCR has been used for bacterial DNA detection in the farm environment, which constitutes the main reservoir of C. burnetii. The objectives of this study were to assess and compare the sensitivities and specificities of one commonly used PCR test in BTM (PCR BTM) and of a PCR applied to environmental samples (PCR DUST) in dairy cattle farms. BTM and dust samples were collected (using environmental swabs) in 95 herds. The evaluation of the performance of the 2 tests was conducted using latent class models accounting for within herd disease dynamics. Parameter estimation was carried out using MCMC, within a Bayesian framework. Two types of priors were used for the specificity of PCR DUST. A model with a uniform prior on 0–1 fitted the data better than a model with a uniform prior on 0.95–1. With the best model PCR DUST had a lower sensitivity than PCR BTM (0.75 versus 0.83) and a specificity of 0.72. The moderately low value for the specificity of PCR DUST suggests that the presence of bacteria on farm is not always associated with persistent infections and shedding of bacteria in milk.
Introduction
Coxiella burnetii (C. burnetii) is the infectious agent responsible for Q fever, a zoonosis with worldwide distribution (with the exception of New Zealand). Infection in humans is usually asymptomatic but can induce acute or chronic disease [1]. In livestock C. burnetii infection can lead to abortion, stillbirth and fertility disorders [2]. C. burnetii is shed through birth products, feces, urine, milk and vaginal mucus [3][4][5]. C. burnetii infection in humans and livestock occurs mainly after inhalation of contaminated aerosols, with shedding ruminants considered as the main reservoir for transmission to humans [6]. The detection of 'contaminated farms', where C. burnetii is present, could therefore help to prevent infection in humans.
Different tests are available to determine the C. burnetii status of herds. These tests are based on either the detection of antibodies directed against C. burnetii (ELISA) or of bacterial DNA (PCR). As bulk tank milk (BTM) provides an aggregated measure at the herd level and is easy to collect, it is frequently the target sample. ELISA tests applied to BTM are cheap and thus used in epidemiological studies. However, these tests are not well suited for detecting infectious farms because a positive test result can be due to persistent antibodies from past infection. PCR tests performed in BTM allow the detection of C. burnetii shedder cows. However, falsely negative responses may occur as infectious cows can shed bacteria in milk intermittently [5], or when the shedder cows are dried-off.
C. burnetii is highly resistant in the environment which therefore constitutes the main source of contamination for both humans and animals. Recently tests based on the detection of bacterial DNA in the environment have been developed. As a result C. burnetii has been detected in airborne dust samples and surface area swabs in BTM-positive goat farms during an outbreak in the Netherlands [7][8][9]. Such environmental samples could thus be a complementary option to assess a herd's C. burnetii status regarding the presence of the bacteria. To our knowledge, the sensitivity and specificity of tests based on DNA detection have not yet been evaluated in either environmental samples or BTM.
The difficulty associated with such an evaluation is that there is no reference test, i.e. gold standard, against which to compare the outcomes of environmental and BTM PCRs. There exists a rich literature on modelling disease status and test outcomes in the absence of a gold standard [10]. Most of the work in this area builds on an article by Hui and Walter (1980) who derived a method for estimating disease prevalences and test characteristics in the absence of a gold standard when several tests were available [11]. The numbers of populations and tests required for the estimation procedure to be accurate were constrained by the number of parameters to estimate. Further assumptions were that the tests had the same characteristics in all populations and that the test results were conditionally independent. Using Bayesian methods [12], it becomes possible to relax the constraints on the numbers of populations and tests by putting priors on parameters for which some information is already available [12,13]. A further improvement consists in modelling the covariances between test results [12]. Finally, with longitudinal data, the latent statuses at consecutive points in time may be correlated. Incorporating a time correlation in the latent states should therefore lead to a more accurate estimation of model parameters [14][15][16].
The objectives of this study were to assess and compare the sensitivities and specificities of one commonly used PCR test in BTM and of a PCR test applied to environmental samples in dairy cattle farms using latent class analysis. Both single tests and a combination of tests, used in parallel or in series, were evaluated.
Ethics Statement
Except the permission of the farmers who kindly accept to participate to this study, no specific permissions were required for the data collection. Moreover, this study did not involve endangered or protected species.
Sample collection
Data were collected in the Finistère department located in the north western part of France. Ninety-five dairy cattle herds were selected in different parts of the department. These herds were followed for a total period of 1 year. In each herd, BTM samples and indoor dust were collected every 4 months. There were thus 4 sampling times for each herd. Passive accumulation of dust was collected using environmental swabs placed in the barn for a 2-week period. Swab samplings were standardized between herds towards the likelihood of detecting C. burnetii. Swab locations were chosen to minimize the distance to cows and maximize the distance to the main door as shown in Fig 1. In addition, data collection was calibrated between operators in order to ensure homogeneity of the collection process.
Diagnostic tests
Two diagnostic tests were performed at the herd level: transposase. The environmental swabs were vortexed with 40 mL of phosphate buffered saline solution (PBS). To avoid false negative results due to low concentration of the bacteria in the swabs, 1.5 mL of the PBS solution was then centrifuged to concentrate the bacteria. Finally, extraction was performed on the centrifugation sediment. As the extraction is usually performed from 200μL of solution, raw results were divided by 7.5 to account for the impact of centrifugation (corresponding to the ratio 1.5mL/200μL) to obtain the total number of bacteria per ml of PBS.
In both cases, the results were expressed in number of C. burnetii/ mL.
Statistical analyses
Models considered. The evaluation of the performance of the 2 tests was conducted using latent class models. Parameter estimation was carried out using MCMC, within a Bayesian framework. This type of analysis allows the evaluation of sensitivity and specificity of one or several tests, in the absence of a gold standard. A latent class model refers to situations where the event of interest is not directly observed, i.e. latent. In this study, what was measured in the farms was the shedding of bacteria in the milk of infected cows (based on PCR applied to BTM) and the environmental contamination (using the PCR applied to dust).
Within the current study design, contrary to the approach followed by Toft et al. (2007), it was difficult to split the available herd population into 2 or more groups with different disease prevalences [17]. On the other hand, the 4 sampling times per herd provided some information on the herd status that can be exploited. In order to account for these constraints, the Hui-Walter model was adapted. The model outcome was one of the 4 possible combinations of two test responses in a herd on a given sampling time, which followed a multinomial distribution. This was modelled as follows: Where O ij was the combined response of test 1 (T 1 , PCR on BTM) and test 2 (T 2 , PCR on dust), with 4 possible outcomes: ++, +-, -+ and-, on time i in herd j. These outcomes occurred with probability p 1 ij to p 4 ij respectively which depended on the latent status at time i in herd j, denoted S ij .
The simplest version of the model assumed conditional independence between tests parameters (CID model). If the outcomes of the2 tests were independent the probabilities p 1 ij to p 4 ij could be written as: where Se 1 and Se 2 are the sensitivities of test 1 and test 2 respectively and Sp 1 and Sp 2 are the specificities of test 1 and test 2 respectively.
Because the outcome of one test could be correlated with the outcome of the other test, the covariance between the 2 sensitivities was modelled (COD model). Since one of the specificities was assumed to be equal to 1 (see below), the covariance between them was not modelled. To accommodate for conditional dependence between sensitivities, the equations were modified as follows: where γ Se was the covariance between the 2 sensitivities. Constraints were put on the covariance as described in Toft et al. (2007): It was hypothesized that the status of farm j on time i-1 could provide some information on the status of herd j on time i. The variable S ij was assumed to follow a Bernoulli distribution with parameter t S ðiÀ1Þj : where τ 0 was the probability of a new infection occurring on a farm between two consecutive tests and τ 1 was the probability of not eliminating the infection ('absence of cure') between two consecutive tests. τ 0 and τ 1 were assigned uniform priors on 0-1. For the first of the 4 sampling times, there was no previous test result to inform S 1j . It was assumed that at the start of the study, the disease prevalence was in a state of equilibrium in the population, in which case the number of 'cures' equals the number of 'new infections'. If π is the disease prevalence at equilibrium, this means that τ 0 (1−π) = (1−τ 1 )π. This allows expressing π as: The estimated prevalence of the latent state at equilibrium was used as a prior for S 1j . Not accounting for a potential conditional dependence could lead to considerable bias in the estimates of the tests' properties [18]. Therefore the goodness-of-fit of CID and COD models were compared using deviance.
Parameter estimation. Parameters were estimated using MCMC in a Bayesian framework. Uninformative priors (uniform on 0-1) were used for the tests' sensitivities as well as for the τ. parameters, but not for specificities. As specificity decreases, the proportion of false positives increases. Based on experts' opinion, it was considered that when bacterial DNA was amplified in a sample, there really were C. burnetii in this sample. Thus, a positive PCR BTM was assumed to indicate with certainty that at least one cow was shedding bacteria in her milk. On the other hand, the significance of amplifying C. burnetii DNA from the environment was evaluated by testing various priors for the specificity of PCR DUST. Two distributions were tested as priors. In a first model (Model 1), a uniform distribution on 0.95-1 was used to model a high specificity for PCR DUST. This means that when there were no bacteria in the farm, the test could yield at most 5% of positives. However, there could also be situations in which bacteria are present on the farm but do not play any epidemiological role, for instance bacteria transported by wind from another farm which do not subsequently infect any cow. Therefore, in a second model (Model 2), a uniform prior on 0-1 was put on PCR DUST. This prior put no constraints on the probability for a PCR DUST positive sample to be associated with animal shedding.
The models were implemented in OpenBUGS [19], dedicated to Bayesian analysis using Markov Chain Monte Carlo (MCMC) methods. For each model, three chains were run for 10,000 iterations. The first 5,000 iterations were discarded (burn-in). The last five thousand iterations were used for the evaluation of posterior distributions. Convergence of the MCMC chains was assessed using the Gelman-Rubin diagnostic [20]. Convergence was assumed for values below 1.1 [21]. Posterior inference was done by calculating means and 95% posterior credibility intervals (PCI) of all the parameters. Raw data and R code used for analyses are available in the supplementary files (S1 Dataset and S1 R Code).
Test combinations
Combinations of tests used either in parallel or in serial reading were also evaluated for both Model 1 and Model 2. In serial reading, the combined response is positive only if both tests are positive. In parallel reading, the combined response is positive if one or both results are positive. With the model assuming conditional independence (CID), posterior means of sensitivities and specificities were estimated as follows:
Results
Sixty-nine percent of the test responses were in agreement between PCR tests (Table 1). Eighteen percent were PCR DUST positive while PCR BTM negative. When responses were divergent, around half less bacteria were found in the positive samples, either in BTM or in dust samples, compared to situations where both responses were positive.
Several models were tested, which differed by the priors put on the specificities and by the inclusion of a covariance term accounting for conditional dependence between the 2 sensitivities. The covariance term was never significant (the credible interval included 0) and the models had a larger deviance than equivalent models which did not include this variable. Therefore, the 2 final models presented in Table 2 assume conditional independence (CID) between test sensitivities. In Model 1, the assumption was made that PCR DUST returned less than 5% of positives in latent status negative farms. In Model 2, the proportion of false positives with PCR DUST could take any value between 0 and 1. Model 2 had a lower deviance, indicating that not constraining the specificity of PCR DUST resulted in a better model fit. In this model, the posterior mean for the specificity of PCR DUST was 0.72 which means that 28% of truly negative herds would test positive with this test. Model 2 also had a higher posterior mean for the sensi- (Table 3). On the other hand, as expected, the serial reading led to the best specificity (equal to 1 with PCR BTM), whatever the model.
Discussion
Models based on latent class analysis were used to estimate the farm-level performances of 2 PCR tests for the detection of C. burnetii from BTM and dust samples. From the model that Table 2. Posterior means and 95% posterior credibility intervals (PCI) of sensitivities (Se) and specificities (Sp) for the PCR tests performed in bulk tank milk (PCR BTM) and indoor dust samples (PCR DUST), for the 2 models with different priors for the specificity of PCR DUST. PCR BTM (n = 380) and PCR DUST (n = 380) tests were performed in 95 dairy cattle herds in the Finistère department, France between November 2012 and April 2014. fitted the data best (Model 2), a PCR performed on dust samples had a sensitivity of 0.75 and a specificity of 0.72 while a PCR performed on bulk tank milk, which was assumed to have a perfect specificity, had a sensitivity of 0.83. Since the parameterization was forcing all PCR BTM positive samples to be true positives, the latent state can be defined as Presence of at least one cow excreting C. burnetii in her milk within a farm. With this model, the estimated prevalence of the latent state was of 0.62. Model 1, in which both tests were associated with a close to perfect specificity, did not fit the data as well. Assuming that a positive PCR was associated with the presence of bacteria in the sample (BTM or DUST), this would imply that the presence of bacteria on a farm is not systematically associated with infectiousness of cows. In this case, the latent state can be defined as Presence of C. burnetii within the farm. This finding contradicts the classical assumption of extreme infectiousness of C. burnetii [22]. From Table 2 the discrepant responses PCR DUST positive-PCR BTM negative were more frequent than PCR DUST negative-PCR BTM positive. The PCR DUST positive-PCR BTM negative responses were associated with lower bacterial loads in the test positive samples, compared to situations where C. burnetii DNA was detected in both the BTM and dust samples. This is consistent with Model 2 and reflects a low exposure of cows to bacteria from the environment and, possibly, an absence of shedding of bacteria by cows in the environment.
Thanks to the longitudinal study design with a constant time interval between sample collections, we were able to take the temporal correlation in farm statuses between sampling times into account. We propose a new model parameterization that allows evaluating disease dynamics through the estimation of an infection rate (τ 0 ) and of a clearance rate (1-τ 1 ) within a SIS (Susceptible-Infectious-Susceptible). Although the 2 prior distributions considered resulted in an estimated 10% difference in latent status prevalences, the estimated values for the probabilities of new infection (0.15 to 0.18) and infection persistence (0.91 to 0.93) were relatively close. This parameterization presents the further advantage of allowing the incorporation of previous herd data for the estimation of the latent (true) herd status. This can be helpful for diseases that are not eliminated easily and for which diagnostic tests have a poor sensitivity. This was the case for Q fever, but would also apply to other diseases of importance in farm animals such as paratuberculosis. To address this problem, other authors have developed Bayesian models with change points representing the transition from non-infected to infected [14,16]. Our approach is simpler, but requires that the tests are carried out at equally spaced time intervals.
The different priors tested in the 2 models allowed us to reconsider the definition of the latent state. Our initial assumption was that it was very unlikely for a PCR to yield a positive result when there were no C. burnetii in the sample tested. Furthermore, because the bacteria are considered to be highly infectious, we had assumed that their presence was likely associated with the spread of the infection in the farms in which they were identified. However, relaxing the constraints on the prior for the specificity of PCR DUST was associated with a better model fit and a posterior mean specificity of 0.72 for PCR DUST. This therefore indicates that a PCR performed on DUST can be positive even though the herd is negative for the latent status. Our interpretation is that bacterial DNA was amplified from the sample, but, given the constraints imposed by the model and the data, these bacteria were not associated with a positive latent status. This latent status was determined from both the results of the 2 tests and the previous latent status. Regarding the latter, the transition from the previous to the current status was constrained by 2 model parameters representing new infections and cures. Both the probabilities of acquiring (0.15) and of curing (1-0.91 = 0.09) the infection were relatively small and resulted in between 5 and 6% ((1-π) τ 0 = π (1-τ 1 )) of all herds acquiring and curing the infection between consecutive sampling times. This could have led to some herds positive for PCR DUST being classified as negative for the latent status, especially if they were negative for PCR BTM on the current (perfect specificity of PCR BTM) and next (small probability of cure) sampling times. Therefore, from an initial hypothesis where the identification of bacterial DNA was considered as significant from an epidemiological point of view, a model incorporating disease dynamics suggests that, in some cases, the presence of bacteria may not be sufficient to consider that C. burnetii are circulating between animals. While latent class analysis is usually performed to evaluate test characteristics and disease prevalence, it can also be used to investigate disease dynamics. In our case, it led to questioning the meaning of the latent status.
The two PCR tests appear to be complementary to identify contaminated farms, i.e. where C. burnetii is present. From Model 2, 92% of them were likely to be detected, in case the responses from both PCR tests were considered using a parallel reading. This increase in sensitivity associated with combining PCR tests responses (0.92 instead of 0.83 when considering the PCR BTM response alone) was related to their ability to detect very low bacterial levels in at least one sample (dust or milk). Thus, a perspective of this study could be to investigate the C. burnetii status of professionals (farmers, abattoir workers, veterinarians. . .) at risk of being exposed to the bacteria, and to assess the extent to which different levels of exposure within contaminated farms are associated with infection in humans. In this case using PCR DUST and PCR BTM would allow maximizing sensitivity.
The presence of C. burnetii on farm may not always be associated with active and persistent infections which contradicts the classical assumption of extreme infectiousness of the bacteria. When the objective is to detect the presence of shedder cows on farm, a PCR test performed on BTM should be preferred. When the objective is to detect the presence of bacteria on farm, whatever their epidemiological role, a PCR test based on the detection of C. burnetii DNA in dust samples collected with environmental swabs has shown good performance and could therefore be proposed, alone or in combination with PCR applied to BTM.
Supporting Information S1 Dataset. Raw data used in this manuscript, including binary and continuous outcomes to both PCR applied to BTM and dust samples. (CSV) S1 R Code. R codes used in the analyses. (R) | v3-fos |
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} | s2 | Chlorophyll Fluorescence and Yield Responses of Winter Wheat to Waterlogging at Different Growth Stages
Abstract The agronomic and physiological effects of waterlogging in winter wheat were examined at four growth stages in the 2011/2012 and 2012/2013 seasons. In both seasons, the greatest yield penalties occurred by waterlogging at the tillering stage (10%–15% decrease), followed by the jointing stage; however, waterlogging at the grain filling stage had less effect on the yield. The lower grain yield caused by waterlogging at the tillering stage was primarily reflected in reductions in spike and grain numbers per m2. Waterlogging at the jointing and booting stages reduced grain weight through reduced dry matter translocation. In addition, waterlogging at the tillering stage significantly reduced chlorophyll content and thus photosynthetic capacity, resulting in a lower Fv /Fm ratio, apparent electron transport rate (ETR), effective quantum yield of photosystem II (ΦPSII) and photochemical quenching (qP). However, waterlogging at the grain filling stage improved the leaf photosynthetic capacity and grain yield. We found that the tillering stage was most the susceptible to waterlogging in wheat; therefore, the maintenance of photosynthetic performance after anthesis could be a reasonable strategy for increasing grain yield.
Waterlogging is a global constraint on wheat (Triticum aestivum) production worldwide, particularly in irrigated areas and high rainfall environments (Shao et al., 2013;de San Celedonio et al., 2014). Waterlogging affects approximately 1 -15 million ha wheat globally, representing 15 -20% of the 70 million ha of wheat cultivated annually (Setter and Waters, 2003). The effects of waterlogging are most widespread in the rice-wheat rotation regions of south and southeast Asia, including Bangladesh, Pakistan, India, Nepal and China (Samad et al., 2001). In recent years, due to the increase in extreme climate events (Wollenweber et al., 2003;Shao et al., 2013), the occurrence of waterlogging has increased. Approximately one-third of the winter wheat area in southwestern China is devoted to tillage in rice-wheat rotation. This area is frequently saturated with water from the excessive rainfall during the growing season, especially in autumn, and waterlogging often exceeds 4 weeks. This results in poor seeding stand establishment and weak growth. These conditions represent a significant risk for intermittent waterlogging resulting from irregular and unseasonal rainfall.
At the agronomic level, the typical response of waterlogging is; restricted root growth, reduced dry matter accumulation, premature leaf senescence, increased wilting and sterile floret production, and reduced tillering, kernel weight and grain yield (Zhang et al., 2006;Jiang et al., 2008;Hossain and Uddin, 2011;Shao et al., 2013). Sairam et al. (2008) and Zheng et al. (2009) reported induced chlorophyll degradation and reduced photosynthesis and chlorophyll fluorescence under waterlogged conditions. Mineral nutrient deficiencies and microelement toxicities at the physiological level were reported by Setter and Waters (2003) and Setter et al. (2009). Waterlogging can reduce winter wheat grain yield by approximately 20 to 50%, depending on several factors, which includes the stage of crop development (Setter and Waters, 2003) and severity and duration of waterlogging (Collaku and Harrison, 2002;Malik et al., 2002). Several studies have shown that the variations in wheat yield were primarily reflected in grain number, with little influence on individual grain weight (González et al., 2005;Peltonen-Sainio et al., 2007). The reduced plant biomass production could be directly associated with limited stomatal conductance and photosynthesis, which reduces carbon assimilation (Mielke et al., 2003). Many studies have also been reported on waterlogging impacts at different growth stages. For example, Li et al. (2001) concluded that waterlogging treatment during vegetative growth improves tolerance to waterlogging after anthesis in wheat. de San Celedonio et al. (2014) concluded that the greatest yield reduction occurred when the plant was waterlogged during the period from seven leaves on the main stem to anthesis. In their studies, reduction in grain number was primarily reflected in the reduced grain numbers per spike. Saqib (2002) demonstrated that waterlogging for 25 days at the tillering stage did not significantly reduce the grain yield of bread wheat genotypes in Pakistan. However, the largest reductions in grain yield and 1000 grain weight were observed when waterlogging was applied at the stem elongation and grain filling stages. In southwest China, little is known about the critical period of sensitivity to waterlogging in wheat. Additionally the agronomic and physiological changes in response to waterlogging have not been characterized.
The aim of this study was to examine the effects of applied waterlogging at different growth stages, on the agronomic and physiological traits of wheat to identify the most waterlogging-sensitive period of this plant. This study was conducted to help in the development of a more functional approach to simulate wheat responses to waterlogging and its mitigation.
General conditions, treatments and experimental designs
Field experiments were conducted in Guanghan County, Sichuan Province, China (104º 25´N 30º 99´E, 450 m above sea level) over two growing seasons (2011 / 2012 and 2012 / 2013). Two popular wheat varieties were used, Neimai836 and Chuanmai104. Neimai836 was bred by Neijiang Academy of Agriculture Science and released in 2008. It was widely used in the hilly areas of southwest Sichuan. Chuanmai104, a high yielding variety, was bred by Crop Research Institute of Sichuan Academy of Agriculture Science and released in 2012. The field soil was a clay loam with 43.84 g kg −1 organic matter, 186 mg kg −1 alkali-hydrolyzable N, 9.6 mg kg −1 Olsen-P, and 113 mg kg −1 exchangeable K in the 0 -20 cm soil profile. Wheat was sown on 31 October 2011 and 2 November 2012 in plot areas of 13.68 m 2 (3.6 m wide × 3.8 m long in 18 rows, 20 cm apart) with line socket spacing of 20 cm × 10 cm. Ten seeds per socket in Neimai836 and 7 seeds per socket in Chuanmai104 were sown according to the seed germination rate (Chuanmai104 was 99%, Neimai836 was 76%). Nitrogen basal fertilizer was applied at 135 kg ha −1 . Other cultivation and management measures were consistent with the field production.
The experiments were arranged using a split plot design with three replicates, with the main plots as wheat varieties, while the waterlogging treatments were split plots. Four treatments (T1 -T4) were used to evaluate the effects of waterlogging (WL) at Feekes' stages 2 (treatment T1 at the tillering stage, tillering initiated), 4 (T2 at the jointing stage, stem elongation approximately 1 cm,), 9 (T3 at the booting stage, heads emerging through flag leaf sheaths) and 10.5 (T4 at the grain filling stage, flowering initiated) after Large (1954) based on physiological indicators (SPAD and chlorophyll fluorescence parameters), growth, and wheat yield from 2011 to 2013. All waterlogged treatments were conducted for 35 days, which was achieved by pumping water onto the plots 2 -3 times per day to maintain a 1-2 cm layer of free water on the field surface in the daytime during the entire waterlogging period. The control (CK) was not irrigated.
Agronomic and physiological measurements
Two rows of wheat in each plot were tagged for tiller number observations, which were taken at the three-leaf, jointing and maturity stages. The percentage of productive tillers was defined as the number of spikes that developed from tillers expressed as a percentage tiller numbers at the jointing stage. At the end of the waterlogging treatment, leaf area index (LAI) was determined using the formula of leaf area divided by ground area. Plants from three rows in each plot (except those in border rows) were harvested at maturity (early to mid May) for grain yield determination, which was adjusted to 13% moisture. The yield components, spike number per m -2 , grain number per spike, grain number per m -2 , and 1000-kernel weight (TKW), were determined by sampling randomly three sockets from each plot (excluding those in border plants).
The total above-ground dry mass was measured at the end of waterlogging at the tillering, jointing, booting and grain filling stages. Two sockets of plants from each plot were sampled from the third row to minimize the border effect. Total dry matter (DM) was determined after drying at 70ºC to a constant weight and by noting the final weight. In addition, DM at anthesis and maturity was also determined. DM remobilized into grain, remobilization efficiency and DM contribution to grain, were calculated using the following formula: DM remobilized into grain = above ground DM at anthesis minus the accumulated nongrain DM at harvest; Remobilization efficiency = DM remobilized into grain /DM at anthesis × 100; and DM contribution to grain weight = DM remobilized into grain/total grain yield × 100.
The greenness of the topmost, fully expanded lamina, was measured in both cultivars during waterlogging and after anthesis, using a non-destructive, hand-held chlorophyll meter (SPAD-502; Konica Minolta Sensing Inc., Osaka, Japan). The SPAD readings were obtained from the one-third and two-third positions of each lamina. Ten lamina were measured in each subplot, and these values were averaged. The chlorophyll fluorescence was also measured in the topmost leaf at the end of waterlogging at different stages and at 15, 25, and 35 days after anthesis (DAA) using a hand-held fluorometer, FluorPen FP100 (Photon Systems Instruments, Czechoslovakian Republic). The chlorophyll fluorescence data were collected on three occasions. At the onset of flowering, five plants in each plot were tagged and successive readings were obtained from the same plant. Prior to each measurement, a clip was placed on the leaf for 30 min for dark adaptation. The weak-modulated irradiance, "actinic light", and saturating pulses were 0.8, 1200, and 4,000 μmol m -2 s -1 , respectively. The parameters; F v /F m , ETR, qP and NPQ, were calculated according to Maxwell and Johnson (2000).
Statistical analysis
The treatment effects were analyzed using analysis of variance (ANOVA) in the SAS statistical analysis package (SAS version 8.0 for Windows, SAS Inc., IL, USA). Treatment means were compared using the least significant difference (LSD) test at P ≤ 0.05, unless specified otherwise.
Grain yields and yield components
Significant differences in the grain yields were observed between varieties. The grain yield of Chuanmai104 was higher than that of Neimai836 across all treatments in both years (Table 1). Waterlogging at the tillering stage showed the greatest effect on grain yield, with a 10 -15% reduction compared with the control (CK), followed by jointing, booting and grain filling stages. In 2011 /2012, grain yield in treatments T3 and T4 showed a slight increase compared with CK, although not statistically different. The effect of waterlogging on Neimai836 in 2012 /2013 was similar to that observed in 2011 /2012. Chuanmai104 grain yield was significantly reduced by all waterlogging treatments, except for T4. In both years and varieties, the decrease in the yield in T1 was due to a significant decrease in spike numbers m −2 and grain numbers m −2 , however other yield components remained unaffected.
In both years, the spike numbers m −2 and grain numbers m −2 in Chuanmai104 were larger than those in Neimai836, reflecting the higher grain yield in Chuanmai104. The spike numbers m −2 were significantly reduced in T1 in both cultivars. The 1000-kernel weight in both varieties was significantly reduced in treatments T2 and T3 compared with CK. Waterlogging treatments did not significantly affect the grain number per spike in either cultivar.
The phenological events were significantly affected by waterlogging treatments in both cultivars and seasons. In 2011/2012, days to jointing was 4 days shorter in T1 than significantly decreased LAI, but that at other stages had no significant effect on LAI. In Chuanmai104, waterlogging at the vegetative stages (tillering and jointing stage) had no significant effect on LAI, while waterlogging at the booting stage reduced LAI, and that at the grain filling stage increased it.
In 2011/2012, dry matter (DM) accumulation was not significantly influenced by waterlogging at any stage in both varieties. In 2012 /2013, however, waterlogging at jointing significantly increased DM accumulation and that at the grain filling stage significantly reduced DM accumulation in Chuanmai104 though not in Neimai836.
Dr y matter at anthesis and maturity and DM remobilization
There was no significant genotype variation (p > 0.05) in DM accumulation was observed in either season (Table 4). In 2011/2012, T2 treatment significantly increased DM at anthesis and maturity in Neimai836, while it reduced DM remobilization into grain, remobilization efficiency, DM contribution to grain and harvest index compared with CK. DM accumulation at maturity was significantly reduced in T1, T3 and T4 in Neimai836. In Chuanmai104, DM at anthesis and maturity, and the harvest index, were significantly reduced in T1 treatment, while other DM parameters were increased compared with CK. DM remobilized into grain, remobilization efficiency and harvest index were markedly reduced in T2, while the remobilization efficiency and DM contribution to the grain were reduced in T4 treatment.
In 2012/2013, both cultivars exhibited similar responses to waterlogging at different growth stages. T1 reduced DM accumulation and remobilization parameters except DM at maturity, but had no effect on harvest index. Treatments T2 and T3 did not affect dry matter parameters compared in CK in both varieties. In addition, the dates of anthesis and maturity in T1 and T2 were delayed 2 days in Neimai836. In T3 and T4, the date of anthesis was not delayed, but the date of maturity was delayed 3 days. Thus, the grain filling duration of Neimai836 was longer in T3 and T4 than in CK. In Chuanmai104, the days of anthesis and maturity were delayed by all waterlogging treatments by 1 -4 days, and the grain filling duration was increased by 2-3 days compared with CK.
In 2012 /2013, the date of jointing in T1 was 7 days earlier than in CK in both varieties. However, in T2, the day of jointing was 6 days earlier than in CK in Neimai836 and 2 days earlier in Chuanmai104. Moreover, in comparison with CK, treatment T1 delayed anthesis and maturity in both varieties by 3 days, while the other treatments did not delay either stage, regardless of the variety.
Tiller number, Leaf area index and Dry mater accumulation at different stage
Tiller number was larger in Neimai836 than in Chuanmai104 at tillering and jointing stages, but smaller in the former than in the latter at maturity. In both seasons, treatment T1 significantly decreased tiller numbers at jointing and maturity compared with CK (Table 2). However, the number of tillers was less affected by T2, T3 and T4 treatments, even though all of the waterlogging treatments increased the percentage of productive tillers.
The stage-dependent changes in the leaf area index (LAI) in the four treatments in the two seasons are shown in Table 3. In 2011 /2012, waterlogging at the tillering stage significantly reduced LAI in both varieties, but waterlogging at the grain filling stage tended to increase it. In 2012 /2013, waterlogging at the tillering stage with CK. T4 decreased DM at anthesis in Neimai836, and DM remobilized into grain, remobilization efficiency, and DM contribution to the grain in Chuanmai104.
SPAD reading and Chlorophyll fluorescence
(1) SPAD reading SPAD readings during the 35 days of waterlogging significantly varied with the treatment (T1 -T4) in both wheat varieties (Fig. 1). Significant reductions in SPAD readings were observed at 15 days in T1, but at 20 days in T2. Responses to waterlogging were not observed in T3 and T4 had no effect on the SPAD readings until the end of the treatment period (35 days), suggesting that waterlogging during vegetative growth improved leaf SPAD reading attenuation, while waterlogging during reproductive growth delayed leaf senescence. Changes in SPAD readings after anthesis are shown in Fig. 2, which exhibited a sharp reduction at 15 days after anthesis in both varieties; however, the reduction in T1 and T4 was less pronounced than in T2 and T3. Genotype differences were observed at 35 days after anthesis, at which T1 had the least effect on the SPAD readings in Neimai836, while T4 showed the least effect on the SPAD readings for Chuanmai104. effect on ΦPSII, ETR and qP compared with CK.
There were no significant differences in chlorophyll fluorescence parameters (F v /F m , ΦPSII and qP) at the early grain filling stage (15 days after anthesis, DAA) among the waterlogging treatments (T1 -T4) in either wheat varieties, except for F v /F m in Chuanmai104 in T4 (Table 6). At the mid-grain filling stage (25 DAA), a reduction in the F v /F m was observed in T4 in comparison with the other waterlogging treatments, in both varieties, but no significant difference was observed in ΦPSII among waterlogging treatments. Moreover, Neimai836 showed no difference in qP with the waterlogging treatment, while Chuanmai104 was markedly affected by treatments T2, T3 and T4 compared with CK. A significant decrease in the F v /F m and ΦPSII was observed at the late grain filling stage (35 DAA), compared with early and mid-grain filling Where CK is the control and T1, T2, T3 and T4 denote the waterlogging treatments at tillering, jointing, booting, and grain filling stages, respectively.
(2) Chlorophyll fluorescence Waterlogging at the tillering stage significantly decreased F v /F m , ΦPSII, ETR and qP, but increased NPQ parameters (Table 5). Differences in the chlorophyll fluorescence parameters between the two varieties were observed at the jointing stage: the chlorophyll fluorescence parameters in Neimai836 were not affected by waterlogging, while the F v /F m , Φ PSII and qP were significantly reduced by waterlogging in Chuanmai104. Waterlogging at the grain filling stage increased F v /F m and reduced NPQ in both cultivars, while it had no significant stages. Furthermore, chlorophyll fluorescence parameters were significantly increased in T1 and T4,(F v /F m , ΦPSII and qP) compared with other waterlogging treatments in both varieties.
Discussion
Waterlogging occurring at different developmental stages could reduce the final grain yield of winter wheat, and the extent of the yield reduction depends not only on the severity of the waterlogging, but also on the stage of plant development. Several studies examined the critical period of waterlogging on wheat grain yield, suggesting that the reproductive stages was more adversely affected than the vegetative growth stages (Li et al., 2001;Setter and Waters, 2003). However, some studies have demonstrated that the period from the beginning of stem elongation to anthesis were most sensitive to waterlogging, in terms of yield penalties (Shao et al., 2013;de San Celedonio et al., 2014). In the present study, tillering was most susceptible stage, followed by jointing, booting, and grain filling stages (Table 1).
In this area, shorter growth period, earlier tillering stage and longer grain filling stage often results in fewer spikes per m 2 , so higher yield depends largely on more spikes per m 2 (Tang et al., 2006). Waterlogging at the tillering stage reduced yield as a consequence of reduction in spike number per m 2 and grain number per m 2 , rather than grain number per spike or the 1000-grain weight. The observed reduction in spike number per m 2 was due to the inhibition of tiller initiation and increased rate of tiller abortion which is in agreement with Shao et al. (2013). Nevertheless, several other studies have demonstrated that waterlogging at the early phase of growth significantly reduced neither biomass nor yield of wheat because waterlogging occurring early in the crop cycle allowed plants to recover from stress by different mechanisms.,This would be related to the waterlogging duration and other factors. The duration of waterlogging in most previous studies were less than 20 days (Cannell et al., 1980;Jiang et al., 2008;de San Celedonio et al., 2014), but our study showed that after 35 d of waterlogging at different stages, the wheat was still alive and had some photosynthetic capacity. This was due to the soil texture of the experimental area. In our study, the soil was clay loam in the topmost 20 cm of soil, while in the deeper layer, the soil was sandy with weak water retention, which was good for water infiltration. On the other hand, waterlogging at the seeding stage has long been the major constraint, which resulted in production of waterlogging-tolerant varieties by the breeder. In the present study, waterlogging at the early crop phases (seeding to tillering) significantly reduced biomass at the reproductive stage (Table 4), consistent with the results of previous studies of Malik et al. (2002) and Pang et al. (2004). Waterlogging at the early phases reduced tiller appearance, leaf area index, wheat growth and dry matter content at the middle or later phases of wheat growth. In wheat, symptoms and injury are initially evident in the roots. When the soil is saturated with water, oxygen deficiency rapidly develops in the roots, causing a sequence of chemical and biochemical reactions, producing components that might be injurious to root metabolism (Palta et al., 2010). In addition, waterlogging at the tillering stage delayed the time of anthesis and maturity, which is consistent with previous studies (Robertson et al., 2009). Since anthesis was delayed by the events at early stages of development, this is likely associated with higher order tiller appearance (i.e. secondary and tertiary tillers). However, the higher-order tillers could not compensate for the early tiller mortality, because the final number of spikes per m 2 was markedly reduced in this experiment.
Waterlogging at the jointing and booting stages also reduced grain yield, although no significant difference was observed compared with CK. This response was reflected in the reduction in grain weight, which is not consistent with the results of Belford et al. (1985), who reported that waterlogging at the jointing stage reduced yield through decreased grain number per spike. In the present study, the reduction in1000-grain weight by waterlogging at the jointing stage was attributed to poor accumulation of dry matter per kernel, and reduced the remobilization of stored carbohydrates from stems/leaves to grains, which is consistent with the previous reports of Jiang et al. (2008) and . Waterlogging at the jointing stage in this study was reflected in reduced SPAD readings and photosynthesis which affected remobilization and grain weight. Therefore, most of the photosynthate used to complete grain weight was largely derived from carbohydrate accumulated in the stems and its translocation to the grains, since the photosynthetic active leaf area was severely affected (Serrago et al., 2011). However, the reduction in the grain weight suggests that the translocation was not sufficient to fulfill the previously established grains. In this sense, it was shown that reduction in grain growth due to waterlogging at the booting stage was attributable to decreased current assimilation and the poor remobilization of water-soluble carbohydrates (Jiang et al., 2008;. Moreover, Calderini et al. (2001) demonstrated that reduction in the carpel size determined reduction in the potential grain weight. Thus, waterlogging around anthesis was likely to reduce grain size potential, through reductions in the carpel size and the number of endospermatic cells, resulting in a lighter grain weight. Notably, in the previous treatment (water logging at the booting stage) had an additional adverse effect on the photosynthetically active leaf area.
The anaerobiosis induced by waterlogging could reduce water uptake by roots, resulting in decreased leaf turgor and stomatal conductance, leading to CO 2 deficiency in the leaves. The decrease in plant biomass production in this case could be directly associated with reduced photosynthesis. The restriction of photosynthetic activity has been attributed to stomata closure (Yordanova et al., 2005), a decrease in leaf chlorophyll content (Bradford, 1983), and the disruption of the translocation of photosynthates (Chen et al., 2005). In the present study, senescence, leaf yellowing and a reduction in total chlorophyll content was observed during waterlogging at the vegetative stages (tillering and jointing), but not at all or only slightly during waterlogging at the reproductive stages. This indicates that waterlogging during the early growth phase reduces photosynthetic performance (reduced LAI and SPAD reading), while waterlogging during later phases may improve the performance (increase LAI and SPAD readings), which is consistent with Shao et al. (2013). Thus, waterlogging at the vegetative stages could lead to leaf yellowing, reflecting a reduction in leaf nitrogen (Bacanamwo and Purcell, 1999), N fixation and the production of toxic substances, such as nitrites and sulfides, which move upward from the soil through the roots to the leaves in large quantities (Ezin et al., 2010). In addition, waterlogging at the grain filling stage delayed the attenuation of the post-anthesis chlorophyll content, improving the translocation of photosynthates to the grain from leaves and stems, prolonging grain filling duration. Therefore, waterlogging at the grain filling stage had a positive effect on grain yield.
Chlorophyll fluorescence has been suggested as a sensitive indicator of stress-induced damage to photosystem II (Maxwell and Johnson, 2000). F v /F m was thought to indicate the effects of environmental stress on photosynthesis (Lavinsky et al., 2007;Jing et al., 2009). For example, a reduction in F v /F m is a good indicator of photosynthetic impairment resulting from waterlogging stress. Throughout our study, reduction in the F v /F m and SPAD values were observed after waterlogging at the tillering and jointing stages, indicating impairment of PSII. Thus, damage to PSII occurred together with reduction in the pigment content and a decrease in ΦPSII after waterlogging. Thus, the use-efficiency of captured photon energy through PSII was reduced. Consistent with the findings of Zheng et al. (2009), a decrease in qP and ETR was also observed during waterlogging at the tillering stage, mainly due to a decrease in the efficiency of excitation energy capture of the open PSII reaction centers (Roháček and Barták, 1999). However, waterlogging at the grain filling stage improved F v /F m , particularly at 35 days after anthesis, which was likely associated with higher chlorophyll content, indicating that waterlogging at the grain filling stage delayed leaf senescence, prolonged the green leaf stage and improved photosynthate translocation. Furthermore, a similar result in SPAD values at 35 days after anthesis was observed for the F v /F m , ΦPSII and qP. Waterlogging at the tillering stage also improved SPAD values and chlorophyll fluorescence parameters at 35 days after anthesis, thus it is reasonable to speculate that waterlogging at the tillering stage inhibited tiller initiation and improved the photosynthetic capacity of the stem leaf, but this higher photosynthetic capacity could not compensate for the decline in grain yield resulting from the reduction in number of spikes per m 2 .
In summary, the tillering stage was identified as the most susceptible to waterlogging in wheat, followed by the jointing, booting, and grain filling stages. Waterlogging at the tillering stage reduced yield through a reduction in the spike number per m 2 and grain numbers per m 2 , while waterlogging at the jointing and booting stages also reduced grain yield, primarily through reduction in grain weight. Waterlogging at the grain filling stage improved leaf photosynthetic capacity and grain yield, which could be considered a strategy for further increases in grain yield. | v3-fos |
2018-04-03T06:02:05.313Z | {
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} | s2 | Establishment of an Agrobacterium-mediated Inoculation System for Cucumber Green Mottle Mosaic Virus
The infectious full-length cDNA clones of Cucumber green mottle mosaic virus (CGMMV) isolates KW and KOM, which were isolated from watermelon and oriental melon, respectively, were constructed under the control of the cauliflower mosaic virus 35S promoter. We successfully inoculated Nicotiana benthamiana with the cloned CGMMV isolates KW and KOM by Agrobacterium-mediated infiltration. Virulence and symptomatic characteristics of the cloned CGMMV isolates KW and KOM were tested on several indicator plants. No obvious differences between two cloned isolates in disease development were observed on the tested indicator plants. We also determined full genome sequences of the cloned CGMMV isolates KW and KOM. Sequence comparison revealed that only four amino acids (at positions 228, 699, 1212, and 1238 of the replicase protein region) differ between the cloned isolates KW and KOM. A previous study reported that the isolate KOM could not infect Chenopodium amaranticolor, but the cloned KOM induced chlorotic spots on the inoculated leaves. When compared with the previously reported sequence of the original KOM isolate, the cloned KOM contained one amino acid mutation (Ala to Thr) at position 228 of the replicase protein, suggesting that this mutation might be responsible for induction of chlorotic spots on the inoculated leaves of C. amaranticolor.
The infectious full-length cDNA clones of Cucumber green mottle mosaic virus (CGMMV) isolates KW and KOM, which were isolated from watermelon and oriental melon, respectively, were constructed under the control of the cauliflower mosaic virus 35S promoter. We successfully inoculated Nicotiana benthamiana with the cloned CGMMV isolates KW and KOM by Agrobacterium-mediated infiltration. Virulence and symptomatic characteristics of the cloned CGMMV isolates KW and KOM were tested on several indicator plants. No obvious differences between two cloned isolates in disease development were observed on the tested indicator plants. We also determined full genome sequences of the cloned CGMMV isolates KW and KOM. Sequence comparison revealed that only four amino acids (at positions 228, 699, 1212, and 1238 of the replicase protein region) differ between the cloned isolates KW and KOM. A previous study reported that the isolate KOM could not infect Chenopodium amaranticolor, but the cloned KOM induced chlorotic spots on the inoculated leaves. When compared with the previously reported sequence of the original KOM isolate, the cloned KOM contained one amino acid mutation (Ala to Thr) at position 228 of the replicase protein, suggesting that this mutation might be responsible for induction of chlorotic spots on the inoculated leaves of C. amaranticolor.
Keywords : agroinfiltration, CGMMV, infectious clone
Cucumber green mottle mosaic virus (CGMMV), a member of the genus Tobamovirus, is a rod-shaped virus with approximately 300 nm in length and contains a plus-sense single strand RNA (ssRNA) genome of 6.4 kb (Ugaki et al., 1991). The CGMMV genome encodes at least four proteins, including the 5′ terminal 129 kDa protein, its translational read-through product of 186 kDa, a 29 kDa cell-to-cell movement protein, and a 17.4 kDa coat protein (Ugaki et al., 1991). The 129 kDa and 186 kDa proteins are replication-associated proteins. The 129 kDa protein harbors a methyltransferase-like domain in its N-terminal region and a helicase-like domain in its C-terminal region, while the read-through part of the 186 kDa protein contains a polymerase-like domain (Ugaki et al., 1991). In Korea, CGMMV was isolated firstly in 1989 (Lee et al., 1990) and caused widespread 'blood flesh' disease in watermelons and considerable economic damage in 1995 in Korea (Lee, 1996). According to the virus isolates and hosts, CGMMV causes various symptoms, including mottling and systemic mosaic symptoms on leaves and deterioration on fruits of watermelon, oriental melon, cucumber, and zucchini (Lee et al., 1990). In our previous study, we investigated symptomatic characteristics of two CGMMV isolates, KW and KOM, which were isolated from watermelon and oriental melon, respectively, and determined their full-genome sequences (Kim et al., 2003).
Plant RNA viruses accumulate mutations easily because of their error-prone replication activity (Domingo et al., 1985). Constructing infectious cDNA clones is, therefore, needed to maintain molecular and biological characteristics of RNA viruses and to study their genetic aspects. Infectious cDNA clones of many kinds of plant RNA viruses, including Tobacco mosaic virus (TMV), Potato virus X (PVX), and Soybean mosaic virus (SMV), have been constructed under the control of the cauliflower mosaic virus (CaMV) 35S promoter or T7 RNA polymerase promoter (Dawson et al., 1989;Ruiz et al., 1998;Seo et al., 2009b). Previously, a full-length infectious cDNA clone of the chb isolate of CGMMV has been constructed for in vitro transcription and shown to have high infectivity in Chenopodium amaranticolor and cucumber (Zhong et al., 2015). However, preparation of viral in vitro transcripts is cost-ineffective and laborious. On the other hand, Agrobacterium-mediated inoculation of viral infectious cDNA clones only requires bacterial cultivation and easily infiltrated onto plants. In this stuty, we established an Agrobacterium-mediated inoculation method for CGMMV. The construction of infectious cDNA clones of CGMMV-KW and -KOM is described and virulence and symptomatic characteristics of the cloned CGMMV isolates were investigated.
Two CGMMV isolates, KW and KOM (Kim et al., 2003) were propagated in Cucumis melo L. (oriental melon) in a greenhouse. Total RNA extraction was carried out from the Cu. melo L. leaves infected with either CGMMV isolate KW or KOM using the TRI Reagent (MRC, USA) according to the protocols provided by the manufacturer. The extracted total RNA was used for cDNA synthesis of CGMMV-KW or -KOM. Specific primers (CGMMV-SacI-F, 5′-CGAGCTCGTTTTAATTTTTATAATTAAACAAAC AACAACAACAAC-3′ and CGMMV-R, 5′-TGGGCC CCTACCCGGGGAAA-3′) were designed based on previously reported sequences of CGMMV-KW and -KOM (GenBank accession numbers AF417243 and AF417242, respectively). cDNAs of two CGMMV isolates were synthesized using the SuperScript III reverse transcriptase (Invitrogen, USA) with CGMMV-R. The resulting cDNAs were subjected to amplify full-length genomes of CGMMV-KW and KOM using the Pfu Ultra II DNA polymerase (Agilent Technologies, USA) with CGMMV-SacI-F and CGMMV-R. The amplified full-length products of CGMMV-KW and -KOM were then digested with SacI and inserted into between the SacI and SmaI sites in pSNU1 vector (Park and Kim, 2006), which is a modified binary vector containing the CaMV 35S promoter. The resulting constructs were named pCGMMV-KW and pCGMMV-KOM, respectively (Fig. 1). The full-length nucleotide sequences of the cloned CGMMV-KW and KOM were determined by the dideoxy nucleotide termination method and an ABI PRISM 3700 XL DNA Analyzer (Applied Biosystem, USA) located at the National Instrumentation Center for Environmental Management (NICEM, Seoul National University).
The plasmid DNAs of pCGMMV-KW and -KOM were transformed into Agrobacterium tumefaciens strain GV 2260. The Agrobacterium transformants were selected on YEP medium plates containing 100 mg/l of kanamycin and 50 mg/l of rifampicin. After screening by colony PCR, the Agrobacterium transformants carrying pCGMMV-KW or -KOM were incubated for overnight at 28 o C with shaking in YEP liquid medium containing 100 mg/l of kanamycin and 50 mg/l of rifampicin. The Agrobacterium cells were centrifuged at 4,000 × g for 10 minutes and resuspended in the infiltration buffer (10 mM MES, 200 μM acetosyringone, and 10 mM MgCl 2 ) to a final OD600 of ~0.5. The resuspended cells were incubated with shaking for 4 hrs at 28 o C to activate the Agrobacterium Vir genes. To verify whether CGMMV full-length in vivo transcripts generated from pCGMMV-KW or KOM are infectious and the virulences are the same as previously reported (Kim et al., 2003), the Agrobacterium cells were inoculated into Nicotiana benthamiana leaves by agroinfiltration. At 12 days post inoculation (dpi), both pCGMMV-KW and -KOM induced typical systemic mosaic symptoms in N. benthamiana ( Fig. 2A). This result demonstrates that pC-GMMV-KW and -KOM are fully infectious. To examine symptomatic characteristics of pCGMMV-KW and -KOM, the saps of N. benthamiana infected with pCGMMV-KW or -KOM were used as inoculums to mechanically inoculate indicator plants, including C. amaranticolor, Cu. sativus, Cu. melo var. makuwa, Citrullus vulgaris, and Lagenaria leucantha. In the previous study, it has been shown that the CGMMV isolate KOM could not infect C. amaranticolor, while the isolate KW induced chlorotic spots on the inoculated leaves of C. amaranticolor (Kim et al., 2003). However, both of the cloned CGMMV-KW and KOM induced chlorotic spots on the inoculated leaves of C. amaranticolor (Fig. 2B and Table 1). In addition, as same as previously described (Kim et al., 2003), both of the cloned CGMMV-KW and KOM systemically infected Cu. sativus, Cu. melo var. makuwa, Ci. vulgaris, and L. leucantha plants and induced mosaic symptoms in these indicator plants (Table 1). Virus replication in the inoculated plants was confirmed by subjecting total RNAs extracted from the inoculated and upper un-inoculated leaves to RT-PCR detection using the CGMMV-specific primers (5′-AGTTACAAGTATAATAGCGGATGT-3′ and 5′-TCAAATACTTGAAAACCGG-3′) (data not shown).
Because the cloned CGMMV-KOM showed different symptomatic characteristic on C. amaranticolor from the original virus isolate, we determined full genome sequences of the cloned CGMMV isolates KW and KOM to examine if mutations are introduced into the cloned CGMMV genomes. The determined deduced amino acid sequences of the cloned CGMMV genomes were compared together with the previously reported original sequences of the CGMMV isolates KW and KOM (GenBank accession numbers AF417243 and AF417242, respectively). Amino acid sequence comparison result was summarized in Table 2. Two amino acids (Lys to Gln at position 7 of the 129 kDa protein and Cys to Ser at position 1572 of the 186 kDa protein) were mutated in the cloned KW and only one amino acid (Ala to Thr at position 228 of the 129 kDa protein) was substituted in the cloned KOM when compared with the sequences of their original isolates. In addition, only four amino acids (at positions 228 and 699 of the 129 kDa protein and at positions 1212 and 1238 of the 186 kDa protein) differ between the cloned isolates KW and KOM. No amino acid sequence difference was observed in the MP and CP regions among the cloned and original CGMMV genomes. Sequence comparison suggests that the mutation A228T in the 129 kDa of the cloned KOM might be responsible for induction of chlorotic spots on the inoculated leaves of C. amaranticolor, because this mutation is the unique difference between the original and cloned KOM genomes. However, when compared with the sequence of the original KOM isolate, the cloned KW contained same Ala at position 228 of the 129 kDa protein but three different amino acids at position 699 of the 129 kDa protein and at positions 1212 and 1238 of the 186 kDa protein (L699I, Construction of infectious cDNA clones of plant RNA viruses is useful for the investigation of the molecular biology of the viruses including pathogenesis, replication, genome expression, and viral gene functions. In this study, we constructed infectious full-length cDNA clones of two isolates of CGMMV, KW and KOM. Infectious in vivo transcripts of the cloned CGMMV genomes were produced under the control of the 35S promoter of CaMV and processed by a self-cleaving ribozyme sequence and a nopaline synthase poly(A) signal to generate authentic 3′ end of a inserted cDNA sequence. These viral transcription and processing signals enable to produce infectious in vivo transcripts by bypassing the difficulties of in vitro RNA transcription.
It is generally known that RNA viruses exist as quasispecies because of the lack of proofreading activity of viral RNA-dependent RNA polymerase (RdRp) (Domingo et al., 1985). It has been demonstrated that serial passages of a cloned plant RNA virus can result in accumulation of mutations in viral progeny populations (Hajimorad et al., 2003). This genetic heterogeneity of virus population caused by error-prone replication of plant RNA viruses is advantageous to overcome selection pressures that limit virus survival. We firstly determined and reported fullgenome sequences of CGMMV isolates, KW and KOM, in 2003. Since then, the virus isolates have been propagated via several passages in susceptible host plants. The fulllength cDNA clones of these CGMMV isolates were finally constructed in this study and sequence comparison revealed that several mutations have been introduced into the CGMMV genomes during the passages. Two out of six nucleotide mutations resulted in synonymous substitutions in the cloned KW genome, while one out of three nucleotide mutations resulted in synonymous change in the cloned KOM genome (Table 2 and data not shown). Previous studies have shown that a single amino acid substitution introduced by error-prone replication of RNA viruses can result in emergence of resistance-breaking variants (Hebrard et al., 2006;Seo et al., 2009a;Seo et al., 2011). Indeed, one amino acid mutation introduced in the cloned KOM genome seemed to affect original symptomatic characteristic of the isolate in C. amaranticolor ( Fig. 2B and Table 1). Since the cloned CGMMV-KOM infected N. benthamiana and other susceptible hosts successfully, it is likely that the replication-associated proteins (the 129 kDa and/or 186 kDa proteins) of CGMMV functions in elicitation of chlorotic spots in C. amaranticolor. Further studies are needed to characterize the mode of resistance against CGMMV in C. amaranticolor and involvement of the replicationassociated proteins in activation of resistance.
Acknowledgments
This work was supported in part by grants from the Agenda Programs (PJ00922904 & PJ01130602) funded by the Rural Development Administration and the Vegetable Original isolates of CGMMV reported by Kim et al. (2003). b Cloned isolates of CGMMV in this study. | v3-fos |
2019-01-01T23:37:03.895Z | {
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} | s2 | GC-MS Profiling of Aroma Compounds and Microbial Analysis of Philippine Civet Coffee
Comparison of aroma profiles of civet and non-civet coffee beans of Coffea canephora (Robusta variety) and Coffea excelsa species were done under three parameters: coffee species/variety, extent of roasting and type (civet vs. non-civet). Different aroma profiles were identified for different coffee species and varieties, as well as for different extents of roasting, and type. Various volatile compounds contribute to the aroma of coffee. For instance, the presence of pyrazines deliver an earthy and burnt odor. Robusta samples contained more pyrazines, phenols and pyridines while Excelsa variety had more furans and pyrans. Aldehydes for all samples increased from light to medium roast but decreased drastically in full roast. For furans and pyrans, the peak intensity increased proportionately with roasting for both Excelsa and Robusta civet varieties. For the microbial analysis, Robusta, Excelsa and commercial civet coffee samples at three levels of roasting were analyzed for fecal contamination. All 7 samples (6 civet and 1 commercial) were within the limits set by FDA Philippines in terms of colony forming units per mL; and gave a negative result for E. coli. Although samples were within the acceptable range of CFUs/mL and was negative for E. coli, three samples (Robusta civet LR, Robusta civet MR and commercial civet) gave a most probable number (MPN) of fecal coliform per 100 mL count of 150, 4, and 4, respectively, revealing that Robusta civet LR did not pass the MPN per 100 mL count standard set by the FDA Philippines.
INTRODUCTION
Coffee is one of the most traded commodities in the world. It is the second most consumed beverage after tea. More and more people continue to consume it for its stimulating effects, exquisite taste and flavorful aroma. Each coffee variety produces a different taste, distinct flavor and a diverse aroma perceived by our olfactory senses. Arabica is considered to be superior over other coffee varieties as it possesses a sweet, caramel like and fuller aroma. Robusta, the cheapest coffee variety, on the other hand contains an earthy and burnt potato like aroma. Different coffee varieties contain different sets of aroma compounds. Higher concentration of maltol, 1-ethenone, 4-ethyl-2-methoxyphenol and furfurylpyrroles in Arabica coffee are the contributors for its smoother and richer aroma (Ryan, et al., 2004). The presence of higher concentration of alkyl pyrazines in Robusta meanwhile contribute to the earthy and burnt odor. Changing the roasting conditions can also alter the aroma compounds formed and released by the bean. Prolonging the roasting slightly increases the concentration of caffeine. As of present, there are around 1500 chemical constituents of coffee and only 40 of them contribute to the aroma. The market has thus revolved around the search for the most flavorful coffee, in which aroma and taste are heavily scrutinized. From post-harvest processing to brewing methods, from location to variety, the search has expanded to new fronts, some of which have been, and are still being, considered bizarre. One such coffee type, civet coffee, falls into this category. Considered as the most expensive coffee in the world, civet coffee is said to have a more flavorful and richer aroma compared to regular roasted coffee beans. There are certain studies that reveal that the enzymes inside the gastrointestinal tract of the civet cat ferment the raw beans thereby giving it an exotic and exquisite aroma upon roasting. The aroma constituents of the civet coffee are also different from regular ones which are the primary causes of a more flavorful aroma. Moreover, being a defecated product of the animal, it is possible that the civet coffee is contaminated by microorganisms and fecal coliforms. Diseases such as typhoid fever, cholera, dysentery, hepatitis and bacillary could emanate from drinking beverages contaminated with microorganisms.
In this paper, the aroma profile of a Philippine civet coffee obtained from one municipality will be analysed and compare with its noncivet counterpart. A relevant microbial analysis will also be carried out.
METHODOLOGY
Samples. Unroasted ("green") civet coffee beans and corresponding beans of ripe Robusta variety and Excelsa species cherries were picked and harvested from plantations in the town of Alfonso, Cavite province, Philippines during the harvest season of January 2011 to March 2011. All of the green civet beans were initially in feces defecated by civet cats (Paradoxurus hermaphroditus) when these were picked. The animals are freeroaming in the wild. For non-civet beans, these are coffee cherries that are handpicked from the coffee tree and later on dehulled and processed to obtain the green coffee bean.
Processing of Coffee Beans Prior to
Roasting. Raw Civet Coffee Beans. Raw Civet beans were washed several times in running water. The washed samples were then sundried for 24 hours. Identification based on shape of Robusta and Excelsa bean varieties were done and the civet beans were dehulled and were washed again in running water. The Civet beans were then oven-dried afterwards for 4 hours at 40 °C. Civet coffee samples were classified by their respective coffee variety either Excelsa or Robusta according to the beans' size, shape and appearance. Oval or elliptical beans with obtuse base were classified as Robusta civet beans while ovoid and flat form beans with acuminate apex tip were classified as Excelsa civet beans.
Ripe Coffee Cherries. The coffee cherries' pericarp were removed, leaving only the hull or endocarp of the coffee cherries. Samples were sun-dried for 24 hours until the hull was brittle. The dried coffee cherries were then dehulled, washed in running water and were oven-dried for 4 hours at 40 °C.
Coffee Bean Roasting. Sand Preparation. Sand was used to facilitate the roasting of coffee beans. Two (2) cups of sand were washed several times in running water and then boiled for 15 minutes. The cleaned sand was then soaked in 6 M Hydrocholoric acid solution for 48 hours. The sand was then washed several times with running water while maintaining the pH of the sand at 7.0.
Degree of Roasting. Four (4) grams of Non-Civet and Civet coffee beans were roasted in the sand roaster set-up which consisted of the following: beaker, three (3) tablespoons of sand, magnetic stirrer and thermocouple thermometer. Roasting of beans were done at a constant temperature of 240 °C. Three varying roasting conditions were achieved by varying the length of operation: light roast, LR (2 min), medium roast, MR (4 min), and full roast, FR (9 min). Percent moisture or weight lost was the roasting indicator used. Samples were stored in a tightly capped vial (2 cm × 10 cm) for 2 hours prior to aroma analysis.
Aroma Analysis. Headspace Solid-Phase
Microextraction (SPME) Sampling. Four (4) grams of coffee bean samples were ground in a coffee grinder and were placed in a 50 mL Erlenmeyer flask capped with a septum. The flask was first heated for 10 min at 60 °C before SPME syringe was exposed to the headspace above the sample to achieve condensation of volatile compounds on the fibers. A 57324-U SPME fiber was used to adsorb the gas in the vial for 10 minutes. The collected gas was injected to the GC-MS.
GC Analysis. Analyses were carried out on a Perkin
Elmer Clarus 500 Gas Chromatograph-Mass Spectrometer equipped with split injector and a PerkinElmer Elite-5MS capillary column (30m × 0.25mm × 0.25 m; -60 -325/350 o C). The GC oven temperature program was: 40 °C for 10 min followed by an increase of 5 °C/min to 80 °C, held for 12 min, to a maximum temperature of 300 °C. The pressure rate of carrier gas flow (He) was 20.0 psi. (Goldman and Green, 2009). Ten-fold serial dilution of the coffee samples were performed using 9 mL diluent of increasing number of dilution of sterile lactose broth. One mL of the sample was aseptically transferred into the first tube. The same procedure was done for the succeeding tubes. One mL of the suspension was aseptically transferred to a sterile petri dish. Pour plate technique was employed by mixing 20 mL sterile melted agar to the inoculated petri dishes. The same procedure was done for each dilution. Three trials were done in the experiment. The plates were incubated at 37 °C for 18-24 hours.
Microbial Analysis. Heterotrophic Plate Count
Multiple Tube Fermentation Technique (EPA SW-846, 1980). Presumptive Test. Three double strength and six single strength lactose broth with Durham tubes were prepared and sterilized for the presumptive test. Three 10 mL, 1 mL and 0.1 mL of sample were transferred aseptically in the three double strength lactose broth and six single strength lactose broth, respectively. The tubes were incubated at 37 °C for 48 hours. All tubes with gas formation inside the fermentation tube were reported as positive for the presumptive test and were carried over to the confirmed test.
Confirmed Test. One to two loopfuls of samples from each of the positive presumptive test tubes were aseptically inoculated in each Eosin Methylene Blue agar plates using clockstreak method. The plates were incubated at 37 °C for 18-24 hours. The appearance of dark-colored colonies especially with metallic green sheen were reported as positive for the confirmed test. Samples, which tested negative for the confirmed test, were declared safe for consumption. All samples which tested positive for the confirmed test was carried over to the completed test. Temperature was kept constant at 240 o C while varying the length of roasting time in order to observe the changes in chemical reactions occurring during roasting. As the roasting temperature increases, the beans lose approximately more than 5% of their dry weight due to the volatilization of substances, in addition to loss of moisture (Arya and Rao, 2007).
Analysis of Volatiles. Identification of Volatile
Compounds. Volatile compounds were detected using the GC-MS with the aid of the NIST MS 2.0 library. The fragmented ions of the mass spectrum of the compounds were also analyzed to confirm the data shown in the library. The compounds belong to different functional groups all of which have been grouped by chemical class to simplify the comparison of different samples. A representative aroma was common from each class. Caramelic notes are attributed to furans and pyrans group, burnt potato and woody odor for the pyrazine group, smoky aroma for phenols, fruity scent for aldehydes and ketones. The major groups that existed were hydrocarbons, alcohols, aldehydes and ketones, acid anhydrides, furans and pyrans, esters, phenols, pyrroles, thiazoles, pyridines, pyrazines, amines and other nitrogen heterocyclic compounds. Table 2 summarizes these compounds. Notable Aroma Constituents. From the above, previously-established notable compunds were picked for more focused differentiation of Civet and Non-Civet Coffee. Table 3 lists the notable aroma compounds common in both civet and non-civet coffee samples.
2-Furanmethanol.
Having been identified as products of the thermal degradation of cysteine and xylose in tributyrin (Ledl and Severin, 1973), 2-furanmethanol was detected from the studies of Shelddon et al. (1986) in a heated cysteine glucose model system (Flament, 2002). This aroma compound has a known burnt and slightly caramellic, oily odor. For civet Robusta and Excelsa beans, the peak area of 2-furanmethanol increases with increasing roasting conditions. The non-civet counterpart on the other hand increases from light to medium roast but plummets down at full roast. Civet beans also exhibited a higher concentration of 2-furanmethanol as opposed to ordinary beans.
2-Methylbutanal.
2-methylbutanal is formed in the pyrolysis of isoleucine (Merritt, et al., 1963) by the enzyme polyphenol oxidase (Sheldon, et al., 1986) and is also generated through Maillard reaction (Silwar and Lullmann, 1993). Having a buttery chocolatelike aroma, 2-methyl butanal decreases in concentration with an increase in roasting. In all of the samples, the said aroma compound displayed consistent behavior.
Furfural. Usually formed from the oxidation of furfuryl alcohol, furfural can also be formed by the decomposition of pentosans through the dehydration of the furanose form of arabinose (Smith, 1963). This is a feature of lightly roasted coffee to which it imparts a flavor like that of roasted cereals. Studies of Mottram (1994) have shown that furfural can also be formed from the Amadori compound of a pentose and an intermediated 3deoxyosone (Motoda, 1979). This aroma constituent has been identified in the products of thermal degradation of cysteine and xylose in tributyrin (Ledl and Severin, 1973) and in a heated cysteine/glucose model system (Sheldon, et al., 1986). Based from the data generated from the analysis, the percent peak area of furfural increases from light roast to medium roast and suddenly plummets down at full roast. This trend has been explained by Hughes and Smith (1998) content in coffee was high in the early stages of roasting, and then fell rapidly as the extent of roasting increased. Furfural decomposes at higher temp based from study of Silwar and Lullmann (1993). Moreover, furfural has a honey, sweet and almond like aroma.
2,3-Pentanedione. Studies of Heyns, et al. (1966) identified 2,3-pentanedione as a primary volatile product formed by thermal degradation of furaneol. It can also be produced when heating glucose. This aroma compound possesses a sweet caramel like odor. It gradually decreases in concentration as the roasting process lengthens.
Figure 3. Comparison between Robusta and Excelsa at Medium Roast for Civet and Non-civet Coffee.
Benzeneacetaldehyde. Benzeneacetaldehyde only existed in the Robusta beans having a floral, pungent green odor. It is formed from phenylalanine by polyphenol oxidase (Michigan Department of Environmental Quality Water Division, 2004).
In the comparison of Robusta against Excelsa samples under similar roasting conditions, the chromatograms showed a consistent trend that pyrazines, phenols and pyridines are higher for Robusta beans for both civet and non-civet at all roasts. Figure 3 shows, as an example, the comparison at Medium Roast.
Excelsa variety on the other hand contains more furans and pyrans constituent while the presence of aldehydes and ketones are relatively similar for both Robusta and Excelsa beans. Moreover, Robusta in general have more aroma constituents than Excelsa beans. However instances like the presence of additional constituents like methoxypyrazines are known suppressants of odorous compounds found in Robusta beans. This being the case, more aroma constituents detected in the sample does not necessarily guarantee a better and fuller aroma.
In the analysis regarding varying roasting conditions (Figure 4) a consistent trend for aldehyde behavior was revealed. Its peak area increases from light to medium roast but drastically decreases in full roast. The aldehydes are suspected to break down and decompose under intense heat resulting to its drastic decline in its peak area value. Moving on with the pyrrole group, the trend goes as medium roast being the lowest peak followed by the light and full roast for Robusta civet and non-civet and Excelsa civet varieties. For furans and pyrans, the peak intensity increases proportionately with roasting for both Excelsa and Robusta civet varieties. The non-civet Robusta showed a reverse trend as furans and pyrans decrease in concentration as we increase roasting magnitude. The ketone group showed consistency for both civet samples as it is least available for medium roast followed by light and full roast. The non-civet kind has an increasing peak area for ketones as we increase roasting. However, major aroma constituent family pyrazines showed no trending behavior throughout the twelve samples.
Microbial Results. Heterotrophic Plate Count.
Of the 7 samples analyzed, 4 samples (Excelsa civet LR, Excelsa civet MR, Excelsa civet FR and Robusta civet LR) gave a numerical value of average colony forming units per mL while the remaining three samples (Robusta civet MR, Robusta civet FR and Commercial sample) gave very few colonies in a span of 24 hours incubation at 37 °C. Colonies formed beyond 24 hours were not counted as this study is specific only on heterotrophic bacteria which are viable and naturally occurring bacteria within 24 hours. TFTC are reported whenever countable colonies are less than 30. Based from the results in Table 4, a 61% and an 80% decrease of average CFUs/mL was observed as the time of exposure to high temperature of coffee beans through roasting was increased from 2 to 4 minutes then to 9 minutes. A decreasing trend in heterotrophic microorganisms was observed as the degree of roast was increased. Prolonged exposure of beans to 240 °C roasting temperature was effective enough to kill significant number of microorganisms present in the sample. This trend was also observed in Robusta civet samples since Robusta civet MR and Robusta civet FR yielded less than 30 countable colonies (TFTC). Reported values of CFUs/mL in Table 2 were all below the maximum microbial limits set by the Food and Drug Administration (FDA) of the Philippines, which is 1.0 × 10 6 (Bureau of Food and Drugs, 2007).
SUMMARY AND CONCLUSION
By comparing the GC-MS profiles of coffee under three different parameters namely 1) extent of roasting, 2) bean variety/species, and 3) coffee type, a behavior of aroma constituents was established.
In summary (Figure 5), for the Robusta varieties, civet beans have lower aldehyde, furan and pyran content, although it drastically increases as the extent of roasting is intensified; while to opposite trend occurs for phenols. It is therefore conclusive that civet Robusta beans become more aromatic and odorous in full roast while non-civet beans are more superior at low roasting conditions. As for the Excelsa species, aldehyde and ketone content in civet beans are lower than the civet counterpart. However, similar to Robusta, furan and pyran content increases for civet, accompanied by a decrease for non-civet, as the extent of roasting intensifies. This is however exceptional for the non-civet medium roasts.
For the microbial analysis, among 7 samples tested for fecal coliform, none tested positive for microbial contamination. | v3-fos |
2018-11-09T11:03:54.512Z | {
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} | s2 | Water Quality of Agricultural Drainage Systems in the Czech Republic — Options for Its Improvement
Worldwide, artificial agricultural drainage systems create the optimal conditions for crop planting and soil cultivation by removing of excess water from the root zone and providing better trafficability for farm machinery. Although they are benefitial for agricultural produc‐ tion, the extensively used drainage systems considerably affect the hydrological and hydro‐ chemical regimes of catchments in both positive and in negative ways. The runoff characteristics are some of the most affected catchment parameters: differences in runoff volumes and temporal variations of flow rates in the water courses, the lowered groundwater levels and changes in the surface energy balance have frequently been found [1-4]. Problems such as altered hydrological patterns and impaired drainage water quality in agricultural catchments have often been mentioned. Water quality from agricultural drainage systems (both tiles and ditches) has been discussed by the studies which draw attention to the reduced quality of drainage waters caused by elevated concentrations of nutrients (N, P, C) and/or pesticides. The results of direct monitoring of drainage groups or very small drained catch‐ ments [5-11] together with various model approaches have proven that the contribution of agricultural drainage to water pollution in larger areas may be significant [12-15]. In principle, land drainage increases the aeration of the soil profile and thus promotes the mineralization of soil organic matter and reduces denitrification in previously waterlogged soils. Further, the systems are often connected to soil preferential flow paths and so contribute to a rapid movement of water and soluble or particle-bound contaminats to related water bodies [6,10,11,13].
Introduction
Worldwide, artificial agricultural drainage systems create the optimal conditions for crop planting and soil cultivation by removing of excess water from the root zone and providing better trafficability for farm machinery. Although they are benefitial for agricultural production, the extensively used drainage systems considerably affect the hydrological and hydrochemical regimes of catchments in both positive and in negative ways. The runoff characteristics are some of the most affected catchment parameters: differences in runoff volumes and temporal variations of flow rates in the water courses, the lowered groundwater levels and changes in the surface energy balance have frequently been found [1][2][3][4]. Problems such as altered hydrological patterns and impaired drainage water quality in agricultural catchments have often been mentioned. Water quality from agricultural drainage systems (both tiles and ditches) has been discussed by the studies which draw attention to the reduced quality of drainage waters caused by elevated concentrations of nutrients (N, P, C) and/or pesticides. The results of direct monitoring of drainage groups or very small drained catchments [5][6][7][8][9][10][11] together with various model approaches have proven that the contribution of agricultural drainage to water pollution in larger areas may be significant [12][13][14][15]. In principle, land drainage increases the aeration of the soil profile and thus promotes the mineralization of soil organic matter and reduces denitrification in previously waterlogged soils. Further, the systems are often connected to soil preferential flow paths and so contribute to a rapid movement of water and soluble or particle-bound contaminats to related water bodies [6,10,11,13].
In the Czech Republic (CR), there were more than 1 078 000 ha of land drainage built by 1990, which cover about ¼ of the agricultural land in the CR [16]. Many of these systems are located in slopes. Tile drainage systems, built in slopy areas underlaid by crystalline bedrocks, receive by the aeration of soil profile induced by tilling. Subsequent enhanced leaching of nitrates occurs and lasts as long as the drainage system functions [14,[42][43]. These facts have led to the assumption, that land use and agricultural management of areas prone to rapid infiltration profoundly affect nitrate concentration in surface as well as groundwaters [31,[44][45][46].
In this chapter, results from two experimental studies are described. These two studies document linkages between land use within certain geomorphological enclaves of a drainage subcatchment and drainage water quality. Both studies were focused on nitrate nitrogen, but in general, they represent a generalised evidence of drainage runoff formation and its influence on water quality. Case study A was done on twenty-two tile drainage systems and their subcatchments. Case study B was realized on a very small 58 ha tile drained catchment Dehtáře. While case study A focused on monitoring the current status of land use within various drainage subcatchment zones and its relationships to drainage water quality, case study B was aimed at veryfying the effects of grassing in a catchment recharge zone on nitrate concentrations and loads in drainage waters. The main goal of both studies was to get a practical evidence for findings obtained in the CR and abroad by statistical approaches [23,30,44,47] concerning the profoundly mitigative effects that grassing certain catchment areas has on the nitrate burden in drainage and surface waters.
Study areas
Case study A was carried out on 22 tile drainage systems, mostly built in slopes, which were monitored for water quality (N-NO 3 ) and related discharge once a fortnight for three years, 2004 -2006. The plots studied were located in two regions of the Czech Republic ( Figure 1); in the Svihov drinking water reservoir basin on the Zelivka river, and in the Southern Bohemian foothills of the Sumava mountains. The drainage systems which were selected and monitored were supposed to be functioning and not be connected to a surface water course or a pond / sewerage / wastewater outlet. All the examined drainage systems and related subcatchments were situated in crystalline complex with granite or paragneiss as parent rocks. The typical soil types were sandyloam to loamy Cambisols and loam to clayloam gleyic Stagnosols (Planosols).
For each examined drainage system, a design document (detailed construction plan) 1:1000 -1:2000 scale was obtained and georeferrenced (rectified) to specify the exact properties and the positioning of the drainage pipes as well as to determine how the drained land and the related contributive area (subcatchment) were interconnected, using GPS and ArcGIS tools. For these areas, land use characteristics were identified either from digital cadastre maps from land registers or from LANDSAT 7 images with 30 x 30 m resolution, in both cases followed by corrections based on field surveys.
Determination of relative soil infiltration vulnerability
The determination of relative soil infiltration vulnerability and the delineation of infiltrationvulnerable areas was based on an analysis of five-digit codes of valuated soil ecological units (VSEU) using the method established by [38]. The VSEU maps are available as digital layers for the entire Czech Republic at a scale of 1:5 000. The VSEU code serves for the evaluation of soil characteristics according to the following criteria: main soil units, slope, exposure, skeletal character, and soil depth. Based on the categorization of these criteria, soil is classified into five relative groups according to its significance for the infiltration process, with category 1 corresponding to the maximum infiltration capacity. For the subcatchments of all tile drainage systems evaluated in this study, the proportion of land use types (arable land-AR, grassland-GR, forest-FR, built-up-BU) was determined within the infiltration-vulnerable categories I -IV; category V (the lowest infiltration-vulnerable category) was not present in any of the studied localities. An example of a tile drainage subcatchment with delineated infiltrationvulnerable areas / categories and related land use types is depicted in Figure 2.
Data preparation and employed statistical methods
Basic statistics were calculated for all monitored drainage systems. Due to the close relationships between actual nitrate concentrations and runoff [7,11] as representative values for further analyses, flow-weighted concentrations were taken in order to assess the mutual links existing solely between soil and land use catchment characteristics. Flow-weighted concentration values were computed according to the following formula: Where Cfw is flow-weighted concentration Ci is actual solute concentration in the sample Qi is actual runoff during sample withdrawal.
To assess possible relationships between catchment soil and land use characteristics, and flowweighetd nitrate concentration values, principal component and multiple stepwise regression (MR) methods were employed. Principal component analysis (PCA) is a widely applied method, which transforms the original data into new orthogonal coordinates in order to express the information and possible relations contained in the original data using a smaller number of variables. As the dependent variable, flow-weighted concentration (Cfw) of N-NO 3 was selected; as independent variables, the proportion of land use types within individual infiltration-vulnerable categories (AR1-4, GR1-4, FR1-4 and BU1-4). In PCA models, the following indicators were assessed: the cumulative variability explained by the first two components (%), and the component weights, showing how influential the original variables were in determining the structure of individual components. In general, factors found in the same biplot quadrants in the PCA are correlated positively; factors in opposite quadrants are correlated negatively. Factors situated around 90° angles are evaluated as independent. In the MR, the classical parameters of model correctness were considered: mutual parameter correlation -multicolinearity, autocorrelation of residuals -heteroskedasticity, detection of significant points -leverage value, deviation points -outliers (DFFITS diagnostics), and the p-values of the model and of the initial parameters. To compare different models describing identical data, the following indicators were considered: F statistics, R 2 , R 2 adj., (the adjusted coefficient of determination for the number of parameters, or degrees of freedom) and the Mean Square Error (MSE) [48] All analyses were done at the significance level of null hypothesis α=0.05. Table 1 shows the results of the basic statistics calculated on the tile drainage systems which were evaluated. Median N-NO 3 Table 2 is an overview of land use type proportions accross four delineated soil vulnerable categories for all the evaluated drainage systems. The PCA and MR described mutual relationships between the assessed variables for the tile drainage subcatchments evaluated. In the PCA biplot ( Figure 3), the points represent individual drainage subcatchments, and the beams are variables. In the assessed case, the vectors of variables Cfw and AR2 were positively correlated, as were AR3 and AR4 to a lesser extent. The factors FR4, GR4 and GR1 had a negative mutual relationship with Cfw N-NO 3. The variables AR1 and GR3 were located in independent positions, most likely due to the very small area of all land use types in soil infiltration vulnerable category I. The results from various MR analyses are described in Table 3. The best (statistically significant and correct) model is coloured grey. It confirmed the results obtained from the PCA; the positively correlated factors were ratios of arable land within the first two soil infiltration vulnerable categories, and the ratio of grassland within the third soil infiltration vulnerable category appeared to be a mitigative factor on nitrate concentration. The final model from the MR is thus: Table 3. A list of statistically significant and correct multiple regression models (the grey band indicates the best regression model). Based on the acquired results, it can be said that the most important influence on values of nitrate nitrogen in drainage water was, in the case of the drainage systems analysed, the ratio (%) of ploughed land within the most infiltration vulnerable catchment areas.
Study area
The experimental catchment Dehtáře (Figure 1 and Figure 4) is situated in the Bohemian-Moravian Highlands, Czech Republic. It is a locally typical small agricultural catchment, where the tile drainage acts as the only permanent runoff from the catchment and the drainage system was built in the slope. The area is 57.9 ha, with tile-drained areas occupying 19 ha (32%). It has been used mainly as agricultural land, with low forest representation. The agricultural land is mostly exploited as arable, with permanent grassland in the lower part of the catchment. The altitude varies between 549.8 and 497 m a.sl. Total precipitation throughout the vegetation period ranges between 350 and 450 mm, and in the winter months between 250 and 300 mm, with a total annual average of 666 mm. The substrate is formed by partially migmatized paragneiss in various degrees of degradation. Quaternary sediments are represented by slope sands and loams reaching 1-2 m thickness. The representation of soils is variable, with Gleyed Cambisols, Gleysols, and sporadically Histosols. In the recharge area, the soil cover is more homogenous, with Haplic and, Shallow Haplic Cambisols and Cambic Hyperskeletic Leptosol prevailing. The drainage system was built in 1977, with a slope of 5%. The spacing of collection drains is 13 or 20 m apart; the depth of collection drains is 1.0 m, of conduit drains 1.1 m, and the interception drains are deposited at a 1.1-1.8 m depth. Detailed information about the catchment including a geophysical survey was published e.g. by [49].
Design of the pilot plant experiment
The water quality has been monitored since 2003. Samples have been taken at one or two week intervals. Five sites in the drainage system, with different land use in recharge and discharge areas, were chosen to be monitored for this analysis ( Table 4). Part of the recharge area ( Figure 4), with an area of 4. 6
Data evaluation
Similarly to case study A, the solute concentration value data were adjusted to facilitate hydrologic modeling. Flow-weighed nitrate concentration values, computed according to formula (1), were further analysed using the statistical software Statgraphics. In addition to calculating common summary statistics, the analysis of variance and Kruskall-Wallis test were conducted to test whether there were significant changes in nitrate concentrations and nitrogen load caused by grassing.
Results
The nitrate concentrations in drainage waters were strongly variable during the entire period monitored and also between the particular periods. The observed concentrations varied from 18 to 253 mg/l throughout the whole period monitored. The main reasons for this variability were the variable soil nitrogen stocks and the strong concentration dependence on the discharge levels. That is why the highest concentrations were measured in late summer or early autumn -during the period of low drainage discharges and prevailing base flow. On the contrary, during spring snowmelt and summer high-flow events with increased discharge (especially its direct-event component), nitrate concentrations decreased due to a high degree of dilution. The exceptions were some high-flow events measured on sites with arable land in the recharge zone just after the application of fertilizer. The inter-seasonal variability was caused mainly by different precipitation courses in particular seasons and by crop rotation.
The results of the statistical analysis for both periods of the experiment (2004-2006 and 2007-2011) are depicted in Figure 5 and Table 5. The evaluation showed that the flow-weighted nitrate concentrations in period 1 (before grassing the recharge zone) were surprisingly higher in drainage subsystems K1 and K4 with the permanent grassland in drained area (discharge zone) than in the subsystem under arable land. Moreover, the concentrations mostly exceeded the level of 100 mg/l. After grassing the K1 subsystem recharge area, some changes occurred. At first, the nitrate concentration decreased during high-flow events. After that, approximately one year after grassing, the long-term course of NO 3 concentrations changed direction and became decreasing ( Figure 6).
The significance of the changes in nitrate concentration values was tested using the Kruskall-Wallis test comparing the medians of the concentrations from periods 1 and 2 (before and after grassing). The results of this test are presented in Table 6. It is obvious that the statistically significant decrease in nitrate concentrations happened in the grassed recharge zone. Decreases of 32.1% and 25.7% were detected in systematic drainage subsystem K1 and intercepting drain K2 respectively. In the same period, an increase in nitrate concentration was detected in sites without land use change in their recharge zone. There was an increase of 10.8% in the drainage subsystem K5 with arable land in both (recharge and discharge) zones and of 8.6% in the subsystem K4 with grassland in the discharge zone, but arable land in the recharge zone. Evaluating the whole drainage system, the fall in nitrate concentrations by 10.5% was detected after grassing about 20% of this systems recharge zone. Nevertheless, from the statistical point of view, this fall appears to be insignificant. However, what is much more important than the instantaneous level of nitrate concentration, is that the trend in nitrate concentration became permanently decreasing in all measured sites with grassed recharge zone ( Figure 6). While the linear trend was detected increasing in all sites during period 1, it reversed approximately one year after grassing. In association with the change in nitrate concentrations, the nitrate-nitrogen leaching decreased after grassing in recharge area of the drainage system. Basic statistical evaluation of nitrogen leaching from drained subcatchments with different land use is depicted in Figure 7. Again, in all sites with grassed recharge zone, the decrease in all statistical characteristics of nitrogen load happened since part of the recharge zone was grassed (period 2). In the scale of whole drainage system, the monthly average load decreased by 23% from 3.2 kg N/month/ha to 2.6 kg N/month/ha. In the drainage subsystem K1, where the recharge zone was grassed completely, the decrease of the monthly average nitrogen load was even by 47% from 4.75 kg N/month/ha in period 1 to 2.52 kg N/month/ha in period 2. Evaluating drainage subsystems without land use change in the recharge zone, N load stagnation was registered in subsystem K4 (grassland in the discharge zone and arable land in the recharge zone), where the average monthly N load was 4.0 kg N/month/ha in period 1 and 3.9 N/month/ha in period 2. In the subsystem K5 (arable land in both zones), the increase of N load by 17% (from 4.1 to 4.8 kg N/ month/ha) was recorded consequently with N load decrease in subsystems with grassed recharge zones. This decrease manifested as much more significant during high-flow events, which had the biggest share of the total annual nitrogen loads.
Discussion
The results of both studies reported in this chapter corresponds with findings about grassland ability to reduce nitrogen leaching, as reported by many author from the Czech Republic and other countries. As it has been often demonstrated [30,31,45,50,51], nitrate concentrations in waters generally increase in connection with land use gradient from forests, meadows, pastures to arable lands; the last being the most worsening one. According to [44], the nitrate concentrations in small water courses of the Czech Republic are more affected by the area of arable land within their catchments than by the amount -to a certain level-of applied nitrogenous fertilizers. Other authors [52,53,54] have also reported the positive effect of grassing on water quality while some authors mention a certain lag effect of grassing on water quality improvement [55]. The degree of NO 3 concentration and N leaching changes evaluated by the case study B is within the range of findings reported by [44] in the Czech Republic. That work documented by multifactorial regression within the Švihov drinking water reservoir basin the share of arable lands as the most important factor affecting the nitrate concentration in water of small water courses. Similarly, the study [23] proved for catchments of three different scales significant linkages between landuse and water quality, reporting that every decrease in arable land area by 10% would cause an average decrease in C90 NO 3 values of 6.4 mg/l. The work [44] further proved that for the small streams in the Šumava region (Southern CR), improvement of water quality in this region was caused by grassing of arable and tile drained soils. The delay of reaction of nitrate concentration on grassing, detected in the case study B, was approximately one year. This period corresponds to the average residence time of the prevailing drainage runoff component (hypodermic water) in drainage discharge in sloped catchments, as reported e.g. by [56].
The ability of grasslands to reduce nitrate pollution is explained by the fact that grassland can absorb and use bigger amount of nitrogen in comparison to field crops [57]. Permanent grasslands cover the soil year round and have a big stock of active subsurface biomass in the root system, which can immobilize a significant amount of soil nitrogen. Nitrogen in mineral form thus exists in the soil in small concentration because nitrates produced by nitrification are readilly utilized by the grass. Besides this, after grassland is fertilised, nitrogen is quickly immobilised in the soil organic matter and protected againts leaching. Another important factor for grassland efficiency in nitrogen load is the bigger amount and increased activity of soil microbes, which is much higher under grassland than under field crops [58][59][60][61].
The results of the experiment B in the Dehtáře catchment also implied that grassing, being considered as an efficient measure for nitrogen leaching mitigation, should include a proper targeting in certain landscape zones, especially in tile drained catchments [8,44,62]. Drainage systems in the foothill areas of highland are characterized by their location in slopes and a considerable portion of drainage runoff can originate outside of the drained area [18][19]63].
To understand the mechanism of drainage runoff generation in sloped conditions, the theory of catchment slope zones (areas) must be applied. Perceived hydrogeologically, a catchment splits into recharge zones, where rainwater infiltrates and gradually joins groundwater, and discharge zones, where groundwater approaches surface water body or soil surface [22]. The recharge zones are usually situated in the morphologically uppermost areas of a catchment, close to the catchment watershed divide. The soils of recharge zones are typically shallow and stony, with high sand content and high infiltration capacity. The coarse-textured soils of the recharge zones are, with a respect to groundwater resources, well suited to grassing, which, beside water quality benefits, increases their field water holding capacity and enables infiltration of a bigger precipitation amounts -compared to ploughlands, including rainstorms [18,23,[64][65]. The discharge zones are usually situated in the foothills and along surface water courses and lakes and are prone to surface waterlogging. Typical soils in the discharge zones are generally deeper and heavier, with higher clay content and a lower capacity for infiltration. A connection between the recharge zones and the discharge zones is carried out by transient zones, where water from precipitation is either transformed to surface runoff or to groundwater which flows downslope in a quasi-steady way [18,24,27]. The transient zones are situated mainly in the middle sections of slopes. Groundwater in natural catchments flows from the recharge zones to the discharge zones. The discussed drainage systems in slopes are mostly placed in at the interface of the transient and discharge zones or in the discharge zones [18]. The joint influence of different land use, soil properties and tile drainage within various landscape zones on the hydrological regime of a small catchment was demonstrated by [2]. Being built in slope, tile drainage systems represent a shortcut between recharge and discharge zones which significantly curtails the water residence time in catchments, hastens the runoff reaction to precipitation, shortens the time to reach the peak discharge during events and increase the nitrate concentrations and loads in related waters [4,11,17,[66][67][68].
Conclusions
The results presented show that nitrate concentration values in drainage water were influenced the most by the land use of the recharge zones within the drainage subcatchment. These findings can be generalised for slopy agricultural catchments with common land use in soil environments formed on crystalline rocks. The land use and soil analyses together with monitoring the drainage water quality and quantity, and also an experiment with land use change in the recharge zone proves that grassing focused on the proper catchment area can be employed as a useful tool for reducing nitrates in drainage water. While permanent grassland placed directly in the drained area (corresponding to the catchment discharge zone) did not show any influence, the grassing focused on the catchment recharge area demonstrated a significant decrease in both, NO 3 concentrations and N loads. The acquired findings are of crucial importance for improving the water quality of small streams as well as groundwater in agriculturally exploited areas, for planning protective zones within large catchments of potable water reservoirs, and also for protecting small local surface or groundwater sources of potable water. | v3-fos |
2018-04-03T00:28:20.112Z | {
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} | s2 | Evaluation of edible mushroom Oudemansiella canarii cultivation on different lignocellulosic substrates
In this study, the mycelial growth rate, mycelial colonization time, yield, and biological efficiency of the edible mushroom Oudemansiella canarii were determined, and the effects of different substrate combinations on productivity, chemical contents and amino acids were evaluated. Lignocellulosic wastes, such as cottonseed hull, sawdust, corncob, and their combinations supplemented with 18% wheat bran and 2% lime, were used for the cultivation of O. canarii. The biological efficiency (BE) and essential amino acid content of treatment T1, which consisted of 80% cottonseed hull, were the highest among all the tested treatments. Mixtures that included sawdust, such as treatments T2 (80% sawdust), T4 (40% sawdust + 40% cottonseed hull), and T6 (40% sawdust + 40% corncob), exhibited lower yield and BE. Corncob was good for O. canarii production in terms of yield and BE, whereas the mycelial growth rate and colonization time were lower compared to those on other substrates. Comparing the BE, essential amino acids, and other traits of the six treatments, treatment T1 (80% cottonseed hull) was the best formula for O. canarii cultivation and should be extended in the future.
One Oudemansiella sp. strain (HKAS No.76681) sampled in 2011 from Dadugang, Jinghong County, Xishuangbanna City, Yunnan province, China, was identified as O. canarii by Prof. Zhuliang Yang of the Kunming Institute of Botany, Chinese Academy of Sciences (Beijing, China). The cultivation of this mushroom was first reported by Ruegger et al. (2001) using sugarcane bagasse and eucalyptus sawdust substrates. Their biological efficiency (BE) was 55.66% and 19.51%, respectively, which was far lower than the cultivation of O. tanzanica on different substrates (101.9-145.4%) reported by Magingo et al. (2004). To date, there is no report on the cultivation of O. canarii in China. Furthermore, large volumes of cottonseed hull, sawdust, and corncob are produced as agricultural byproducts every year in China and could be used as substrates for mushroom cultivation and to avoid serious environment pollution problem by improper disposal. Therefore, the present study was initiated to determine suitable substrates to improve the BE for cultivation of O. canarii and evaluate the chemical biomass composition of the fruiting bodies grown on different substrates.
Microorganism and spawn preparation
The O. canarii strain used in this study was isolated from the wild (Fig 1.) and preserved in the Beijing Engineering Research Center for Edible Mushroom, Beijing Academy of Agriculture and Forestry Sciences (Beijing, China), where it is designated as JZB2115055. The mycelium was transferred onto potato dextrose agar (PDA; 200 g/l diced potatoes, 20 g/l glucose, 15 g/l agar) medium at 25°C. Spawn preparation was carried out according to the method described by Pant et al. (2006).
Substrate preparation, inoculation, and incubation
The cottonseed hull, sawdust, corncob, and wheat bran used in this study for the cultivation of O. canarii were agricultural byproducts obtained from Beijing Yingliang agricultural development Co., Ltd. (Beijing, China). These materials were analyzed for their carbon (C) and nitrogen (N) contents following the method described by Dundar et al. (2009). Finally, the carbon/nitrogen (C/N) ratios of each raw material were calculated and are shown in Table 1.
All the materials used in this study were sun dried, and there was no contamination with mold. Six treatments (T1, T2, T3, T4, T5, and T6) with different combinations of substrates were designed (Table 2), and the C:N ratio of each treatment was 45.66, 88.53, 45.88, 60.91, 45.76, and 63.23, respectively. Cottonseed hull, sawdust, corncob, and their combination were used as base substrates for mushroom cultivation. Wheat bran and lime were supplementary substances applied to provide nitrogen sources and adjust the pH of the substrate, respectively.
The water content of the final mixture was adjusted to 65% (w/w), and the prepared substrate was placed into polypropylene bags (17 cm · 33 cm · 0.04 cm) at a packing density of 1000 g substrate per bag. The bags were autoclaved at 121°C for 120 min. The sterile substrates were inoculated by spreading the spawn on the surface of substrate at 2% (w/w) of substrate fresh weight. Sixty sterilized polypropylene bags were used and divided into three replicates for each treatment.
The inoculated bags were kept in the spawn running room at 25°C and 70% relative humidity (RH) in the dark. The mycelial growth rate was determined following the method of Gregori et al. (2008) with a modification of the racing tube size (25 mm in diameter and 220 mm in length), and the mycelial colonization time (the number of days from inoculation to complete colonization of the substrate by the mycelium) was also recorded.
Cropping, harvest and determination of BE
After a complete spawn run, the bags were moved to a greenhouse at 20-25°C and 80-90% RH with the upper parts unfolded for cropping. The greenhouse was sprayed intermittently to maintain the desired moisture during the cropping time.
Fruiting bodies were harvested when the mushroom cap surfaces were open. All fruiting bodies were collected in 3 d including the pinheads that formed but never matured. The substrates were incubated for another 7 d after harvesting. The harvested fruiting bodies in each bag were weighed. At the end of the harvesting period, the accumulated data were used to calculate the BE and mushroom weight (Yang et al., 2013).
Chemical biomass composition and statistical analysis
The fruiting bodies of O. canarii were collected after the first flush and dried in an oven at 60°C to constant weight. The dried fruiting bodies were kept at 4°C. Mushroom samples were analyzed for chemical composition (moisture, dietary fiber and ash) using AOAC procedures (AOAC, 1995). Protein concentration was determined according to the method of Leco Manuel (thermal conductivity) by the Kjeldahl method. The nitrogen factor used for protein calculation was 4.38 (N · 4.38) (Chang and Miles, 1989). Energy, fat and carbohydrate levels were determined by the method of Watt and Merrill (1975). Amino acids concentrations were determined based on the methods of Kim et al. (2009). These analyses were performed at the PONY Testing International Group (Beijing, China).
Data obtained from six consecutive harvests and chemical biomass composition analyses were subjected to a one-way analysis of variance. Differences among the means of six treatments were assessed using Duncan's multiple range tests at the 95% confidence level. All statistical analyses were performed using SPSS 20.0 for Windows.
Mycelial growth and mycelial colonization of different treatments
The mycelial growth rate and mycelial colonization time of O. canarii cultivated on different treatment substrates are shown in Table 3. Of the substrate treatments, treatment T2 displayed a significantly faster mycelial growth rate (5.51 ± 0.30 mm/d) compared to the others, followed by treatment T4 (4.93 ± 0.16 mm/d). Treatments supplemented with corncob (T3, T5, and T6) showed slower growth rates than the others. Addition of sawdust (T4 and T6) showed faster mycelial growth rate than their counterparts (T1 and T3) with only one substrate except for wheat bran. In general, the mycelial colonization time of the different treatments was in consistent with the mycelial growth rate. Table 4. Cultivation continued for 85-90 days, and 6 flushes were harvested. Most of the treatments yielded 85-91% of the total fresh mushroom weight in the first 4 flushes except for treatments T5 and T6, which were only 78% and 80%, respectively. Furthermore, approximately 81% of the total fresh mushroom weight was centralized in flush 2, flush 3, and flush 4 for treatment T2, which had 80% sawdust and 18% wheat bran in the medium. The greatest yield and the highest BE were found for treatment T1, which had 80% cottonseed hull and 18% wheat bran in the medium, and the values were 7955.1 ± 217.5 g and 113.64 ± 3.11%, respectively. The second highest values were obtained from treatment T5, which was 40% cottonseed hull, 40% corncob, and 18% wheat bran in the medium, and the values were 7707.9 ± 231.6 g and 110.11 ± 3.31%, respectively. There was no significant difference between treatment T1 and T5 in total fresh weight and BE. The lowest yield occurred in treatment T6, which consisted of 40% sawdust, 40% corncob, and 18% wheat bran as the culture medium.
Chemical biomass compositions of O. canarii
To evaluate the chemical biomass compositions of O. canarii cultivated on six different combinations of substrates, the chemical and amino acid composition of the fruiting bodies were analyzed. Table 5 lists the chemical compositions of O. canarii fruiting bodies grown on different treatments. The moisture and ash contents of O. canarii varied from 6.63 to 6.78 and 7.99 to 8.91, respectively. There were different protein contents in the 6 treatments. Treatment T5 had the highest protein content T1 T2 T3 T4 T5 T6 Cottonseed hull 80 0 0 40 40 0 Sawdust 0 80 0 40 0 40 Corncob 0 0 80 0 40 40 Wheat bran 18 18 18 18 18 18 Lime 2 2 2 2 2 2 with 18.88 ± 0.02 g protein in 100 g dry fruiting bodies, followed by treatment T4 with 18.55 ± 0.05 g protein. The lowest protein content was observed for treatment T2 at 16.35 ± 0.05 g. The fat contents were also different among the 6 treatments and the highest fat content was found for treatment T2, followed by treatment T4. The lowest fat content was observed for treatment T1. The highest dietary fiber content was treatment T2, followed by T6, and the lowest was treatment T1. The carbohydrate contents from treatment T1 to T6 were 33.39 ± 0.08, 30.73 ± 0.05, 30.37 ± 0.02, 30.23 ± 0.09, 30.08 ± 0.04, and 32.02 ± 0.08 g per 100 g dry matter, respectively. The amino acid composition and content (g in 100 g dried fruiting bodies) are shown in Table 6. O. canarii cultivated on the 6 treatments consisted of 18 amino acids, but the content of each amino acid differed among the treatments. The contents of essential amino acids in all treatments varied from 4.19 (treatment T3) to 4.76 g (treatment T1), which amounted to 36.05-40.37% of the total amino acids in the mushroom fruiting bodies.
Discussion
In this study, O. canarii was successfully cultivated on six treatments with cottonseed hull, sawdust, corncob and various combinations of the above agricultural byproducts. However, the mycelial growth rates of the six treatments do not correspond with the yield and BE. Treatment T2 (80% sawdust + 18% wheat bran) showed the highest growth rate and shortest colonization time, whereas the yield and BE of treatment T2 were lower than the others. This might be caused by the following reasons. Firstly, O. canarii grows in nature on dead wood (Fig. 1) as a saprophyte and primary decomposer, so the sawdust in the substrate may induce the secretion of lignocellulosic enzymes to degrade materials for nutrition and therefore promote mycelial growth. Secondly, sawdust can increase the air permeability of the substrates and carbohydrates derived from organic supplements in the substrates, such as wheat bran, will be easily metabolized. Finally, O. canarii may not be suitable for cultivation on sawdust because all the treatments (treatment T2, T4, and T6) containing sawdust had lower yields and BEs compared with treatments without sawdust. Ruegger et al. (2001) also reported that the BE of O. canarii cultivated on eucalyptus sawdust was 19.51%, Figure 2 The artificial fruiting bodies of Oudemansiella canarii on 80% cottonseed hull medium mixed with 18% wheat bran. which was 1/3 the value of O. canarii grown on sugarcane bagasse. Treatment T3 (80% corncob + 18% wheat bran) displayed a lower growth rate and longest colonization time. Although it had better air permeability than all other substrates, corncob had a low water-holding capability and large volume for the same dry weight, which might explain these results. The yield and BE of treatment T3 were quite good compared with others, which might be explained by the easy decomposition of the carbon and nitrogen sources in corncob. In China, most of the industrial mushroom cultivation companies, which demand only one flush for the whole production, supplement parts of corncobs in the substrates to reduce life cycle and achieve a higher yield (Zhang et al., 2014). Treatment T1 (80% cottonseed hull + 18% wheat bran) showed the fastest growth rate, shortest colonization time, and highest yield and BE. As we all know, cottonseed hulls are byproducts of cotton production. Previous studies revealed that cottonseed hulls possess advantages as a substrate material due to their high water-holding capability, nitrogen content and contribution to high mushroom yield (Quinio et al., 1990;Li et al., 2001;Zhou et al., 2011).
The BE of O. canarii was between 75.79-113.64% (Table 4), which was 1.4-2.0-fold higher than that reported on sugarcane bagasse substrate by Ruegger et al. (2001) (55.66%). The C/N ratios of treatments T1, T3, and T5, which had high BEs, were nearly the same at 46:1 (Tables 2 and 4), while other treatments with higher C/N ratios showed lower biological efficiencies, which implies that high nitrogen content in substrates could improve the mushroom yield. This result was in accordance with the reports of other researchers (Dundar et al., 2009;Yildiz and Karakaplan, 2003;Kurt and Buyukalaca, 2010). As shown in Table 7, the highest BE of O. canarii obtained on cottonseed hull substrate was slightly higher than that for other Oudemansiella species on different substrates except for O. submucida on sawdust and cottonseed hulls and O. tanzanica on sisal waste and sawdust. Application of different substrates in the cultivation of the same species had a significant effect on mushroom yield. Therefore, additional research is still needed to optimize the cultivation formula to improve the yield of O. canarii.
Recently, many mushroom chemical contents analyses have been reported (Dundar et al., 2009; (Table 5). The protein contents varied from 16.35 g to 18.88 g and were lower than those of the same species grown on sugarcane bagasse (19.45 g) and eucalyptus sawdust (22.81 g) substrates. The ash contents varied from 7.99 to 8.91 g, which were higher than that of the same species grown on sugarcane bagasse (7.26 g) and eucalyptus sawdust (9.15 g) substrates (Ruegger et al., 2001). The essential amino acid contents in the six treatments were different, and treatment T1, which contained 80% cottonseed hull, showed the highest content (4.76 g) ( Table 6).
In conclusion, O. canarii demonstrated good traits in terms of mycelial growth rate, colonization time, yield, BE, chemical compositions, and amino acid contents when cultivated on treatment T1, which consisted of 80% cottonseed hull, 18% wheat bran, and 2% lime. To the best of our knowledge, this is the first report of the cultivation of this species on lignocellulosic wastes in China. Furthermore, additional experiments using cottonseed hull supplemented with different proportions (less than 40%) of corncob as the substrate should be performed to determine the most efficient one in terms of yield and BE. | v3-fos |
2019-04-08T13:12:29.209Z | {
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} | s2 | Determination of Residues of Metribuzin in Soil and Sugarcane by QuEChERS
Herbicide use in modern agriculture is necessary to reduce the pressure of weeds and insects in monoculture cropping systems. Large quantities of these compounds are applied directly to the soil and the extensive and inappropriate use of these products in agriculture unfavourably affects the whole ecosystem by entering into the food chain and polluting the soil, air, ground and surface water. Hence, the monitoring of herbicide residues in soil environment is essential in the interest of public health safety. For this, the extraction and analysis method should be appropriate and easy to have quick, continuous monitoring of its residues in different matrices. Sample preparation is a very important part of the analytical method. The development of an appropriate sample preparation procedure includes a number of steps, such as extraction and cleanup, to obtain a final extract concentrate of target analytes as free as possible of matrix compounds. Due to the low levels of herbicides that may be found in soil, an enrichment of the analyte concentration must be achieved before its instrumental determination. Herbicides in foods are usually extracted by liquid-liquid extraction (LLE), matrix solid-phase dispersion (MSPD), solid-phase micro extraction (SPME) and QuEChERS (quick, easy, cheap, effective, robust and safe) which was proposed first time by Anastassiades and Lehotay. The QuEChERS sample treatment method has mainly been used for the extraction of different pesticides from Determination of Residues of Metribuzin in Soil and Sugarcane by QuEChERS
INTRODUCTION
Herbicide use in modern agriculture is necessary to reduce the pressure of weeds and insects in monoculture cropping systems. Large quantities of these compounds are applied directly to the soil and the extensive and inappropriate use of these products in agriculture unfavourably affects the whole ecosystem by entering into the food chain and polluting the soil, air, ground and surface water. Hence, the monitoring of herbicide residues in soil environment is essential in the interest of public health safety. For this, the extraction and analysis method should be appropriate and easy to have quick, continuous monitoring of its residues in different matrices.
Sample preparation is a very important part of the analytical method. The development of an appropriate sample preparation procedure includes a number of steps, such as extraction and cleanup, to obtain a final extract concentrate of target analytes as free as possible of matrix compounds. Due to the low levels of herbicides that may be found in soil, an enrichment of the analyte concentration must be achieved before its instrumental determination. Herbicides in foods are usually extracted by liquid-liquid extraction (LLE), matrix solid-phase dispersion (MSPD), solid-phase micro extraction (SPME) and QuEChERS (quick, easy, cheap, effective, robust and safe) which was proposed first time by Anastassiades and Lehotay 1 . The QuEChERS sample treatment method has mainly been used for the extraction of different pesticides from food matrices with high water content 2 . The QuEChERS approach is flexible and serves as a template for modification depending on the analyte properties, matrix composition, equipment and analytical technique available in the lab. However, the use of QuEChERS in soils 3 and sugarcane is limited for analyzing the herbicides especially metribuzin.
So far analysis of metribuzin and its metabolites has mainly been accomplished by different chromatographic methods using either solid phase extraction or liquid-liquid partitioning 4-6 . Microwave-assisted water extraction method (MAWE) was developed for the analysis of metribuzin with its major conversion products in soil was analyzed by HPLC-DAD using 10 mM phosphate buffer, pH 7.0 as extracting solvent and aqueous extracts 7,8 . Perez et al. 9 extracted metribuzin from soil samples in an ultrasonic bath using methanol and obtained 86.7 to 104.2 % recovery in micellar electrokinetic chromatography (MEKC). Niell et al. 10 compared two extraction solvents and conditions for three sulfonylurea herbicides residues in milled rice with liquid chromatography/diode array detection analysis. Moreover, the QuEChERS sample preparation is applied mostly for the LC/MS or GC/MS which are not affordable for all.
Sugarcane (Saccharum officinarum L.) cultivation is one of the most important agricultural activities in India and worldwide where its main end products are sugar, alcohol and derived foods. Continuous use of same group of herbicides causes shift in weed flora and develop herbicide resistant weeds. Also the bio accumulation and biomagnifications of the herbicide residues in soil and crops may takes place. Metribuzin (4-amino-6-tert-butyl-3-methylthio-1,2,4-triazin-5-one), a triazine herbicide used for pre and post emergence control of annuals grasses and broad leaf weeds in sugarcane, soybean, wheat etc. 11 . It is necessary to develop simple extraction and analytical methodologies to monitor triazines mainly metribuzin in the environment, to study fate and transport, modeling, ecotoxicology risk assessment and to develop management strategies.
With this background the present work was carried out to extract the residues of metribuzin from soils and sugarcane plant parts using QuEChERS method by HPLC. Developed method was validated and also used to assess the persistence of metribuzin in post harvest soils and sugarcane plant which treated with metribuzin. Preparation of solutions: The stock solution of metribuzin containing 1000 mg L -1 was prepared in methanol HPLC grade and stored at -18 °C. Intermediate working standard of 100 mg L -1 was prepared in methanol HPLC and was used to prepare the working standard solutions from 0.001 to 5.0 mg L -1 . Working standards were used for spiking the samples of different matrices and preparing the analytical curves in methanol HPLC.
Chromatographic conditions: To determine the optimum chromatographic conditions, an Agilent C18 column (XDB 150 × 4.6 mm i.d., 5 µm particle size) with different mobile phases comprising several combinations of methanol/acetonitrile and Milli-Q water were tested to provide better separation. The pH of the Milli-Q water was adjusted by a thermo pH meter (model ORION 5 STAR). The mobile phases were degassed for 0.5 h in an ultrasonic bath before use. Separation was performed using an Agilent 1200 series HPLC equipped with DAD detector and auto sampler, Rheodyne 20 µL loop injector, connected to EZChrom Elite software (Agilent, USA) for data acquisition. The analytical column was conditioned by passing the mobile phase for 30 min at a flow rate of 1.0 mL min -1 and operated at 30 °C. The flow rate was set to 0.5 mL min -1 for detection and quantification of the metribuzin. The response of detector was recorded from 190 to 400 nm to find out the lambda maximum and minimum for metribuzin with the injection volume of 20 µL. The identification of the herbicides in the samples was accomplished on the basis of their retention time and by comparison between the DAD spectrum of the standard solutions and samples.
QUEChERS sample preparation: A modified QuEChERS method was used for the preparation of sample extracts. According to this method, required quantity (Table-1) of the finely ground sub-sample was placed in a polypropylene centrifuge tube (50 mL) and ultrapure water (milli-Q) was added (Table-1) and mixed using a vortex mixer for 1 min. Subsequently, 20 mL of different extractants (MeOH alone, MeCN and MeOH + MeCN) were added to each set of replication and the mixture was shaken vigorously for 2 min and then sonicated for 30 min at 40 °C. To this, 1.8 g of anhydrousmagnesium sulfatge and 2 g of sodium acetate was added, vortexed for 2 min and then centrifuged at 5000 rpm for 5 min. The extract was then separated from sediments by simple decantation. Clean up: A 10 mL aliquot of the extract was transferred into a polypropylene centrifuge tube containing 100 mg anhydrous magnesium sulphate, per mL acetonitrile extract. The tube was vortexed for 0.5 min and centrifuged at 5000 rpm for 2 min. An aliquot (upper layer) of 5 mL was evaporated under a stream of nitrogen and the residue was re-dissolved in acetonitrile for LC analysis after filtering it with 0.2 µm Paul nylon membrane filter. An aliquot of 5 mL (upper layer) without concentration under stream of nitrogen also injected after filtering for the comparison of results. The optimization procedure was performed in triplicate and injected three times (n = 9) and the determination were carried out in HPLC-DAD. Clean up was also conducted with the use of 0.3 mg PSA/mL of extract for comparison.
Method performance: The linearity of the calibration curve was studied at a concentration ranged between 0.005 and 0.5 µg mL -1 with triplicate injections of seven calibration standards prepared in blank matrix extract in methanol. The accuracy and precision of the method was assessed using spiked samples of different matrices. Recovery of metribuzin from different matrices were determined for four replicates at four spiking levels of 0.01, 0.05, 0.1,0.5 and 1.0 mg kg -1 to evaluate the efficiency of the extraction and clean-up methodology. Limit of quantification was defined as the lowest spiking level, at which the validation was achieved and was determined based on the accuracy and precision data obtained through the recovery studies.
Experimental details: The soil and sugarcane plant samples were collected from sugarcane fields which have not received metribuzin previously and were used for conducting the recovery study. The properties of soils used for the recovery study are given in Table-2. Field experiments were laid out to study the persistence of metribuzin 70 % WP applied to the sugarcane field as early post emergence weed control. The experiments were conducted at Eastern Block Farm of Tamil Nadu Agricultural University, Coimbatore during rabi (Oct.-Nov.) season 2011-12 and late (April-May) season 2012-13. Metribuzin was applied at two levels (500 and 1000 g ha -1 ) along with control and replicated thrice. Sugarcane variety CO 86032 was grown during both the years. Calculated quantity of metribuzin was applied as early post emergence on 20 days after planting the cane by maintaining the optimum moisture in the field. The knapsack sprayer with flat fan nozzle was used for spraying metribuzin with the spray volume of 750 L of water ha -1 . Soil and plant samples were collected from the experimental plots at the time of harvest and stored at -15 °C for residue analysis. The soil of the experimental fields was sandy clay loam and has the electrical conductivity 0.52 dS m -1 , soil reaction 8.18 and organic carbon 0.53 %.
RESULTS AND DISCUSSION
Analytical performance and HPLC-DAD conditions optimization: Several mixtures of mobile phases with acetonitrile and methanol were tested in the binary mode to find a shorter run time with good separation and identification of the metribuzin. The mixture of methanol: 0.1 % formic acid in milliQ water (55:45 v/v) was found to be satisfactory and the matrix interferences was less; besides the run time was short with good resolution. When mixture of acetonitrile: water (70/30, v/v) was used, matrix interferences of plant sample was observed, though the run time was shorter and the substances were detected within 15 min. The use of gradient elution of the mobile phases was not satisfactory. The effective separation of the peaks in the chromatogram was also achieved when the methanol: 0.1 % formic acid in milliQ water (55:45 v/v) mobile phase was used at the flow rate of 0.5 mL min -1 . The response of the detector from 190 to 400 nm ranges showed that the metribuzin have two lambda max viz., 230 and 296 nm (Fig. 1a) and the molecule was resolved at 5.4 min ± 0.15 min. The chromatogram and spectrum of the Fig. 1a and 1b, respectively. Since the interference was less and also the resolution was good at 296 nm, the entire analysis was done at this wavelength. The purity of the metribuzin peak was also excellent at 296 nm (Fig. 2). The standard calibration curve of metribuzin detected by HPLC/DAD was constructed by plotting the analyte concentration versus peak area. The regression equation of the standard calibration curve was y = 10666 x + 2407 (R 2 = 0.996) and the calibration curve showed excellent linearity (Fig. 3) in the concentration ranges of 0.01-1.0 µg mL -1 . The minimum concentration of herbicide molecule that was detected with acceptable certainty called the limit of detection (LOD) by the instrument was assessed by the repeated injection of the lowest concentration for 7 times. The limit of detection for metribuzin was found to be 0.01 µg mL -1 . The limits of detection of the proposed method were determined at a signalto-noise (S/N) ratio of 3 for the metribuzin. Detector showed good sensitivity for the metribuzin standard up to 0.001 µg mL -1 but did not follow the linearity.
Extraction and clean up evaluation: The results of the modified QuEChERS method applied to the extraction of metribuzin from different matrices were obtained by injections into the HPLC-DAD. Acidified acetonitrile, methanol and the mixture of acetonitrile and methanol were tested as extraction solvents. It was observed that the mixture of acetonitrile and methanol was found to be best for the metribuzin extraction from soil and sugarcane with the recovery of more than 80 % (Fig. 4). The increasing proportion of methanol as extractant might enhanced the metribuzin recovery as reported by Locke et al. 12 . In the present study, the metribuzin recovery from soils ranged from 43 to 48, 57 to 63 and 79 to 82 % respectively by different extractants viz., acidified MeCN, MeOH and mixture of both. Similar results were also obtained for the sugarcane plant parts; however the recovery was lower than that obtained for soil. Advantage of the buffered QuEChERS modification has also been reported by the Wang et al. 13 for the extraction of pyrazosulfuron ethyl from different soils with good recovery and RSD. The acidified MeCN and MeOH mixture along with the sodium acetate for extraction might maintain consistent pH throughout the extraction and yielded maximum metribuzin recovery. Use of primary secondary amine for the cleanup reduced the recovery to less than 40 % (data not given) irrespective of matrices and might be due to the reaction of the metribuzin with the primary secondary amine 10 . Similar results were reported by Wang et al. 13 that the addition of 1 % acetic acid in acetonitrile as a modification of QuEChERS method without primary secondary amine and C18 sorbent gave good recovery of pyrazosulfuron ethyl from soil. Sampaio et al. 14 also observed lower recoveries (35.4 % with RSD < 5.11 %) for 2,4-D from sugarcane honey with primary secondary amine clean up. Injection of the upper layer from the centrifuge without concentration under stream of nitrogen was not good since the method detection limit is more than 0.1 mL kg -1 of the sample matrices.
Modified QuEChERS method validation: The developed modified QuEChERS extraction and clean up methodology (mixture of 1 % acidified MeOH and MeCN and without primary secondary amine) was validated using two different soils and different parts of sugarcane viz., juice, stem and leaf.
The estimated method detection limit (EMDL) for metribuzin was found to be 0.03 mg kg -1 for all matrices with the signal to noise ratio of 3:1 as determined by HPLC/DAD and no substrate interferences were observed at this detection limit as evidenced by the control sample analysis. Whereas the limits of quantification (LOQ) were obtained as the lowest spiked level with acceptable recovery and RSD (Table-3). The limits of quantification was estimated to be 0.05 mg Kg -1 for soils and juice and 0.10 mg Kg -1 for the sugarcane leaf and stem corresponding to the lowest spiking level in which more than 70 % recovery was obtained with the RSD of less 10 %. The average recovery of metribuzin from soil and plant parts was given in Table-3.
Persistence of metribuzin in soil and sugarcane parts: The modified QuEChERS method developed was used for the extraction of metribuzin from the real field samples collected at the time of sugarcane harvest which received different doses of metribuzin and analyzed by HPLC-DAD. Results (Table-4) indicated that the herbicide metribuzin was below detectable limit in the soil (0.05 mg kg -1 ) and sugarcane plant parts (0.1 mg kg -1 ) at the dose of 500 g ha -1 . However metribuzin residue was detected in the soil at the higher rate of 1000 g ha -1 . Though it was detected, the quantity was within the limits of phyotoxicity concentrations to the sensitive crops suggested for atrazine (0.0005-0.8 ppm) in soil which is also belongs to a triazine family 15 . Since the metribuzin has high mobility with the Koc value of 24.3-106.0 mL/g and DT50 value of 5.2 to 22.4 days 16 , it was not persist in the experimental soil at the recommended lower rate of application. Previous researchers [16][17][18][19][20] have indicated that soil organic carbon content is largest single factor responsible for metribuzin sorption in soils. Though, very small quantity of metribuzin residue was detected in the present field experimental soil at a higher rate of application, the continuous and in appropriate use of this herbicide might cause pollution of water bodies due to its high mobility 6 in light textured soils like sandy soils as it can readily leach 21 . Janaki et al. 22 and Tandon and Singh 23 also reported the detection of atrazine residues in the soils grown with maize when it was applied at higher rates than the recommended level.
The residue of metribuzin in the sugarcane plant parts viz., stem, juice and leaves were below detectable limit (Table-4) which was well under the MRL suggested by the PMRA 24 for the sugarcane (0.1 ppm) and its molasses (2.0 ppm). EFSA 16 reported that after 100 days, less than 10 % of metribuzin residues were present in plant and also confirmed that the residues were not accumulated in the plant. It is therefore, concluded that the significant residues of metribuzin will be it is unlikely present in the sugarcane plant parts at present levels of application (500 g or 1000 g ha -1 ).
Conclusion
The proposed method offers good accuracy and precision to determine metribuzin residues in soil and sugarcane plant parts. The modified QuEChERS method is validated through recovery studies using different soils and sugarcane plant parts. It was found that the method is rapid and selective, with a simple sample preparation procedure that could be used for the detection and quantification of metribuzin residues in soil and sugarcane plant parts using the HPLC-DAD. Modified QuEChERS method was also applied to study the persistence of metribuzin in soil and sugarcane plant parts from the experimental fields which received two different doses of metribuzin. It was found that the residues of metribuzin in soil and sugarcane parts were below the detection limit (0.01 mg kg -1 ) except in the soil at the higher dose of application. | v3-fos |
2019-03-31T13:45:15.651Z | {
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} | s2 | Phytochemical Analysis and Antibacterial Activity of Seed Extracts of Macrotyloma Uniflorum (Horse Gram)
The present study deals with preliminary phytochemical screening of seed extracts of Macrotyloma uniflorum (horse gram) and its antimicrobial activity against human bacterial pathogens. Aqueous and alcoholic extracts of Seeds of horse gram were evaluated for antibacterial using well diffusion method against some human bacterial pathogens. Phytochemical studies revealed the presence of carbohydrate, steroid, tannins, phenol, protein and amino acid, and absence of alkaloids, glycosides, flavonoids and saponins. Antibacterial activity was tested against 9 human bacterial pathogens using alcoholic and aqueous extract. On comparing the antibacterial activity by alcoholic and aqueous extracts, they showed a moderate to high activity against 9 human pathogens. On considering the rate of antimicrobial activity against pathogens, alcoholic extract showed a better result in controlling the growth of bacteria than that of aqueous extract.
INTRODUCTION
Horse Gram, M. uniflorum is the most extensively grown pulse in south India, the maximum area being in Andhra Pradesh, Karnataka and Tamil Nadu.
Macrotyloma is a nutritious food legume. It is rich in protein, iron, calcium and polyphones.
Green plant of horse gram is a valuable green manure. Horse grams that fail to meet food grade standard can be used as livestock feed, because of their high protein content and lack of digestive
Plant Materials
M. uniflorum seeds were washed, shadow dried and subjected to pulverization to get coarse powder.
Preparation of Aqueous Extract
The aqueous extract was prepared by mixing 10g of powdered seeds of this plant by mixing with sterile distilled water and boiled to slow heat for 2 hours. It was then filtered through 8 layers of muslin cloth and centrifuged at 5000 rpm for 10 minutes. The supernatant was collected and the procedure was repeated twice. The extracted supernatant was concentrated to make the final volume one-fourth of the original volume [9]. It was then autoclaved 121°C at 15 lbs pressure and stored at 40°C.
Preparation of Alcoholic Extract
The powdered seeds of about 20g were extracted with alcoholic in a soxhlet apparatus. Then, the extract was evaporated in a rotatory vacuum evaporator at 40°C under reduced pressure. The crude extract of about 13g was obtained which is equivalent to about 20% of total extraction.
Phytochemical Tests
The preliminary phytochemical analysis was performed as per the method [10]. Using standard protocols the biomolecules such as carbohydrate, steroid, tannins, phenol, protein, amino acid, alkaloids, glycosides, flavonoids and saponins were tested for their presence.
Microorganisms
The bacterial strains of Escherichia coli, Klebsiella pneumonia, Pseudomonas argentinensis, Pseudomonas sp, Bacillus subtilis, Vibrio harveyi, Salmonella paratyphi, Pseudomonas aeruginosa and Vibrio mimicus were maintained in nutrient agar slants respectively and stored at 4°C.
Preparation of Stock Culture and Bacterial Suspension
Standard nutrient agar (NA) medium was used for bacterial strains throughout the research.
In a hard glass screw cap tube, sterile slants of NA were prepared. Older cultures were transferred to freshly prepared NA slants separately for each species via sterile bacterial loop. In such a way, nine test tubes were freshly prepared for each bacterial pathogen. These test tubes of inoculated slants were incubated at 37 0 C in an incubator. After 18-24 hours of inoculation each culture was used throughout for antibacterial screening studies. For preservation of the stock culture, one set of culture slants were kept in polythene bag, properly tied and preserved as stock culture at 10 0 C. Subcultures were maintained and tested at 3 to 4 week intervals to ensure culture viability.
Antibacterial Activity
The extracts were screened for their antibacterial activity invitro by agar well diffusion method against E. coli, K. pneumonia, P. argentinensis, Pseudomonas sp, B. subtilis, V. harveyi, S. paratyphi, P. aeruginosa and V. mimicus. Bacterial colonies were selected and transferred to 5 ml broth with a loop and the broth cultures were incubated at 37° C for 24 hours. For Screening the antibacterial activity Muller-Hinton agar was prepared and seeded with respective human bacterial pathogens. Then the wells were made by using a sterile cork borer and was added with different volumes (50µl, 75µl and 100µl) of the crude extract of M. uniflorum (1g/10ml distilled water) and kept for incubation at 37° C for 24 hours. Triplicates were maintained for the said concentrations. After incubation at 24h and 48h the results were recorded for the formation of zone inhibition. Streptomycin (10µg/5ml) was used as standard [11] to compare the antibacterial activity of the test plant.
Statistical Analysis
Zone of inhibitions observed in the present study were subjected to one-way analysis of variance (ANOVA) and the significance of the difference between means was determined by Duncan's multiple range test (P<0.05) using Statistics (Statsoft Inc., Tulsa, USA). Values expressed are means of three replicate determinations ± standard deviation [12].
Phytochemical Analysis
Aqueous and alcoholic extract of seeds of M. uniflorum were taken and analysed to find the presence of various phytoconstituent ( Table 1). The result showed positive respond to the phytoconstituents like carbohydrate, steroid, tannins, phenol, protein and amino acid. Both extracts of seeds of M. uniflorum exhibited negative result for alkaloids, glycosides, flavonoids and saponins.
Antibacterial-Sensitivity Test
Antibacterial activity of M. uniflorum was screened against human bacterial strains such as E. were reported [13][14][15][16][17][18][19]. Among the two extracts studied the alcoholic extract was found to have better antibacterial activity than the seeds extracted with aqueous. Organic extracts provided more potent antibacterial activity as compared to aqueous extracts. The polarity of secondary metabolites and antibacterial compounds make them more readily extracted by organic solvents because Secondary metabolites are more soluble in organic solvents than water, and using organic solvents does not negatively affect their bioactivity against bacterial species suggesting that organic solvents are clearly better solvents of antimicrobial agents [20,21]. Antibacterial activity exhibited by the seed extracts of M. uniflorum may be due to the better solubility of the active compounds in solvent [22]. The antimicrobial efficiency exhibited against gram positive and gram negative bacterial human pathogens might be due to the presence of phytoconstituents such as phenol and tannins. Similar results were reported against bacterial human pathogens due to phytochemicals obtained after extraction with various solvents in M. uniflorum [23,24] and also in Hyptis suaveolens, Aerva lanata and Andrographis paniculata respectively [25,26] and Usha Raja Nanthini, et al. [27]. The findings of the present study suggested that seeds of M. uniflorum have potent antibacterial activity against human bacterial pathogens. The presence of tannins and phenolic compounds noticed in the present study are responsible for antibacterial activity and they may bring out antibacterial efficiency by cell membrane lysis, inhibition of protein synthesis, proteolytic enzymes and microbial adhesions as suggested in earlier study [28]. Amino acid + + 7
CONCLUSION
Alkaloids --8 Glycosides --9 Flavonoids --10 Saponins -- Mean within a column followed by the same letters (a,b,c) are significantly different according to one way ANOVA and Duncan's multiple range test (P < 0.05). Mean within a column followed by the same letters (a,b,c) are significantly different according to one way ANOVA and Duncan's multiple range test (P < 0.05). | v3-fos |
2016-05-04T20:20:58.661Z | {
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} | s2 | Selenium Nanoparticles for Stress-Resilient Fish and Livestock
The fisheries and livestock sectors capture the highest share of protein-rich animal food and demonstrate accelerated growth as an agriculture subsidiary. Environmental pollution, climate change, as well as pathogenic invasions exert increasing stress impacts that lead the productivity momentum at a crossroads. Oxidative stress is the most common form of stress phenomenon responsible for the retardation of productivity in fisheries and livestock. Essential micronutrients play a determinant role in combating oxidative stress. Selenium, one of the essential micronutrients, appears as a potent antioxidant with reduced toxicity in its nanoscale form. In the present review, different methods of synthesis and characterization of nanoscale selenium have been discussed. The functional characterization of nano-selenium in terms of its effect on growth patterns, feed digestibility, and reproductive system has been discussed to elucidate the mechanism of action. Moreover, its anti-carcinogenic and antioxidant potentiality, antimicrobial and immunomodulatory efficacy, and fatty acid reduction in liver have been deciphered as the new phenomena of nano-selenium application. Biologically synthesized nano-selenium raises hope for pharmacologically enriched, naturally stable nanoscale selenium with high ecological viability. Hence, nano-selenium can be administered with commercial feeds for improvising stress resilience and productivity of fish and livestock.
Introduction
The fisheries and livestock sectors represent an important agriculture subsidiary and are currently attracting wide attention because of their accelerating growth and high market demand. Among that, fishery is becoming popular as fishes are important food sources rich in simple, digestible animal proteins and beneficial lipids. Globally, fish products are indispensable to one billion individuals for protein security and particularly vital for juvenile and pregnant women [1]. Besides these, it functions as a major source of income and job creation, facilitates rural livelihood, and revamps equipment manufacturing, ice making, and processing industries. In 2010, wild fisheries and aquaculture engaged 54.8 million people globally in the primary fish productivity sector only [2]. Thus, a high growth potential has been forecasted for this sector in the coming years [3].
Currently, developing countries are passing through a phase of livestock revolution. Globally, livestock system holds $1.4 trillion asset value, provides employment to at least 1.3 billion people, and maintains the livelihood of 600 million farming communities [4]. Among total dietary value, it contributes 33 % of protein and 17 % of total kilocalorie consumption [5]. On the other hand, developed countries which showed a historically stronger potential of meat and livestock supply have almost reached its saturation in the productivity and maintained the growth momentum with a share of 53 % agricultural gross domestic product (GDP) [6]. These combinatorial high and sustained demands in developing as well as industrialized countries have created big market for professional livestock husbandry and will show heightened impetus in the near future.
Fisheries and livestock sectors are currently facing vast challenges due to high input costs (land, labor, feed, medicine, etc.), reduction in farmyard, and emergence of multiple stressors. Among different kind of stresses, abiotic stresses including climate change impact, pollution, and biotic factors like pathogenic infestation and consequent disease outcome have resulted in the depletion of productivity in fisheries and livestock [4,7,8]. To address such challenges, new interventions like environmental bioremediation, discovery of new drug candidates, or changes in the culture protocols are important, but supplementation and delivery of targeted enrichment including micronutrient is one of the key physiological maneuvers necessary for revamping the productivity.
Oxidative stress is a universal patho-physiological phenomenon that damages cells through continuous release of reactive oxygen species (ROS) originated largely due to the exposure to biotic and abiotic stressors [9]. The common feature of different ROS varieties is to cause damage to the biomolecule of the cell or the building blocks like DNA, protein, and lipids [10]. Cells possess an array of evolutionary conserved, non-enzymatic, and enzymatic detoxification mechanisms to prevent the effects caused by oxidative stresses. The detoxification mechanism happens to be threatened due to stress impacts which in turn enhance the extent of ROS release. Dietary administration of antioxidative supplement can be an important strategy for better production of livestock and fisheries. The potential role of selenium as a counteractive trace element for oxidative stress and inducing apoptosis in stressed cell is a good option, which has been applied successfully [11].
The word "selenium" originates from the Greek word Selene, which means moon goddesses. It was discovered by Jacob Berzelius in 1818 [12]. Primarily, selenium is found immobilized in the sedimentary rocks and soils and exhibits high persistence and is closely influenced by oxidation reduction potential, pH, and solubility of soil. This immobilized selenium turns into the bioavailable form due to weathering of soil or by microbial reduction and making it available to the members of the lower tropic level of aquatic ecosystems like phytoplankton and zooplankton before its entry into higher food chain [13]. Naturally, selenium is found in both inorganic and organic forms. Selenite (Se 4+ ), selenate (Se 6+ ), and selenide (Se 2− ) are the three inorganic forms of selenium found in nature. Selenocysteine is a 21st amino acid, and selenomethionine is a naturally occurring seleniumconjugated amino acid that is highly bioavailable (Fig. 1) and the most suitable form of selenium for nutritional supplementation. Generally, selenium acts as a cofactor and is present in some enzymatic structures called selenoproteins in animals. The first selenoprotein identified was glutathione peroxidase (GSHPx) that helps in the catalysis of reducing hydroperoxide to respective alcohols [14]. Selenium has a major role in male reproduction, antioxidative mechanism, thyroid metabolism, anti-carcinogenesis, and muscle functioning and development [15][16][17]. Selenium is also an essential trace element for normal physiological function of growing animals [18]. Farm animals like livestock or poultry consume selenium primarily from plants, but all these natural selenium sources are generally low in quantity and fluctuating in their presence. To achieve time-bound, sustainable productivity in commercial farming, delivery of standard selenium dose is desirable. On the other hand, toxicity reports are also in surface as the effects of selenium administration [19]. For example, selenium treatment on the zebra fish (Danio rerio) embryos elicited a dose and time-dependent alteration in cardiac and neural development [20].
Nanotechnology is the field of science that deciphers the properties of materials at the nanoscale level. It has proved to be a great boon for modern day science and can be applied to obtain efficacious physicochemical, mechanical, and bioactive properties of various elements [21]. Among the multifaceted applications of nanoparticles in the fisheries and livestock world, reports are also appearing on enhanced efficacy of nanoscale selenium in reproduction, digestion, growth, and immunomodulation [22]. Moreover, the toxicity impact of selenium has been reduced with synthesized nano-selenium proposed by Wang et al. [23], and new physiological and biological properties such as its role in microbial inhibition and fatty liver prevention have been explored that were not elucidated earlier. Hence, nano-selenium can be administered to reduce oxidative stress and to increase the productivity of stress-ridden fish and livestock. The above Fig. 1 Schematic diagram depicting the structure of bioavailable selenium mentioned functional diversity of selenium nanoparticle has been represented in a schematic diagram (Fig. 2).
Synthesis and Characterization of Selenium Nanoparticles Synthesis
Different methods have been reported to be used for the synthesis of nano-selenium including physical, chemical, and biological methods. In physical methods, hydrothermal treatments, microwave irradiation, and laser ablation are some of the important routes of synthesis for selenium nanoparticles. Quintana et al. [24] synthesized it by pulsed laser ablation method using 532-nm harmonic wavelength laser and power densities of 10 8 W/ cm 2 with 10-ns pulse. The laser-ablated samples were deposited on silicon wafers, glass, and metallic gold films with characterization done by atomic force microscopy. The laser ablation method involves the removal of material (metal) from a solid or liquid (occasionally) surface upon irradiation with a high intensity of laser pulse energy, which converts the material into plasma. Plasma containing high concentration of metal ions is aggregated in to minute embryonic nuclei upon mutual collision, followed by slow growth and stabilization of nanoparticles [25]. Another physical synthesis was reported on t-selenium nanotubes in a hydrothermal route, following a nucleation-dissolution-recrystallization based growth mechanism. In this procedure, sodium selenite(0.5 mM), sodium hydroxide(2.4 M), and sodium formate (2 mM) were added in different ratios into an autoclave functioned at 100°C for 25 h. A large quantity of dark-gray colorfloated particles was observed on top of the solution earmarked as nanoscale selenium [26].
In chemical synthesis, different reductants have been used to synthesize nano-selenium from its precursor salt and several reports have been published regarding its chemical synthesis. It was reported that varying ratios of 100 mM sodium selenite and 50 mM ascorbic acid can be used to chemically synthesize nano-selenium and after synthesis, nanoparticle solution appeared as light orange color [27]. Ascorbic acid is a potential antioxidant and functioned in the reduction and conversion of selenium to nanoscale selenium. Dwivedi et al. [28] described the synthesis of spherical, 35-70-nm-sized nano-selenium using organic acid such as acetic acid and oxalic acid under ambient conditions with polyvinyl alcohol (PVA) as stabilizing agent. In its acid-induced synthesis, a carboxylic group of organic acids was found to reduce selenium salt to nanoparticles [29]. Beside acetic acid, the other carboxyl groups containing organic acids like benzoic acid and gallic acid can also be used. Similarly, selenium nanowires were reported to be synthesized by adding sodium selenite with glucose in water followed by 20-min vigorous stirring [30]. It has been hypothesized that aldehyde group of glucose is oxidized to the carboxyl group due to the nucleophilic addition of hydroxyl group (OH − ), which eventually reduces metal ions to metal nanoparticles [31].
Recently, biological synthesis of selenium nanoparticle is gaining popularity due to its easy available source, less toxicity, and pharmacological significance [22]. Among biomaterials, synthesis was primarily reported using microbes such as bacteria and fungi with a few from plant origin. Among plants, synthesis of nano-selenium was reported in details using Vitis vinifera (raisin) fruit [32]. Lignin-coated selenium nanoballs of 3-18-nm size were synthesized using V. vinifera fruit extract and selenous acid (selenium precursor). V. vinifera (raisin) fruit extract was prepared by soaking shed dried fruits overnight and crushed followed by refluxing in distilled water for 30 min. Filtered extract was added to selenous acid solution and refluxed for 15 min to form spherical-shaped (nanoball) nanoparticles. Raisin constitutes flavonoids, vitamins, sugars, etc. which might be responsible for nanoparticle synthesis. Nano-selenium (20-50 nm) was prepared from Spirulina polysaccharides by solution phase method [33]. "Solution phase method" is an important synthetic process of combinatorial chemistry that can employ a mixture of reactants and ensure the reaction of all constituents under the conditions used. In this context, solution phase redox system was used where sodium selenite (selenium precursor) was mixed in aqueous solution of Spirulina polysaccharide followed by the addition of ascorbic acid solution. It was observed that ascorbic acid reduced the sodium selenite into selenium nanoparticles and Spirulina polysaccharide has been attached as surface decorator. These nanoparticles showed anti-cancerous activity against A375 human myeloma cell lines [33].
Among microbial sources, Fesharaki et al. [34] reported the synthesis of 245-nm-sized selenium nanoparticles from bacterial species, Klebsiella pneumoniae, using selenium chloride as a precursor. In this process, reduction potential of 24 h old K. pneumoniae culture extracts was evaluated in different culture media, from which tryptic soy broth (TSB) showed maximum reductive (1.92 mgml −1 ) potential. In another experiment, Tam et al. [35] reported the Shewanella sp. HN41-mediated synthesis in the presence of lactate and selenite where lactate served as an electron donor and selenite acted as a sole electron acceptor during the synthesis. The reduction of selenite is presumed to be the result of the respiratory electron transfer system and the soluble selenite reductases of the bacterial system. Singh et al. [36] reported its synthesis by Bacillus sp. JAPSK2 using selenium chloride as a precursor. Shrivastava et al. [37] described the biosynthesis of selenium nanostructures by bacteria Zooglea ramigera with selenium oxyanions. The formation of spherical crystalline monoclinic nanoparticles having a size of 30-150 nm was observed by transmission electron microscopy (TEM). It was also reported to be synthesized from selenite (sodium selenite as a precursor) stress tolerated bacteria, Pantoea agglomerans [38]. Intra and extracellular syntheses were reported from bacterial sp. P. agglomerans inoculating bacterial cells in tryptic soy broth containing 1 mM sodium selenite salt [32]. It was observed under TEM analysis that nanoparticles synthesized through intracellular route during early phase of incubation were ejected out from the cells after 24 h. The reaction mechanism involves reductases enzymes associated with cell membrane to produce selenium nanoparticles [38]. In a separate report, production of elemental nano-selenium from probiotic bacteria like Lactobacillus casei, Streptococcus thermophilus, and Lactobacillus acidophilus was described and it was observed that the size variability of nanoparticles depends on pH of the medium as pH plays important roles in its dissolution kinetics [39]. Some special features of biologically synthesized selenium nanoparticles have been presented in Table 1.
Characterization of Nano-selenium
The structural properties of nano-selenium is determined and characterized by studying parameters like size, shape, etc. For analyzing the structural properties, the following methods are employed: UV-visible absorption spectral analysis, X-ray diffraction analysis (XRD), Fourier transform resonance spectroscopy (FTIR) analysis, dynamic light scattering (DLS) analysis, transmission and scanning electron microscopy, etc.
UV-vis spectroscopy determines the "absorption maxima" of nanoparticles depending on the concentration of the precursor and other component of reaction mixtures. The researchers synthesized nano-selenium applying different physical, chemical, and biological methods, and among these methods, there are very less information of absorption maxima from chemical and physical routes. Though there are few reports from biological routes, these are widely varied and not confirmatory. Microbial source such as Bacillus cereus-mediated selenium nanoparticles showed absorption maxima at 590 nm, whereas nanoparticles synthesized from lemon leaf extract exhibited maximum absorption at 395 nm [40,41]. Moreover, these ranges are supposed to be altered with other genotypes. Biologically synthesized nano-selenium had different absorption maxima than chemically synthesized one due to its low and variable band gap energy [42]. Band gap calculated for chemically formed nano-selenium is 2.1 eV which is significantly different from biological source (band gaps for nanoselenium from Sulphurospirillum barnessi, Bacillus selenitireducens, and Selenihalanaerobacter shriftii are 1.62, 1.67, 1.52 eV).
The absorption spectra of biologically synthesized nano-selenium from K. pneumoniae was demonstrated at 218 and 248 nm within 200-300-nm scan range [34]. These two absorption peaks were found because of the presence of its two different species within bacterial spheres [42]. Consistent with this information, we have synthesized selenium nanoparticles and examined its absorption spectra. The absorption spectra data showed that this nanoparticles exhibited absorption maxima at 280 nm (Fig. 3a).
X-ray diffraction technique was used to examine the composition and phase of resultant samples of nanoselenium. Nano-selenium synthesized by green method showed crystalline nature with lattice constants at a = 4.363 Å and c = 4.952 Å and XRD data are in agreement with the literature value (JCPDS File No. 06-0362) [43]. Here, "Green method" basically categorized the nanoparticles synthesis using plant, microbes, or animal origin because it is ecofriendly, benign, and less toxic and minimum additives are used. Characteristic peaks of "2θ" values for nano-selenium were observed at 23.680, 29.788, and 43.9 indicating the presence of nanoparticles synthesized from Bacillus sp. JAPSK2 [37]. Selenium in its nanoscale form exhibits a standard XRD pattern (23,30,43) which confirms its nanoscale character, and it is similar to nano-selenium originated from all different sources. In the current context, standard 2θ value confirmed its synthesis from Bacillus sp. JAPSK2. Consistent with these reports, we have also conducted its synthesis and examined its characteristic peaks of 2θ (Fig. 3b).
Fourier transform infrared spectroscopy (FTIR) was used to analyze the surface interaction between synthesized nanoparticles with other molecules took part in the synthesis and stabilization of nanoparticles. It was reported that nano-selenium can be synthesized by using selenite as a precursor, ascorbic acid as reducing agent, and Spirulina polysaccharide (SPS) as surface decorator [33]. FTIR analysis reported some weak interactions between SPS and nano-selenium (SeNPs). Analyzing FTIR spectra of SPS (Spirulina polysaccharide) and SPS-SeNPs (nano-selenium), a characteristic stretching vibrations of the hydroxyl group (-OH) were observed in the two spectra, but the absorption bands of -OH group at 3446 nm was shifted slightly to 3438 nm. These results suggested the presence of some weak interactions between SeNPs and SPS. The weakening of absorption intensity of -OH group indicated the decrease in free -OH group after linking SPS with nano-selenium. Dynamic light scattering (DLS) technique was used to measure hydrodynamic effective diameters of synthesized nanoparticles. Selenium nanoparticles synthesized from dried V. vinifera (raisin) extract showed a zeta average diameter of 8.12 ± 2.5 nm with 0.212 polydispersity index(PDI) [32].
Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) with selected area electron diffraction (SAED) are well-known techniques to determine the structure, morphology, and size of prepared nanoparticles. Nano-selenium synthesized from Shewanella sp. HN 41 showed the amorphous nature of nanoparticles confirmed by high-resolution TEM and SAED [35]. Another report suggested that the particle size of nanoparticles having a surface decorated with Spirulina polysaccharide (SPS) was in the range of 90-550 nm as determined by TEM analysis. It was further reported that the size observed was decreased with increasing concentration of SPS and reported to be 20-50 nm with homogenous spherical structure [33]. Scanning electron microscopy showed that synthesized nanoparticles exhibited spherical nanospheres with a size of 150-200 nm showing selenium-nanospheres were present freely around the cells and also present in aggregates connected to bacterial cell mass [40].
Role of Nano-selenium in Reproduction
Fish and animal breeding are the key areas of productivity enhancement, and its performance determines the future stock. Among the different causes of reproductive failure, male sterility is an important obstacle to successful breeding and fertilization where selenium has appeared as a probable solution [44]. Selenium is one of the most important elements in the male reproduction, as it is an essential component for the normal development of spermatozoa and is also incorporated into the mitochondrial capsula protein [45,46]. Selenium (Se) is also reported to be essential for spermatogenesis, normal testicular development, and spermatozoa motility and function [47]. Among different important regulatory proteins necessary for spermatogenesis, selenoprotein P and phospholipid hydroperoxide glutathione peroxidase (PHGPx) are responsible for transporting of selenium to the testis [48,49].
Recent studies reported that the supplementation of nano-selenium (0.3 mg/kg body weight) significantly improved the testicular selenium level, semen glutathione peroxidase activity, and ATPase activity in male boar goats as compared to control (0.06 mg/kg body weight nano-selenium supplementation). The basal level of selenium requirement is 0.5 mg/kg body weight; therefore, supplementation of 0.06 mg/kg nano-selenium in control/unsupplemented group resulted in selenium deficiency which in turn resulted in abnormal spermatozoal mitochondria and damaged spermatozoal membrane [44]. Supplementation with nano-selenium enhanced the testis selenium content and testicular and semen GSHPx activities and protected the membrane system integrity as well as the tight arrangement of the midpiece of the mitochondria [44]. Hence, nanoscale selenium appears to be more effective to enhance male reproductive efficacy than the other form of elemental selenium.
Nano-selenium as an Antioxidant
Biological systems and its constituent macromolecules are susceptible to oxidative damages which disrupt their structure by distorting native chemical composition. Apart from these, oxidative stress (OS) leads to the generation of reactive oxygen species (ROS) like superoxide ion, hydroxide radicals, hydrogen peroxide etc. which trigger the apoptosis in tissues. To neutralize these adverse effects of ROS, the living system uses several antioxidative defense systems including various enzymes like catalase, superoxide dismutase, glutathione-S-transferase and peroxidase, etc. Likewise, selenium is also an important antioxidant located at the catalytic site of thioredoxin reductase and glutathione peroxidase enzymes [50].
When nano-selenium is administered to sheep as feed supplements, it reduces the levels of thiobarbituric acid reactive substances (TBARS) in plasma indicating a decrease in lipid peroxidation [51]. Antioxidant effects of inorganic, organic, and elemental nano-selenium were studied in growing weaned Taihang black male goats in a 90-day experiment wherein higher antioxidative activities were observed in nanoparticle-treated animal compared to control [52]. An improved glutathione peroxidase activity and antioxidant status were also monitored when they were applied as dietary supplementation in a fish like crucian carp (Carassius auratus Gibelio) [53]. It has also been reported that nano-selenium can act as a chemopreventive agent when administered at a smaller particle size [54].
Nano-selenium showed protective effects against chromium-induced oxidative stress and cellular damage in rat thyroid [55]. It also has a potential role in correcting the levels of reduced glutathione, catalase, superoxide dismutase, and malondialdehyde due to thyrotoxicity from exposure to hexavalent chromium [55] and is also known to increase the activity of glutathione-S-transferase in comparison with selenomethionine at supra-nutritional level in mice [56]. It can be hypothesized that nano-selenium induces the formation of selenomethionine. Selenomethionine leads to the formation of the Secysteine from the precursor through Se-cystathionine. Se-cysteine is a constituent for the formation of Seglutathione. Se-glutathione plays an active role in the neutralization of ROS and H 2 O 2 in association with glutathione peroxidase. Nano-selenium reported to induce the expression of selenium-dependent glutathione peroxidase through the formation of selenophosphate, which is an integral part of tRNA selenocysteiyl [57]. Sedependent glutathione peroxidase plays pivotal role in decreasing the ROS level inside the cell. Considering the above facts, a schematic model has been designed to showcase selenium nanoparticles induced marked attenuation in reactive oxygen species in fish and other organisms (Fig. 4).
Nano-selenium Improves Growth Performance
Faster growth rate through nutritional manipulation is an important facet for professional farming system. The dietary application of selenium has exhibited quick growth response in farm animals [58]. Nanoscale selenium also affects reproductive maturity and growth performance of fishes and farm animals like broiler chickens [59]. Nanoselenium when administered as feed supplement at a dose of 0.3 mg/kg to growing weaned Taihang black male goats showed an increase in body weight as compared to inorganic and organic selenium [52]. Scientists have investigated the effects of bulk selenium (Na 2 SeO 3 ) and nanoscale selenium on the meat quality of finishing pigs (Duroc × Landrance × Yorkshire). It was reported that nano-selenium is effective in increasing antioxidant capacity, selenium content and decreasing drop loss in comparison with sodium selenite [60]. It exhibited higher growth performance in broiler chicken as compared to bulk selenium at concentration range of 0.4-1.0 mg/kg. Chicken fed with a dose of 0.03-1.3 mg/kg dietary selenium exhibited an increased selenium concentration in serum, breast muscle, and liver, but this increase was comparatively greater when chicken were fed with nanoparticles [61].
Nano-selenium and selenomethionine supplemented with basal diet to crucian carp (Carassius auratus Gibelio) improved the relative gain rate, the final weight of the fish, Fig. 4 Schematic diagram representing the probable antioxidant mechanism of selenium nanoparticles as well as increased the selenium concentration in muscle [53]. It was also observed that nanoscale selenium is more effective than organic selenomethionone to increase the muscle selenium content [53]. Another study with broiler chicken showed that upon nano-selenium supplementation at 2 mg/kg dose, there was a linear and a quadratic increase in selenium concentration in the muscle and liver [61]. It was also suggested that an optimal and maximum level of its supplementation could not be more than 1.0 mg/kg in broilers [62]. Plateau in survival rate, feed and gain ratio, and average daily weight gain was observed when the selenium feed concentration was 0.15-1.20 mg/ kg in broiler chicken [61]. Effects of different levels of selenium supplementation on survival, growth, and reproduction of Nile tilapia were studied. It was observed that nano-selenium at a concentration of 0.6 ppm is effective to increase blood red cells counts, white blood cells, hemoglobin, and PCV% and showed best values in alanine transaminase (ALT), aspartate transaminase (AST), triglyceride, and cholesterol compared to the control diet. Therefore, the supplementation with nanoselenium at 0.6 ppm maintains the normal level of cholesterol and triglycerides in comparison to control diet in Nile tilapia [63].
Nano-selenium Helps in Feed Digestion
Digestion is an important physiological process in animal nutrition as it determines the assimilation and uptake of nutrients from ingested food. Xun et al. [64] reported that upon supplementation of nano-selenium and yeast selenium in male sheep (average 43.32 ± 4.8 kg body weight), the total ruminal volatile fatty acid concentration was increased, whereas ruminal pH, concentration of ammonia nitrogen(NH 3 -N), and molar proportion of propionate were decreased during the 25th day experimental regime. Selenium supplementation in sheep diet showed improved ruminal microbial activity, higher bioavailability, catalytic efficiency, and strong adsorbing ability which results into higher proficiency in digestion. Improved ruminal fermentation and feed conversion efficiency were monitored in nanoscale selenium, and it was concluded that it can be potentially used as a selenium source in ruminant nutrition [64]. It was found that the nano-selenium supplemented individual showed better tract digestibility of organic matters and its dietary supplementation improved the feed utilization.
Nano-selenium as Antimicrobials
Livestock including cattle and aquatic animals have been reportedly infected by pathogens leading to the decrease in their productivity, such as tilapia infected with Streptococcus sp. develops serious health problems or skin infection like fin rot, gill rot, etc. in rainbow trout caused by Aeromonas bestiarum [65,66]. Mastitis is a most prevalent, common bacterial disease due to S. aureus infection in bovines triggering symptoms like decreased milk productivity [67]. Antibiotics are usually applied as a potential therapeutic agent to treat animals against major infectious diseases. But with multidrug resistance phenomenon in microbes, nanotechnology has appeared as a potential alternative for antimicrobial preparations [68]. There have been plenty of reports on antimicrobial activity of nano-formulations like silver and zinc oxide nanoparticles etc. against different pathogens where nano-selenium is a new addition [69].
Besides its role as an antioxidant and trace element in living systems, few reports have been published regarding antimicrobial potency of nano-selenium [70]. Its efficacious role on the inhibition of Staphylococcus aureus propagation and preventing biofilm formation has also been evaluated and reported [69,71]. Selenium nanoparticles were also found to be effective antimicrobials against Pseudomonas species [36]. Coating of nano-selenium on titanium substrates has the potential to inhibit S. epidermidis growth as compared to uncoated materials [72]. Delivery of red elemental nanoparticles for the antibacterial study in P. aeroginosa strain JS-11 showed that it could serve as molecular marker for end point, qualitative, and quantitative antibacterial assays [73].
However, its antimicrobial effect should be evaluated on other multiple bacteria as well as on fungus and protozoan infections in veterinary and fishery sector. Possible mechanism of its antimicrobial function has not yet been explored, but its role on creating an osmotic imbalance or breaking some important biochemical bonds in the membrane may be predicted like other metal nanoparticles.
Nano-selenium and Cancer
Cancer is a fatal animal disease referred to as a multigene disorder and is due to environmental as well as pathogenic preponderance [74]. Occurrence of cancer in domestic and farm animals has a long history and currently, rate of cancer has increased in farm animals due to environmental pollution and pathogenic outbreak [75]. Selenium is a trace element which is inserted as selenocysteine in the body via translation with the help of its own codon present on mRNA and protects the cells from oxidative damage [76]. An animal intervention study has confirmed the role of selenium as a cancer preventive agent [16]. There are reports in animals where selenium yeast reduced the risk of prostate cancer by the process of apoptosis in male dogs when supplemented with 3 or 6 μg/kg body weight per day for 7 months where no such effects were found in the control group [77]. There are several mechanisms which narrate the role of selenium as potent anti-cancer agent. Protein kinase "C" can be inactivated by the interaction of selenometabolites (CH 3 SeO 2 H) with catalytic site of protein kinase C which can lead to inhibition of tumor growth [78]. Nanoparticles in the range of 10-100-nm size are able to penetrate through cancerous tissues due to the higher pore size of blood vessels (100-800 nm) in tissues within tumors and kill them but not through healthy cells due to comparatively small pore size (2-6 nm) of blood vessels within healthy tissues [72].The anti-cancerous effect of nano-selenium on HeLa cell line was reported by Huang et al. [79], and they found that nano-selenium had potential to induce vacuolization and apoptosis in HeLa cells. They have reported that after 24-h treatment with these nanoparticles, HeLa cells exhibit vacuolization under microscope. The vacuolization and apoptotic effects of nano-selenium were found to be increased in a dose-dependent manner. Endocytosis of the nanospheres leads to membrane fusion of the vesicles which results in vacuolization [79]. An explanation for this may be the fact that vacuoles are delivered to lysosomes but cannot be degraded by acidic lysosomal enzymes, and thus, their prolonged accumulation would damage the cell leading to apoptosis [79]. A schematic model depicting the apoptosis of cancerous cell in presence of nano-selenium is represented in Fig. 5. Selenium nanoclusters coated with titanium substrates was found to inhibit cancerous osteoblast proliferation [72]. It also acts as a chemopreventive and chemotherapeutic agent for human cancer [80]. Selenium nanoparticles were found to be effective to inhibit the proliferation of human breast cancer cell line MCF-7 in a dose dependent manner [81]. Although antioxidative and antiinflammatory properties of nano-selenium might be the basic mechanism of the anti-cancer effect, further studies are essential to elucidate the underlying mechanism of its anti-cancerous activity.
Currently, "surface decoration" is an important technique in drug delivery, and polysaccharides are attached to selenium nanoparticle to convey higher efficacy and new property. Experiments were conducted in glioblastoma where poor permeability of glioma parenchyma appears as a major limitation for anti-glioblastoma drug delivery. Gracilaria lemaneiformis polysaccharide (GLP) has a high binding affinity to αvβ3 integrin overexpressed in glioma cells and was employed as surface decorator to functionalize nano-selenium (SeNPs) for achieving higher anti-glioblastoma efficacy. GLP-SeNPs showed satisfactory size distribution, high stability, and selectivity between cancer and normal cells along with higher cellular uptake than its native form (SeNPs) [82].
Immunomodulatory Role of Nano-selenium
Oxygen is highly required for the aerobic living system, but higher oxygen concentration generates reactive oxygen species (ROS) which can cause oxidative stress [83]. Oxidative stress can be the result of either ROS overproduction or decreased antioxidant defense. Since oxygen is ubiquitous for oxidative metabolism, oxidative stress response is a common phenomenon and effective defense mechanisms are required to maintain its homeostasis. Generally, antioxidative defense mechanisms are grouped as enzymatic and non-enzymatic systems. Enzymatic mechanisms of ROS detoxification are enzymatic cascades leading to complete detoxification by reacting directly with ROS or acting as redox regulators. For example, the importance of catalase could thus be seen not only for detoxification of hydrogen peroxide but consequently in adaptation to endogenous oxidative stress and lipid peroxidation also. Non-enzymatic antioxidative systems are not as specific as enzymatic ones, but nevertheless, they are in the first line of antioxidative defense and are therefore of high importance in cellular response to oxidative stress like vitamin C which quenches radicals and forms an ascorbyl radical, a stable radical which causes less oxidative damage and vitamin E which has been involved in signal transduction by modulating many specific enzyme activities and also transcription factors like NF κB [84].
Summarizing the knowledge of ROS and antioxidative defense mechanisms, a feedback system can be monitored in the maintenance of redox balance (oxidative homeostasis) within the cell. Efforts have also been made to synthesize multifunctional antioxidants which could be considered as "biological response modifiers" for maintaining oxidative homeostasis, both in health and in disease. Nano-selenium can be introduced for these multifunctional, versatile roles, but these important immunomodulatory phenomena are partially investigated. The role of these nanoparticles was assessed on oxidative stress induced by acetaminophen in tissues of albino rats [85]. Selenium nanoparticles decorated by sulfated Ganoderma lucidum polysaccharides has been shown to inhibit LPS-stimulated nitric oxide (NO) production by macrophages and down regulated mRNA gene expressions of pro-inflammatory cytokines including inducible NO synthase (iNOS), interleukin-1(IL-1), and TNF-α in a dose-dependent manner. On the other hand, the anti-inflammatory cytokine IL-10 has been markedly increased under its treatment [86,87]. Selenium nanoparticles were also reported to increase the production of Th1 cytokines, such as IFN-γ and IL-12, in splenocytes of tumor bearing mice. The delayed type hypersensitivity (DTH) response of mice with tumor was also reported to increase in comparison to the control mice. It was reported that the survival rate of mice treated with nano-selenium was notably higher when compared to the control. From these reports, it can be suggested that its administration can result in considerable induction of the Th1 platform of the immune response through the elevation of IFN-γ and IL-12 and may be of use for the treatment of mice with tumors [88]. Considering all the above information, a schematic model has been presented in Fig. 6 showing the role of selenium nanoparticles in immunomodulation. These immunomodulatory activities can be extensively trialed in fish and livestock before its commercial application.
Nano-selenium Treatment to Cure Fatty Liver in Animals
Fatty liver is a sign of metabolic disorder affecting 50 % of the transition dairy cows directly after calving which is caused due to hepatic fat deposition [89]. Fatty liver can create an inflammatory response in the liver resulting a scarring and hardening and death of the cow [90]. In such cases, mortality can reach to 25 % without any proper treatment.
There are some dietary as well as anti-obesity regimes to recover from these diseases, but application of nanoselenium as feed supplement can be effective for fatty liver therapy. Role of nanoscale selenium and its supplementation were studied in male Wistar rats (200-250 g body weight) with fatty liver disease [91]. The rats were divided into four groups of eight animals each with positive and negative control and fed with and without Fig. 6 Schematic model showcasing the role of selenium nanoparticles in immunomodulation nano-selenium diet in an experimental regime of 10 days. Redox-parameters and transmethylating ability of experimental rats were assayed along with histological examinations. In comparison to control, disease group exhibited low level inflammation and free radial release which was validated by transmethylating ability and histological analysis of the samples. This experiment demonstrated the application of bioactive nanoselenium against fatty liver disorder [91], but more animal trials are required to confirm its therapeutic details.
Nano-selenium Toxicity in Fishery and Livestocks
Apart from benefits of bulk and nano-form of selenium in the fisheries as well as livestock, excess dietary amount of selenium (>20-30 ppm) is toxic to most animals including livestock and fish [92,93]. Reduction in survival rate, growth performance, feed uptake, as well as reproductive rate were monitored in fish as a consequence of selenium toxicity and have been reported to be transferred from parents to offspring [94]. Toxicity of selenium in waste water from coal fired power plant was studied over two decades on fish from Belews Lake, North Carolina. Chronic selenium toxicity was found in fish community including symptoms like telangiectasia (swelling) of gill lamellae, reduced hematocrit and hemoglobin levels, corneal cataracts, pathological alterations in major organs, reproductive failure, and teratogenic deformities [95]. Another report showed that rainbow trout (0.08 g) fry exposed to selenite at concentration 47 μg/L for 60 days resulted in reduced length and mortality [96].
Dietary concentration of selenium in excess of 3 ppm in dry feed over a longer period of exposure might become toxic to rainbow trout [95].The exact mechanism of selenium toxicity is still unclear, but there are multiple data regarding its pro-oxidant effect specially in the form of selenite, whereas selenocysteine and selenomethionine confer less toxicity [97]. Selenium at inorganic form reacts with tissue thiols like glutathione to form selenotrisulphides and also with other thiols to generate oxygen free radicals such as superoxide which trigger oxidative stress. Selenium toxicity can occur due to the formation of methyl-selenide which also creates superoxide radicals. Besides forming free radicals, selenium exhibits an inhibitory effect on thiol proteins having antioxidant effect. Hence, selenium maintains a fine balance between its antioxidant and pro-oxidant activity. The other important cause of selenium toxicity in fish and animals is bioaccumulation in tissues such as the liver, kidney, gonads, and gills at lower concentration and can be biomagnified during transfer of selenium through the food chain to higher level organism and reach to toxic levels [98]. Different sizes and doses of nano-selenium have shown variations in its impacts on cellular protein contents and enzyme activities of intracellular sodium potassium adenosine triphosphatase, lactate dehydrogenase, glutathione peroxidase, and superoxide dismutase in primary cultured intestinal epithelial cells of crucian carp, Carassius auratus Gibelio [21]. Evaluations on toxicity assessment of elemental nano-selenium on rats showed that nano-form of selenium is less toxic as compared to organic and inorganic forms of selenium [99]. More detailed comparative study are required in fish and animal models to elucidate the toxicity regimes, but recently developed biologically synthesized nano-selenium can be seen as a low toxicity candidate due to its ecofriendly nature containing minimum additives.
Conclusions
Selenium is a very important trace element for counteracting stress responses in fish and livestock and showed significant efficiency at nanoscale level. Animal and fishery researchers can initiate nano-selenium work because of its more bioavailability, bioefficacy, and low toxicity. Industry can select this multipurpose feed additive against diseases like cancer, gastro enteritis, etc. or as a common antidote and immunomodulatory molecule against any single or composite stressors. As controlling oxidative stress at the first level is alternative to axing multiple diseases preponderance, application of nanoselenium can be conducted as a potential, commercial molecule to be applied to any form of delivery like drug, feed, emulsions, etc. Application of nanoscale selenium in place of precursor selenium will definitely add value to the available proximate composition of commercial "fish and animal feed" as well as to increase its selling price index. Biologically synthesized nanoscale selenium opens a wide array of options to produce ecologically viable pharmacological additives. Nano-selenium research is still in its infancy and the potentiality of this nanoparticle should be explored in order to accelerate the production in livestock and fisheries in the present stress-hit global scenario. | v3-fos |
2016-05-04T20:20:58.661Z | {
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} | s2 | Characterising the bacterial microbiota across the gastrointestinal tracts of dairy cattle: membership and potential function
The bacterial community composition and function in the gastrointestinal tracts (GITs) of dairy cattle is very important, since it can influence milk production and host health. However, our understanding of bacterial communities in the GITs of dairy cattle is still very limited. This study analysed bacterial communities in ten distinct GIT sites (the digesta and mucosa of the rumen, reticulum, omasum, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum) in six dairy cattle. The study observed 542 genera belonging to 23 phyla distributed throughout the cattle GITs, with the Firmicutes, Bacteroidetes and Proteobacteria predominating. In addition, data revealed significant spatial heterogeneity in composition, diversity and species abundance distributions of GIT microbiota. Furthermore, the study inferred significant differences in the predicted metagenomic profiles among GIT regions. In particular, the relative abundances of the genes involved in carbohydrate metabolism were overrepresented in the digesta samples of forestomaches, and the genes related to amino acid metabolism were mainly enriched in the mucosal samples. In general, this study provides the first deep insights into the composition of GIT microbiota in dairy cattle, and it may serve as a foundation for future studies in this area.
Diversity, richness and composition of the digesta-associated bacterial communities across cattle GITs. Number of OTUs, Shannon diversity index and richness differed significantly among regions in the digesta samples (Table 1), and the Chao 1 value, number of OTUs and Shannon index in the forestomach were significantly higher than in the small and large intestines (Table 1). When bacterial composition of digesta microbiota among GIT regions was compared using the unweighted UniFrac distance, digesta-associated bacterial communities of the forestomach, small intestine and large intestine were separated spatially from each other ( Fig. 2A). An unweighted distance-based analysis of molecular variance (AMOVA) was used to assess the statistical significance of the spatial separation observed among various regions of the principal coordinate analysis (PCoA) plots. Statistically significant dissimilarities were observed across most regions with respect to bacterial diversity, with the exception of similarities between the cecum and the rectum (p = 0.052), the colon and the cecum (p = 0.179), the rectum and the colon (p = 0.485) and the jejunum and the duodenum (p = 0.123) (Table S2). In addition, digesta-associated bacterial communities in the forestomach and large intestine samples clustered close to one another, while those from the small intestine samples did not ( Fig. 2A).
At the phylum level, 21 bacterial phyla were identified in the digesta samples (Table S3). The majority of the sequences obtained belonged to Firmicutes (64.81%), Bacteroidetes (15.06%) and Proteobacteria (13.29%) (Fig. 3A). In addition, only Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetae, Cyanobacteria and Tenericutes were found in all samples. Among the 10 GIT sites, the rumen and abomasum harboured most of the phyla and groups (19 phyla), while the lowest number of phyla was observed in the cecum (12 phyla). When bacterial composition was compared regionally, the phylum Firmicutes dominated all bacterial communities along the GIT except for in the duodenum, where Proteobacteria (45.6%) was predominant. Bacteroidetes was the second most prevalent in the forestomach, while Proteobacteria was the second most prevalent in digesta samples of the jejunum, ileum, cecum and colon (Fig. S2).
At the genus level, 542 taxa were observed throughout cattle GITs; however, 44.6% of all sequences were not identified at the genus level. For clarity and visualisation purposes, Fig. 4A presents the most abundant taxa (those with a relative abundance of ≥ 2% in at least one GIT region). Results showed that predominant genera in cattle GITs included Prevotella, Treponema, Succiniclasticum, Ruminococcus, Acetitomaculum, Mogibacterium, Butyrivibrio and Acinetobacter, as well as those unclassified derived from Peptostreptococcaceae (family), Ruminococcaceae (family), Enterobacteriaceae (family), Prevotellaceae (family), Clostridiales (order), Rikenellaceae (family) and Bacteroidales (order). In the digesta samples, the dominant taxa, Prevotella, unclassified Ruminococcaceae, unclassified Bacteroidales and unclassified Rikenellaceae were enriched significantly in the digesta of forestomach samples ( Fig. 4B and Table S4). The unclassified Enterobacteriaceae were enriched [false discovery rate (FDR) < 0.001] in the small intestine, cecum and colon, and a large proportion of Acetitomaculum, Ruminococcus and unclassified Lachnospiraceae were enriched (FDF < 0.001) in the jejunum. Proportions of Butyrivibrio were significantly higher in the abomasum, duodenum and jejunum than in other GIT regions. The unclassified Peptostreptococcaceae and Turicibacter were enriched (FDR < 0.001) in the ileum and large intestine, while the Clostridium were more enriched in the large intestine (FDR < 0.001) than in the forestomach and small intestine.
At the OTU level, the study identified 5,573 OTUs in the digesta samples (Fig. S3). Of them, one OTU, OTU-3825, classified in the family Enterobacteriaceae was the most dominant among the dominant OTUs (representing ≥ 2% of all sequences in at least one region in all samples), and its abundance was the greatest (FDR < 0.001) in the duodenum digesta samples ( Fig. S4 and Table S5).
Diversity, richness and composition of mucosa-associated bacterial communities across cattle GITs. Number of OTUs, Shannon diversity index and richness differed significantly among regions in mucosa samples (Table 1). In the mucosal tissue, the Chao 1 value and the number of OTUs in the forestomach were significantly higher than in the small intestine. No significant differences were observed in the Shannon index among regions, with the exception of the omasum and the cecum (Table 1). When bacterial composition of mucosal microbiota among various GIT regions were compared using unweighted UniFrac distance, the mucosa-associated communities in the forestomach clustered more closely to each other than did other members of the combined large intestinal communities (Fig. 2B). AMOVA testing of mucosal samples revealed that compositions of bacterial communities differed significantly across GIT regions (except for abomasum vs omasum, p = 0.082; ileum vs jejunum, p = 0.328; cecum vs colon, p = 0.949; cecum vs rectum, p = 0.224; and colon vs rectum, p = 0.585) (Table S2). At the phylum level, 22 bacterial phyla or groups were identified in mucosal samples (Table S6). The majority of the sequences obtained belonged to Firmicutes (42.22%), Bacteroidetes (21%) and Proteobacteria (17.56%), and Firmicutes, Bacteroidetes, Proteobacteria, Actinobacteria, Tenericutes, Spirochaetae, Cyanobacteria and Lentisphaerae were found in all samples (Fig. 3A). Most of the phyla (18-20/22 phyla) were found among the 10 GITs sites. Firmicutes dominated all mucosa-associated bacterial communities along the GITs except for in the duodenum, where Proteobacteria (37.26%) was predominant. However, relative abundance of the second most predominant phyla varied markedly among mucosal tissue by GIT region (Fig. S2). Bacteroidetes was the second most prevalent phyla in mucosal samples of the reticulum, omasum, abomasum, colon and rectum, whereas Proteobacteria was the second most prevalent in mucosal tissues of the rumen, jejunum and ileum. Firmicutes and Spirochaetae were the second most dominant phyla in mucosal samples of the duodenum and cecum, respectively.
At the genus level, an analysis of the most-abundant taxa by sample revealed that abundances of Butyrivibrio, Campylobacter and Desulfobulbus were enriched significantly in mucosal samples of rumen and reticulum ( Fig. 4C and Table S7). In the abomasum, a large proportion of Mycoplasma, Acetobacter, unclassified Acetobacteraceae and unclassified Bifidobacteriaceae were enriched (FDR < 0.05). In the ileum, Turicibacter dominated (FDR < 0.001) compared with the forestomach, duodenum and jejunum samples, and in the cecum, Anaerovibrio were enriched significantly compared with the forestomach and small intestine samples. Relative abundance of unclassified Peptostreptococcaceae was higher in the ileum and large intestine (FDR < 0.001) than in the forestomach samples, while Acinetobacter was more enriched (FDR < 0.001) in the small intestine than in the forestomach samples. Treponema dominated represented as relative abundances on the Y-axis. Boxes with a star symbol above their whiskers are significantly different between the digesta and its corresponding mucosa in each GIT site at p < 0.05 using a t-test analysis. D: digesta samples; M: mucosal samples.
(FDR < 0.001) in the mucosa of the cecum and colon, and Prevotella was enriched significantly in the omasum and abomasum. Unclassified bacteria derived from the families Ruminococcaceae and Rikenellaceae were more enriched in the forestomach and large intestine than in the small intestine. In addition, unclassified Bacteroidales were more enriched in the forestomach and large intestine than in the small intestine samples, and unclassified Prevotellaceae dominated (FDR < 0.001) in the forestomach compared with the large and small intestine samples, except for those from the rectum.
At the OTU level, 6,327 OTUs were identified in mucosal samples (Fig. S3). Of them, OTU-332 classified to Acinetobacter was the most dominant among the dominant OTUs in the samples, and its abundance was the greatest (FDR < 0.001) in mucosal tissues of the duodenum and jejunum (Table S8 and Fig. S4). Comparison of diversity, richness and composition of bacterial microbiota between corresponding digesta and mucosa samples. When alpha diversity indices were compared between mucosal tissue and digesta of each GIT region, OTU values in the ruminal digesta were significantly higher than in the rumen epithelium (Fig. S5A). In contrast, the numbers of OTUs in mucosal tissues of the omasum, cecum, colon and rectum were higher (p < 0.05) than in their respective digesta. Mucosal tissues of the reticulum, omasum and large intestine exhibited higher (p < 0.05) Chao1 index values than in their respective digesta (Fig. S5B). The Shannon index was significantly higher for digesta of the rumen and reticulum than for their corresponding mucosal tissues, while mucosal tissues of the duodenum, ileum and large intestine had a higher Shannon index than their corresponding digesta (pv < v0.05) (Fig. S5C). In addition, a PCoA profile (Fig. 2C) and AMOVA analysis (Table S9) revealed significant differences in composition and structures of bacterial communities between the mucosal tissue and digesta of each GIT region. At the OTU level, the study found 5,040 OTUs across all samples, 533 exclusively in the digesta and 1,287 in the mucosa (Fig. S3).
At the phylum level, the proportion of Firmicutes in the digesta of the forestomach, jejunum and large intestine was significantly higher than in their corresponding mucosal tissues (Fig. 3B). The abundance of Bacteroidetes was higher (FDR < 0.001) in the digesta of the rumen and reticulum, while it was lower (FDR < 0.001) in the digesta of the duodenum, jejunum and large intestine when compared with their corresponding mucosal tissues. Mucosal tissues of the forestomach and rectum presented higher (FDR < 0.001) proportions of Proteobacteria than their corresponding digesta samples, while digesta of the duodenum showed a comparatively higher proportion of Proteobacteria.
At the genus level, in the rumen, the proportions of Prevotella, unclassified Ruminococcaceae, unclassified Rikenellaceae, unclassified Christensenellaceae and unclassified Bacteroidales were significantly higher in digesta samples than in mucosal samples, while rumen mucosa presented higher (FDR < 0.001) percentages of Butyrivibrio, unclassified bacteria, Desulfobulbus and Campylobacter (Fig. S6A). In the small intestine, luminal samples presented a significantly higher abundance of unclassified Enterobacteriaceae and a lower abundance of Acinebacter compared with corresponding mucosal samples (Figs S6B, S6C and S6D). In the large intestine, unclassified Peptostreptococcaceae, Turicibacter and Clostridium were dominant in the lumen (Figs S6E, S6F and S6G), while Treponema and unclassified Ruminococcaceae were more abundant in the mucosa.
Total bacterial populations in the GIT of dairy cattle. Total bacterial populations in various GIT
regions were estimated with a real-time PCR analysis by measuring the total copy number of bacterial 16S rRNA genes. Regional sites affected bacterial density of dairy cattle significantly ( Table 2). Higher digesta-associated bacterial numbers (p < 0.05) were observed in the colon and omasum, and higher mucosa-associated bacterial numbers were present in the rumen and omasum ( Table 2). In addition, mucosa-associated bacterial densities in the jejunum, ileum, cecum, colon and rectum were significantly lower than in their corresponding digesta (Table 2). However, digesta-associated bacterial numbers in the duodenum were lower than mucosa-associated bacterial densities (p = 0.002).
Predicted molecular functions of bacterial microbiota.
To gain insight into the molecular functions of bacterial microbiota across cattle GITs, we used PICRUSt to predict the metagenomic contribution of the communities observed. PICRUSt predicts metagenomic potential by imputing the available annotated genes within a known sequenced database, such as the Kyoto Encyclopaedia of Genes and Genomes (KEGG) and the Clusters of Orthologs Groups (COGs) catalogue, based on the presence/ absence of OTUs in a 16S rRNA survey. With PICRUSt, one can calculate nearest sequenced taxon index (NSTI), which measures how closely related the average 16S rRNA sequence in an environmental sample is to an available sequenced genome. When this number is low, PICRUSt is likely to perform well in predicting the genomes of the organisms in an environmental sample. This study used the KEGG database to match the chosen reference OTUs, and the average NSTI for the 120 samples was 0.075. This low NSTI metric suggests that PICRUSt may perform well when predicting the molecular function of microbial communities in the GITs of dairy cattle. Using PICRUSt as a predictive exploratory tool, the present study inferred that 39 gene families were identified in the digesta and mucosa samples (Fig. 5A). A principal component analysis (PCA) on the relative abundance values of the KEGG pathways represented from the digesta and mucosal microbiota showed a clear distinction between the clustering of the intestine digesta and that of the forestomach samples (Fig. 5B). In the mucosal tissues, PCA observed a separate clustering of the forestomach and intestine samples, except for those of the rectum (Fig. 5C).
Of the 39 gene families, the majority of the genes belonged to membrane transport (17.82% in digesta-associated microbiota and 17.61% in mucosa-associated microbiota, respectively), carbohydrate metabolism (10.68% in digesta, 10.79% in mucosa), amino acid metabolism (8.36% in digesta, 9.13% in mucosa), replication and repair (7.70% in digesta, 7.62% in mucosa) and energy metabolism (4.69% in digesta, 4.84% in mucosa). Of the 39 gene families, 33 gene families in the mucosa-associated microbiota had significantly different abundances among GIT regions (Table S10), and the prevalence of 37 gene families in the digesta-associated microbiota was significantly different among GIT regions (Table S11). Of the five predominant gene families mentioned earlier, in the digesta samples, the relative abundances of the genes involved in carbohydrate metabolism and replication and repair in the microbiota of forestomach samples were significantly higher than in the microbiota of the cecum and colon (Fig. 5D and Table S12). The abomasum had the highest (FDR < 0.001) abundance of genes involved in amino acid metabolism, while the proportion of gene families involved in amino acid metabolism in the rectum was the lowest (FDR < 0.001) throughout the GIT (Table S12). In mucosal samples, there was a notable enrichment (FDR < 0.001) of genes related to amino acid metabolism in the duodenum when compared with those in the forestomach and large intestine. The microbiomes in the abomasum and the omasum were significantly enriched in categories associated with carbohydrate metabolism (Table S12).
Of the five predominant gene families, when compared with corresponding digesta samples, the abundance of genes related to membrane transport was significantly higher in the mucosa of the reticulum, while it was lower (FDR < 0.05) in the mucosa of the duodenum and rectum (Fig. S7A). The proportion of genes involved in carbohydrate metabolism was higher (FDR < 0.001) in the digesta of rumen and reticulum compared with their corresponding mucosa, while it was significantly lower in the digesta of duodenum and rectum compared with their corresponding mucosal samples (Fig. S7B). Genes related to replication and repair were significantly enriched in abundance in the ruminal and reticulum digesta-associated microbiota compared with the mucosa samples (Fig. S7C). Genes involved in amino acid metabolism were higher in percentage in mucosa-associated microbiota (except for in the abomasum, cecum and colon) (FDR < 0.001) than they were in their corresponding digesta samples (Fig. S7D). In addition, genes related to energy metabolism were significantly higher in mucosa of the rumen, reticulum, cecum, colon and rectum compared with their corresponding digesta samples (Fig. S7E).
Discussion
This study characterised the compositions and phylogenetic distributions of digesta-and mucosa-associated microbiota in the GITs of Holstein dairy cattle. Results showed significant differences in bacterial richness and diversity, as indicated by the Chao 1 values and Shannon index, among GIT regions ( Table 1), indicating that GIT region exhibit strong determinants of the microbial community composition in dairy cattle. These results may be explained by the difference in the luminal pH values of different regions, as well as by the gut motility, redox potential, nutrient supplies and host secretions 10 . In addition, results from PCoA profiling and AMOVA analysis revealed significant differences among sections of the GIT, implying that GIT region is strongly determinant of microbial community structure.
Overall, findings of the present study revealed that the taxonomic groups represented within cattle GIT were Firmicutes, Bacteroidetes and Proteobacteria: These varied considerably among regions in abundance and in the number of genera composing them (Fig. 4A). In general, the digesta-associated microbiota of the forestomach exhibit greater relative abundances of Firmicutes and Bacteroidetes, whereas the small intestine and large intestine, except for the rectum, show higher relative abundances of Firmicutes and Proteobacteria (Fig. S2). Interestingly, the phylum Firmicutes, which was prominent in digesta-associated microbiota of the large intestine, was composed mainly of the genera Clostridium, Turicibacter and unclassified Peptostreptococcaceae (Table S4), which together reached up to 70% of the total reads in some samples. However, the dominant taxa belonging to Firmicutes in the digesta-associated forestomach microbiota were unclassified Ruminococcaceae, unclassified Rikenellaceae, unclassified Christensenellaceae and unclassified Lachnospiraceae (Table S4), which have been detected widely in the rumen and implicated as playing an important role in degradation of starch and fibre 11 . The fact that members of Ruminococcaceae, Christensenellaceae and Lachnospiraceae dominated in the forestomach while Turicibacter, Clostridium and members of Peptostreptococcaceae were enriched in the large intestine revealed significant differences in composition of the predominant microbial communities between the forestomach and large intestine.
The phylum Bacteroidetes was significantly less abundant in digesta-associated microbiota of the small and large intestine, whereas in the rumen, it was prominent and mainly composed of the genus Prevotella (Table S4), which reached up to 19.08% of the total reads in some digesta samples. This finding was consistent with a previous study by Stevenson and Weimer 12 , who reported that Prevotella were the most abundant (making up 17-50% of total bacterial reads) of all genera identified in rumen samples from lactating cows. High abundance of this genus in the rumen is thought to relate to the high genetic variability of this genus, which enables its members to occupy various ecological niches within the rumen 13 . However, the exact mechanism explaining the result that the genus Prevotella was less abundant in digesta-associated microbiota of small and large intestines is not clear yet, and further studies are required. The phylum Proteobacteria was significantly less abundant in digesta-associated microbiota of the forestomach, whereas its abundance was significantly increased in digesta samples of the small and large intestines, except for the rectum (Fig. 3A). The high abundance of Proteobacteria in digesta of the small intestine was attributed mainly to OTUs representing unclassified Enterobacteriaceae (Table S5). Unclassified Enterobacteriaceae refers to bacterial genera encompassed by the Enterobacteriaceae family, about the function of which little is known yet 14 . As these unclassified gut bacteria have not yet been evaluated functionally, the cause of the increase in abundance of unclassified Enterobacteriaceae in the digesta of the small intestines is not entirely clear, and future studies are needed to clarify these issues.
Gastrointestinal mucosa-associated microbiota could play important biological roles due to their close proximity to the animal host, but knowledge of their composition in cattle still is limited to calves 6,15 . The mucosal microbiota of calves has previously been investigated using culture-based methods and culture-independent DNA techniques 6,16 , and these studies revealed the presence of mucosa-associated bacterial communities with bacterial species that differed from those associated with the digesta of calves. In the present study, our data revealed significant differences in the diversity index of mucosa-associated bacteria communities among most GIT regions (Table 1). In addition, PCoA profiling and AMOVA analysis revealed significant differences in composition and structure of mucosa-associated bacteria communities among GIT sections. Thus, the present study has provided further evidence of mucosa-associated bacterial communities along the GITs of dairy cattle, which appears to support previously reported trends regarding gastrointestinal region-specific microbiota.
Among the regions of the GIT, in contrast to the rumen epithelium, the mucosa-associated bacterial microbiota of the small and large intestines has been studied infrequently. The present study highlighted the dominant presence of the aerobic bacterial genus Acinetobacter in small intestine mucosa. This finding is in accordance with previous works showing the presence of oxygen at the apical surface of the intestinal epithelial cells 17 , representing a possible mechanism of exclusion of strictly anaerobic, extremely oxygen-sensitive microorganisms 18 . In addition, the present study found a higher abundance of Butyrivibrio (belonging to Firmicutes) in the rumen and reticulum mucosal samples across the GITs of dairy cattle. As the mucosal butyrate producers release butyrate close to the epithelium, species of Butyrivibrio may enhance butyrate bioavailability for the host, which may be particularly useful in proliferating rumen and reticulum epithelium 19,20 . In addition, the present study's finding of the enrichment of the genus Treponema (belonging to Spirochaetae) in large intestine mucosa may have health implications. Previous studies revealed that Treponema spp., well adapted to oxidative stress 21 , are involved in a number of diseases of the skin or mucus membranes in several mammals 22 . Additionally, Treponema spp. are believed to be associated with ulcerative mammary dermatitis and bovine digital dermatitis in cattle and contagious ovine digital dermatitis in sheep [23][24][25] . Thus, enhanced Treponema in large intestine mucosa could have deleterious effects on hindgut health. Altogether, findings of the present study revealed that abundances of dominant genera in mucosa-associated microbiota varied considerably among GIT regions, and uniform distribution of the attaching bacterial compositions along the rumen, small intestine and hindgut is likely due to host-bacterium interactions in the mucosa.
Consistent with the findings in bovine calves using denaturing gradient gel electrophoresis, clone library and pyrosequencing 6,15 , the present study revealed a higher proportions of the predominant taxa Prevotella, unclassified Ruminococcaceae, unclassified Enterobacteriaceae and unclassified Peptostreptococcaceae in the digesta-associated microbiota (Fig. S6) and a larger percentage of Butyrivibrio, Acinetobacter and Treponema in the mucosa. Previous studies revealed that the genus Prevotella, unclassified Ruminococcaceae and unclassified Peptostreptococcaceae might play important roles in feed digestion 26,27 and that members of the genera Butyrivibrio, Acinetobacter and Treponema were more involved in epithelium proliferation and diseases 6,28 . These findings imply that sampling sites show strong determinants of microbial community structure and function of bacterial communities among regions.
The cattle gastrointestinal microbiome presents many physiological functions that are lacking in the host, and therefore, they can be considered essential to cattle life. To determine the potential functions of the gastrointestinal microbiota in the samples, the present study used PICRUSt to infer putative metagenomes from 16S rRNA gene profiles 8 . The study inferred that the most abundant functional categories were those corresponding to the functions of carbohydrate metabolism, amino acid metabolism, membrane transport and replication and repair. This is consistent with the general metabolic functions (such as carbohydrate, protein and amino acid metabolism) being essential for microbial survival 29,30 , and it is in line with the observations of other metagenomic studies in mice and humans [31][32][33] . Findings of the present study revealed significant differences in bacterial function among regions across the GIT (Fig. 5B,C). For example, genes relating to carbohydrate metabolism were more abundant in the digesta-associated microbiota of the forestomach than in that of the hindgut. The increased occurrence of these genes mirrors the increase in sequences affiliated with carbohydrate degradation, as discussed above, supporting the importance of these bacteria within the forestomach. In addition to these findings, the present study inferred that genes associated with amino acid metabolism were more enriched in the mucosa-associated microbiota of most GIT regions than in their corresponding digesta (Fig. S7D). One possibility is that the mucosal tissue provides a decreased supply of carbohydrates and that bacteria may derive energy from amino acid fermentation 15 . In addition, these results imply that the mucosal microbiota may be more necessary to amino acid degradation. In this study, next-generation sequencing on the Miseq platform and bioinformatics analyses were performed to investigate the GIT bacterial microbiota of dairy cattle. Results revealed that microbial communities of dissimilar composition and metabolic function occupied different regions within the GIT ecosystems of dairy cattle, while there were some shared traits across all microbiota. The forestomach, small intestine and large intestine were characterised by a specific microbial community, likely shaped by different physicochemical conditions, such as pH value. Specifically, the taxonomic shift between digesta-and mucosa-associated bacteria and from the rumen to the rectum within cattle GITs supports the assumption that digesta-associated microbiota might play an important role in feed digestion, while the mucosa-adherent microbiome may be involved in epithelium proliferation and diseases, indicating that the structure and function of mucosal and ruminal bacterial communities are distinct. Similarly, the present study inferred that genes related to amino acid metabolism were overrepresented in mucosal samples. These findings indicate that the microbial community associated with mucosa may be more necessary to amino acid degradation. In general, this research has revealed partially the high level of heterogeneity in species composition and functional capacities of microbial assemblages across the bacterial ecology system of the GIT, and these findings can be used to potentially modulate gastrointestinal microbiota and improve health, nutrient use and milk production in dairy cattle.
Materials and Methods
Ethical approval. The Animals and sample collection. The study used six Holstein dairy cattle aged five years (body weight: 607 ± 55.6 kg; milk yield = 29.72 ± 4.7 kg/day, 140 to 189 days in lactation). The cows' diets were formulated to meet or exceed the energy requirements (at 24 kg/day dry matter intake) of Holstein cattle yielding 35 kg of milk/day with 3.50% milk fat and 3.10% true protein (Table S13). Diets were fed ad libitum as a total mixed ration to avoid the selection of dietary components. The cattle were fed at 07:00 and 18:00 h, one-half of the allowed daily ration at each feeding. The experimental period was 84 d; the first 83 d were used for diet adaptation and the last day was used for measurements. Throughout the experimental period, the cattle were housed in tie stalls and fed ad libitum to assure 5% orts, and they were given free access to fresh water during the trial.
On day 84, the cattle were slaughtered, and mucosal tissue and digesta samples were collected from the rumen, reticulum, omasum, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum. Mucosal tissue samples (60 total) were rinsed 3 times with sterile, phosphate-buffered saline (PBS) (pH 7.0) to remove the digesta, cut into 4-5 mm 2 and immediately frozen in liquid nitrogen. The digesta of the rumen, reticulum, omasum, abomasum, duodenum, jejunum, ileum, cecum, colon and rectum were homogenised, separately. The pH values of the contents of each GIT segment were determined immediately using an Accumet gel-filled polymer-body combination pH electrode (Fisher Scientific; Fairlawn, NJ, USA). Then, the homogenised digesta from each GIT segment were sampled (60 total) and immediately frozen in liquid nitrogen. The remaining samples were centrifuged immediately at 2,000 × g, and the supernatants were stored at −20 °C until they were analysed for VFA. The amount of VFA was measured using capillary column gas chromatography (GC-14B, Shimadzu; capillary column: 30 m × 0.32 mm × 0.25 mm film thickness; column temperature = 110 °C, injector temperature = 180 °C, detector temperature = 180 °C) 27 .
DNA extraction, PCR amplification, illumina MiSeq sequencing and sequencing data processing. For DNA extraction, three gram (wet weight) of homogenised samples (120 total) of digesta and mucosal tissue from each GIT segment of each cow was used. DNA was extracted by a bead-beating method using a mini-bead beater (Biospec Products; Bartlesville, USA), followed by phenol-chloroform extraction 27 . The solution was precipitated with ethanol, and the pellets were suspended in 50 μ L of Tris-EDTA buffer. DNA was quantified using a Nanodrop spectrophotometer (Nyxor Biotech; Paris, France) following staining using a Quant-it Pico Green dsDNA kit (Invitrogen Ltd.; Paisley, UK). DNA samples were stored at −80 °C until further processing.
The V3-V4 regions of the bacteria 16S rRNA gene were amplified by PCR (95 °C for 2 min, followed by 25 cycles at 95 °C for 30 s, 55 °C for 30 s, 72 °C for 30 s and a final extension at 72 °C for 5 min) using primers 338F (5′-barcode-ACTCCTRCGGGAGGCAGCAG)-3′ and 806R (5′-GGACTACCVGGGTATCTAAT-3′), where barcode is an eight-base sequence unique to each sample. PCR reactions were performed in a triplicate 20 μ L mixture containing 4 μ L of 5 × FastPfu Buffer, 2 μ L of 2.5 mM dNTPs, 0.8 μ L of each primer (5 μ M), 0.4 μ L of FastPfu Polymerase and 10 ng of template DNA. Amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences; Union City, CA, USA) according to the manufacturer's instructions and quantified using QuantiFluor ™ -ST (Promega; USA). Purified amplicons were pooled in equimolar and paired-end sequenced (2 × 250) on an Illumina MiSeq platform according to standard protocols 34 .
Raw fastq files were de-multiplexed and quality-filtered using QIIME (version 1.70) 35 , with the following criteria: 1) The 250 bp reads were truncated at any site receiving an average quality score < 20 over a 10 bp sliding window, discarding the truncated reads that were shorter than 50 bp; 2) Exact barcode matching, 2 nucleotide mismatch in primer matching, reads containing ambiguous characters were removed; 3) Only sequences that overlapped longer than 10 bp were assembled according to their overlap sequence. Reads that could not be assembled were discarded. OTUs were clustered with a 97% similarity cut-off using UPARSE (version 7.1 http://drive5.com/uparse/), and chimeric sequences were identified and removed using UCHIME 36 . The most abundant sequences within each OTU were designated as 'representative sequences' and aligned against the core set of Greengenes 13.5 37 using PYNAST 38 with the default parameters set by QIIME. A PH Lane mask supplied by QIIME was used to remove hypervariable regions from the aligned sequences. FASTTREE 39 was used to create a phylogenetic tree of the representative sequences. Sequences were classified using the Ribosomal Database Project (RDP) classifier with a standard minimum support threshold of 80% 40 . Sequences identified as chloroplasts or mitochondria were removed from analysis. Community diversity was estimated using the ACE, Chao1 and Shannon indices. The unweighted UniFrac distance method was used to perform a principal coordinate analysis 41 , and an unweighted distance-based analysis of molecular variance (AMOVA) was conducted to assess significant differences among samples using the programme MOTHUR v.1.29.0 42 . | v3-fos |
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} | s2 | Identification of miRNAs Responsive to Botrytis cinerea in Herbaceous Peony (Paeonia lactiflora Pall.) by High-Throughput Sequencing
Herbaceous peony (Paeonia lactiflora Pall.), one of the world’s most important ornamental plants, is highly susceptible to Botrytis cinerea, and improving resistance to this pathogenic fungus is a problem yet to be solved. MicroRNAs (miRNAs) play an essential role in resistance to B. cinerea, but until now, no studies have been reported concerning miRNAs induction in P. lactiflora. Here, we constructed and sequenced two small RNA (sRNA) libraries from two B. cinerea-infected P. lactiflora cultivars (“Zifengyu” and “Dafugui”) with significantly different levels of resistance to B. cinerea, using the Illumina HiSeq 2000 platform. From the raw reads generated, 4,592,881 and 5,809,796 sRNAs were obtained, and 280 and 306 miRNAs were identified from “Zifengyu” and “Dafugui”, respectively. A total of 237 conserved and 7 novel sequences of miRNAs were differentially expressed between the two cultivars, and we predicted and annotated their potential target genes. Subsequently, 7 differentially expressed candidate miRNAs were screened according to their target genes annotated in KEGG pathways, and the expression patterns of miRNAs and corresponding target genes were elucidated. We found that miR5254, miR165a-3p, miR3897-3p and miR6450a might be involved in the P. lactiflora response to B. cinerea infection. These results provide insight into the molecular mechanisms responsible for resistance to B. cinerea in P. lactiflora.
Introduction
Herbaceous peony (Paeonia lactiflora Pall.) is a perennial root flower belonging to the Paeoniaceae family. It is popular worldwide due to its high ornamental values in locations including New Zealand, Australia, Europe, Asia, and North America [1]. In China, P. lactiflora has been widely applied in urban and rural landscaping due to its high levels of resistance to infection, tolerance to environmental factors, and easy maintenance, making it ideal for a variety of specialized gardens, flower beds, and perennial borders [2]. However in practice, P. lactiflora cultivated in a landscape greenbelt in the middle and lower reaches of the Chinese Yangtze River region was highly susceptible to Botrytis cinerea after flowering. This infection mainly damaged the P. lactiflora leaf and resulted in rot and led to the death of the entire plant, which was consistent with the previous findings in Nanjing, Shanghai and Hangzhou [3]. Lan [3] reported that the optimum temperature for B. cinerea growth and sporulation was 20 °C-24 °C and the optimum pH was 4-5, and it could be controlled by many chemical treatments. However, chemical spraying is expensive, requires manual labor, pollutes the environment, and leaves white stains on the leaves, ultimately reducing the ornamental value of P. lactiflora while not necessarily preventing B. cinerea infection. Conversely, breeding resistant cultivars is the best method to solve this problem, and the rapid development of genetic engineering technology in recent years has laid the foundation for effective development of this field. Recent studies have provided compelling evidence demonstrating that microRNAs (miRNAs) are essential endogenous regulatory factors and play an important role in plant response to biotic stress [4,5]. Analysis of miRNAs thus provides a novel method to study the molecular mechanism of resistance in P. lactiflora B. cinerea.
miRNAs are approximately 21-nucleotides (nt) in length and are non-coding small RNAs (sRNAs) found in animals and plants, typically encoded by endogenous genes. miRNAs could play an important regulatory role at the post-transcriptional level by targeting mRNA degradation and leading to translation repression [6]. Since they were first found in Caenorhabditis elegans [7], a large number of miRNAs have been continually identified in higher plants, including Arabidopsis thaliana [5], Zea mays [8], Triticum aestivum [9] and Oryza sativa [10]. The latest version of the miRNA database (miRBase 21.0, http://www.mirbase.org/) contains 28,645 entries of hairpin precursor miRNAs (pre-miRNAs), expressing 35,828 mature miRNA products over a range of 223 species [11]. Moreover, numerous studies have revealed that miRNAs are involved in diverse biological and metabolic processes, such as the regulation of plant organ development [12,13], signal conduction of plant hormones [14,15], abiotic stress response [16,17], and pathogen defense [18]. To the best of our knowledge concerning B. cinerea, only Jin et al. [19,20] have reported that tomato miRNAs had a functional role in resistance to B. cinerea. However, there no P. lactiflora miRNAs have yet been deposited in miRBase and no related reports on this topic have been completed. In order to investigate the roles of P. lactiflora miRNAs in response to B. cinerea stress, two cultivars, "Zifengyu" and "Dafugui," with significantly different levels of resistance to this pathogen were processed for sRNA and transcriptome sequencing. In this study, miRNAs and their target genes responsive to B. cinerea were identified in P. lactiflora, and these results provide a foundation for understanding the functions and regulatory mechanisms of miRNAs in P. lactiflora resistance to B. cinerea.
Plant Materials
P. lactiflora was grown in the germplasm repository of Horticulture and Plant Protection College, Yangzhou University, Jiangsu Province, China (32°30' N, 119°25' E). Under field conditions, two cultivars, "Zifengyu" and "Dafugui", with significantly different levels of resistance to B. cinerea (Figure 1, in the later stage infected by B. cinerea, the resistant cultivar "Zifengyu" grew well with few disease spots, while the susceptible cultivar "Dafugui" became weak and almost entirely withered) were used as the experimental materials for sRNA and transcriptome sequencing. After flowering, P. lactiflora was naturally infected by B. cinerea, and the infected and fully expanded leaves from the fourth apical node in four developmental stages (S1, late May; S2, mid June; S3, early July; and S4, late July) were taken from May to July 2013. The sample population of each cultivar were sixty plants (four stages, fifteen plants each stage). The leaves collected from four stages each cultivar were then equally mixed to prepare for two independent sRNA libraries (i.e., "Zifengyu" and "Dafugui"). All samples were immediately frozen in liquid nitrogen and stored at í80 °C until further analysis. Figure 1. The infection status of the cultivars "Zifengyu" and "Dafugui" under field conditions by B. cinerea. S1, late May; S2, mid June; S3, early July; and S4, late July.
Small RNA Library Construction and Sequencing
Total RNA was extracted according to a modified CTAB extraction protocol [21]. Prior to sRNA library construction, RNA samples were examined by a spectrophotometer (Eppendorf, Hamburg, Germany) and 1% agarose gel electrophoresis. Moreover, RNA fragments of 18-30 nt long were separated from total RNA using polyacrylamide gel electrophoresis. The Solexa adaptors were added to the fragments at both 5'-and 3'-ends, and they were converted to cDNA according to a reverse transcription PCR kit (Invitrogen, Carlsbad, CA, USA). The purified fragments were sent for sequencing at the Beijing Genomic Institute (Shenzhen, China) using the Illumina HiSeq 2000 platform (Illumina Inc., San Diego, CA, USA). The data from "Zifengyu" and "Dafugui" were submitted to the National Center for Biotechnology Information (NCBI) under accession numbers SRS926009 and SRS926051, respectively.
miRNA Identification and Corresponding Target Gene Prediction
After getting rid of low-quality sequences (reads with 5' primer contaminants, reads without 3' primer, reads without the insert tag, reads with poly A and reads shorter than 18 nt), unique reads were screened against GenBank as well as Rfam (http://rfam.sanger.ac.uk) to remove ribosomal RNA (rRNA), transfer RNA (tRNA), small nuclear RNA (snRNA), and small nucleolar RNA (snoRNA). Moreover, the common and specific sequences between two libraries were identified through the comparison of corresponding genes annotated by transcripts. After these, the merged unique reads were also screened against the miRBase 21.0 using a nucleotide-nucleotide Basic Local Alignment Search Tool (BLASTn) to identify the conserved miRNAs [11]. Meanwhile, in order to identify the novel miRNAs, all candidate precursors with hairpin-like structures were obtained using the Mireap program (http://sourceforge.net/ projects/mireap). Additionally, the unigene sequences of "Zifengyu" and "Dafugui" transcriptomes submitted to the NCBI with accession numbers SRS774325 and SRS774327 were used to predict the target genes of miRNAs by the psRNA Target program (http://plantgrn.noble.org/psRNATarget) with the default parameters. The specific methods were from Allen et al. [22] and Schwab et al. [23].
Differentially Expressed miRNAs and Their Target Gene Annotation
miRNAs expression levels were calculated according the value of reads per million reads (RPM). Differentially expressed miRNAs were defined based on strict criteria (p value 0.05 and differential expression fold > 2). Functional annotation of target genes was performed using various bioinformatics procedures, including GO and KEGG. The specific methods were referred to in Gong et al. [24].
Digital Gene Expression Analysis
Firstly, eight cDNA libraries from "Zifengyu" and "Dafugui" in four developmental stages were constructed. After quantification and qualification of the sample library using the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA, USA) and ABI StepOnePlus Real-Time PCR System (Applied Biosystems, Foster, California, CA, USA), the samples were also sequenced using the Illumina HiSeq 2000 platform (Illumina, San Diego, CA, USA). The gene expression level was compared with S1, respectively (S1/S1, S2/S1, S3/S1, S4/S1), and calculated using the reads per kb per million reads (RPKM) method [25] based on the numbers of reads uniquely mapped to the specific gene and the total number of uniquely mapped reads in the sample.
Expression Analysis of Target Genes by qRT-PCR
Expression levels of selected target genes were analyzed by quantitative real-time PCR (qRT-PCR) with three biological replications each sample via a CFX96 Real-Time System (Bio-Rad, Hercules, CA, USA). The specific methods were referred to in Zhao et al. [26]. The cDNA was synthesized from 1 g RNA using PrimeScript RT reagent Kit With gDNA Eraser (TaKaRa, Kyoto, Japan). P. lactiflora Actin (JN105299) had been used as an internal control in this study [27]. Gene-specific primers were designed using PRIMER5.0 software and listed in Table S1. Two μL of the cDNAs of each sample were used for ordinary PCR to test the amplification specificity of the corresponding primer pairs. qRT-PCR was performed using the SYBR Premix Ex Taq (Perfect Real Time) (TaKaRa). The amplification system consisted of an initial denaturation of 95 °C/30 s, followed by 40 cycles of 95 °C/5 s, 51 °C/30 s, 72 °C/30 s. Gene relative expression levels were calculated by the 2 í¨¨Ct comparative threshold cycle (Ct) method [28]. The Ct values of the triplicate reactions were gathered using the Bio-Rad CFX Manager V1.6.541.1028 software (Bio-Rad, Hercules, CA, USA, 2008).
Sequence Analysis of sRNAs
To identify miRNAs responsive to B. cinerea in P. lactiflora, two independent sRNA libraries were sequenced from different cultivars collected at four developmental stages and equally mixed, both subject to B. cinerea infection, but one of which ("Zifengyu") is resistant to the pathogen. A total of 24,008,974 and 22,108,093 reads were generated from "Zifengyu" and "Dafugui", respectively. The low quality sequences were removed including 5' contaminants, those missing the 3' primer or insert tag, sequences with a poly A tail, and finally those shorter than 18 nt. The final data sets consisted of 23,520,582 and 21,452,306 clean reads in "Zifengyu" and "Dafugui", respectively, which was in both cases more than 97.97% of the total original reads. Subsequent analysis revealed the number of total sRNAs (i.e., sum of sRNAs) was 4,592,881 in "Zifengyu" and 5,809,796 in "Dafugui" (Figure 2A), while the number of unique sRNAs (i.e., variety of sRNAs) was 2,960,307 and 3,033,015, respectively ( Figure 2B). Moreover, the length distribution of sRNA was similar between the two libraries, where the sRNAs ranging from 21 to 24 nt was the most frequent length (more than 80%) identified, c (more than 47%), followed by 22 nt, 20 nt, and 24 nt ( Figure 2C). These sRNAs were classified into different categories after screening against GenBank and Rfam using BLAST searches, and the results from these analyses are presented in Table 1.
Identification of Conserved miRNAs
To identify conserved miRNAs, all mappable sRNA sequences were compared with the known plant miRNAs in miRBase. A total of 271 and 298 conserved miRNA sequences were identified in "Zifengyu" and "Dafugu", respectively (Tables S2 and S3). The read counts among different miRNA families were markedly different. A few conserved miRNA families such as miR5078, miR166a, miR167a, miR157a, miR6113, miR718, miR1882e-3p, miR3353 and miR8019-5p were enriched in both of the libraries. The secondary structures of some conserved pre-miRNAs in "Zifengy" and "Dafugu" are listed in Figures S1 and S2, respectively. Moreover, putative target genes of conserved miRNAs were predicted, with 406 and 458 potential target genes from 133 (out of 271) and 136 (out of 298) conserved miRNAs identified in "Zifengy" and "Dafugu", respectively (Tables S4 and S5).
Identification of Novel miRNAs
After searching for potential pre-miRNAs and predicting their hairpin-like structures, 9 and 8 unique sequences were identified as novel miRNAs in "Zifengyu" and "Dafugui", respectively (Tables 2 and 3), only 2 of which (pla-MIR11601 and pla-MIR11605) were shared by both cultivars. The novel miRNA sequences were 20 to 23 nt in length, and among these 21 nt reads were the most abundant. The pre-miRNAs ranged from 76 to 262 nt in "Zifengyu" and 76 to 274 nt in "Dafugui" (Tables 2 and 3) in length. We also obtained the secondary structures of select novel pre-miRNAs ( Figure S3). The average minimum free energy values were í41.31 kcal/mol in "Zifengyu" and í42.35 kcal/mol in "Dafugui". Furthermore, we predicted the putative target genes of novel miRNAs were predicted, with 12 and 40 potential target genes from 8 (out of 9) and 7 (out of 8) novel miRNAs identified in "Zifengyu" and "Dafugui", respectively (Tables S6 and S7).
Comparative Analysis of miRNAs and Corresponding Target Genes between Two Libraries
To identify key miRNAs between the two P. lactiflora libraries, their conserved miRNAs were comparatively analyzed based on "Zifengyu" as the control group. A total of 237 differentially expressed miRNAs were obtained ( Figure 3A and Table S8), and 136 miRNAs were up-regulated, whereas 101 miRNAs were down-regulated. We found that 436 potential target genes were identified from 115 (out of 237) differentially expressed miRNAs. In order to further evaluate the potential functions of these target genes, a Kyoto Encyclopedia of Genes and Genomes (KEGG) functional classification was performed. In the KEGG functional classification analysis, only 130 target genes could be assigned to 12 KEGG pathways, among which metabolic pathways demonstrated the largest number of target genes, followed by biosynthesis of secondary metabolites, endocytosis and ether lipid metabolism. In addition, some pathways closely related to plant resistance were found including plant hormone signal transduction, phenylpropanoid biosynthesis, and plant-pathogen interaction (Table S9).
Similarly, the novel miRNAs were also comparatively analyzed, and 9 differentially expressed miRNAs were identified, including 2 up-regulated and 5 down-regulated miRNAs ( Figure 3B and Table S10). Among these sequences, 8 potential target genes were identified from 6 (out of 7) differentially expressed miRNAs. After KEGG functional classification, only 2 target genes could be assigned to 1 KEGG pathways (Table S11).
Analysis of the Candidate B. cinerea-Responsive miRNAs
In order to identify the miRNAs responsive to B. cinerea stress, the analyses of differentially expressed miRNAs and their target genes in two libraries were performed. According to the target genes annotated in KEGG pathways, 9 genes were screened that were linked to phenylpropanoid biosynthesis (beta-glucosidase, BGLU), diterpenoid biosynthesis (gibberellin 2-oxidase, GA2OX), plant hormone signal transduction (ethylene receptor, ETR), plant-pathogen interaction (nonhost1, NHO1; peroxin-10, PEX10; serine/threonine-protein kinase PBS1, PBS1; WRKY transcription factor 29, WRKY29; calcium-dependent protein kinase, CDPK). The corresponding miRNAs were miR5254, miR846, miR6450a, miR165a-3p, miR6432, miR6450a, miR5558-3p and miR3897-3p, respectively (Table 4). When "Zifengyu" was regarded as the control group, the expression levels of the majority of the candidate miRNAs in "Dafugui" were up-regulated, except for miR6450a and miR5558-3p. Furthermore, the expression patterns of 9 target genes were analyzed in four developmental stages using digital gene expression. The results showed that these genes were essentially up-regulated after infection by B. cinerea. Additionally, BGLU, NHO1, CDPK and WRKY29 were highly expressed in "Zifengyu", whereas the opposite trend was observed in ETR, which harbored expression levels negatively correlated with corresponding miRNAs (miR5254, miR165a-3p, miR3897-3p and miR6450a). Figure 4. qRT-PCR validations of expression levels of target genes from digital gene expression analysis. Expression levels by qRT-PCR of selected target genes of P. lactiflora cultivars "Dafugui" and "Zifengyu" were validated from the levels of digital gene expression data. The corresponding genes are specified above each map. The Y axis represents the normalized log2 value of gene expression levels. The X axis represents the comparisons of different stages. "S2/S1" indicates a comparison of gene expression levels between S1 and S2. "S3/S1" and "S4/S1" indicate analogous comparisons. S1: late May; S2: mid June; S3: early July; S4: late July.
Discussion
It has been recently found that miRNAs play important roles in physiological processes as a non-coding gene expression and regulating factor [29]. With the dramatic changes in the environment, more attention has been paid to the protective role of miRNAs in plants. Response to adversity stress in plants includes the differential expression of miRNAs, causing the accumulation of select substances and altering metabolic pathways [4,5,30]. Plant adversity stress is divided into abiotic and biotic categories, with more in-depth studies focused on plant miRNAs in response to abiotic stress, which includes stresses related to changes in nutrition [31], water [32], temperature [33], and heavy metals [34]. Meanwhile, miRNAs also play an important role in response to biotic stress; in particular, when plants are infected by pathogens, the expression of a variety of miRNAs and related target genes will change [35,36]. In the present study, high-throughput sequencing technology was used to identify miRNAs responsive to B. cinerea infection in P. lactiflora for the first time. Two cultivars, "Zifengyu" and "Dafugui", with significantly different levels of resistance to B. cinerea were selected as the materials. When they were subjected to B. cinerea infection, "Zifengyu" was resistant to the pathogen. The two plant cultivars with different genotypes were used as experimental materials and compared in terms of many stress responses, such as temperature stress response [32] and Verticillium dahliae and Sporisorium reilianum infection [37,38]. In B. cinerea infection, our group compared the digital gene expression (DGE) of "Zifengyu" and "Dafugui" subjected to B. cinerea infection, and a great deal of disease resistance-relevant genes were successfully screened [24]. Thus, these two cultivars might be good materials to study the functions and molecular mechanisms of miRNAs in P. lactiflora resistance to B. cinerea. Through comparing two independent sRNA libraries, 23,520,582 and 21,452,306 sRNAs in "Zifengyu" and "Dafugui" were obtained, respectively. The length distribution of sRNAs in the libraries was very similar with the majority ranging from 20 to 24 nt. Among these sequences, the 21 nt sRNAs were the most abundant, followed by 22 nt, which is consistent with reports for Chinese yew [39] and Norway spruce [40]. However, in reports for other plants, such as celery [33], trifoliate oranges [41], and olives [42], the 24 nt sRNAs were the most abundant. These differences are mainly because the length of sRNAs is dependent on specific enzymes. For example, the sRNAs are 21 nt in length when processed by DCL1, while they are 24 nt when processed by DCL2 [43]. These sRNAs were classified into different categories, with the rRNA and miRNA groups enriched, which is consistent with what has been found in winter wheat [44], suggesting that sRNAs have been conserved in plant evolution. In the comparative analysis of miRNAs between "Zifengyu" and "Dafugui", 237 conserved and 7 novel differentially expressed miRNAs were obtained. We examined the KEGG pathways with which they were associated in order to distinguish those likely to be involved in resistance to B. cinerea from those related to other phenotypic differences between the two cultivars.
The molecular mechanistic changes in plants infected by B. cinerea are complex; however, previous studies mainly focused on the transcriptional level of this response. De Cremer et al. [45] analyzed the transcriptome of lettuce infected by B. cinerea, and identified a complex network of genes, including the induction of those related to the phenylpropanoid pathway, terpenoid biosynthesis, and photosynthesis. At the same time, through sequencing the tomato transcriptome, Smith et al. [46] found that almost immediately after B. cinerea infection, a variety of processes were suppressed including photosynthesis as well as pathways involved in growth, energy generation, and response to stimuli. Simultaneously, some processes were also induced such as various defense-related genes, including pathogenesis-related protein 1 (PR1), a beta-1, 3-glucanase (glucanase), and a subtilisin-like protease. At the post-translational level, the relevant reports concerning B. cinerea infection have been limited to the tomato. Firstly, Jin et al. [20] identified three B. cinerea stress-responsive miRNAs using microarray analysis, which regulated metabolic, morphological, and physiological adaptations of tomato seedlings at the post-transcriptional level. Subsequently, Jin and Wu [19] investigated the miRNA expression patterns in tomato in response to B. cinerea stress using high-throughput sequencing, and found that 57 conserved miRNAs and one novel miRNA were differentially expressed in B. cinerea-infected leaves, and additionally that miR319, miR394 and miRn1 might be involved in the tomato leaf response to B. cinerea infection. In the present study, 7 candidate differentially expressed miRNAs related to adversity stress were screened, and the 9 corresponding target genes were annotated in phenylpropanoid biosynthesis, diterpenoid biosynthesis, plant hormone signal transduction, and plant-pathogen interaction using KEGG. Among the candidate miRNAs, miR5254, miR846, miR165a-3p, miR6432 and miR3897-3p revealed higher expression levels in "Dafugui" than "Zifengyu", while the conserved miRNAs, including miR6450a and miR5558-3p, had the opposite expression pattern. For the target genes analyzed, the expression levels of BGLU, NHO1, CDPK, and WRKY29 in "Zifengyu" were always higher than those in "Dafugui", whereas that of ETR was always lower. The expression levels of PEX10 and PBS1 were higher in "Zifengyu" than "Dafugui" at an early stage of infection (S2), but lower later during the infection (S3 and S4), while that of GA2OX was lower in "Zifengyu" than "Dafugui" at S2 and S4, but higher at S3. In previous studies, BGLU was associated with many biological processes in plants that could resist abiotic and biotic stresses by activating plant hormones and resistant pathways [47]; for example, overexpression of an Arabidopsis BGLU gene enhanced drought resistance in creeping bentgrass [48]. Lu et al. [49] found NHO1 was required for general resistance against Pseudomonas bacteria in Arabidopsis. CDPK has multiple functions in plant disease resistance, such as enhancing the production of active oxygen species (AOS) by stimulating NADPH oxidase activity [50]. Additionally, as a member of the complex family of WRKY transcription factors, WRKY29 has been proved to be a positive regulator of disease resistance [51], while ETR negatively regulated ethylene responses [52]. The expression levels of these 5 target genes in the present study were consistent with previous studies, which indicated that they might be involved in the P. lactiflora response to B. cinerea infection at the transcriptional level. Moreover, these 5 target genes were negatively correlated with their corresponding miRNAs (miR5254, miR165a-3p, miR3897-3p and miR6450a), which also suggested that they might be involved in the P. lactiflora response to B. cinerea infection at the post-transcriptional level. However, to the best of our knowledge concerning miRNAs, only miR165a was previously reported in response to abiotic stress [53], meaning the roles of miR5254, miR3897-3p and miR6450a in response to B. cinerea infection require further study. These results would further the understanding of miRNA regulation in response to B. cinerea stress in P. lactiflora.
Conclusions
In this study, high-throughput sequencing technology was used to characterize the miRNAs in the B. cinerea-infected two P. lactiflora cultivars "Zifengyu" and "Dafugui" with significantly different resistance to B. cinerea. After stringent quality checking and data cleaning, a total of 23,520,582 and 21,452,306 clean reads were obtained. Differential expression analysis revealed 237 conserved and 7 novel miRNAs between "Zifengyu" and "Dafugui" might be associated with B. cinerea stress resistance. Among screening, miR5254, miR165a-3p, miR3897-3p and miR6450a might be involved in the P. lactiflora response to B. cinerea infection. Our work was useful for breeding new cultivars of B. cinerea stress resistance. | v3-fos |
2015-09-18T23:22:04.000Z | {
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} | s2 | Determination of Free Radical Scavenging, Antioxidative DNA Damage Activities and Phytochemical Components of Active Fractions from Lansium domesticum Corr. Fruit
Lansium domesticum Corr. or “long-kong” is one of the most popular fruits in Thailand. Its peel (skin, SK) and seeds (SD) become waste unless recycled or applied for use. This study was undertaken to determine the bioactivity and phytochemical components of L. domesticum (LD) skin and seed extracts. Following various extraction and fractionation procedures, 12 fractions were obtained. All fractions were tested for antioxidant capacity against O2−• and OH•. It was found that the peel of L. domesticum fruits exhibited higher O2−• and OH• scavenging activity than seeds. High potential antioxidant activity was found in two fractions of 50% ethanol extract of peel followed by ethyl acetate (EA) fractionation (LDSK50-EA) and its aqueous phase (LDSK50-H2O). Therefore, these two active fractions were selected for further studies on their antioxidative activity against DNA damage by hydrogen peroxide (H2O2) in human TK6 cells using comet assay. The comet results revealed DNA-protective activity of both LDSK50-EA and LDSK50-H2O fractions when TK6 human lymphoblast cells were pre-treated at 25, 50, 100, and 200 μg/mL for 24 h prior to H2O2 exposure. The phytochemical analysis illustrated the presence of phenolic substances, mainly scopoletin, rutin, and chlorogenic acid, in these two active fractions. This study generates new information on the biological activity of L. domesticum. It will promote and strengthen the utilization of L. domesticum by-products.
Introduction
Thailand has a variety of fruits; however, only some of them are widely consumed. Among these is the fruit of Lansium domesticum Corr. which is known in Thai as "long-kong". It has been very popular in Thailand and surrounding countries in Southeast Asia. It belongs to the Meliaceae family and is known by numerous common names. In Indonesia, it is known mainly as langsat, duku, or kokosan while in Malaysia it is known as langsat, lansa, langseh, or langsep. In the Philippines, it is known as lansones and it is known as bòn-bon in Vietnam [1,2]. The well-known and economic fruit long-kong is largely cultivated in peninsular Thailand, especially in the southern region. Long-kong develops between 15 and 25 fruits per bunch with little non-sticky sap on the skin. The appearance of long-kong fruit is globular in shape with an average size of 1.2-2.4 inches in diameter ( Figure 1). It has a brittle and rough skin. It is almost seedless, with five segments of white translucent flesh [3]. The bark of L. domesticum is used traditionally as an anti-malarial remedy by the native people of Borneo [4]. The leaves have been used by indigenous people in the Philippines for the control of mosquitoes [5]. Previous phytochemical studies on the peels and seeds of L. domesticum found several types of triterpenoids [6,7]. The peel of this fruit is traditionally known to be toxic to domestic animals. Phytochemical investigations of the peels revealed the presence of triterpene glycosides and seco-onoceranoids such as lansic acid [8].
Over-production of free radical leads to "oxidative stress" that can be defined as the state of imbalance between the high production of reactive oxygen species (ROS) and the low amount of antioxidant defense systems [9]. This imbalance can cause damage to cells, contributing to cellular dysfunction and leading to chronic degenerative diseases such as atherosclerosis, diabetes, cancer, neurodegeneration, The bark of L. domesticum is used traditionally as an anti-malarial remedy by the native people of Borneo [4]. The leaves have been used by indigenous people in the Philippines for the control of mosquitoes [5]. Previous phytochemical studies on the peels and seeds of L. domesticum found several types of triterpenoids [6,7]. The peel of this fruit is traditionally known to be toxic to domestic animals. Phytochemical investigations of the peels revealed the presence of triterpene glycosides and seco-onoceranoids such as lansic acid [8].
Over-production of free radical leads to "oxidative stress" that can be defined as the state of imbalance between the high production of reactive oxygen species (ROS) and the low amount of antioxidant defense systems [9]. This imbalance can cause damage to cells, contributing to cellular dysfunction and leading to chronic degenerative diseases such as atherosclerosis, diabetes, cancer, neurodegeneration, and cardiovascular diseases [10,11]. Therefore, the balance of free radical production and a sufficient level of antioxidants are essential for health [12]. Most antioxidants found in foods and supplements are of the non-enzymatic type. They boost the human enzymatic antioxidant defense system and prevent the depletion of our enzymatic antioxidants. Epidemiological evidence has supported that antioxidants have a role in the prevention of several chronic diseases including cardiovascular disease, cancer, and diabetes [13,14]. Fruits, vegetables, and medicinal herbs are the richest sources of antioxidant compounds. They are loaded with key antioxidants such as vitamin A, C, E, β-carotene, and important minerals, including selenium and zinc [15]. Moreover, the natural flavonoids (e.g., catechin, quercetin) or other phenolic (e.g., ferulic acid) or polyphenolic compounds (e.g., resveratrol) found in fruits also exert significant antioxidative ability [16].
Nowadays, the trend of using natural antioxidants has markedly increased due to the concern about the safety of synthetic antioxidants. Consequently, fruit is considered to be an important source of natural antioxidants, especially the peels and seeds which become waste unless recycled or applied to use. Even though Thailand has a variety of fruits, only some of them are widely consumed. Among these, the fruits of long-kong have been very popular in Thailand and countries in Southeast Asia. However, there is little information concerning the biological activity, particularly antioxidant activity, of peels and seeds of long-kong fruits. Therefore, this study was undertaken on long-kong to investigate the biological activities, particularly antioxidant mechanisms, using both cell-based (antioxidative DNA damage activity) and non-cell-based (ROS scavenging property) systems. Also, the phytochemical components of active fractions from L. domesticum Corr. fruit extracts were investigated.
Sample Preparation and Extraction
Mature L. domesticum (long-kong) fruits were purchased from Talad-Thai market in Prathumthani, Thailand. After washing, the peel or skin (SK) and seeds (SD) of the fruits were separated and air-dried at 50˝C in hot air oven for 1-2 days until weight constant. Each dried sample was then ground with an electrical grinder. The grounded samples were extracted with 50% or 95% (v/v) ethanol by maceration method. Firstly, each 100 g of fine air-dried peel and seeds was mixed with 300 mL of 50% or 95% (v/v) ethanol and left overnight at room temperature. Then, supernatant of each sample was kept and added to 50% or 95% (v/v) ethanol. This step was performed 12 times to reach completion of extraction. All 12 extracts were pooled, then filtered using Whattman No.1 filter paper before being evaporated by a rotary evaporator at 45˝C to get rid of ethanol. The aqueous phase residues were further fractionated with 100 mL ethyl acetate (EA) 5 times as well as dichloromethane (DCM) of similar volume and time. All fractions were then concentrated by a rotary evaporator at 45˝C. The obtained 12 semisolid fractions were named as shown in Table 1. They were stored at 4˝C in dark conditions until utilization. The antioxidant capacity of 12 above-mentioned fractions of the peel and seeds of long-kong fruits was determined using PHOTOCHEM (Analytik Jena, Thuringia, Germany), whose principle is based upon measurement of PCL. Briefly, superoxide anion radicals (O 2´b ullet ) were generated in the system by optical excitation of luminol, which was a photosensitizer substance. The antioxidant capacity of samples was measured by their inhibitory effect on luminescence generation compared with the standard antioxidant (constructed a calibration curve). The results were presented in equivalent units (nmol) of ascorbic acid for the antioxidative capacity of the water-soluble substances (ACW) system or trolox (synthetic vitamin E) units for antioxidative capacity of the lipid-soluble substances (ACL) system. For the measurement, the L. domesticum fractions were prepared by weighing 10 mg of each sample fraction and dissolved it in 1 mL of dilution reagent (reagent 1) supplied with the ACL or ACW reagent kits. The solution was sonicated for 10 min at room temperature to facilitate complete solubility. The supernatants were filtered through 0.45 µm syringe filter. The reaction was initiated by adding 10 µL of standard antioxidant compound (ascorbic acid and trolox) or test samples (long-kong fractions) to the mixture of 2300 µL of dilution reagent (reagent 1), 200 µL of reaction buffer (reagent 2), and 25 µL of protosensitizer (reagent 3). All samples were conducted and measured in triplicate.
Deoxyribose Assay
Deoxyribose assay was performed to evaluate hydroxyl radical (OH bullet ) scavenging activity of the 12 fractions. The method was based on the determination of malondialdehyde (MDA) pink chromogen which was a degraded product of 2-deoxyribose (2-DR) damaged by OH bullet . All sample fractions were prepared as previously mentioned in PCL assay except using distilled water as solvent. Typical reactions were started by the addition of 50 µM FeCl 3 to solutions (0.5 mL final volume) containing 5 mM 2-DR, 100 µM ethylenediaminetetraacetic acid (EDTA), 10 mM phosphate buffer (pH 7.2), 0.5 mM H 2 O 2, and various concentrations of sample fractions in presence of 100 µM ascorbic acid (reducing agent) for starting the reaction and generated OH bullet . Reactions were carried out for 10 min at room temperature and stopped by the addition of 0.5 mL 2.8% trichloroacetic acid (TCA), followed by the addition of 0.5 mL thiobarbituric acid (TBA) solution. After boiling for 15 min, solutions were allowed to cool at room temperature. The absorbance of reaction mixture was measured to determine MDA pink chromogen at 532 nm in micro-plate reader system (GENios Plus, TECAN , Port Melbourne, Victoria, Australia). All samples were tested in triplicate.
Cell Culture and Preparation
The TK6 human lymphoblasts (ATCC CRL-8015, Rockville, MD, USA) were cultured in RPMI-1640 medium (Gibco, Rockville, MD, USA) supplemented with 10% heat-activated horse serum and 1% (v/v) penicillin-streptomycin in tissue culture flask. They were maintained at 37˝C in humidified atmosphere containing 5% CO 2 as exponential growing phase prior to the experiment. Cell density at 2ˆ10 5 cells/mL was employed for each comet assay experiment. All treatments resulted in a minimum of 70% viable cells, a level sufficient for avoiding cytotoxicity artifacts in the comet assay [17].
Cell Treatment
After overnight culture, TK6 cells were centrifuged and the pellets were adjusted to 2ˆ10 5 cell/mL in fresh medium. One milliliter of cell suspension was added to 1 mL volumes of complete medium contained 25, 50, 100, or 200 µg/mL of LDSK50-EA (fraction of 50% ethanol extract of peel followed by ethyl acetate (EA) fractionation) or LDSK50-H 2 O (aqueous phase of 50% ethanol extract of peel followed by EA) in a 12 well-plate and incubated at 37˝C in 5% CO 2 incubator for 24 h.
Hydrogen Peroxide Treatment
After treatment, the chemical-containing medium was removed by centrifugation at 3500 rpm for 3 min. Cells were washed twice with cold phosphate buffered saline (PBS) before being collected by centrifugation at 3500 rpm for 3 min. The cells were resuspended in 1 mL of fresh medium containing 50 µM H 2 O 2 and incubated at 4˝C for 5 min to produce oxidative DNA damage to the cells. At the end of incubation period, the H 2 O 2 treated cells were washed twice with cold PBS and resuspended in cold PBS prior to subjection to comet assay.
Comet Slide Preparation
The procedure for slide preparation performed using the standard technique was described by Singh et al. [18] with some modifications. Comet slides were prepared by pre-coating clean regular microscope slides with 0.75% (w/v) normal melting point (NMP) agarose. Slides were allowed to dry for 1-2 h at room temperature. The second or cell-containing layer was generally prepared from mixing 25 µL of treated cells with 75 µL of 0.5% (w/v) low melting point (LMP) agarose at 37˝C and the cell suspension was rapidly spread onto a pre-coated slide. The slides were gently covered with the coverslips and placed on a cold flat surface to allow the agarose to solidify for about 5 min. The coverslips were gently removed by sliding them sideways from the slides, and 80 µL of 0.5% LMP agarose was spread on glass slides, recovered with the coverslips and left on cold surface for agarose to solidify. At least two slides were made for each treatment.
Lysing, Unwinding, and Electrophoresis
The coverslips were gently removed and slides were submerged into freshly prepared lysis solution (2.5M NaCl, 100 mM EDTA, 10 mM Tris, 10% dimethyl sulfoxide (DMSO), 1% Triton X-100, pH 10; (4˝C)) for 2 h. After lysis, the slides were equilibrated in the freshly prepared electrophoresis buffer containing alkaline buffer (300 mM NaOH, 1 mM EDTA, pH > 13 at 4˝C) to allow unwinding of double-stranded DNA for approximately 20 min. The slides were then transferred into an electrophoresis unit with the same buffer and subjected to an electrophoretic field at 300 mA and 25 V at 4˝C for 20 min. The level of the electrophoresis buffer was adjusted in order to achieve 300 mA.
Neutralization and DNA Staining
Following electrophoresis, the slides were neutralized in 0.4 M Tris (pH 7.5) for 5 min three times. After removing the neutralization buffer, the slides were washed with cold water and allowed to dry at room temperature. The DNA was stained with 50 µL of 0.2% ethidium bromide.
Comet Cell Scoring
From each slide, fifty comet cells were randomly selected for comet analysis. The comet images were scored using the fluorescence microscope (at 200ˆmagnification) connected with charge coupled device (CCD) camera. The camera was linked to a personal computer containing an automatic comet image analysis software (Comet Assay III, Perceptive Instruments, Haverhill, UK). The two parameters selected as indicator of DNA damage were tail length (TL, the distance of DNA migration measured from the center of the nucleus towards the end of the tail, µm) and tail moment (TM, a measure of the distance between the center of the tail and the center of the head, multiplied by the percentage of DNA in the tail, %).
Statistical Analysis
The mean values of 50 comet cells of all experiments were analyzed. All experiments were repeated on three separate occasions. The homogeneity of variance between concentration levels was determined using Levene's test. The statistical significance of the results was determined by means of one-way analysis of variance (one-way ANOVA). When the results were significant, pair-wise comparisons of data from treated cultures with the controls were conducted using Tukey multiple comparisons. A result was considered statistically significant when the p-value ď 0.05. All analyses were performed using the SPSS statistics version 17.0 (IBM, Chicago, IL, USA).
Thin Layer Chromatography (TLC)
Stock solution containing 100 mg/mL of LDSK50-EA and 10 mg/mL of each standard was prepared by dissolving in absolute ethanol. Then, approximately 10-20 µL of LDSK50-EA stock solution and standard phytochemicals of interest (e.g., rutin, chlorogenic acid, scopoletin) were spotted on silica gel F 254 plates Alufolien (Darmstadt, Merck, Germany). The TLC plate was developed with various solvents to select the suitable system for separation and identification.
Total Phenolic Content (TPC) Determination
The total phenolic contents were determined by using Folin-Ciocalteu method [19,20]. The reaction mixture contained 100 µL of 2 mg/mL LDSK50-EA in ethanol, 500 µL of the Folin-Ciocalteu reagent, and 1 mL of 20% sodium carbonate. The final volume was made up to 10 mL with pure water. After 1 h incubation, the absorbance at 760 nm was measured and used to calculate the phenolic contents using gallic acid as standards. Total polyphenol contents were expressed as mg gallic acid equivalents (GAE) per mg sample extract (mg GAE/mg extract). Triplicate reactions were conducted. Data were reported as mean˘standard deviation (SD).
Total Flavonoid Content (TFC) Determination
The total flavonoid content was determined using the aluminum chloride colorimetric method [21] with some modification. Briefly, 1 mL of the LDSK50-EA (2 mg/mL) or rutin standard solution was mixed with 5 mL of distilled water in a test tube, followed by addition of 300 µl of a 5% (w/v) sodium nitrite solution. After 5 min, 300 µl of a 10% (w/v) aluminium chloride solution was added and the mixture was allowed to stand for a further 1 min before 2 mL of 1 M NaOH was added. The mixture was made up to 10 mL with distilled water and mixed well. The absorbance was measured immediately at 510 nm. The results of triplicate analyses were expressed as mg of rutin equivalents (RE) per mg sample extract (mg RE/mg extract).
Hydroxyl Radical Scavenging Activity
The inhibitory effect of L. domesticum fractions on 2-DR degradation was determined by measuring the competition between 2-DR and sample fractions for the OH bullet generated from the Fe 3+ /ascorbate/EDTA/H 2 O 2 system. The antioxidant activity of OH bullet scavenging was expressed as % inhibition of 2-DR degradation for the test sample of 0.5, 1.0, and 2.0 mg/mL. As shown in Table 2, the results of deoxyribose assay exhibited a wide range of OH bullet scavenging activity, demonstrated from 0.50˘0.12 to 93.44˘0.84 in % inhibition of 2-DR degradation. Results were expressed as mean˘standard deviation (SD) The antioxidant capacity of 12 L. domesticum fractions determined by PCL and deoxyribose assays was summarized in Table 3. Regarding results demonstrated in Table 3, the L. domesticum fractions that exhibited the greatest antioxidant activity by PCL and deoxyribose assays were LDSK50-EA and LDSK50-H 2 O. These two fractions were classified as active fractions and selected for further study on their DNA-protective property against H 2 O 2 .
Antioxidative DNA Damage Activity of LDSK50-EA and LDSK50-H 2 O on TK6 Cells
To investigate the antioxidative activity of LDSK50-EA and LDSK50-H 2 O in protection of DNA damage, the TK6 cells were separately pre-treated with these two fractions at 25, 50, 100, and 200 µg/mL concentrations for 24 h prior to H 2 O 2 induction. Treatments of TK6 cells with LDSK50-EA and LDSK50-H 2 O at these assigned doses for 24 h did not exhibit an inhibitory effect on cell growth rates. Results demonstrated in Table 4 indicated the percentage of TK6 living cells prior to H 2 O 2 exposure (pre-H 2 O 2 ) and after H 2 O 2 exposure (post-H 2 O 2 ) with different concentrations of LDSK50-EA and LDSK50-H 2 O fractions. In this study, any concentrations that produced cell viability of less than 70% were discarded in order to distinguish the oxidative effect from the cytotoxic effect. Results detected by comet or SCGE assay revealed that treatment of 50µM H 2 O 2 for 5 min produced DNA damage (% TM, Figure 3 Results detected by comet or SCGE assay revealed that treatment of 50µM H2O2 for 5 min produced DNA damage (% TM, Figure 3) in TK6 cells at about 10-fold greater than untreated cells. Interestingly, this DNA damage could be prevented by pre-treating the TK6 cells with LDSK50-EA at 25, 50, 100, and 200 µg/mL for 24 h. The effect was found to be in a dose-dependent manner. The highest DNA preventive effect was found at 200 µg/mL concentration. In contrast, the LDSK50-H2O fraction exhibited a slight inhibitory effect on oxidative DNA damage when tested at similar concentration ranges. The DNA protective effect against H2O2 of LDSK50-H2O was indicated by a reduction in TL ( Figure 2) and TM (= distance between the centre of gravity of the head to the centre of gravity of the tail) × (tail DNA intensity/total comet DNA intensity) (Figure 3) damage parameters in comparison to cells treated with H2O2 alone. fractionation) and LDSK50-H2O (the aqueous phase product when the L. domesticum skin was extracted with 50% aqueous ethanol and partitioned with EA) fractions followed by H2O2 damage induction by comet assay. Results were expressed as means ± standard deviation (SD) (n = 3). * Significant difference was detected from 50 µM H2O2 treatment groups at p ≤ 0.05.
Fluorescence images of comet TK6 cells evaluated for the different treatment groups were demonstrated in Figure 5. (Table 5).
Fluorescence images of comet TK6 cells evaluated for the different treatment groups were demonstrated in Figure 5. Nutrients 2015, 7 13 Table 5. DNA damage parameters including tail length (TL) and tail moment (TM) and % inhibitory effect on DNA damage of LDSK50-EA and LDSK50-H2O in TK6 cells by comet assay.
Determination of Phytochemical Components in LDSK50-EA TLC
LDSK50-EA was dissolved in absolute ethanol at a concentration of 100 mg/mL, and spotted in 10-20 µL aliquots onto silica gel F254 plates. The developing solvents were System 1:
Determination of Phytochemical Components in LDSK50-EA TLC
LDSK50-EA was dissolved in absolute ethanol at a concentration of 100 mg/mL, and spotted in 10-20 µL aliquots onto silica gel F 254 plates. The developing solvents were System 1: toluene:ethyl acetate:formic acid (5:4:1) and System 2: ethyl acetate: formic acid: acetic acid: water (137: 11:11:26). After development, the plates were dried and sprayed with PEG reagent. Bands were visualized under ultraviolet (UV) detector at 366 nm and their R f values were recorded and compared with three standard phytochemicals including scopoletin, rutin, and chlorogenic acid. TLC analysis of LDSK50-EA was shown in Figure 6. Under the detecting condition used in this study, the results clearly revealed a presence of scopoletin (R f 0.44), rutin (R f 0.34), and chlorogenic acid (R f 0.49) in LDSK50-EA. toluene:ethyl acetate:formic acid (5:4:1) and System 2: ethyl acetate: formic acid: acetic acid: water (137: 11:11:26). After development, the plates were dried and sprayed with PEG reagent. Bands were visualized under ultraviolet (UV) detector at 366 nm and their Rf values were recorded and compared with three standard phytochemicals including scopoletin, rutin, and chlorogenic acid. TLC analysis of LDSK50-EA was shown in Figure 6. Under the detecting condition used in this study, the results clearly revealed a presence of scopoletin (Rf 0.44), rutin (Rf 0.34), and chlorogenic acid (Rf 0.49) in LDSK50-EA.
TPC Amount
The content of phenolic compounds was determined following the Folin-Ciocalteu method in comparison with standard gallic acid. The results are expressed in terms of mg GAE/mg sample extract. From our study, the TPC value for LDSK50-EA was 0.198 ± 0.001 mg GAE/mg extract.
TFC Amount
The content of flavoniod compounds was determined using the aluminum chloride colorimetric method in comparison with standard rutin and the results are expressed in terms of mg rutin equivalents (RE)/mg sample extract. This study showed that the TFC value of LDSK50-EA was 0.415 ± 0.005 mg RE/mg extract.
TPC Amount
The content of phenolic compounds was determined following the Folin-Ciocalteu method in comparison with standard gallic acid. The results are expressed in terms of mg GAE/mg sample extract. From our study, the TPC value for LDSK50-EA was 0.198˘0.001 mg GAE/mg extract.
TFC Amount
The content of flavoniod compounds was determined using the aluminum chloride colorimetric method in comparison with standard rutin and the results are expressed in terms of mg rutin equivalents (RE)/mg sample extract. This study showed that the TFC value of LDSK50-EA was 0.415˘0.005 mg RE/mg extract. [22]. In such conditions, the dietary intake of antioxidant compounds is needed to assist the body in neutralizing the free radicals and to remove the harmful effects of oxidative stress. Therefore, this study is aimed at evaluating the free radical scavenging activity of long-kong L. domesticum extracts. PCL measures the potential antioxidant property of L. domesticum fractions by two different protocols, e.g., ACW and ACL, that measure the antioxidant capacity of the water-and lipid-soluble components, respectively [23,24]. The antioxidant property of compounds is quantified and expressed in equivalent concentration units of ascorbic acid and trolox equivalents for water-and lipid-soluble systems, respectively [25]. Our study found that all 12 L. domesticum fractions exhibited O 2´b ullet scavenging activity at different degrees of activity for both ACL and ACW measurement systems. Results of the ACL demonstrated that the overall antioxidant capacity of the 12 fractions ranges from 0.380 to 6.625 nmol of trolox when all samples were tested at 10 µg/mL concentration. Among these, LDSK50-EA possessed the highest antioxidant activity with an equivalent to 6.625 nmol of trolox whereas other fractions exhibited slightly different antioxidant capacities. Interestingly, the antioxidant capacity of the ACW system indicated that the 50% ethanol extract of peel (LDSK50) still had a high antioxidant capacity. A wide range of antioxidant capacities of all fractions were found from´0.065 to 98.733 nmol of ascorbic acid. The highest antioxidant activity was found in the fraction of LDSK50-H 2 O (98.733 nmol of ascorbic acid), followed by LDSK50-EA (54.660 nmol of ascorbic acid).
PCL and Deoxyribose
Regarding the PCL results, they indicated that peels of L. domesticum fruits possessed higher O 2´b ullet scavenging activity than seeds, particularly when extracted with 50% aqueous ethanol and partitioned with ethyl acetate (LDSK50-EA), which had high potential of both hydrophilic and lipophilic antioxidants. The results of ACL and ACW suggested that the O 2´b ullet scavenger in LDSK50-EA fractions was of both polar and non-polar phytochemical groups. Furthermore, the OH bullet radical scavenging activity of L. domesticum was also determined by the deoxyribose assay, another cell-free radical generating system. This assay monitored an inhibitory effect of L. domesticum fractions on 2-DR degradation by measuring the competition between 2-DR and sample fractions for the OH bullet generated from the Fe 3+ /ascorbate/EDTA/H 2 O 2 system. OH bullet radicals formed in the solution were detected by their ability to degrade 2-DR into fragments that, on heating with TBA at a low pH, formed a pink chromogen [26,27]. The absorbance read at the end of the experiment was used for the calculation of the percentage inhibition of 2-DR degradation by the test samples [28,29]. When L. domesticum fractions were added to the reaction mixture, they removed OH bullet from the sugar and prevented their degradation. The scavenging effect of L. domesticum fractions on OH bullet was determined by monitoring the reduction of deoxyribose degradation. Results were expressed as % inhibition of 2-DR degradation. In the presence of L. domesticum fractions (0.5, 1.0, and 2.0 mg/mL concentration), a wide range of OH bullet scavenging activity was found from 0.50˘0.12 to 93.44˘0.84. The LDSK50-H 2 O fraction has clearly presented to be the most effective inhibitor of the OH bullet by exhibiting 93.44%˘0.84% inhibition on 2-DR degradation. However, the wide range of % inhibition values among various L. domesticum fractions was possibly caused by their solubility character in the water, which was the solvent mainly used in the deoxyribose assay.
Antioxidative DNA Damage Activity of Two Active Fractions, LDSK50-EA and LDSK50-H 2 O, on TK6 Cells by Comet Assay
In the last two decades, the comet assay or SCGE has swiftly become one of the most popular methods in genetic toxicology. Its advantage is based upon a relatively fast, simple, and sensitive technique for the analysis of single-strand break (SSB), double-strand break (DSB), alkali-labile site (ALS) of DNA, and incomplete excision repair sites in eukaryotic individual cells [30,31]. Moreover, the comet assay has been extensively used for the investigation of the effects of antioxidants [32][33][34]. Among underlying principles, the alkaline (pH > 13) version of comet assay is superior for evaluating a broad spectrum of DNA lesions, and maximizes sensitivity for the detection of low levels of damage. Thus, it has been chosen as a useful general tool for monitoring DNA damage [31,35].
In this study, comet assay on TK6 cells was performed with the aim to evaluate the antioxidative DNA damage mechanism of LDSK50-EA against H 2 O 2 induction. H 2 O 2 is a direct non-radical reactive oxygen species. Though H 2 O 2 itself is incapable of damaging DNA directly, it is the main source of OH bullet through the Haber-Weiss and Fenton reactions [36,37]. The analysis of results obtained from the comet assay results was based on two major DNA damage parameters, e.g., the tail length (TL, in µm) and tail moment (TM, in %). However, there are comments concerning the use of these parameters since TL would reach a plateau value after migrating a certain distance but would still grow in intensity. Therefore, TM is generally considered the main representation of DNA damage [38,39].
The results of the comet assay from this study revealed that the treatment of H 2 O 2 at 50 µM for 5 min produced DNA damage (% TM) in TK6 cells at about 10-fold greater than in untreated cells. This indicated that H 2 O 2 clearly played the important role of oxidative DNA damage in TK6 cells. The geno-protective activity of LDSK50-EA and LDSK50-H 2 O in TK6 cells was found when cells were pre-treated with one of these two active fractions (25, Interestingly, the H 2 O 2 -induced DNA damage in TK6 cells was prevented by LDSK50-EA pre-treatment at 25, 50, 100, and 200 µg/mL, in a dose-dependent manner. The highest DNA preventive effect was found at 200 µg/mL concentration with % DNA damage inhibition equal to 53.47˘1.99. However, the treatment of LDSK50-EA at a dose greater than 200 µg/mL (up to 250 µg/mL) caused a very little change in the % inhibitory effect, but induced high cytotoxicity. In contrast, the LDSK50-H 2 O fraction exhibited slight inhibitory oxidative DNA damage activity when tested at similar concentrations as LDSK50-EA. Nevertheless, the pre-treatment of cells with the highest dose (more than 1000 µg/mL) of LDSK50-EA did not induce a higher % inhibition effect.
Determination of Phytochemical Components in LDSK50-EA
TLC is a separation technique that has been generally used in chemistry to separate compounds in the mixture. It is generally agreed that TLC is most effective for the low-cost analysis of samples requiring minimal sample clean-up, or where TLC allows a reduction in the number of sample preparation steps.
In this study, the TLC technique was used to detect the presence of phytochemicals in the LDSK50-EA active fraction. Following chromatogram development, the TLC plates were sprayed with various reagents, such as PEG reagent, to detect the phenolic compounds [40].
Phenolic compounds are characteristic of plants and as a group they are usually found as esters or glycosides rather than as free compounds. Current classification divides the broad category of phenolics into polyphenols and simple phenols, based solely on the number of phenol subunits present. Polyphenols possess at least two phenol subunits, including flavonoids, and those compounds with three or more phenol subunits are referred to as tannins (hydrolyzable and non-hydrolyzable) [41,42].
Under the natural product-PEG detecting condition, the results clearly revealed the presence of scopoletin (R f 0.44), rutin (R f 0.34), and chlorogenic acid (R f 0.49) in LDSK50-EA. Subsequently, the TPC of LDSK50-EA was determined using Folin-Ciocalteu reagent to quantify the amount of phenolic compounds [20]. The results are expressed in terms of mg GAE/mg sample extract. From this study, the TPC value for LDSK50-EA was 0.198˘0.001 mg GAE/mg extract. At the same time, the TFC was determined using the aluminum chloride colorimetric method in comparison with standard rutin and the results are expressed in terms of mg RE/mg sample extract [43]. The results illustrated the TFC value of LDSK50-EA to be 0.415˘0.005 mg RE/mg extract. Overall, the results of determination of the phytochemical composition in the peel extract of L. domesticum fruits (LDSK50-EA) have shown that it was the major source of phenolic and flavonoid compounds. This finding was consistent with the earlier studies [44][45][46].
The data of this study warrant the good biological activities of LDSK50-EA, including antioxidant and antioxidative DNA damage activities. Its potent biological activities may be related to the occurrence of high potential phenolic and flavonoid substances. Many studies have demonstrated the antioxidant action of phenolic compounds, acting as terminators of free radical chains and as chelators of redox-active metal ions that are capable of catalyzing lipid peroxidation [47]. Similarly, the potent radical scavenging abilities of flavonoids could contribute by inhibiting lipid peroxidation and oxidation of the low density lipoprotein (LDL) [48].
A number of in vitro experiments have found that flavonoids exert a significant antioxidative ability due to the presence of the hydroxyl groups in the B ring of the basic flavonoid structure. It donates hydrogen atoms to radical reactions. The double-bond at position 2, 3 in conjugation with the 4-oxo-group in the C ring of the flavonoid structure, and the hydroxyl groups are capable of binding transition metal ions such as iron and copper. Hence, these contribute to the chelating ability of flavonoids. In the organism, the positive effect of flavonoids is exerted via several pathways. In addition to the antioxidative effect mentioned above, flavonoids also possess other antioxidative abilities, e.g., through the stimulation of antioxidative enzymes, and have vasodilating, anti-thrombotic, anti-inflammatory, and anti-apoptic effects. Moreover, flavonoids also exhibit anti-mutagenic abilities and can inhibit the bond of cancerogenic compounds to DNA [48,49].
Conclusions
The peel of L. domesticum fruits possessed higher O 2´b ullet and OH bullet scavenging activity than the seeds, particularly when extracted with 50% aqueous ethanol and partitioned with ethyl acetate (LDSK50-EA). This fraction had high potential of both hydrophilic and lipophilic antioxidants.
Moreover, LDSK50-EA had a geno-protective effect by reduction of the DNA damage induced by H 2 O 2 radicals, proven by comet assay in TK6 cells. This study generated new and updated information on the biological activity of extracts of long-kong fruits. It may lead to a discovery of new alternative sources of natural antioxidant and anti-genotoxic substances for the prophylaxis or treatment of free radical-related diseases as well as the development of the nutraceutical product industry. | v3-fos |
2019-03-20T13:02:01.545Z | {
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} | s2 | Effects of Malathion Dust and Mexican Tea Powder (Chenopodium ambrosoides) Combinations on the Maize Weevil, Sitophilus zeamais Mostch. (Coleoptera: Curculionidae) on Maize
The experiment was conducted in the laboratory at the Bako Agricultural Research Center, from February to July 2012. Combinations of different rates of Malathion and Mexican tea powder were evaluated against the maize weevil in no choice situations. The treatments were laid out in a randomized complete block design with three replications. After three months of initial infestation the duration of their effectiveness of the treatments was evaluated by re-infesting with the same number of weevils as the previous. Analysis of variance indicated significant differences among the treatments in all of the parameters measured. The rate of mortality in all of the treatment combinations ranged from 19100%, while that of the untreated check ranged from 0-3% following 90 days after infestation. Similarly, the number of progeny weevils emerged, percentages of grain damaged and seed weight losses in all of the treatment combinations were significantly lower than that of the untreated check after 90 days of infestation. In terms of adult mortality all of the combinations were as effective as standard check following 90 days after infestation. The combination treatments showed persistent effect and gave significant control over the untreated check for up to five months. However, from economic analysis (cost of treatments) point of view the least cost was observed in treatment six (T6) and can be used as a component of maize weevil management strategy. Key: Malthion, Mexican Tea Leaf Powder and Maize Weevil.
INTRODUCTION
Maize is one of the important cereal crops in Ethiopia, and grows in all parts of the country across varied agro ecological zones. However, the yield of maize is very low due to several constraints. From a survey conducted on the productivity gains of maize hybrids Beyene et al. (1996) found that about 20% storage losses and 25% price reduction for the weevil damaged grains resulted in large income losses with value ratio not greater than one. According to Abraham (1997) and Firdisa and Abraham (1998), insect pests in the farm store caused over 16% loss on maize in the Bako area. Different management options such as physical (solar heating), inert dusts (wood ash, sand and SilicoSec), varietal tolerance, mixing with small cereal grains such as tef and millet (eragrostic tef), botanicals (plant powders and vegetable oil) and synthetic chemicals have been recommended to mitigate the problem. For instance, among the botanicals tested so far the Mexican tea (Chenopodium ambrosiodes (L.)) leaf powder was found to be the most effective and comparable to the synthetic insecticides (Pirimiphosmethyl 2% D) at 5%w/w (Mekuria 1995;Abraham 2003). According to Mekruia (1995), MTP at 2 and 4% was comparable to Actelic 2% dust in protecting maize from Sitophilus weevils. Tapondjou et al. (2002) tested powder and essential oil obtained from dry ground leaves of Chenopodium ambrosiodes at the rates ranging from 0.8 to 6.4% against six insect pests including the granary and the maize weevils on wheat and maize and reported that the highest dosage of 6.4% induced 100% mortality of both species two days after treatment, although mortality of larger grain borer was only 44%. Regardless of numerous control methods available, storage insect pests are still problematic and Ethiopian farmers relay on synthetic chemicals. Although the use of pesticides are one means of protecting stored grain, the associated side effects on the environment and human health, development of genetically resistance insect strains, erratic supply and prohibitive costs have become a major concern and thus given imputes to the search for alternative methods of pest control. A major limitation to the practical utilization of locally available plant products and vegetable oil is the high volume required to effectively disinfest grains (Don-Pedro 1989). Lale and Mustapha (1999) reported that the integrations of natural plant products from locally available plants and malathion dust for use in storage against bruchids (Callosobruchus maculates) may lead to the sustainable management of the bruchid especially in subsistence agriculture. Larry (2002) also reported the importance of integrating several tactics lies in the desire for sustainability or durability of management program. Moreover, combining two or more control options may minimize the risk and costs of chemicals, reduce resistance development against the treatments and increase effectiveness of the treatments. The objectives of this study were to assess the combined effect of a botanical, Mexican tea (Chenopodium ambrosoides) leaf powder and Malathion dust recommended for use against the maize weevil, and determine the minimum effective rate(s) of the combinations that can provide adequate protection to maize against the pest.
Preparation of experimental materials
Maize hybrid BH-540 was obtained from the Bako National Maize Research Program and multiplied in the center to obtain the F 2 generation seeds in sufficient amount for the experiment. Mexican tea leaf (Chenopodium ambrosoides) was collected from Holetta and Addis Ababa areas along roadside. The botanical was dried under shade, decorticated and ground into fine powder with mortar and pestle. Malathion 5%D was obtained from the General Chemical Trading PLC, Addis Ababa. Establishment of S. zeamais culture Sufficient number of adult S. zeamais was reared on F 2 seeds of BH540 hybrid maize variety following the procedure suggested by Strong and Subur (1968) and used by Abraham (1991). Hundred kilograms of the seed with moisture contents of 12.5-13% were disinfested by keeping in a deep freezer at -20 o c for fortnight and divided in to two kgs. Two kgs of each seed was put in a three-liter capacity plastic jar and there were arranged in to five replications. Adult weevils that were collected from the Bako Agricultural Research Center store were introduced into each replication in the ratio of 1 weevil to 2-3 gm kernels (660 weevils/ 2 kg maize) for incubation. Seven days later, the adult weevils were sieved and transferred to another disinfested and newly prepared kernels of the same variety. Finally, all of the adult weevils were removed and discarded. The grain was kept for progeny emergence. As soon as the progeny emergence began, adults were collected daily until sufficient numbers of weevils for the studies were obtained. Those emerged on the same day were transferred to the same glass jar, so that each jar had adults of identical age for the experiment.
Treatment application
The treatment details are shown in table 1. The maize kernels were cleaned and disinfested following the same procedure as above. The moisture content of the grains was adjusted by adding water as recommended by Wright et al. (1989). Two hundred grams of kernels were put in a 250 cm 3 capacity glass jar with brass screen lid that permit ventilation. Adult maize weevils were introduced in each jar at the ratio of one weevil to two to three (1:2-3) gm kernels (50 weevils/200 gm maize). Recommended rates of Malathion dust (MTD) and Mexican tea leaf powder (MTP) being 50gm/qt and 5%w/w, respectively, their various proportional combinations shown in table 1 were the treatments applied immediately after introduction of the weevil including the untreated check. The experiment was laid out in a completely randomized block design with three reapplications. Ninety days after the initial infestation the treated seeds were re-infested with the same number of weevils to evaluate the persistence of the treatments. Germination of the seeds under each treatment was tested on 100 seeds randomly picked from respective treatments and placed on moist filter paper in a petridish for five days. Temperature and relative humidity of the laboratory were recorded daily.
Data collection
Dead weevils were counted at the 2, 4, 6, 12, 18, 24 and 30 days after initial infestation (dai). During the last counting, both dead and live weevils were counted and removed and the grains were kept under the same conditions for the emergence of the F 1 generation. Up on emergence the F 1 progeny weevils were counted and removed each day until no further emergence. Data on the number of dead adult weevils, number of emerged progeny weevils, number and weight of damaged and undamaged grains were collected.
The percentages of seed weight losses were calculated using the count and weigh method (Boxall, 1986) as follows:- Where, Wu= weight of undamaged seed, Nu=Number of undamaged seed, Wd= weight of damaged seed, Nd= Number of damaged seed. Similar data were collected following the re-infestation. The proportion of germinated seeds to the total was taken as percentage seed germination.
Statistical analysis
Mortality data was corrected before analysis using Abbot's formula, %CM= (%T-%C) x 100 (100-%C) Where, CM= corrected mortality, T= mortality in treated grain and C = mortality in untreated grain (Abbott, 1925). Percentages of mortality were transformed by angular (ASIN) transformation and number of emerged progeny weevils, percentage damaged grain and grain weight losses were square root transformed. Data were subjected to statistical analyses using SAS Version 6.12 computer software. Means were separated using Student-Newman-Keuls (SNK) Range Test.
RESULTS
The rates of mortality in all of the combinations of MTD and MTP and their respective pure treatments were significantly (p<0.05) higher than that of the untreated check (Table 2). Mortality in T 5 and T 6 were significantly (p<0.05) higher than that of the other treatment combinations at two, four and six days after infestations. The rate of mortality in T 2, T 3 and T 4 at 2, 4 and 6 dai was low ranging from 19-26%, 30-36% and 42.67-50.67%, respectively. The rate of mortality reached 100% as early as 6dai in T 1, T 5 , T 6 and T 7 , while the remaining treatments except the untreated check attained this level on 12 dai (Table 2). This shows that efficacy of the combination treatments has improved with the increase in the proportion of MTD in the mixture. Significant differences were observed among the different combinations of Malathion dust and Mexican tea powder with respect to progeny emergence, grain damage, grain weight losses and seed germination (Table 3). No progeny emergence, grain damage and weight loss were observed in all the treatments except the untreated check. Seed germination was significantly (P<0.05) lower in the untreated check compared to that of the other treatments among which no difference was observed (Table 3). Significant (P<0.05) differences were observed in the different combinations of MTD and MTP with respect to the percentage of adult mortality when the treated grains were re-infested 3 months after treatment application (Fig.1). Significantly (P<0.05) lower rates of mortality were recorded in the untreated check at all dates considered. The rate of mortality increased with time after reinfestation (days after re-infestation, dari) in all of the treatments. Pure MTD and MTP treatments at recommended rates (T 1 and T 7 ) showed better persistence and resulted in complete control of the reinfested adults as early as 6 dari. The persistence of the combinations was observed to increase with the increase in the proportion of MTD in the mixture. This was indicated by the complete adult mortality obtained under T 5 and T 6 earlier at 12 dari, while similar effects were recorded six days later by T 2, T 3 and T 4 (Fig1). Similarly, the pure MTD and MTP treatments and their various combinations significantly reduced progeny emergence from the reinfestation and thereby grain damage and weight loses compared to the untreated check (Table 4). Moreover, the pure treatments and their combination did not show significant variation among themselves with respect to seed germination at about five months after initial infestation. Germination of the untreated check, however, was significantly (P<0.05) reduced. Economic analysis (costs of treatments) have done for the treatments used in the laboratory (200gm/jar) and converted to fifteen (15) quintal of maize seeds ( Figure 2). For the reason that the assumption is each individual farmer can store an average of fifteen quintals/year.
The costs of treatments are in the increasing order from T 6 , T 7 , T 5 , T 4 , T 3 and T 1 , respectively, which means the minimum cost was observed in the T 6 from combined treatments and the maximum were recorded in T 1 (pure treatment of MTP). T1 T2 T3 T4 T5 T6 T7 T8 Percent mortality Treatments 2 4 6 12 18
DISCUSSIONS AND CONCLUSION
The combination of Malathion dust and Mexican tea powder provided effective control of weevils as the synthetic insecticide for up to 5 months. This finding is in agreement with numerous works on combinations of different materials against storage pests. For example, Stather and Credland (2003) studied the combinations of diatomaceous earth with plant extracts, insecticides and entomopathogenic fungi and found that the combination of diatomaceous earth and plant extracts at reduced level or with soil bacterial metabolites, formulated as "All Natural" and "Spindeba", prevented progeny emergence of Prostephanus truncatus at 50-100 ppm. A reduced level of the combinations provided adequate protection of maize from maize weevils for more than six months. Ulrich and Mewis (2000) showed that combination of diatomaceous earth fossil shield (1 gm kg -1 ) and a commercial neem product Azal-T/S (1 gm kg -1 ) resulted in higher mortality of weevils, low progeny emergence and effective control of Tribolium castaneum and S. oryzae for more than three months. The result of this study showed that the efficacy and persistence of the combinations improved as the proportion of MTD in the mixture increases. However, the treatments with lower proportion of MTD in the combination gave complete control of the pest about a week latter compared to those with higher doses of MTD in the mixture. Fabiane and Sonia (2005) also reported that mixing diatomaceous earth with deltamethrin, the mortality of S. zeamais was affected by the dosages and by the exposure time. Dead insects were registered in the first day after application. The same study also reported that treatments using diatomaceous earth combined with low dosages of deltamethrin dust provided an efficient control of Sitophilus zeamais for more than six months. According to Barbosa et al. (1994), the efficacy of diatomaceous earth was improved when it was mixed with pirimiphos-methyl and deltamethrin against Prostephanus truncatus (Horn). Treatments using high rates of diatomaceous earth combinations with low dosages of powder deltamethrin represent an efficient control measure against Sitophilus zeamais in stored corn because insect mortality is faster than in treatments using diatomaceous earth alone and residues of active ingredients were much lower than using the insecticide in high dosage. Bridgeman (2000) also obtained satisfactory results when diatomaceous earth was combined with fumigation. According to Kassis and Sawasan (2002), methoprene would be an effective alternative to synthetic pyrethroid for control of Rhyzopertha dominica and could be used in rotation program as part of resistance management strategy. Mixtures of methoprene (as Apex 5E) in combination with pirimiphos-methyl or carbophos (Malathion) were developed for the control of the rice weevil, the grain borer (Rhyzopertha dominica), flour beetle and meal beetle (Kogteva and Zakladnolg, 2001). According to Arthur (2002), combinations of insecticidal pyrazole ethiprol, applied at the rates of 7.5, 10 parts per/million with deltamethrin, piperonyl butoxide and chlorpyrifosmethyl resulted in dead weevils after one week and no progeny weevils emerged. In addition, Obeng-Ofori (1995) reported that oils and insecticide mixtures also completely inhibited the development of the eggs, early and late larval stages of S. zeamais compared to the treatments with oil or pirimiphos-methyl alone in which only the eggs and early larval instars were killed. The current study showed that use of reduced rates of mixtures of the synthetic insecticide Malathion dust and Mexican tea leaf powder controlled the maize weevil, as effective as synthetic insecticide at recommended rate. Therefore, using combination at reduced rate of malathion helps to reduced the amount of the pesticide to be used which minimizes the costs of control and treatment residue. Moreover, the combination could be applied in rotation with MTD and MTP as an integrated management of the pest to handle development of resistance. On the other hand, economic analysis (cost of treatments) showed that the least cost was obtained in T 6 from uncombined treatments and the maximum cost was recorded in T 1 (pure MTP). Even though all combined treatments showed similar effects in controlling the maize weevils after five months of storage time, treatment six (T 6 ) is the least cost and can be used by the farmers to overcome the problem of weevils on stored maize ( Figure 2). | v3-fos |
2019-03-31T13:42:35.511Z | {
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} | s2 | Substitution of Soybean Meal with Indigofera Zollingeriana Top Leaf Meal on Egg Quality of Cortunix Cortunix Japonica
This research aimed to study the substitution of soybean meal (SBM) with Indigofera zollingeriana top leaf meal (ILM) in the diet on egg quality of Japanese quails. The experiment used a completely randomized design with five treatments and four replications (ten quails of each replication). The dietary treatment contained five combination of SBM and ILM, R0= diets contained 18% SBM without ILM, R1= diet contained 16.2% SBM and 2.66% ILM, R2= diet contained 14.4% SBM and 5.32% ILM, R3= diet contained 12.6% SBM and 7.98% ILM, R4= diet contained 9% SBM and 13.3% ILM. The results showed that the use of 13.3% ILM (R4) significantly (P<0.05) increased feed consumption, egg weight, yolk colour score, egg cholesterol, and reduced malondialdehyde level. The conclusion of this study was I. zollingeriana top leaf meal could be used as much as 13.3% in the diets. The use of I. zollingeriana top leaf meal could improve the quality of eggs physically and chemically.
INTRODUCTION
The quail egg is one of highly nutritious animal protein source that most efficient in providing animal protein sources (Handarini et al., 2008) with an average weight of 6-16 g (Sezer, 2007). A quail egg composed of 56.83% of albumin, 34.61% yolk and 8.56 % eggshell (Kumari et al., 2008). The quail egg was rich in essential amino acids and minerals such as Ca, P, and Fe (Tolik et al., 2014).
In quail formulated ration, source of feed protein is usually derived from meat meal, fish meal and soybean meal at a quite expensive price. In 2013, Indonesia has imported soybean meal up to 3.53 million tons (Ditjen PPHP, 2014). Condition seems to continue to increase in accordance with increasing livestock population. This problem might be overcome by substituting the conventional protein source e.g soybean meal with legume forages. Indigofera zollingeriana is one of the legume tree that has high production and available throughout the year. Total production of I. zollingeriana is 7-10 kg/ ha/crop. The production is based on dry matter of the I. zollingeriana top leaf meal defoliation harvested at 68 days of 1805 kg/ha/cutting with an estimated produc-tion reached 10830 tons/ha/year (Abdullah & Suharlina, 2010).
I. zollingeriana has potency as a source of poultry feed ingredient. The leaves of I. zollingeriana had a 27.68% crude protein, 0.08% tannin, 0.41% saponin, 1.16% calcium (Ca), 0.26% phosphorus (P), 3.70% crude fat (CF) and crude fiber (CF) 15.25% (Abdullah, 2010;Akbarillah et al., 2008). Vitamin content of I. zollingeriana top leaf meal (ILM) were: vitamin D as much as 42.46 mcg/100g, vitamin K 1.149 ppm, α-tocopherol 148.74 mg/kg and β-carotene 507.6 mg/kg that was not found in soybean meal (Palupi et al., 2014b). Beta carotene is a carotenoid that was also found in ILM for yolk pigmentation. Based on the potency of I. zollingeriana, this research was conducted to study the effect of substitution of soybean meal with I. zollingeriana top leaf meal in the formulated quail ration.
Experimental Design, Bird Management, and Experimental Diets
I. zollingeriana top leaf meal (ILM) was obtained from Bogor Agricultural University Plantations Education and Research in Jonggol, West Java. I. zollingeriana top leaf meal was processed into flour by sundrying for 30 min and then was ground to become ILM powder. The protein content of the ILM powder was 28.41%. The content of crude protein in I. zollingeriana was 27.68% or 28.98% (Palupi et al., 2014b).
This study used nine weeks old laying quail (Cortunix Cortunix Japonica) with an average egg production of 50%. A completely randomized design of five treatments and four replications consisted of 10 birds in each replication was used in this in study. The birds were distributed into 20 units of cages (60 x 40 x 20 cm). The dietary treatments contained five combinations of soybean meal (SBM) and ILM, R0= diets contained of 18% SBM without ILM, R1= 16.2% SBM and 2.66% ILM, R2= 14.4% SBM and 5.32% ILM, R3= 12.6% SBM and 7.98% ILM, R4= 9% SBM and 13.3% ILM. Each cage was equipped with a lighting bulb. Drinking water was supplied ad libitum and the feed was given twice, once in the morning and once in the afternoon. Prior to the experiment, the birds were acclimatized to the experimental rations for one week before and the data collection was done for 8 weeks after acclimatization. Rations were formulated according to the standard of nutrient requirements for quail (NRC, 1994), It composed of 20% crude protein and 2900 Kcal/kg of metabolizable energy. Composition and nutrient content of the treatments are showed in Table 1.
Variables Measured
Feed consumption. Feed consumption was measured every week by substracting the amount of rations given with the amount of leftover.
Physical eggs quality. The eggs physical quality analysis began in the second week of observation. Egg collection was carried out for six consecutive weeks. There eggs per experimental replication were sampled randomly once a week. Egg weight (g), eggshell weight (g), yolk weight (g), and albumen weight (g) were measured by using digital scales (Osuka-HWH®, Japan). The thickness of the shell and the height of egg white (mm) were measured by using 150 Digital Caliper of Nankai®, Japan). Haugh unit was measured according to the methods of Buckle et al. (1986), and egg yolk score was determined by comparing standards color of Egg yolk on Roche Yolk Colour Fan (Ovo Color, Aktiengesellscharft BASF, Germany).
Yolk cholesterol. The determination of yolk cholesterol levels was carried out at the end of the observation. One egg from each replication was sampled at random for analysis. Analysis of egg cholesterol was conducted in accordance with the method of Liebermann Burchard (Burke et al., 1974) and the absorbance was read using spectrophotometer reading of Hitachi U-2001, Japan at 500 nm wavelength (λ).
Yolk malondialdehyde (MDA).
Malondialdehyde was analyzed by using method of Rice-Evans et al. (1991). MDA measurement was carried out at the end of the study. About one gram of egg yolk, PBS (phosphate buffered saline) with pH 4, KCl 11.4 g/L, containing cold KCl with the ratio of 1: 2 was added and then homogenized by using centrifuge at a speed of 10000 rpm for 20 min at a temperature of 40 o C. 0.5 mL of supernatant formed was added into a mixture of concentrate HCl (2.23 mL) with 15 g TCA (thricloroacetic), 0.38 g TBA (thiobarbituric acid) and 100 mL of distilled water. Homogeneous samples were then stored in the oven with a temperature of 80 o C for one hour, centrifuged with a speed of 3000 rpm for 15 min and cooled before absorbance reading. Absorbance was read using spectrofometer Hitachi U-2001, Japan in wave (λ) of 523 nm.
Data Analysis
Data were analyzed by using the Statistical Package for Social Sciences (IBM®SPSS® version 21.0). Significantly different means level was determined by one-way analysis of variance (ANOVA). The mean value differences were considered significant at the level of P<0.05, the data were further analyzed by using Duncan multiple range test (Mattjik & Sumartajaya, 2006)
Feed Consumption and Physical Quality of the Eggs
Results of this study indicated that the use of ILM as much as 13.3% (R4) as the substitution of 50% protein soybean meal significantly (P<0.05) increased feed consumption (Table 2). This condition indicated that the diet containing ILM had good palatability. Phytochemical content in the constituent material ration affected the palatability of diets, ILM had a low phytochemical content as much as 0.29% tannin and 0.036% saponin (Palupi et al., 2014a). Saponin tolerance in poultry rations was 0.37% and 0.5% tannins according to Kumar (2005) and Leeson & Summer (2005), respectively. Feed consumption was affected by environmental temperature, also the quality and quantity of ration (Leeson & Summer, 2005).
Physical Quality of the Eggs
Substitution of soybean meal with 13.3% (R4) ILM significantly (P<0.05) increased egg weight and score of yolk colour ( Table 2). The average eggs weight in this study ranged from 8.73 to 9.32 g and the results obtained were still at the normal range of 6-16 g (Sezer, :192-197 2007). Egg size is influenced by the content of protein as amino acids. I. zollingeriana top leaf meal has amino acid score as well as soybean meal (Palupi et al., 2014b). According to Grindstaff et al. (2005), the process of egg formation is influenced by the nutrients in the diets consumed by poultry. In general, actually the addition of carotenoids in the feed increased score of yolk colour (McGraw, 2006;Amo et al., 2013;Jiang et al., 2013;Palupi et al., 2014a). In term of yolk color, substitution of soybean meal with ILM by 2.66%-13.3% in the diets improved the egg quality. The increase in score of yolk color due to the addition of ILM indicates that β-carotene contained in ILM is possibly deposited into the yolk. Deposition of beta-carotene in the yolk depended on the efficiency of transferring carotene from the intestine into the ovum (Hammershoj et al., 2010). The content of carotenoids and xanthophyll in the ration was contributed by ILM and greatly affected the colour of egg yolk (Akbarillah et al., 2010). Most of β-carotene was also an antioxidant that would be converted into an anti-free radical (Loetscher et al., 2013).
However, the addition of ILM in quail's ration did not affect eggs shape, haugh unit, eggshell or albumen (Table 2). The egg shape is the ratio between the width to the length of the whole eggs. In this study, eggs produced tended to be rounded as was indicated by an increase in egg shape value. An ideal shape value of quail's egg was 79.90 (Kumari et al., 2008). A slight increase but not statistically significant of haugh units in R4 was probably influenced by the contribution of dietary protein and amino acid. This was supported by the content of amino acid balance in ILM that was close to soybean meal amino acid balance score (Palupi et al., 2014b). Albumen height was influenced by the viscosity of albumen (Zita et al., 2012). The high value of haugh units would describe the quality of the eggs (Alkan et al., 2010). In this study the unit ranging from 91.05 to 92.39 was considerably good. According to Zita et al. (2013) haugh units was influenced by the factors of age, 9-17 weeks old quails have haugh units of eggs 90.13-90.50. The percentage of egg shell in the study showed a slight increase, compared with the control diets. The balance of calcium (Ca) and phosphorus (P) in the ration played an important role in the formation of egg shell. According to the NRC (1994) laying quail ration needed 2.5% Ca and 0.55% P. The balance of the two minerals was very important because Ca and P also would affect egg production (Amoah et al., 2012).
Chemical Quality of the Eggs
Malondialdehyde (MDA) is one indicator to see antioxidant activity (Chen et al., 2009). Increased free radicals would stimulate the process of lipid peroxidation and oxidative stress, which could be measured by analyzing the content of MDA (Valko et al., 2006). Substitution of soybean meal with 5.32%-13.3% (R1-R4) ILM in quail diets significantly decreased (P<0.05) the MDA and increased yolk cholesterol (Table 3). The lower content of MDA in egg yolk in R4 was probably due to the role of antioxidants in the ILM which reduced lipid peroxidation. Antioxidants were actually stable which could reduce the levels of MDA in the yolk as well as in serum and liver (Sahin et al., 2008;Ni et al., 2012;Kurtoglu et al., 2008). Beta carotene in ILM acted as an antioxidant so did the isoflavone. The process of lipid peroxidation was triggered by the separation of hydrogen. The presence antioxidants donates a hydrogen group to ILM substitution (Wang et al., 2005).
Quail's eggs had a high concentration of polyunsaturated fatty acids with cholesterol content of only 7.78 mg/g (Mennicken et al., 2005;Kazmierska et al., 2005). Increased yolk cholesterol with the increase ILM substitution was influenced by the role of β-carotene as an antioxidant for anti-free radical as to minimize lipid peroxidation process without interfering the formation of cholesterol. Giving antioxidants and β-carotene could reduce the levels of SGOT (Serum transaminases Glutamix Oxaloatic) and SGPT (Serum Glutamic Pyruvic Transaminase), showing the occurrence of lipid peroxidation (Jaya, 2013). Βeta carotene supplementation in the diet would affect the activation of lipid peroxidation and antioxidant enzyme that protected cholesterol from damage (Shih et al., 2008). This condition would benefit the quail, because cholesterol is needed in the process of embryos development to produce DOQ (day old quail). Egg yolk is rich in lipids, vitamins A, E and β-carotene which will be transferred to a membrane bag by the phagocytosis to form lipoprotein particles that are released into the circulation of embryos that supports the growth and development of the embryo (McGraw, 2006).
CONCLUSION
Indigofera zollingeriana top leaf meal (ILM) could be used in the diet of laying quail (Cortunix Cortunix Japonica) up to 13.3% as substitution of 50% protein in soybean meal. Supplementation of ILM increased feed consumption, egg weight, egg yolk colour, egg yolk cholesterol and reduced levels of malondialdehyde in the quail's eggs. | v3-fos |
2016-05-04T20:20:58.661Z | {
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} | s2 | Seed shattering: from models to crops
Seed shattering (or pod dehiscence, or fruit shedding) is essential for the propagation of their offspring in wild plants but is a major cause of yield loss in crops. In the dicot model species, Arabidopsis thaliana, pod dehiscence necessitates a development of the abscission zones along the pod valve margins. In monocots, such as cereals, an abscission layer in the pedicle is required for the seed shattering process. In the past decade, great advances have been made in characterizing the genetic contributors that are involved in the complex regulatory network in the establishment of abscission cell identity. We summarize the recent burgeoning progress in the field of genetic regulation of pod dehiscence and fruit shedding, focusing mainly on the model species A. thaliana with its close relatives and the fleshy fruit species tomato, as well as the genetic basis responsible for the parallel loss of seed shattering in domesticated crops. This review shows how these individual genes are co-opted in the developmental process of the tissues that guarantee seed shattering. Research into the genetic mechanism underlying seed shattering provides a premier prerequisite for the future breeding program for harvest in crops.
Introduction
The emergence of fruit represents a major evolutionary innovation in angiosperms, and the evolutionary success of wild plant species depends essentially on their capacity to scatter their offspring (Nathan and Muller-Landau, 2000). The seed shattering or fruit shedding is usually used to describe the detachment of the fruit from the pedicel in cereals and fleshy fruit species, respectively. While in dry dehiscent fruit taxa, such as Legumes and crucifers, pod dehiscence refers to the shattering of the pod shell, which enable the successful shattering of seeds. Although these processes happen in non-homologous tissues, the abscission layer is an essential tissue both for the shattering or shedding process (Estornell et al., 2013).
The fruit morphology and associated dispersal strategies are of significant adaptive importance, which are under strong selective pressures. While in seed crops, premature seed shattering is an undesired character and has been selected against during the domestication process of distinct crops. Most of our knowledge on the genetic regulation of pod dehiscence has been obtained in the model organism Arabidopsis thaliana, a Brassicaceae species with a characteristic dry dehiscent fruit that shatters the seeds through the dehiscence zones (DZs) along the silique after maturity (Ferrándiz et al., 1999). The differentiation of the DZ is under the control of intricate regulatory networks involving multiple transcription factors. Recent investigations in pod dehiscence regulation have uncovered another layer of the regulatory network that include phytohormones in specifying the DZs (Sorefan et al., 2009;Arnaud et al., 2010;Marsch-Martinez et al., 2012).
Evidence from comparative studies in the taxa related to Arabidopsis suggests modest genetic changes in the key regulatory component could be responsible for the phenotypic changes that are associated with fruit function and novel dispersal strategies (Avino et al., 2012;Fourquin et al., 2013;Mühlhausen et al., 2013). Studies on the fruit shedding process in tomato, a model for fleshy fruits, have provided new insights into the regulatory networks responsible for the control of cell separation (Mao et al., 2000;Nakano et al., 2012;Liu et al., 2014). These findings reveal that there are strong similarities between dry and fleshy fruits in the molecular networks governing fruit dehiscence and maturation. Meanwhile, our understanding about the genes involved in the loss of seed shattering in crops has increased dramatically, offering us a great opportunity to examine the details regarding the molecular basis of such convergent morphological adaptation in the face of artificial selection in a wide array of species.
In this review, we try to incorporate the recent insights into the molecular and hormonal regulation of tissues that are necessary for seed shattering and fruit shedding in model species and discuss how the genetic modification of the regulatory genes is co-opted in the evolutionary process to generate altered fruit morphologies with novel dispersal strategies. We also review the recent findings in the genetic control of nonshattering (indehiscent) fruit in crop species and highlight the prevalence of parallel molecular evolution in plant domestication. A comprehensive understanding of the factors influencing the seed shattering process is particularly important, as it might have great potential in the facilitation of future crop domestication and breeding procedures to prevent unwanted seed loss.
Genetics of Pod Dehiscence in Arabidopsis thaliana and its Relatives
The model species A. thaliana belongs to the Brassicaceae family, which develops a typical dry dehiscent fruit called the silique. Essentially, the silique develops from the gynoecium composed of two congenitally fused carpels (Ferrándiz et al., 1999). The developmental program of the fruit initiates from fertilization of the ovules. In the transverse view of the mature fruit, the out layer consists of three principal tissues, the valves, the replum, and the valve margins. The valve margins are sandwiched between the valve and replum and are further differentiated into lignified layer (LL) and separation layer (SL), which together form the DZ along the silique (Figures 1A-C; Ferrándiz et al., 1999). The LL cells are connected with the endocarp b (enb) layer of the valves, which is also rigidly lignified. The SL is composed of several isodiametric cells, and will be degraded autonomously before pod dehiscence (Seymour et al., 2013). When the silique becomes dry with loss of water, these highly organized structures produce a spring-like tension within the pod valves that force the silique to shatter from the weakest position, the SL (Figures 1C,D). Therefore, the silique dehiscence is a dynamic process that depends on the proper positioning and formation of the DZs along the silique (Ferrándiz, 2002).
The Genetics of DZ Development and Pod Dehiscence in Arabidopsis
The spatial specification of DZ, valve cells and replum is under the control of a complex genetic regulatory network and dynamic hormonal interactions with several transcription factors involved (Figure 2; Lewis et al., 2006;Østergaard, 2009;Ferrándiz and Fourquin, 2014). This regulatory network has recently been extended to include genes that are involved in the leaf development and the establishment of dorsoventral axes of the lateral organs (e.g., FILAMENTOUS FLOWER, YABBY3, ASYMMETRIC LEAVES1/2) as well as the meristematic potential maintenance (BREVIPEDICELLUS) (Hay et al., 2006;Alonso-Cantabrana et al., 2007). This review mainly focuses on the core regulatory genes specific to silique dehiscence, thus those remotely related genes are not included in this article. A thorough description of all these interactions can be found elsewhere in the literatures (Dinneny et al., 2005;Lewis et al., 2006;Østergaard, 2009).
Two MADS-box transcription factor encoding genes SHATTERPROOF1 (SHP1) and SHP2 act redundantly to control the pod dehiscence as neither single mutant displays a detectable phenotype from wild type . The shp1/2 double mutant produces indehiscent fruit devoid of cell differentiation in the DZ . Expressions of SHP1/2 are specifically localized in the DZs and developing seeds during late fruit development Colombo et al., 2009). Further genetic analysis shows that SHP1/2 act at the top of the genetic cascade that direct the development of DZ for pod dehiscence (Figure 2; see below ;Ferrándiz, 2002;Lewis et al., 2006).
Acting down-stream of and in parallel with SHP1/2 are two b-HLH transcription factors, INDEHISCENT (IND) and ALCATRAZ (ALC; Figure 2). IND directs the differentiation of DZ into LLs and SLs. Similar to shp1/2 double mutant, ind mutation fully abolishes the specification of DZs and results in indehiscent fruits (Liljegren et al., , 2004. By contrast, ALC specifically establishes the cell identity in the separation layer and mutation in ALC leads to partially indehiscent fruits (Rajani and Sundaresan, 2001). Both IND and ALC are specifically expressed in the DZ during late fruit development. Evidence indicates that IND acts downstream of SHP1/2 to control pod dehiscence, as illustrated by the observation that IND expression is completely lost in the shp1/2 mutant (Liljegren et al., , 2004Rajani and Sundaresan, 2001). The valve identity is regulated by the activity of the FRUITFULL (FUL) MADS-box gene (Gu et al., 1998;Ferrándiz et al., 2000). Expression of FUL initiates in the carpel primordia very early in flower development, and soon after becomes restricted in the gynoecium and further in the carpel valves (Gu et al., 1998). In the ful mutant, the valves fail to elongate and are cracked by the inner developing seeds (Gu et al., 1998). FUL negatively regulates SHP1/2 expression thus delimitates the boundary of SHP1/2 expression in the valves (Ferrándiz et al., 2000). When FUL is mutated, SHP1/2 and IND are ectopically expressed in the valves promoting the mesocarp cells to adopt lignified valve margin cell identity instead of normal parenchymatous cell identity (Gu et al., 1998;Ferrándiz et al., 2000). The ful mutant phenotype can be partially rescued by combining the ful mutant with mutations in the SHP1/2 genes, and largely rescued in the ind mutant background, suggesting that IND has a more specialized role in DZ cell specification than SHP1/2. On the other hand, fruits of 35S::FUL transgenetic lines are indehiscent as the result of complete conversion of DZ cells into valve cells (Ferrándiz et al., 2000). Interestingly, the activity of SHP1/2, IND, ALC, and FUL is all necessary for the lignification of cells in the enb layer (Ferrándiz et al., 2000;Liljegren et al., 2004).
In addition to FUL, the DZ-specific expression of SHP1/2 and IND is also restricted by the REPLUMLESS (RPL), which encodes a homeodomain transcription factor and contributes to the specification of replum identity (Roeder et al., 2003). Expression of SHP1/2 and IND is expanded into the replums in the rpl mutant genetic background (Figure 2; Roeder et al., 2003). Fruits from the rpl mutant are partially indehiscent due to loss of replum identity with ectopic cell lignification, in which the replumlignified cells are coalesced into a single stripe that is connected with the lignified valve margin cells (Roeder et al., 2003). The loss of replum identity in rpl mutant can be largely rescued by further removal of SHP1/2 activity, suggesting that the ectopic expression of SHP1/2 is responsible for the rpl mutant phenotype (Roeder et al., 2003). Thus, both RPL and FUL are necessary for the proper development of a functional DZ by restricting the expression of SHP1/2 in the valve margins. Recently, it was demonstrated that the rpl mutant phenotype can be rescued largely by ap2 mutation (Ripoll et al., 2011). AP2, well known for its role in floral organ identity determination, encodes a transcription factor belonging to AP2/ERF family. AP2 acts to prevent replum and valve margin overgrowth by negatively regulating replum and valve margin identity gene expression, respectively (Ripoll et al., 2011).
After the differentiation instruction of specific cell identity is established, the next step should be the final differentiation of distinct cell types. NAC SECONDARY WALL THICKENING PROMOTING FACOTR1 (NST1) and SECONDARY WALL-ASSOCIATED NAC DOMAIN PROTEIN1 (SDN1, also called NST3) are the master transcriptional switches controlling secondary cell wall thickening (Zhong et al., 2010). In the fruits, NST1 and SND1 are expressed in the valve enb layer, while only NST1 is specifically expressed in the developing LL cells of DZs (Mitsuda and Ohme-Takagi, 2008). In the nst1 null mutant, the fruits are indehiscent due to the loss of lignification of valve margin cells, and all the lignified cells except the vessel cells in the replums are lost in the nst1 snd1 double mutant (Mitsuda and Ohme-Takagi, 2008). Expression of SHP1/2 and IND appears to be normal in the nst1 snd1 double mutant, suggesting that NST1 and SND1 act downstream of these transcription factors. Mitsuda and Ohme-Takagi (2008) further show that ectopic cell wall thickening in the valve cells in the ful mutant can be eliminated by mutation of NST1. Taken together, these data suggest SHP1/2 regulate the lignification of valve margin cells by the path of NST1 (Figure 2).
Intriguingly, NST1 and SND1 are predominantly expressed in the interfascicular fibers and xylems in the stems where SHP1/2 are not expressed and are responsible for the secondary cell wall thickening in these cells (Zhong et al., 2006;Mitsuda et al., 2007). Furthermore, NST1 and SND1 are also identified as master regulators for xylem fiber differentiation (Zhong et al., 2006;Mitsuda et al., 2007;Oda and Fukuda, 2012). It is apparent that the developmental program of the stem interfascicular fibers and lignified valve margin cells are distinct. It seems that the valve margin specific expression of NST1 represents an evolutionary innovation in the cis-regulatory elements that correlate with the establishment of lignified valve margin cells. How the NST1 gene is co-opted in the SHP1/2-regulated network that direct the lignified valve margin cell development is an interesting question and worthy to be clarified in the future.
Prior to pod dehiscence, the cells in the separation layer secret enzymes to degrade the cell wall matrix, which bring about a reduction in cell-to-cell adhesion, thus facilitate the fruit to commit to dehiscence (Roberts et al., 2002). ARABIDOPSIS DEHISCENCE ZONE POLYGALACTURONASE1 (ADPG1) and ADPG2 encode plant specific endo-polygalacturonases (PGs) and are expressed in the separation layer of flower organs and fruit DZs (Ogawa et al., 2009). ADPG1 and ADPG2 are essential for enzymatic breakdown of cell middle lamella and are necessary for silique dehiscence, as genetic lesion in either genes leads to indehiscent fruits (Ogawa et al., 2009). IND is required for normal expression of ADPG1 in the silique DZs (Ogawa et al., 2009). Thus, it seems that ADPGs are the final regulators of pod dehiscence in the separation layers (Figure 2).
Hormonal Regulation of DZ Specification
Hormonal homeostasis and interactions are recently found as immediate downstream outputs from the core genetic network. Expression of IND is responsible for the formation of local auxin minimum in the valve margin by coordinating auxin efflux in the separation layer cells (Sorefan et al., 2009). Further analysis shows that another b-HLH transcription factor SPATULA (SPT), which is required for the carpel fusion early in female reproductive organ development, can interact with IND physically (Girin et al., 2011). The interaction of IND and SPT promotes the localization of PIN3 in the plasma membrane of valve margin cells to create the auxin depletion in the valve margin thus offering a proper hormonal environment for specific cell differentiation (Sorefan et al., 2009;Girin et al., 2011). Auxins and cytokinins often play an antagonistic role in plant development (Bishopp et al., 2011). Consistent with this scenario, the cytokinin signaling pathway is recently found to be active in the valve margin, and such a signaling pathway is disrupted in shp1/2 and ind mutant. However, local application of cytokinin in developing fruits can restore valve margin formation and further increases dehiscence in shp1/2 and ind mutants, suggesting that cytokinins play a crucial role in valve margin differentiation (Marsch-Martinez et al., 2012). In addition to auxins and cytokinins, gibberellins (GAs) have also recently been implicated as having roles in the establishment of separation layer cell identity (Arnaud et al., 2010). According to the "relief of restraint" model, GA-mediated degradation of DELLA protein is central to GA signaling and also required to activate downstream genes (Harberd, 2003;Sun and Gubler, 2004). GA3ox1, which catalyzes the final step in the synthesis of bioactive GAs, is demonstrated as the direct target of IND. ALC physically interacts with DELLA repressors, and the local production of GAs destabilize the DELLA protein and relieve the ALC to exert its function in SL cell specification (Arnaud et al., 2010). Taken together, these findings indicate involvement of several phytohormones in the specification of DZs and suggest that a precise balance between their biosynthesis and response is of fundamental importance. Notwithstanding with the investigations where the role of hormones in DZ development has been extensively explored, very few reports on how these hormonal signals are coordinated in the DZ are available. Therefore, one of the main challenges for future work remains to decipher the complete picture of the molecular mechanisms and interactions of plant hormones underlying DZ differentiation in dry fruits.
Evolutionary Origin of Novel Fruit Characters by Modification of DZ Specification Genes
The family Brassicaceae contains over 300 genera, including a number of important vegetables and crops, such as broccoli and cauliflower (Brassica oleracea), oilseed rape (Brassica napus), and common radish (Raphanus sativus). As noted above, the basic fruit type in Brassicaceae is dry dehiscent silique, while there still exist bountiful morphological fruit variations within this family.
Heteroarthrocarpic fruit is a two-segmented fruit with an indehiscent distal part containing rudimentary ovules and a dehiscent proximal part consisting of normal ovules that develop into seeds. Phylogenetic reconstruction combined with morphological analysis shows that heteroarthrocarpic fruit has evolved multiple times within the tribe Brassiceae with nearly half of genera being heteroarthrocarpic (Hall et al., 2011). Erucaria erucarioides and Cakile lanceolata produce heteroarthrocarpic fruit with different dehiscent patterns. Avino et al. (2012) isolated the homologs of SHP1/2, IND, ALC, FUL, and RPL from both species and conducted comparative expression examinations. They found that the expression patterns of these genes in the fruit dehiscent segments are largely conserved between these species and in Arabidopsis, especially the genes that are involved in the establishment of valve margin identities (Avino et al., 2012). On the other hand, the fruit indehiscent segment is correlated with loss of gene expression of the entire valve margin genetic pathway. These expression data support the hypothesis that heteroarthrocarpy is evolved from dehiscent fruit via repositioning the valve margins (Avino et al., 2012).
Loss of fruit dehiscence has independently evolved in several genera across Brassicaceae (Appel and Al-Shehbaz, 2003). In the genus Lepidium, two phylogenetically related species, L. campestre and L. appellianum, bear dehiscent and indehiscent siliques, respectively (Mummenhoff et al., 2009). Mühlhausen et al. (2013) conducted a comparative analysis of the expression patterns of SHP1/2, IND, ALC, FUL, and RPL orthologs in these two species. They found that the expression patterns of these orthologous genes are highly conserved between L. campestre (dehiscent fruit) and A. thaliana (Mühlhausen et al., 2013). Transgenic plants of L. campestr with down-regulation of SHP1/2, IND, ALC, FUL, and RPL are found to be defective in fruit dehiscence; further anatomical examinations reveal that the fruit structure of these transgenic plants are similar to that of respective Arabidopsis mutant (Lenser and Theißen, 2013a). By contrast, the expression of these respective orthologs is completely abolished in the corresponding tissues of indehiscent L. appellianum fruit (Mühlhausen et al., 2013). These studies support the notion that the dehiscent network is basically conserved in Brassicaceae and further suggest that genetic changes in the upstream components of SHP-regulated pathway are responsible for the evolutionary origin of novel fruit characters (Mühlhausen et al., 2013). This idea is further supported from studies of Brassica species. B. rapa and B. oleracea produce dehiscent fruits and share similar anatomical structure with A. thaliana fruits. Functional analysis shows that BraA.IND.a and BolC.IND.a are orthologous to IND since mutation or down-regulation of either genes results in valve margin defect . Sequence alignment of the promoters of IND-like genes of A. thaliana and B. rapa reveals a 400-bp conserved sequence, which direct valve margin-specific expression of IND in A. thaliana. Further analysis shows that the specific activity of the 400-bp promoter sequence depends on the SHP1/2 and FUL ). An independent study in Brassica species reveals that loss of RPL gene expression is responsible for the evolutionary origin of the typical narrow replum in this genus. It is found that a point mutation in the promoter region significantly reduces RPL expression in the fruits and is associated with the narrow replum character (Arnaud et al., 2011). More recently, an independent research found that the genomic regions that encompass the key regulators of DZ specifying genes are associated with the natural variations in the pod dehiscence character in Brassica napus (Raman et al., 2014).
In Medicago, a genus of the legume family with a close phylogenetic relationship with Brassicaceae, some species develop coiled pods representing a novel strategy of collective seed dispersal. It is observed that the coiled pod morphology is tightly correlative with increased valve margin lignification, which is associated with a change in the protein sequence of SHP orthologs (Fourquin et al., 2013). Further analysis shows that the protein sequence modification alters the properties of the protein by affecting the affinity for other protein partners involved in a high-order complex (Fourquin et al., 2013). It is possible that SHP-directed secondary cell wall thickening is an evolutionary conserved module in Rosids (Ferrándiz and Fourquin, 2014). Nonetheless, it remains to determine the exact cellular and genetic basis that contributes to this indehiscent fruit morphology.
On the whole, the evidence outlined above points to a conserved genetic network controlling the pod dehiscence process and modifications of gene expression and protein properties in the core genetic components are associated with the origin of novel fruit characters.
Genetics of Fruit Ripening in Tomato
Like pod dehiscence in dry fruit species, the emergence of fleshy fruit represents another evolutionary innovation in which they attract animals for seed dispersal (Dilcher, 2000). Fleshy fruit can be divided into two classes, non-climacteric (e.g., strawberry and grape) and climacteric fruits (e.g., tomato and apple). In the fleshy model plant tomato (Solanum lycopersicum), the initiation of fruit ripening process is signified by a concomitant increase in respiration and biosynthesis of ethylene (Giovannoni, 2004;Seymour et al., 2008). In recent years, great advances have been made in dissecting the transcriptional regulation of ripening by the identification of genes with mutations that abolish the normal ripening process. Evidence shows that fruit ripening is a wellorchestrated process with the initiation of multiple genetic and biochemical pathways, which finally brings about the remarkable changes to the metabolic and physiological traits in a ripening fruit. The genetic regulation of the fruit ripening process has recently been thoroughly reviewed by several authors (Seymour et al., 2013;Ferrándiz and Fourquin, 2014). Here we only briefly introduce the genetic mechanisms underlying the fruit ripening process.
The SEPALLATA4 clade of MADS-box gene RIPENING INHIBITOR (RIN) gene is demonstrated to act as the master switch of the fruit ripening process by directly activating the expression of ACC Synthase 2 (ACS2), which is involved in the switch to system-2 ethylene production (Vrebalov et al., 2002;Martel et al., 2011). The spontaneous epigenetic modification of the promoter sequence of the SQUAMOSA Promoter Binding (SPB) protein encoded by the COLORLESS NON-RIPENING (CNR) gene decreases the expression level of CNR in the developing fruits, which effectively blocks the ripening process and results in fruits that fail to produce elevated ethylene at the onset of fruit ripening and an insensitivity to ethylene applications (Manning et al., 2006). Similar to the rin mutant, genetic lesions in the NAC transcription factor NON-RIPENING (NOR) gene lead to a non-ripening phenotype with a green fruit (Tigchelaar et al., 1973).
TOMATO AGAMOUS LIKE1 (TAGL1), which encodes the orthologous gene of AtSHP1/2, is a positive regulator of fruit ripening (Itkin et al., 2009;Vrebalov et al., 2009). TAGL1 interacts with RIN to regulate the ethylene production by directly activating ACS2 expression (Leseberg et al., 2008;Vrebalov et al., 2009). Overexpression of TAGL1 in Arabidopsis results in an array of phenotypes that are similar to SHP1/2 over-expressors, which points to a basically conserved role of SHP-like genes in organ identity determination (Pinyopich et al., 2003). However, the expression of TAGL1 in shp1/2 mutant genetic background only partially rescues the indehiscent fruit phenotype, indicating that TAGL1 has evolved a novel function in fruit development compared with the Arabidopsis counterparts. Other positive regulators of fruit ripening include two closely related FUL-like homologs FUL1 (also known as TDR4) and FUL2 (also known as MBP7), which interact with RIN protein to regulate fruit ripening by coordinating the expression of genes involved in cell wall modification, cuticle production, volatile production, and glutamate accumulation (Bemer et al., 2012;Shima et al., 2013). Interestingly, the expression of TAGL1 is found to be upregulated in the pericarp of FUL1/2 RNAi fruits, indicating a negative feedback loop from FUL1/2 to TAGL1 (Bemer et al., 2012). The negative regulation of FUL to SHP is also evident in the valve of Arabidopsis (Ferrándiz et al., 2000). These data point to a conservation of the regulatory network in the FUL and SHP between Arabidopsis and tomato. On the other hand, the homologs of the AP2-ERF protein SlAP2a are demonstrated to act as negative regulators of ripening by inhibiting ethylene biosynthesis and signaling pathways (Chung et al., 2010;Karlova et al., 2011). SlAP2a seems likely to act downstream of CNR as CNR protein can bind to the promoter of SlAP2a in vitro (Karlova et al., 2011).
As outlined above, it appears that genes (including AP2, SHP, and FUL) in fruit development are functionally conserved between Arabidopsis and tomato. In the case of the SHP-FUL module, it is plausible to assume that the genetic interaction between SHP and FUL in fruit development might have been established before the split of rosids and asterids. In the fleshy tomato, SHP and FUL are further co-opted in the RIN-regulated ethylene pathway to regulate fruit ripening subsequent upon sub-functionalization and neo-functionalization after lineagespecific gene duplication. The broad conservation of the SHP-FUL functional module in dry and fleshy fruits further suggest that fruit dehiscence and ripening may share a common origin and are parallel evolutionary innovations by recruiting a deeply conserved regulatory network (Ferrándiz and Fourquin, 2014).
Genetic Control of Fruit Shedding in Tomato
In tomato (Lycopersicon esculentum), fruit shedding requires the proper development of the abscission zone (AZ) in the knuckle region of the pedicle (see reviews in Roberts et al., 2002;Estornell et al., 2013). The AZ is composed of several layers of smaller and densely cytoplasmic cells (Figure 3, lower panel). Cells in the AZ appear to be predetermined very early in development and are arrested in the following differentiation process (Roberts et al., 2002;Nocker, 2009). Several genes are found to be associated with the initial establishment and further differentiation of the AZ (Figure 3; also see reviews in Roberts et al., 2002). JOINTLESS (J), which encodes a SVP/AGL24 clade MADS-box gene, is required for the proper AZ development, as j mutant fails to develop the AZ in the pedicle and fruit shedding does not occur normally (Mao et al., 2000). MACROCALYX (MC) encodes another MADS-box protein that falls into the AP1/FUL clade. Similar to the j mutant, the AZ is completely lost in the pedicle of MC RNAi plants (Nakano et al., 2012). Further analysis shows that the MC protein interacts physically with J to form a heterodimer with DNA-binding activity. It seems that J and MC regulate a common set of target genes, including transcription factors regulating meristem maintenance. These data further suggest the AZ cells possess meristematic potential (Roberts et al., 2002;Nakano et al., 2012). The J-MC protein complex has recently been extended to incorporate the SEP-like MADS-box protein SLMBP21. The SLMBP21 protein interacts with J and MC to form a higher-order protein complex to confer transactivation activity . Knockdown of SLMBP21 completely abolishes AZ development, while overexpression of SLMBP21 results in ectopic AZ-like cells at the proximal region of the pedicle . Because J, MC, and SLMBP21 regulate a common set of target genes, it is possible that the obligate J-MC-SLMBP21 complex works synergistically to direct the expression of AZ development genes. In line with this notion, the expression of LATERAL SUPPRESSOR (LS), which encodes a VHID protein of the GARS transcription factor family, is found to be down-regulated in j, mc, and SLMBP21 RNAi pedicles (Nakano et al., 2012;Liu et al., 2014). The LS was initially identified as a positive regulator of axillary meristem maintenance and the ls mutant also brings about impaired AZ development (Schumacher et al., 1999). It will be interesting to address how LS is co-opted in AZ cell meristematic potential maintenance under the control of J-MC-SLMBP21 complexdirected pathway.
Convergent Evolution of the Non-Shattering Character in Domesticated Crops
From the evolutionary perspective, natural selection enables the wild plant species to possess elaborate mechanisms to disperse their seeds and fruits. While from the agronomic perspective, the natural seed dispersal is an undesired trait in crops as it leads to severe seed loss in harvest. As a result, natural seed dispersal is severely selected against by ancient humans to assure efficient cultivation during the domestication process (Harlan, 1992;Purugganan and Fuller, 2009;Lenser and Theißen, 2013b). The non-shattering or indehiscent character has been regarded as the milestone of domestication in the seed crops (such as cereals and legumes) as it renders the domesticated species more dependent on human activity for propagation and further facilitates the fixation of other domestication characters (Doebley et al., 2006;Purugganan and Fuller, 2009). In the seed crops, the reduction of seed shattering capability is evolved independently and is a convergent morphological adaptation to artificial selection (Doebley et al., 2006;Purugganan and Fuller, 2009;Lenser and Theißen, 2013b;Olsen and Wendel, 2013). In Section "Parallel Evolution of the Non-Shattering Trait in Cereal Crops, " we will review the cellular and genetic mechanisms underlying the morphological transition from shattering to nonshattering in domesticated crops (Figure 3, lower panel).
Parallel Evolution of the Non-Shattering Trait in Cereal Crops
In cereal crops (such as rice and sorghum), the fruit dehiscence or seed shattering is implemented by an abscission layer in the joint between lemma and pedicel (Figure 3, lower panel). In rice (Oryza sativa), several transcription factor coding genes have been found to be associated with the reduction of seed shattering (Figure 3). Shattering4 (Sh4) encodes a transcription factor with homology to Myb3 and is necessary for the development of a functional abscission layer in the pedicel (Li et al., 2006). A single amino acid change in the putative DNA biding domain is closely associated with the reduction in seed shattering in domesticated rice. In addition, the expression of the domesticated allele is also remarkably decreased compared with the wild allele (Li et al., 2006). Thus, it appears that the combination of coding and regulatory change of Sh4 impairs the developmental program of the abscission layer, thus weakens the shattering phenotype (Li et al., 2006). qSH1 is a major QTL on chromosome 1 controlling seed shattering in rice. The underlying gene, qSH1, encodes a BEL1-type homeobox transcription factor that is highly homologous to AtRPL (Konishi et al., 2006). qSH1 is required for formation of the abscission layer in the pedicel. A single nucleotide polymorphism (SNP) in the 5 ′ -regulatory region completely eliminates qSH1 expression in the provisional abscission layer early in the development process and results in non-shattering trait in domesticated rice (Konishi et al., 2006). Notably, the regulatory SNP in the promoter sequence of RPL homologs is also responsible for the difference in seed dispersal structures produced by natural selection in Brassica species with reduced replum development (Arnaud et al., 2011). These examples demonstrate a remarkable convergent mechanism in which the same regulatory SNP can explain the developmental variations in seed dispersal structures relevant to both domestication and natural selection in a distantly related species (Arnaud et al., 2011;Gasser and Simon, 2011).
SH5 is another BEL1-type homeobox gene with high homology to qSH1. SH5 is highly expressed in the abscission layer (Yoon et al., 2014). Silencing of SH5 suppresses the development of the abscission layer and inhibits seed shattering. Overexpression of SH5 gives rise to an increase in seed shattering, a consequence of decreased lignin levels in the pedicel (Yoon et al., 2014). The expression of Sh4 is found to be significantly up-regulated in the SH5-overexpressor, suggesting SH5 positively regulates Sh4 to direct abscission layer development (Yoon et al., 2014). Recently, the regulatory pathway of the abscission layer development was extended to include an AP2-transcription factor coding gene, SHATTERING ABORTION1 (SHAT1, Zhou et al., 2012). SHAT1 is required for seed shattering through specifying the abscission layer. The expression of SHAT1 in the abscission layer is positively regulated by Sh4. qSH1 expression is completely lost in the abscission layer in either shat1 and sh4 mutant background, suggesting qSH1 functions downstream of SHAT1 and Sh4 in the establishment of the abscission layer (Zhou et al., 2012). Interestingly, qSH1 is also required for the expression of SHAT1 and Sh4 in the abscission layer. Therefore, qSH1 is probably involved in a positive feedback loop of SHAT1 and Sh4 by maintaining the expression of SHAT1 and Sh4 in the abscission layer (Zhou et al., 2012). Although SH5 and SHAT1 play roles in the differentiation of abscission layer, it remains to be determined whether these two genes are domestication genes targeted by artificial selection.
Similar to rice, the reducing of seed shattering in domesticated sorghum (Sorghum bicolor) results from the loss of abscission layer in the joint connecting the seed hull and pedicel. Seed shattering in sorghum is controlled by a single gene, Shattering1 (Sh1), which encodes a YABBY transcription factor. The non-shattering character can be accounted for by one of three distinct loss-offunction mutations that are independently selected upon during the sorghum domestication process (Lin et al., 2012). Notably, the Sh1 orthologs in rice and maize (Zea mays) harbor mutations that are possibly associated with the shattering reduction in respective crops (Paterson et al., 1995;Lin et al., 2012). Whether Sh1 is rewired into the SH5-directed seed shattering network in rice remain to be explored in the future (Figure 3, lower panel). In Sorghum propinquum, a wild sorghum relative, seed shattering is conferred by the SpWRKY gene. It is postulated that SpWRKY negatively regulates cell wall biosynthesis genes in the abscission layer. Nonetheless, the SpWRKY has not been crafted by artificial selection to make a contribution to the nonshattering trait in domesticated sorghum (Tang et al., 2013). Taken together, these above findings have raised an intriguing possibility that the convergent domestication of non-shattering crops might have achieved through parallel selection on the same underlying genetic targets (Figure 3, lower panel; Lin et al., 2012;Lenser and Theißen, 2013b).
The Q gene in domesticated wheat (Triticum aestivum) is an important domestication gene as it confers the freethreshing character (the loss of tendency of the spike shattering; Simons et al., 2006). Q gene encodes a member of AP2-family transcription factor. The cultivated Q allele is transcribed more abundantly than the wild q allele. Furthermore, the two alleles also differ in a single amino acid that significantly enhances the homodimerization capacity of the domestication allele (Simons et al., 2006). Thus, similar to the case of Sh4, the evolution of the free-threshing trait in domesticated wheat may have attributed to the combination of both coding and regulatory changes in the domestication gene. The expression difference between Q and q seems more important as it can largely explain the free-threshing trait in the domesticated wheat (Simons et al., 2006;Zhang et al., 2011). Although the mutation that gives rise to Q had a profound effect in the domestication process of wheat as it enables the farmers to harvest the grain more efficiently, the exact cellular basis leading to the free-threshing trait is still unknown.
The Domestication of Indehiscent Fruit in Legume Crops
In addition to cereals, loss of pod dehiscence also occurs in dicot crops, such as legumes. Species in the Legume family develop a characteristic dry dehiscent fruit (a legume or more generally a pod), which is derived from a monocarpellate pistil. The legume species disperse seeds by shattering the pod along the ventral suture after maturation (Tiwari and Bhatia, 1995). In cultivated soybean (Glycine max), the indehiscent pod is a major domestication trait that is targeted by artificial selection (Hymowitz, 1970;Harlan, 1992). The cellular basis and molecular mechanisms leading to the indehiscent pod have very recently been characterized. It is shown that the excessive lignification of the fiber cap cells (FCCs) in the ventral suture is responsible for the indehiscent fruit character (Figure 3, upper panel; Dong et al., 2014). Unexpectedly, the abscission layer is found to be functionally unchanged in the cultivated soybeans (Dong et al., 2014). , which is homologous to AtNST1/2 that acts as master transcriptional activator of secondary cell wall biosynthesis, resides in a QTL controlling pod dehiscence. Expression of SHAT1-5 is specifically localized in the developing FCCs. The lack of any fixed amino acid difference between the cultivated allele and wild allele, and that both alleles are capable of fully restoring the secondary cell wall thickening in the interfascicular fibers of nst1-1;nst3-1 double mutant suggest that the differential expression of SHAT1-5 in the FCC upon regulatory changes might be important for the indehiscent fruit. Using Laser Capture Microdissection system, Dong et al. (2014) reveal that a significant up-regulation of SHAT1-5 in FCC of cultivated soybean is responsible for the excessive cell wall deposition in the FCC, which in turn prevents the pod from committing dehiscence after maturation (Figure 3, upper panel). Further analysis show that the over transcription of SHAT1-5 in cultivated soybean FCC is attributable to the disruption of a repressive cis-regulatory element in the 5 ′ -promoter region (Dong et al., 2014). Expression of SHAT1-5 is related to the organs with severe secondary cell wall thickening, which is a common process during plant development (Dong et al., 2013). It seems that artificial selection would have discarded the null mutant in this gene due to pleiotropic effect, leaving a change in the specific regulatory element as a preferred mechanism for producing the desired phenotype. qPDH1 (QTL for Pod Dehiscence 1) is another major QTL controlling pod dehiscence in soybean that have very recently been cloned and shown to encode a dirigent-like protein with a possible function in lignin biosynthesis (Suzuki et al., 2010;Funatsuki et al., 2014). Expression of PDH1 is correlated with the lignin deposition in the inner sclerenchyma of the pod walls (Figure 3, upper panel). PDH1 promotes pod dehiscence by increasing the twisting force in the pod wall, which serves as a driving force for pod dehiscence (Funatsuki et al., 2014). In cultivated soybean, the indehiscent fruit is attributable to a premature stop codon in PDH1, which generates a nonfunctional protein (Funatsuki et al., 2014). Although the exact cellular and biochemical mechanisms leading to indehiscent pod by PDH1 remain to be elucidated, it is apparent that artificial selection might have targeted multiple cellular mechanisms and the controlling genes, including SHAT1-5 and PDH1, to minimize seed loss during soybean domestication. Meanwhile, these findings also raise an intriguing question as to how SHAT1-5 and PDH1 interact genetically to fine-tune the indehiscence degree of cultivated soybean that are adapted in different environments. Future analysis of allele frequency combined with careful phenotypic evaluation in a large collection of cultivated soybean germplasms would help to address this question.
The domesticated common bean (Phaseolus valgaris) originated in the Mesoamerican and Andean regions independently (Schmutz et al., 2014). Similar to other legume crops, the reduction of pod dehiscence represents a key domestication syndrome in the domesticated common bean. The indehiscent fruit results from the loss of fibers in the sutures ("stringless"), which is under the control of a major QTL, St locus (Koinange et al., 1996). PvIND1, a homolog of AtIND in common bean, was recently mapped in a region near the St locus. It appears that PvIND may not be directly involved in the control of pod dehiscence and may not be the causal gene underlying St, as polymorphism in the PvIND gene fails to link with the genotype on St locus and co-segregate with the dehiscent/indehiscent phenotype (Gioia et al., 2013). While PvIND is postulated as the AtIND homolog based on sequence homology in the conserved b-HLH domain, the IND-related transcription factors are specific to Brassicaceae and its role in valve margin cell lignification may have been acquired since the duplication event happened recently in the HECATE3 (HEC3) gene clade in Brassicaceae (Liljegren et al., 2004;Girin et al., 2010). Therefore, it is possible that polymorphisms in other AtIND homologs in the common bean genome may have been associated with pod indehiscence. Alternatively, considering that the fibers are mainly composed of sclerenchyma cells with well-developed secondary cell walls, it is also likely that genes involved in the regulation of secondary cell wall deposition or fiber cell differentiation may have contributed to the St locus in controlling pod dehiscence. Future work is necessary to discriminate these possibilities.
Conclusions and Future Perspectives
In the past 15 years, our understanding of the genetic control and evolution of the seed shattering/pod dehiscence processes has been advanced significantly by the implement of a combination of multiple experimental approaches. In Arabidopsis, the homostasis and interaction of hormones is revealed to work in another regulation layer in establishing the DZs. The core regulatory module (SHP-FUL) controlling DZ development is found to be largely conserved in dry fruit species that are closely relative to Arabidopsis while modification of the key regulatory genes frequently contributes to the evolution of specialized fruit morphology with novel dispersal strategies. Studies in the genetic control of the fleshy fruit maturation process further extend the conservation of SHP-FUL module into angiosperms and suggest that fruit dehiscence and ripening are in parallel evolved characters by co-opting the same underlying regulatory networks. Although we can now begin to understand the molecular and biochemical basis of fruit dehiscence and ripening in model species, a challenge remains to obtain greater molecular data from other non-model species, to unveil the evolutionary mechanisms of fruit diversification widespread in nature.
In the domesticated crops, it is apparent that the convergent evolution of non-shattering (indehiscent) fruit is often employed by the same gene or strikingly, the same mutation, while non-homologous genes are also frequently evident in different crops. In the future, with the growing interest in the molecular mechanisms of domesticated syndromes that arise as the result of evolutionary implications and their agriculture importance, an equally important and complementary issue will be the advances in the application of high throughput sequencing technology (next-generation sequencing, NGS) combined with genotypephenotype associations (genome-wide association analysis, GWAS) to zoom in on the exact mutations leading to the nonshattering character in additional crops. Overall, the list of genes that participate in the seed shattering process has experienced an unprecedented explosion in the past few years (Table 1), we can now begin to think about how to translate this basic knowledge into practice in crop breeding programs to feed the world in the face of growing population pressures. Exemplary work has been done in Brassica juncea by over-expression AtFUL to make pods resistant to shattering (Østergaard et al., 2006). | v3-fos |
2015-03-21T21:52:17.000Z | {
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} | s2 | Characterization of one sheep border disease virus in China
Background Border disease virus (BDV) causes border disease (BD) affecting mainly sheep and goats worldwide. BDV in goat herds suffering diarrhea was recently reported in China, however, infection in sheep was undetermined. Here, BDV infections of sheep herds in Jiangsu, China were screened; a BDV strain was isolated and identified from the sheep flocks in China. The genomic characteristics and pathogenesis of this new isolate were studied. Results In 2012, samples from 160 animals in 5 regions of Jiangsu province of China were screened for the presence of BDV genomic RNA and antibody by RT-PCR and ELISA, respectively. 44.4% of the sera were detected positively, and one slowly grown sheep was analyzed to be pestivirus RNA positive and antibody-negative. The sheep kept virus positive and antibody negative in the next 6 months of whole fattening period, and was defined as persistent infection (PI). The virus was isolated in MDBK cells without cytopathic effect (CPE) and named as JSLS12-01. Near-full-length genome sequenced was 12,227 nucleotides (nt). Phylogenetic analysis based on 5'-UTR and Npro fragments showed that the strain belonged to genotype 3, and shared varied homology with the other 3 BDV strains previously isolated from Chinese goats. The genome sequence of JSLS12-01 also had the highest homology with genotype BDV-3 (the strain Gifhorn). Experimental infections of sheep had mild clinical signs as depression and short-period mild fever (5 days). Viremia was detected in 1–7 days post-infection (dpi), and seroconversion began after 14 dpi. Conclusions This study reported the genomic and pathogenesis characterizations of one sheep BDV strain, which confirmed the occurrence of BDV infection in Chinese sheep. This sheep derived BDV strain was classified as BDV-3, together with the goat derived strains in China. These results might be helpful for further understanding of BDV infection in China and useful for prevention and control of BDV infections in the future.
BDV infects small ruminants (sheep and goats) and causes border disease worldwide. Several BDV strains have been proved to infect pigs and cattle under experimental or nature conditions [4,5]. BD shares some similar characteristics with BVDV infections in cattle and goats, however, with more pronounced emphasis on a wide range of productive diseases, such as abortions, stillbirths or mummified fetuses, barren ewes, malformations and the birth of weak lambs, which leads to a considerable economic effect. The affected lambs show abnormal body conformation and "hairy-shaker" syndrome named due to the hairy fleeces and tremors of the suffered lambs [6]. Small weak lambs can be persistently infected (PI) and the virus is wide spread in all organs in infected animals. However, BDV infections in pregnant goats result exclusively in abortions and malformations in fetuses and neonates, and PI goats are rarely found out via placenta [7]. An experiment infection was carried out in pregnant ewes with BDV-4, besides a high number of stillbirths up to 32%, significantly reduced bodyweight of lambs was also observed [8]. Although severe clinical outbreaks of BD are unusual, several epizootics have been reported in sheep and goats [9][10][11].
The pestivirus genome consists of a positive singlestranded RNA approximately 12.3 kb in length, encoding a single open reading frame (ORF) flanked by 5'-and 3'untranslated regions (UTR). The genome codes 4 structural proteins, the capsid (C) and three envelope proteins (E rns , E1 and E2), plus seven or eight non-structural proteins [12,13]. Except the 5'-UTR region, the N pro and E2 genes have also been used for genetic classification of new virus isolates [14,15]. Based on recent reports, BDV isolates have been divided into seven genotypes at least, and widely distributed in different countries, such as many European countries, Australia, New Zealand, Canada, the United States, India, Turkey, and Japan [7,16]. In 2012, BDV infections were first confirmed in several goat herds suffering serious diarrhea, and three BDV strains were isolated in China [11]. This was the first confirmed evidence of BDV genotype 3 circulations in Chinese goats, In order to further investigate the epidemic information of BDV in goats and sheep in the same regions of China, BDV seroepidemiological survey was carried out in our lab. One BDV strain named JSLS12-01 was isolated from one slowgrown sheep. And the genomic characteristics and pathogenesis of the isolate was determined. The data might be more supplement for BDV epidemiology, pathogenicity as well as its relationship with clinical diseases in China.
Antibody and viral detection
One hundred and sixty sera from sheep and goats in five regions of Jiangsu, China were collected and detected by BDV ELISA kits (SVANOVA). The positive rate was 44.4% (71/160), with 46.3% (63/136) of goats and 33.3% (8/24) of sheep, respectively. The positive rates varied from 16.7% (2/12) to 85.7% (12/14) with the flocks (Table 1). Sero-prevalence was at least 50% in two sheep herds and one goat herd from two regions of Jiangsu (Table 1).
In the sheep herds, an antibody-negative sheep (2 month old) from Nanjing, Jiangsu was detected positive by RT-PCR, which showed the very bright bands of 290 bp and 225 bp amplified by panpesti generic primers and BDV specific primers PBD1/PBD2, respectively. The RT-PCR products were purified and sequenced, which shared high homology with BDV strains by BLAST analysis. The RT-PCR results also showed two samples from goats were tested positive, 5'-UTR sequences were compared to sequences from GenBank, and shared 100% homology with JS12-04 strain reported previously.
Virus isolation
The BDV RNA-positive serum was cultured and passaged in MDBK cells. After the third passage, BDV cultures have been positively detected by RT-PCR and confirmed with sequencing. However, no CPE was observed during the process of passage. The new BDV isolate was named as JSLS12-01.
Subsequent clinical observations and serological analysis
Four sampling sheep including the BDV positive were continued to rear for clinical investigation subsequently, with the same feed and management conditions. Compared to the BDV negative sheep, the infected lamb was thinner, weaker, and poorer growth, and the body weight was about 20% less at the end of fattening period (6 month long). However, no other clinical signs were observed. The four sheep were tested once 4 weeks apart, and BDV RNA was positively detected by RT-PCR and the BDV specific antibody was negative for the original BDV positive animal in the whole grown period.
Complete genome sequencing and phylogenetic analysis
RT-PCR products ( Figure 1) were purified and cloned to pJET1.2 vectors for sequencing. The near full genome sequence of BDV JSLS12-01 strain was obtained and deposited in GenBank under accession number KC963426 and reported recently [17], the obtained genome of JSLS12-01 was 12, 227 nucleotides (nt) in length. The isolate shared 80.3% nucleotide homology and 89.9% amino acid homology with goat derived strain Gifhorn (a prototype of BDV-3), respectively ( Table 2). It shared 72.2-77.6% homology with other BDV genotypes strains available in GenBank ( Table 2). The homology with CSFV and BVDV strains were about 71% and 67%, respectively ( Table 2). The whole genome sequence based phylogenetic analysis indicated that JSLS12-01 was classified into the same branch with Gifhorn with 100% bootstrap value, and matched up with the result of the Blast analysis. The isolate clearly differed from other BDV strains and other pestivirus species (CSFVs or BVDVs) ( Figure 2). 5'-UTR and N pro sequences of the virus were aligned with the corresponding sequences of BDV reference strains and the evolutionary relationship between these isolates was estimated by phylogenetic analysis to further characterize the JSLS12-01 isolate. The phylogenetic tree based on 5'-UTR region (225 bp) showed that the JSLS12-01 strain was grouped with BDV-3 respective strains ( Figure 3). Comparison of 5'-UTR sequences revealed that BDV JSLS12-01 shared nucleotide identities of 78.6%, 83.5% and 94.4% with BDV-3 Chinese strains AH12-02, AH12-01 and JS12-04, respectively. The virus was 87.7%, 87.4% and 89.0% homology with other BDV-3 strains including Gifhorn from Spanish goats, 90-F-6338 and 90-F-6227 from sheep of France, respectively (Table 3); and also 82.5% to 85.7% with BDV-1; 84.1% with BDV-2; 76.4% to 85.1% with BDV-4; 84.2% to 85.0% with BDV-5; 86.7% with BDV-6; 71.5% to 72.9% with BDV-7; and 70.5% to 72.6% with BDV Tunisian; respectively ( Table 3). The highest identity of nucleotide sequence was 94.4% with the strain JS12-04 isolated in 2012 from Chinese goats (Table 3). JSLS12-01 shared the highest homology (73.2% to 80.7%) with other BDV-3 members on the N pro sequences (Table 3). And based on the phylogenetic tree of the N pro sequences also grouped the strain JSLS12-01 into BDV-3 (data not shown).
Pathogenicity of BDV JSLS12-01
All 3 lambs (45 day old) infected with BDV JSLS12-01 cell cultures showed only moderated depression without other clinical signs. The infected animals developed high rectal temperatures (40.0-41.0°C), with peak temperatures appearing on 3-7 day-post-infection (dpi) and returned to the normal level on 8 dpi, while the control sheep kept normal during the same period ( Figure 4). RT-PCR and virus isolation revealed that the virus could lead to viremia in the infected animals at 1-7dpi. The infected animals began seroconverted on 14 dpi and kept to increase in the following period ( Figure 5).
Discussion
Goats are major rearing small ruminants, and the numbers of sheep and rearing sheep farms are relative a few in Jiangsu and Anhui provinces of eastern China. BDV had been identified in Chinese diseased goats [11]. In the present study, BDV sero-epidemiological survey was carried out for goat and sheep by BDV ELISA kit and RT-PCR. Serum samples from seven flocks (4 of goats and 3 of sheep) in five regions were tested positive by ELISA (Table 1), which indicated the ubiquity of BDV infection in the small ruminant flocks. Four sheep including one was BDV RNA positive with RT-PCR were kept for the next 6 month rearing. The sheep was BDV Ab negative and viremia for the observation period; and identified as one PI animal according to the reports [7]. The PI sheep mainly showed poor-growing were agreement with BDV-4 virus infections [8]; however, classical clinical signs of BD such as paralysis and an abnormal fleece known as 'hairy shaker' were not appeared. In addition, the previous goat derived BDVs were identified from herds with diarrhea [11]. These uncharacteristic signs emphasized the difficulty of BD diagnosis based on clinical signs and the requirement for routine and accurate laboratory tests. Phylogenetic segregations of pestiviruses into individual species and subgroups are only identified by the branching order of the phylogenetic tree [18]. The genetic diversity of BDV is greater than that of other pestivirus species. According to the molecular diversity, BDV have been divided to seven groups at least [7,19,20]. The near full sequence of the JSLS12-01 had a closer relationship with BDV-3 strains at gene level comparing with other pestivirus reference strains (BDV-1,BDV-2, BDV-3, BDV-4,BDV-5 and BDV-7). And the strain should be one new BDV-3 strain with a lot of nucleotide or amino acid variation to the respective BDV strains ( Figure 2, Table 2). The isolate JSLS12-01 was the highest homology with the strain JS12-04 on the 5'-UTR and N pro gene compositions, and the two viruses were isolated from sheep or goats in different regions of Jiangsu province, however, the virus JSLS12-01 had much lesser identity with the other two viruses AH12-01 and AH12-02 on the gene levels (Table 3 and Figure 3), and the late two were from Anhui province (neighborhood each other). It indicated the epidemic BDV strains in China might have complex endemic situations, and have existed for a relative long period. The BDVs in China have mutated a lot, and may form different subbranches, such as the two strains JS12-04 and JSLS12-01 isolated in Jiangsu province formed one cluster, and the strains AH12-01 and AH12-02 from Anhui were much closed each other (Figure 3).
In addition, based on sequence alignment and phylogenetic analysis, the 4 Chinese BDV strains showed the high diversity of on the 5'-UTR compositions (Table 3) even though all of them were in BDV-3 genotype (Figure 3) [11]. The strain JSLS12-01 was only 83.5% and 78.6% homology with the strains AH12-01 and AH12-02 on 5'-UTR gene (Table 3), respectively. Furthermore, it was also found that JSLS12-01 had a very high homology of 5'-UTR sequences with other genotype viruses, such as 85.1%, 86.7% and 85% with the strains BU-1CRA22 (BDV-4), 92-F-7119 (BDV-6) and 93-F-7289 (BDV-5) (Table 3), respectively. It was true that the homology of BDV strains in the same genotype might be much less than the viruses being other genotypes. And it appeared that the BDV genotyping based on the 5'-UTR sequences could be still consummated.
Animal experiment was performed upon conventionally rearing sheep to evaluate the pathogenicity of the new BDV strain. JSLS12-01 could induce mild clinical diseases; the infected animals showed viremia at 1-7 dpi and disappeared after 7 dpi, during the same period, mild short-term pyrexia was observed (Figure 4). In addition, the infected animals seroconverted from 14 dpi (
Conclusions
In conclusion, BDV infections of sheep were demonstrated in China, and the BDV JSLS12-01 strain was clustered in BDV-3 subgroups, the predominant genotype in China. The BDV infections of goats and sheep appeared with various clinical signs and epidemic information. More studies should be carried out to make sure of the virulence and biologic characteristics of BDV.
Ethics statement
This study was performed in strict accordance with the guidelines of Jiangsu Province Animal Regulations (Government Decree No 45). The protocol was approved
Clinical sampling and observation
Serum samples were collected from 3 young sheep farms and 4 goat farms (about 2 months old) from 5 different regions in Jiangsu province of China (Table 1). A total of 24 sera from sheep and 136 sera from goats were collected. The sheep tested for BDV positive were continuously carried out for subsequent clinical observations and serological analysis in next 6 months (the fattening period) after the first sampling.
ELISA
BDV antibody detection was performed on serum samples of goats and sheep using a commercially available kit (SVANOVA BDV-Ab kit, SVANOVA Biotech, Uppsala, Sweden) according to the manufacturer's instructions.
Virus isolation
Virus isolation was carried out on the positive samples of pestivirus 5'-UTR RT-PCR as reports [16] and briefly introduced as following: the serum samples were centrifuged at 12,000 rpm for 20 min at 4°C and filtered through 0.22 μm filter, and subsequently inoculated onto confluent monolayers of Madin-Darby bovine kidney (MDBK) cells (obtained from China Institute of Veterinary Drugs Control) to culture for 96 hours with 1% FCS DMEM at 37°C and 5% CO 2 conditions. The original cells and FCS were proven to be free of pestivirus antigen and antibodies. The isolation of BDV was checked by RT-PCR as next described using Panpesti generic primers and BDV specific primers PBD1/PBD2 [21,22]. For the genomic long RNA RT-PCR, the extension time was 1 kb for 1 min. Amplification products were detected by electrophoresis in 1.2% agarose gels. Positive RT-PCR fragments were purified (Axygen), cloned to pJET1.2 vector (Thermo), and then transformed to E. coli DH5α. Positive clones, as confirmed by PCR and enzyme digestion, were sequenced. Three positive clones of each RT-PCR fragment were sequenced using the appropriate PCR primers for correct check.
RT-PCR detection and complete genomic sequence analysis
Briefly, six pairs of primers were designed to amplify the 6 overlapping fragments covering the virus genome, and summarized as Table 4. The retrieved sequences were edited and assembled with SeqManTM program version 5.03 of the DNASTAR package to obtain the complete sequence of this new BDV strain.
Phylogenetic analysis
The complete coding sequence of the virus was aligned with some represented BDV, BVDV 1, BVDV 2 and CSFV strain genome sequences. The 5'-UTR and N pro sequences were analyzed with sequences of BDV reference strains using 1.83 and MEGA 4.0.2, the 225 bp 5'-UTR fragments (PBD1/PBD2 product) and 487 bp N pro gene (corresponding to 394-880 bp of Gifhorn genome) sequences were used for analysis, respectively. Phylogenetic analysis was carried out using the neighbor-joining (NJ) method using 1000 replicates for determination the bootstrap values.
Experimental infection
Six one-month-old healthy sheep were tested negative for pestivirus (BDV and BVDV) infections by commercial ELISA kit (BDV: SVANOVA and BVDV: BIO-X) and RT-PCR mentioned above. They were further confirmed to be free of micoplasma infections by PCR. The sheep were randomly divided into two groups, with 3 animals in each group. Sheep of the experimental group was infected by intramuscular injection with 10 5 TCID 50 of BDV JSLS12-01 cell cultures, while the sheep in control group were inoculated with PBS buffer. All animals were monitored daily for clinical signs including depression, nasal discharge, diarrhea, coughing and rectal temperature. Serum samples were collected at day −2 to 0 prior to infection and 1, 3, 5, 7, 14, 21, 28, 35 and 42 dpi. Serum samples of days 1, 3, 5, 7, 14 and 21 were tested for viremia by RT-PCR described above. And the procedures to isolate BDV from the sera were described above. Serum samples of days 0, 7, 14, 21, 35 and 42 were tested for BDV specific antibodies using commercial ELISA kit (SVANOVA). | v3-fos |
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} | s2 | Effect of Application Ratio of Potassium over Nitrogen on Litchi Fruit Yield, Quality, and Storability
Soils of litchi orchards in China are commonly deficient in nitrogen and potassium. The cultivar Feizixiao litchis planted in a typical acidic upland orchard, which is low in nitrogen and potassium, were used as a subject in field experiments with different ratios of potassium to nitrogen (K2O:N = 0.6, 0.8, 1.0, 1.2, and 1.4). Field experiments were conducted from 2009 to 2012. The effects of K2O:N ratio on the yield, quality, and storability of litchi were investigated and discussed. Results indicated that with the increase of K2O:N ratio, fruit yield initially increased and then decreased, and litchi had the highest yield whenK2O:Nwas 1.2.WhenK andN fertilizers were applied at the ratio of 1.2, litchi had a better fruit quality with higher vitamin C content, soluble sugar, and soluble solid. With the increase of K2O:N ratio, healthy fruit rate initially increased and then decreased. This rate reached the maximum value when K2O:N was 1.2. Meanwhile, fruit-rotting rate, peel-browning index, cell membrane permeability, and peroxidase (POD) activity decreased at first and then increased and reached the minimum value when the K2O:N ratio was 1.2. Therefore, litchi fruit had the highest yield, better quality, and best storage property when K2O:N was 1.2. Thus, this ratio is recommended for the main litchi production areas in China. Litchi chinensis Sonn, a famous subtropical fruit originated in south China and southeast Asia, has been regarded as the rare fruit of China and the choice of fruit in Lingnan. This fruit is planted in tropical and subtropical Asia as well as in South Africa, Australia, the United States (Phunchaisri and Apichartsrangkoon, 2005; Wall, 2006). With a litchi-cultivated area and production accounting for over 80% of the world, China is the largest country producing litchi (Liu et al., 2014; Xu et al., 2010). However, litchi’s unit yields are generally low and unstable (Xu et al., 2010). Unreasonable litchi orchard fertilization (Yao et al., 2009), generally low N and K soil contents (Li et al., 2011, 2012), and litchi trees with low K nutrition (Yao et al., 2009) are some of the most significant reasons for these low and unstable unit yields. Furthermore, as a nonclimacteric fruit, litchi is harvested in hot and humid summer and can easily undergo pericarp browning, flesh deterioration, and fruit rotting after harvest (Hu et al., 2005; Jiang and Fu, 2000). Thus, litchi is one of the fruits with the shortest storage duration. Currently, litchi is treated with low temperature and controlled atmosphere storage, medication, packaging improvement, smoldering sulfur, and pickling for longer shelf life (Jiang et al., 2003). Nevertheless, ‘‘cold chain’’ circulation facilities are still deficient in China (Wu et al., 2001). Chemical treatment leaves drug residue, whereas packaging storage can lead to low O2 and high CO2 concentrations, which result in accumulation of smelly substances, such as acetaldehyde and ethyl alcohol caused by anaerobic glycolysis (Duan et al., 2004). Therefore, this issue in litchi production should be urgently solved to improve the storability and preservation of fresh litchi fruit. Research has revealed that mineral element is important to the improvement of fruit storability (Fallihi, 1985, 1988). Litchi sprouts and roots repeatedly in a growth year and consumes a large amount of nutrients in its growth and fruitage period. Potassium and nitrogen are two mineral nutrition elements required most in normal litchi growth and development (Yao et al., 2009). However, Chinese litchi orchards are usually deficient in nitrogen and potassium (Li et al., 2011, 2012). In addition to its significant effect on fruit yield and quality, potassium and nitrogen nutrition is also essential to fruit storability. Earlier studies showed that appropriate application of potassium can improve the fruit storability of peach (Cummings, 1980), longan (Wei et al., 2008), orange (Lin et al., 2006), kiwifruit (Wang et al., 2006), fig (Huang, 2007), and sweet cherry (Xu et al., 2009). However, few studies have focused on the effect of potassium and nitrogen nutrition on litchi fruit yield, quality, and storability after harvest. Thus, this paper takes ‘Feizixiao’, which is the leading litchi cultivar in China, as the research object and discusses the effect of different application ratio of potassium over nitrogen on litchi fruit yield, quality, and storability after harvest to find a theoretical foundation for scientific litchi fertilization, and improvement of litchi fruit yield and storability. Materials and Methods Plant material, growth conditions Field experiments were carried out in Shouwang orchard (23.0290 N, 114.5551 E) located in Huidong County, Guangdong Province, from June 2009 to June 2012, during three fruit harvest seasons. The ‘Feizixiao’ variety of the litchi species was used and planted in 1995 with a spacing of 5m · 6m (330 plants per hectare) in the slope terraces. The crown was in good order and complete. The tree vigor, cultivation environment, and all horticultural practices were the same. ‘Feizixiao’ is the dominant litchi cultivar in China. It has wide environmental adaptation, and the crops grow well in most growing areas. The soil in this orchard was the lateritic red soil type, which is typical in southern China. Soil samples were collected at 0 cm to 60 cm soil depth before the experiment. The soil contained orangic matter (8.6 g·kg), alkali-hydrolysable N (44.1 mg·kg), NH4 -N (2.0 mg·kg), and NO3 -N (1.2 mg·kg) and contained P (7.9 mg·kg), K (73.3 mg·kg), Ca (866.4 mg·kg), Mg (66.1 mg·kg), Zn (0.45 mg·kg), B (0.16 mg·kg), andMo (0.08 mg·kg). In addition, the soil had a pH value of 4.61 and a loamy clay texture. Experimental treatments and design The field experiments were conducted using five treatments, more specifically, five fertilizers with specific K2O:N ratios. The K2O:N ratios of 0.6, 0.8, 1.0, 1.2, and 1.4 were set and denoted as K0.6N, K0.8N, K1.0N, K1.2N, and K1.4N. Each treatment was conducted in three replicates with five trees in each plot. The usage rates of N in litchi were 198, 129, and 165 kg·ha in 2009–10, 2010–11, and 2011–12, respectively. K2O was applied at rates that were 0.6, 0.8, 1.0, 1.2, and 1.4 times that of N in each growth year. In addition, the same amount of P, Ca, Mg, Zn, B, and Mo was added in all treatments in the same year to prevent nutrient deficiencies other than that of N and K. All fertilizers were divided and applied after fruit harvest, before blossoming, at flower fading, and fruit Received for publication 5 Jan. 2015. Accepted for publication 22 Apr. 2015. This work was financially supported by the earmarked fund for Modern Agro-industry Technology Research System (CARS-33) fromMinistry of Agriculture of P.R. China. To whom reprint requests should be addressed; e-mail lyaolx@163.com. 916 HORTSCIENCE VOL. 50(6) JUNE 2015 developing stages. Urea, super phosphate, potassium chloride, lime, magnesium sulfate, zinc sulfate, borax, and ammonium molybdate were used in this experiment. In the entire growth period, three circular canals or three holes were ditched by the dripping line. The fertilizer was sprayed into the canals or holes. The soil was covered and then watered. Data collection and measurement Yield and quality.Yields were recorded in the experiment, as fruit fresh weight per tree at commercial harvest, so as to calculate yield per hectare. Fresh fruits, consisting of 50 fruits for each plot, were obtained for quality analysis, as well as to examine vitamin C, soluble sugar, organic acid, soluble solid, and pH at each harvest during 2010–12. Biomass composition of fruit. Five litchi fruits were picked from the south, west, north, and east of a litchi tree crown. A total of 20 fruits were harvested from one tree, and 100 litchi fruits from each plot were picked to obtain the composite sample. The fruit was peeled and divided into peel, pulp, and kernel. The fruit was weighed, and the percentage of the weight of each part of the fruit was calculated. Natural storage at room temperature. Fruits were picked from each plot with similar size and maturity and without pests and mechanical injury. The fruits were wrapped with fresh-keeping film, and the natural storage experiment was initiated at room temperature (25 ± 1 C). Samples were taken every 2 d to determine relevant indexes. The specific methods of determination are enumerated and explained below. Calculation of the healthy fruit rate follows the method suggested by Tian et al. (2006). A total of 40 fruits picked from each area were divided into five grades according to the fruit appearance: grade 1 = bright red pericarp, without browning on epicarp or endocarp; grade 2 = the browning area is less than one-fourth of the fruit surface; grade 3 = the browning area is one-fourth to one-third of the fruit surface; grade 4 = the browning area is one-third to two-thirds of the fruit surface; and grade 5 = the browning area is more than two-thirds of the fruit surface. The healthy fruit rate is computed as follows: healthy fruit rate (%) = (quantity of grade 1 fruits + quantity of grade 2 fruits)/total fruit quantity · 100%. A specified number of fruits (40 from each area) were picked for fixed observation. The rotting rate is denoted as the percentage of fruits with mildew, musty pericarp, and liquid flesh from the overall number of the observed fruits. The formula for rotting rate is as follows: rotting rate = quantity of rotten litchis/total litchi quantity · 100%. Calculation of the pericarp browning index follows the method suggested by Jiang (2000) with slight modification. A total of 40 fruits were picked from each area and were divided into five grades according to the percentage of the browning area from the total area of the fruit surface. The grading standards are as follows: grade 0 = no pericarp browning; grade 1 = browning area#25% (slight browning); grade 2 = 25% < browning area #50%; grade 3 = 50% < browning area#75%; grade 4 = browning area >75%. The browning index is calculated as follows: browning index % = (0 · N0 + 1 ·N1 + 2 ·N2 + 3 ·N3 + 4 ·N4) · 100/(4 · NT). In the formula, N0–N4 refers to the quantity of fruits in relevant browning grade, and NT corresponds to the overall number of fruits. The measurement of pericarp cell membrane permeability follows the method suggested by Jiang and Chen (1995) with slight modification. Fifteen litchi fruits picked from each area were processed with a 10-mm puncher to obtain 15 round slices. About 20 mL of distilled water was added and let stood for 20 min. Conductivity was measured with a conductometer. The slices were kept in boiling water for 20 min, and the amount of water evaporated was added. The slices were cooled to ambient temperature, and conductivity was again measured. The ratio between the two measured conductivities is the cell membrane permeability. The polyphenol oxidase (PPO) activity of the pericarp is determined with phosphate extraction colorimetry. About 1.0 g of fresh pericarp was cut into pieces and placed into a mortar. The pericarp was mixed with an appropriate amount [1:3.5 (w/v)] of 0.1 mol·L phosphate buffer (pH 6.8) and ground into homogenate in ice bath. All homogenateswere transferred intoa centrifuge tube and centrifuged for 10 min at 6000 r·min at a low temperature (4 C). The liquid supernatant is the extracting solution of crude enzyme. About 3.5 mL of 0.1 mol·L phosphate buffer (pH 6.8), 1 mL of 0.2 mol·L catechol solution, and 0.2–0.5 mL of crude enzyme were added into a 10-mL stoppered test tube. The liquid was mixed to a 30 C water bath for 15 min, and absorbance A was measured at 525 nm. The value of absorbance is the relative activity of PPO. Peroxidase (POD) activity is determined with o-methoxyphenol method. About 1.0 g of fresh pericarp was cut into pieces and placed in a mortar. The fresh pericarp was mixed with 5 mL of tris-HCl buffer (pH 8.5) and ground into homogenate. The homogenate was placed in a centrifuge for 5 min at 4000 r·min at a low temperature (4 C). The liquid supernatant was poured out for standby application. Two 1-cm cuvettes were used; 1 mL of extracted enzyme solution and 3 mL of reaction mixture were added into one cuvette. The stopwatch was started immediately. Subsequently, 0.2 mol·L phosphate buffer (pH 6.0) was added into the other cuvette for contrast. The optical density (OD) at wavelength 470 nm was measured after 5 min of reaction. Enzymatic activity is the change of the OD within 1 min (a change in value of 0.01 of OD at 470 nmwithin 1 min represents one activity unit). Statistical analyses All the data were the means of three replications, and results were represented as mean ± SE. Analysis of variance with least significant difference was performed using SAS/STAT software (SAS V9, SAS Institute Inc., Cary, NC). Figures in this paper were made using EXCEL 2013.
Litchi chinensis Sonn, a famous subtropical fruit originated in south China and southeast Asia, has been regarded as the rare fruit of China and the choice of fruit in Lingnan. This fruit is planted in tropical and subtropical Asia as well as in South Africa, Australia, the United States (Phunchaisri and Apichartsrangkoon, 2005;Wall, 2006). With a litchi-cultivated area and production accounting for over 80% of the world, China is the largest country producing litchi (Liu et al., 2014;Xu et al., 2010). However, litchi's unit yields are generally low and unstable (Xu et al., 2010). Unreasonable litchi orchard fertilization (Yao et al., 2009), generally low N and K soil contents (Li et al., 2011(Li et al., , 2012, and litchi trees with low K nutrition (Yao et al., 2009) are some of the most significant reasons for these low and unstable unit yields. Furthermore, as a nonclimacteric fruit, litchi is harvested in hot and humid summer and can easily undergo pericarp browning, flesh deterioration, and fruit rotting after harvest (Hu et al., 2005;Jiang and Fu, 2000). Thus, litchi is one of the fruits with the shortest storage duration. Currently, litchi is treated with low temperature and controlled atmosphere storage, medication, packaging improvement, smoldering sulfur, and pickling for longer shelf life (Jiang et al., 2003). Nevertheless, ''cold chain'' circulation facilities are still deficient in China (Wu et al., 2001). Chemical treatment leaves drug residue, whereas packaging storage can lead to low O 2 and high CO 2 concentrations, which result in accumulation of smelly substances, such as acetaldehyde and ethyl alcohol caused by anaerobic glycolysis (Duan et al., 2004). Therefore, this issue in litchi production should be urgently solved to improve the storability and preservation of fresh litchi fruit.
Research has revealed that mineral element is important to the improvement of fruit storability (Fallihi, 1985(Fallihi, , 1988. Litchi sprouts and roots repeatedly in a growth year and consumes a large amount of nutrients in its growth and fruitage period. Potassium and nitrogen are two mineral nutrition elements required most in normal litchi growth and development (Yao et al., 2009). However, Chinese litchi orchards are usually deficient in nitrogen and potassium (Li et al., 2011(Li et al., , 2012. In addition to its significant effect on fruit yield and quality, potassium and nitrogen nutrition is also essential to fruit storability. Earlier studies showed that appropriate application of potassium can improve the fruit storability of peach (Cummings, 1980), longan (Wei et al., 2008), orange , kiwifruit (Wang et al., 2006), fig (Huang, 2007), and sweet cherry (Xu et al., 2009). However, few studies have focused on the effect of potassium and nitrogen nutrition on litchi fruit yield, quality, and storability after harvest. Thus, this paper takes 'Feizixiao', which is the leading litchi cultivar in China, as the research object and discusses the effect of different application ratio of potassium over nitrogen on litchi fruit yield, quality, and storability after harvest to find a theoretical foundation for scientific litchi fertilization, and improvement of litchi fruit yield and storability.
Plant material, growth conditions
Field experiments were carried out in Shouwang orchard (23. 0290°N, 114.5551°E ) located in Huidong County, Guangdong Province, from June 2009 to June 2012, during three fruit harvest seasons. The 'Feizixiao' variety of the litchi species was used and planted in 1995 with a spacing of 5 m · 6 m (330 plants per hectare) in the slope terraces. The crown was in good order and complete. The tree vigor, cultivation environment, and all horticultural practices were the same. 'Feizixiao' is the dominant litchi cultivar in China. It has wide environmental adaptation, and the crops grow well in most growing areas. The soil in this orchard was the lateritic red soil type, which is typical in southern China. Soil samples were collected at 0 cm to 60 cm soil depth before the experiment. The soil contained orangic matter (8.6 g · kg -1 ), alkali-hydrolysable N (44.1 mg · kg -1 ), NH 4 + -N (2.0 mg · kg -1 ), and NO 3 --N (1.2 mg · kg -1 ) and contained P (7.9 mg · kg -1 ), K (73.3 mg · kg -1 ), Ca (866.4 mg · kg -1 ), Mg (66.1 mg · kg -1 ), Zn (0.45 mg · kg -1 ), B (0.16 mg · kg -1 ), and Mo (0.08 mg · kg -1 ). In addition, the soil had a pH value of 4.61 and a loamy clay texture.
Experimental treatments and design
The field experiments were conducted using five treatments, more specifically, five fertilizers with specific K 2 O:N ratios. The K 2 O:N ratios of 0.6, 0.8, 1.0, 1.2, and 1.4 were set and denoted as K 0.6 N, K 0.8 N, K 1.0 N, K 1.2 N, and K 1.4 N. Each treatment was conducted in three replicates with five trees in each plot.
The usage rates of N in litchi were 198, 129, and 165 kg · ha -1 in 2009-10, 2010-11, and 2011-12, respectively. K 2 O was applied at rates that were 0.6, 0.8, 1.0, 1.2, and 1.4 times that of N in each growth year. In addition, the same amount of P, Ca, Mg, Zn, B, and Mo was added in all treatments in the same year to prevent nutrient deficiencies other than that of N and K. All fertilizers were divided and applied after fruit harvest, before blossoming, at flower fading, and fruit developing stages. Urea, super phosphate, potassium chloride, lime, magnesium sulfate, zinc sulfate, borax, and ammonium molybdate were used in this experiment. In the entire growth period, three circular canals or three holes were ditched by the dripping line. The fertilizer was sprayed into the canals or holes. The soil was covered and then watered.
Data collection and measurement
Yield and quality. Yields were recorded in the experiment, as fruit fresh weight per tree at commercial harvest, so as to calculate yield per hectare. Fresh fruits, consisting of 50 fruits for each plot, were obtained for quality analysis, as well as to examine vitamin C, soluble sugar, organic acid, soluble solid, and pH at each harvest during 2010-12.
Biomass composition of fruit. Five litchi fruits were picked from the south, west, north, and east of a litchi tree crown. A total of 20 fruits were harvested from one tree, and 100 litchi fruits from each plot were picked to obtain the composite sample. The fruit was peeled and divided into peel, pulp, and kernel. The fruit was weighed, and the percentage of the weight of each part of the fruit was calculated.
Natural storage at room temperature. Fruits were picked from each plot with similar size and maturity and without pests and mechanical injury. The fruits were wrapped with fresh-keeping film, and the natural storage experiment was initiated at room temperature (25 ± 1°C). Samples were taken every 2 d to determine relevant indexes. The specific methods of determination are enumerated and explained below.
Calculation of the healthy fruit rate follows the method suggested by Tian et al. (2006). A total of 40 fruits picked from each area were divided into five grades according to the fruit appearance: grade 1 = bright red pericarp, without browning on epicarp or endocarp; grade 2 = the browning area is less than one-fourth of the fruit surface; grade 3 = the browning area is one-fourth to one-third of the fruit surface; grade 4 = the browning area is one-third to two-thirds of the fruit surface; and grade 5 = the browning area is more than two-thirds of the fruit surface. The healthy fruit rate is computed as follows: healthy fruit rate (%) = (quantity of grade 1 fruits + quantity of grade 2 fruits)/total fruit quantity · 100%.
A specified number of fruits (40 from each area) were picked for fixed observation. The rotting rate is denoted as the percentage of fruits with mildew, musty pericarp, and liquid flesh from the overall number of the observed fruits. The formula for rotting rate is as follows: rotting rate = quantity of rotten litchis/total litchi quantity · 100%.
Calculation of the pericarp browning index follows the method suggested by Jiang (2000) with slight modification. A total of 40 fruits were picked from each area and were divided into five grades according to the percentage of the browning area from the total area of the fruit surface. The grading standards are as follows: grade 0 = no pericarp browning; grade 1 = browning area #25% (slight browning); grade 2 = 25% < browning area #50%; grade 3 = 50% < browning area #75%; grade 4 = browning area >75%. The browning index is calculated as follows: browning index % = (0 · N0 + 1 · N1 + 2 · N2 + 3 · N3 + 4 · N4) · 100/(4 · NT). In the formula, N0-N4 refers to the quantity of fruits in relevant browning grade, and NT corresponds to the overall number of fruits.
The measurement of pericarp cell membrane permeability follows the method suggested by Jiang and Chen (1995) with slight modification. Fifteen litchi fruits picked from each area were processed with a 10-mm puncher to obtain 15 round slices. About 20 mL of distilled water was added and let stood for 20 min. Conductivity was measured with a conductometer. The slices were kept in boiling water for 20 min, and the amount of water evaporated was added. The slices were cooled to ambient temperature, and conductivity was again measured. The ratio between the two measured conductivities is the cell membrane permeability.
The polyphenol oxidase (PPO) activity of the pericarp is determined with phosphate extraction colorimetry. About 1.0 g of fresh pericarp was cut into pieces and placed into a mortar. The pericarp was mixed with an appropriate amount [1:3.5 (w/v)] of 0.1 mol · L -1 phosphate buffer (pH 6.8) and ground into homogenate in ice bath. All homogenates were transferred into a centrifuge tube and centrifuged for 10 min at 6000 r · min -1 at a low temperature (4°C). The liquid supernatant is the extracting solution of crude enzyme. About 3.5 mL of 0.1 mol · L -1 phosphate buffer (pH 6.8), 1 mL of 0.2 mol · L -1 catechol solution, and 0.2-0.5 mL of crude enzyme were added into a 10-mL stoppered test tube. The liquid was mixed to a 30°C water bath for 15 min, and absorbance A was measured at 525 nm. The value of absorbance is the relative activity of PPO.
Peroxidase (POD) activity is determined with o-methoxyphenol method. About 1.0 g of fresh pericarp was cut into pieces and placed in a mortar. The fresh pericarp was mixed with 5 mL of tris-HCl buffer (pH 8.5) and ground into homogenate. The homogenate was placed in a centrifuge for 5 min at 4000 r · min -1 at a low temperature (4°C). The liquid supernatant was poured out for standby application. Two 1-cm cuvettes were used; 1 mL of extracted enzyme solution and 3 mL of reaction mixture were added into one cuvette. The stopwatch was started immediately. Subsequently, 0.2 mol · L -1 phosphate buffer (pH 6.0) was added into the other cuvette for contrast. The optical density (OD) at wavelength 470 nm was measured after 5 min of reaction. Enzymatic activity is the change of the OD within 1 min (a change in value of 0.01 of OD at 470 nm within 1 min represents one activity unit).
Statistical analyses
All the data were the means of three replications, and results were represented as mean ± SE. Analysis of variance with least significant difference was performed using SAS/STAT software (SAS V9, SAS Institute Inc., Cary, NC). Figures in this paper were made using EXCEL 2013.
Results
Fruit yield. As shown in Table 1, with the increase of K 2 O:N ratio, fruit yield initially increased and then decreased. The trees treated with K 1.2 N produced the highest fruit yield. Table 1 also illustrates that the K 2 O:N ratio affected the fruit yield more obviously as the application time of K and N fertilizers extended. Yield and weight data from 2012 show that the litchi fruit yield and weight per fruit have a positive correlation and were nearly the same with significant level (r = 0.7869, P = 0.0516). Therefore, improving the K 2 O:N ratio can increase the litchi yield as this improvement promotes fruit expansion and single fruit weight. Consequently, the proper application of K and N fertilizer can considerably increase the fruit yield.
Fruit quality. There was no significant difference in vitamin C (Vc) content among treatments with different use ratios of K 2 O:N in 2010 and 2011, however, the Vc content increased and then decreased as the K 2 O:N ratio elevated in 2012 (Table 2). Fruits obtained after the K 1.2 N treatment contained significantly higher Vc than all the other treatments. The soluble solid content had similar changing trends as the vitamin C for all three harvests. It seemed that the soluble sugar content was not closely related with the K 2 O:N ratio for all three harvests. Significant and positive correlation between organic acid content and K 2 O:N ratio was observed for 3 years (Fig. 1), which could be contributed to the enhanced metabolism of organic acid, such as malic acid, by increased K nutrition (Lu, 2003). Increased content of organic acid might be beneficial for the production of litchi wine while brewing (Liu et al., 2011). Simultaneously, significant and negative relation was found between sugar:acid ratio and K 2 O:N ratio (Fig. 1). Figure 1 also illustrates that the K 2 O:N ratio affected the organic acid content and sugar:acid ratio more obviously as the application time of K and N fertilizers extended. As more organic acid in fruit was generated with increasing K 2 O:N ratio, consequently, the fruit pH decreased. The change in sugar:acid ratio in different treatments indicated that the taste of litchi fruit could be affected by the application of K and N fertilizer. Decreased or increased use of ratio of K 2 O:N might worsen the fruit taste.
Fruit storability. The postharvest storability of litchi fruit was compared. Tables 3-8 suggested that at the beginning of the experiment, the pericarp cell membrane permeability was different although the processed litchis showed the same healthy fruit rate, rotting rate, and pericarp browning index. A significant difference in the pericarp PPO and POD activity was observed. Both enzymatic activities declined significantly with the increase in the K 2 O:N ratio. As the storage duration prolonged, the healthy fruit rate of all the processed fruits declined dramatically, whereas the rotting rate and pericarp browning index rose significantly. On the 4th day, the rotting rate increased rapidly, and the fruits entered the peak stage of senescence and deterioration.
As the storage duration extended, litchi fruits softened and rotted slowly. Tables 3 and 4 suggested that, in an 8-day storage cycle, the healthy fruit rate increased first and then declined with the increase in the K 2 O:N ratio. The rate reached the maximum when the K 2 O:N ratio was 1.2. The rotting rate changed in an opposite way. In contrast to K 0.6 N treatment, when the fruits were treated with K 0.8 N, K 1.0 N, K 1.2 N, and K 1.4 N, the healthy fruit rate increased by 8.7%, 20.0%, 27.5%, and 15.0% on the 4th day, respectively, and the rotting rate declined by 9.1%, 27.3%, 68.2%, and 27.3%, respectively. On the 6th day, the healthy fruit rate of fruits treated with K 0.8 N, K 1.0 N, K 1.2 N, and K 1.4 N increased by 38.2%, 55.3%, 81.6%, and 0.0%, and the rotting rate declined by 5.0%, 12.0%, 43.0%, and 4.0%, respectively. On the 8th day, all treated fruits became completely rotten. Therefore, K 1.2 N treatment was significantly effective for reducing the rotting rate of litchi fruit, and the effect was more obvious as the storage time prolongs within 6 d of storage. The appropriate application of potassium-nitrogen fertilizer can inhibit litchi fruit rotting and benefit the healthy fruit rate. The effect was more evident on the 4th to 6th day of storage and reflected good fruit storability.
Tables 5 and 6 suggested that as the K 2 O: N ratio increased, the pericarp browning index and cell membrane permeability declined first and increased later and reached the minimum when the K 2 O:N ratio was 1.2. In contrast to K 0.6 N treatment, when the fruits were treated with K 0.8 N, K 1.0 N, K 1.2 N, and K 1.4 N, the pericarp browning index declined by 2.6%, 7.7%, 56.3%, and -28.2% on the 4th day of storage and declined by 0.0%, 12.2%, 44.1%, and 13.0% on the 6th day of storage, respectively. K 1.2 N treatment was effective for inhibiting pericarp browning, delaying membrane lipid peroxidation, and deterring growth of pericarp membrane permeability.
As the K 2 O:N ratio increased, the POD activity of the pericarp declined first and 0.0 ± 0.0 a 1.9 ± 0.6 b 8.1 ± 1.7 ab 49.6 ± 1.3 a 87.1 ± 8.5 a K 0.8 N 0.0 ± 0.0 a 1.7 ± 0.4 bc 7.9 ± 2.2 ab 49.6 ± 4.4 a 86.3 ± 3.8 a K 1.0 N 0.0 ± 0.0 a 1.0 ± 0.4 c 7.5 ± 3.8 ab 43.5 ± 9.5 a 83.3 ± 9.1 a K 1.2 N 0.0 ± 0.0 a 0.2 ± 0.4 d 3.6 ± 1.9 b 27.7 ± 5.6 b 62.3 ± 7.7 b K 1.4 N 0.0 ± 0.0 a 2.7 ± 0.4 a 10.4 ± 5.7 a 43.1 ± 5.3 a 82.8 ± 6.6 a Treatment means followed by a different letter are significantly different (P < 0.05). increased later and reached the minimum when the K 2 O:N ratio was 1.2 (Table 7). In contrast to K 0.6 N treatment, when the fruits were treated with K 1.2 N, the pericarp POD activity reduced by 23.7%, 27.3%, 16.4%, 16.7%, and 31.6% on the 0th, 2nd, 4th, 6th, and 8th day of storage, respectively. Table 6 suggested that, within the first 2 d, as the K 2 O:N ratio increased, PPO activity of the pericarp declined and reached the minimum when the K 2 O:N ratio was 1.4. After the 2nd day, the activity declined first and increased later and reached the minimum when the K 2 O:N ratio was 1.2. The fitting of the relationship between the PPO activity and the K 2 O:N ratio on the 2nd day reflected that the relationship between the two satisfies the linear equation in one unknown (y = -1.582x + 5.8389, R 2 = 0.8421, P = 0.029) and showed a significant negative correlation. The K 1.2 N treatment inhibited pericarp browning by significantly reducing the PPO activity and delayed fruit senescence by significantly reducing the POD activity.
Moreover, the K 1.2 N treatment was the best for fruit storability and prolonged shelf life. In litchi production, potassium-nitrogen fertilizer should be applied to improve fruit storability.
Biomass composition of fruit. Table 9 indicated that under the treatment, pulp percentage showed certain difference in the first year, and the difference became significant in the third year. As the K 2 O:N ratio increased, the pulp percentage declined first and then increased and reached the minimum when the K 2 O:N ratio was 1.2. The peel percentage changed in an opposite way and reached the maximum when the K 2 O:N ratio was 1.2. With the increase in K 2 O:N, the edible rate of the fruit declined first and then increased later, and the peel thickness changed in an opposite way. When the K 2 O:N ratio was 1.2, the litchi peel thickness increased most significantly.
Discussion
Nutrition is the base of fruit growth and development, yield formation, and quality improvement. Potassium is one of the recognized quality elements. Application of K can accelerate fiber compounding and epidermal tissue development, thicken the cell wall, and improve the mechanical resistance of collenchymas against bacterial parasite. In addition, K can adjust cell membrane permeability, increase turgor pressure, improve membrane stability and tissue resistance, and prolong the postharvest storage duration and shelf life of fruiters (Huang et al., 2000). According to the report by Koo (1985), as the application amount of potassium increased to the most appropriate range, the incidence of stem-end rot and green mold of sweet orange reduced during storage. According to this research, the rotting rate of litchi fruit declined first and increased later with the increase of the K 2 O: N ratio and reached the minimum when the K 2 O:N ratio was 1.2. This finding indicated that appropriate application of potassiumnitrogen fertilizer can effectively inhibit the postharvest rotting of litchi fruit. As shown in the study of Cummings (1980), the shelf life of peach prolonged, and fruit browning was effectively inhibited after potassium fertilizer is applied. Pericarp browning, one of the most serious issues in litchi storage, is the primary factor that inhibits the longtime storage of litchi. Pericarp browning also shortens shelf life and reduces commodity value. Earlier studies have shown that litchi pericarp browning was closely related to the PPO and POD activities (Ruenroengklin et al., 2009;Zhang et al., 2005). This research found that as the K 2 O:N ratio increased, litchi pericarp browning index and POD activity declined first and increased later and reached the minimum when the K 2 O:N ratio was 1.2; the PPO activity declined within 0-2 d with an increase in the K 2 O:N ratio and reached the minimum when the K 2 O:N ratio was 1.4; after the 2nd day, the PPO activity declined first and increased later and reached the minimum when the K 2 O:N ratio was 1.2, indicating that appropriate application of potassium-nitrogen fertilizer can effectively inhibit the postharvest rotting of litchi fruit. This finding also showed that the enzymatic browning effect was least significant when the K 2 O:N ratio was 1.2. However, Jiang and Fu (1999) believed that the main cause of browning is the integrity compromise of pericarp cell membrane. This research found that as the K 2 O:N ratio increased, the cell membrane permeability declined first and increased later and reached the minimum when the K 2 O:N ratio was 1.2. Appropriate application of potassium-nitrogen fertilizer can effectively prevent the pericarp cell membrane systems from being attacked and can improve the integrity of pericarp cell membrane, thus further inhibiting the leakage of composition in cell and fruit rotting.
Litchi ripens at high temperature in the intense heat of summer, and the fruit browns .9 ± 0.5 a 22.2 ± 0.6 a 3.9 ± 0.2 a 71.1 ± 1.3 ab 23.0 ± 1.4 a 5.9 ± 0.2 a Treatment means followed by a different letter are significantly different (P < 0.05). and rots after harvest. Pericarp browning is closely related to the water loss of fruit (Scott et al., 1982), which mainly occurs to the pericarp (Jiang and Fu, 1999). By contrast, deficiency in nitrogen and potassium can lead to the water loss of fruit in storage (Lu et al., 2001). Citrus peel becomes thinner under nitrogen deficiency treatment, whereas application of potassium fertilizer can improve the thickness of the pericarp. Fruit storage duration is closely related to the pericarp thickness, i.e., the smaller the thickness is, the shorter the storage duration will be (Lu et al., 2004). This research showed that as the K 2 O: N ratio increased, litchi pericarp thickness increased first and declined later. When the K 2 O:N ratio was 1.2, the thickening effect on litchi pericarp was the most significant, and either excessive large or small K 2 O:N ratio can both reduce the pericarp thickness of litchi fruit. Therefore, to keep litchi fruit fresh, appropriate amount of potassium-nitrogen fertilizer should be applied to increase the pericarp thickness to facilitate fruit storability and to achieve prolonged shelf life.
Conclusions
The reasonable applying proportion of potassium and nitrogen fertilizer can produce high yield and quality, longtime storable fruits. In our trail, litchi fruit showed the highest yield, better quality, and best postharvest storability with applying ratio of K 2 O:N = 1.2 on nitrogen-deficient and low-potassium soil. Therefore, postharvest storability of fruit will be better through plant nutrient management, which is essential supplementary of fruit preservative and fresh-keeping. | v3-fos |
2019-04-25T13:09:53.988Z | {
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} | s2 | An Efficient Weed and Pest Detection System
In an agricultural field, farmers have a wide range of diversity to select suitable fruit and vegetable crops. However, the cultivation of these crops with quality produce is highly technical. Most challenging for farmers is to differentiate between crops and weeds. The proposed method identifies the weeds by using leaf parameters such as shape, color, and texture. Pest/disease detection is also possible by detection of varied shape and color of disease affected crop leaves. In order to improve the accuracy of weed detection, need to develop a weed detection algorithm which could be supported in all the cases accurately. Adding on, crops face many diseases. Pest/diseases are seen on the leaves of the plant. To avoid misclassification of such disease affected plant as weed, a new algorithm is developed for disease identification and included in weed detection algorithm. Recognition of normal leaf, diseased leaf and weed is based on similarity measure.
Introduction
In India most people depend on agriculture. The main goal in farming is increasing agricultural protection. The protection decreased by many factors including weed, pest/disease, environmental conditions. Controlling weed is done by machineries, fertilizers and labours. To identify and remove weed efficiently, computerised weed detection system is proposed. In the proposed system some difficulties are faced such as misclassification of disease affected plant as weed. Because weed detection is based on shape, color, texture features. So the system prescribes same fertilizers used for destroying weed not for disease. In this project an efficient weed and pest detection system has been proposed.
Literature Review
In 'Real-Time Specific Weed Recognition System Using Histogram Analysis' proposed the histogram analysis for real time weed classification system 6 . Control weeds with less herbicide to reduce production costs and to protect the environment. This algorithm is specifically developed to classify images into broad and narrow class for realtime selective herbicide application.
In 'Identification of Leaf Diseases in Tomato Plant Based on Wavelets and PCA', proposed the automatic identification of diseased leaves based on Wavelets and Principal component analysis 5 .
In 'Machine Vision System for Automatic Weeding Strategy in Oil Palm Plantation using Image Filtering Technique 10 ' proposed the an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. In 'Detection of weeds using image processing and clustering' proposed the classification based on the features reveals the type and number of weeds per image 7 . The weeds are extracted from the images described by shape features. Selection can be done using data mining algorithms, which rate the discriminants of the features of prototypes. A feature selection algorithms weight features according to their discrimination abilities.
In 'Color Image Processing of Weed Classification: A comparison of two Feature Extraction Technique', Keywords: Euclidean Distance, Leaf Parameters, Image-Processing, Plant Disease Detection, Weed Detection proposed to analyze which pre-processing method increase the efficiency of weed classification 8 . Two preprocessing techniques are greyscale conversion and excess green method. Along with these techniques two feature extraction techniques are compared for better accuracy. The excess green pre-processing method is effective compared to gray scale conversion for weed classification.
In 'Performance Improvement of Leaf Identification System Using Principal Component Analysis', proposed the leaf identification system using leaf parameters shape, vein, colour, and texture 9 . Using principal component analysis dimension of feature vectors are reduced from 54 to 25 and it is given as input to optimal classifier probabilistic neural network. High accuracy is reached when using 25 features on both dataset.
Modules
Following are the four modules of weed and pest detection system.
• Image Acquisition • Pre processing • Feature Extraction • Recognition Based on similarity Measure
Image Acquisition
The project begins with capturing tomato leaves. Image acquisition is done by Sony digital camera DSC-W510 with the resolution of 4000x2248 3,4 . Normal tomato leaves are captured in the white background. Meanwhile diseased tomato leaves also captured. Totally 60 images for training and 20 images for testing are captured in both normal and diseased leaf. For testing of weed leaf, 20 images of 3 kind of weed leafs are captured.
Pre Processing
After image acquisition images are not suitable for further processing. Pre-processing steps are applied to remove noise and to separate tomato leaves from its background. In this module five pre processing techniques are applied. They are 2,1 • Color Band separation • Excess green removal • Thresholding • Eroding • Dilation
Colour Band Separation
Capture the RGB values individually from captured colour image. Captured tomato leaves processed to separate three bands such as R, G, B. Input to this module is RGB IMAGE. Output is R, G, B bands that are separated from the input image. These values are calculated to find excess green image 2 . The Figure 1.2 shows R, G, B band for tomato leaf.
Excess Green Removal
Computation of excess green using the following formula 2 GE = 2 * G -B -R + 127 Where, GE = excess green image; G = green band image; B = blue band image; R = red band image; 127 = constant. Input to this module is R, G, B bands. Output from this module is Excess Green Image.
Thresholding
Threshold image is calculated. Input to this module is excess green image. Output from this module is threshold images.
Eroding
Erosion and dilation are morphological operations applied gray scale. In a gray scale image erosion reduces the brightness of objects on a dark. The image was eroded and dilated to avoid holes and blobs in the object. Erosion has been used to remove the linking objects. Using this technique, enhance and fine tune the image. Removing structures of certain shape and size, given by structure element. Input to this module is excess green image. Output is eroded image 8 .
Dilation
Dilation in the binary image is used to fill up blobs and holes in the images created and broken perimeter due to class variance or minor problems in thresholding 2 . Input to this module is eroded image. Output is dilated image.
Feature Extraction
Tomato leaf significantly varies from weed leaf images. Geometrical features like shape, color, texture features are extracted.
Shape Features
Shape features such as 2
Recognition Based on Similarity Distance Measure
Extracted features are stored in database. Two databases are maintained, one for normal tomato leaf and another for diseased tomato leaf. Here 4 tomato diseases popularly seen on tomato leaf are addressed. They are 3
Bacterial Pith
Leaves looks like yellowing and wilting blacking and moves to top of plant.
Early Blight
Initially appears a irregular lesions on oldest mature leaves near the ground; lesions expand, becoming dark brown and necrotic with concentric black rings giving a target-like appearance 3 ; may have chlorotic area surrounding lesion.
White Trail
Leaf miner moves on leaves. The adult stage of leaf miners is small yellow and black flies that insert their eggs into the leaves of plants. After hatching, the larvae of leaf miners feed between the leaves surfaces, resulting in the white squiggly lines you found on your tomato plant leaves 4 .
Spot
Lower leaves show symptoms first. Round, yellow or water-soaked spots appear on the undersides of leaves. They quickly emerge on leaf tops and turn to black or brown with tiny black dots in the center. Heavily infected leaves turn completely yellow, then brown, and fall 9-12 . Figure 1.5 shows steps followed in weed and pest (disease) detection system. The works begins with image acquisition. Captured images are pre-processed and trained to database. System is tested using test images of normal, diseased tomato leaf and weed leaf images. First it checks with normal (healthier) plant leaf parameters. If it is matched it is recognized as normal leaf 13 .
Otherwise check with disease parameter if it matches results as diseased leaf then provides, cause and solution. Test image features not matched with both parameters then it is recognized as weed. Euclidean distance measure 4 is used for similarity measure between images. Equation for Euclidean distance is shown below in Equation (2). Euclidean distance uses both features vectors of stored and testing values
Results and Discussions
Screen shots showing results of weed and disease detection system. Figure 1.6 shows given test image is recognized as weed. Figure 1.7 shows result as given plant image identified as diseased leaf 14 . In addition to identification cause and solution for disease also provided. Figure 1.8 shows test image is recognized as normal tomato leaf.
The system is trained with 100 images for both normal and diseased plant leaf. For testing 20 images in each kind of leaf like weed, normal tomato leaf and diseased tomato leaf are tested. Overall accuracy reached up to 92% for three kinds of leafs 15,16 .
Conclusion
In this system tomato plant leaves recognized using Euclidean distance. In this paper, an overview of the efficient weed and pest detection system is presented and similarity distance measure is obtained using feature vectors for better performance to find decision of leaf recognition. Therefore the system can help in reaching optimum accuracy of leaf recognition. A better and efficient solution overcoming the observed disadvantages is proposed. The design of the proposed solution and the implementation details of all modules are discussed.
Future Work
Thus, Weed and pest detection can be enhanced to account the various disease affected on the various parts of the plant for better efficiency than existing systems. The proposed system considers only for specific specie. Future work will consider all species. | v3-fos |
2019-01-02T06:31:42.350Z | {
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} | s2 | Diversity in the Dry Land Mixed System and Viability of Dairy Sheep Farming
Castilla La Mancha is a Spanish region where sheep farming system is traditionally pasture-based. Recently, this territory has undergone a recession of dairy sheep activity, which changed the type and intensity of land utilization and led to environmental and landscape degradation. The present study analyzed the diversity and viability of dairy sheep of mixed systems. Multivariate analysis was conducted on 157 dairy sheep farms, factor analysis selected 3 productivity factors (level of intensification, land use, size and family labour), and cluster analysis classified farms into three groups. Group 1, smallholders – with the smallest size (405.5 ewes and 564.7 ha), lowest area in ownership (1.5%), and agriculture activity (6.5% crops area): family farms (90.8%) highly dependent on external inputs. Group 2, large-scale farms (1058.7 ewes and 1755.1 ha) – with the lowest stocking rate (0.14 livestock unit/ha) and productivity: non-family farms (39.1%) with low area in ownership (4.1%) and agriculture activity (7.6%). Group 3, mixed-technified – with the highest levels of technology and least use of family labour (27.0%): large-scale farms (1387.4 ewes and 955.8 ha), combining milk production with agricultural activities (55.7% crops area), with the highest area in ownership (63.1%) and the best productivity performance. In conclusion, the dry land mixed system of Castilla La Mancha showed diversity of farms. Improving viability requires a systemic approach where the key tool is grazing, allowing the mixed system to be consolidated as a model that enhances the positive impact of livestock on the environment in the Mediterranean basin.
Introduction
The highest proportion of high nature value farmland in the Mediterranean basin corresponds to Greece, Portugal and Spain which have a ratio between 40 and 80% (Jouven et al., 2010). In these places, dairy sheep production is based on small family farms and is mainly characterized by family labour and grazing, where crop and livestock are developed in an integrated manner, in the so called mixed system (Robinson et al., 2011). The integration is especially related to the leading role of livestock in the system and the resources used for food (Peyraud et al., 2014), where the use of resources takes on special importance, either by grazing or use of byproducts (Molle et al., 2008;Milán et al., 2011).
In the last few decades the dairy sector has experienced a progressive specialization which could be explained by higher intensification and concentration of sheep flocks associated with the reduction in the number of farms and the marked increase in the number of animals per flock (Riedel et al., 2007;Gaspar et al., 2008). In consequence, the degree of mechanization and the individual productivity have been improved, while the cost of inputs has been decreased due to economies of scale (Castel et al., 2011;Riveiro et al., 2013). However, there also has been a reduction in the number of flocks due to a significant change in the structure of the dairy sheep sector, with many farmers abandoning the activity (Castel et al., 2011;Ripoll-Bosch et al., 2012). That intensive system of high inputs is environmentally unsustainable and has negative effects on the climate change, biodiversity loss, soil erosion, higher levels of water consumption, among others is demonstrated (Nahed-Toral et al., 2013). Also, this has prompted major changes in the nature and intensity of land use (Caballero, 2009;Jouven et al., 2010).
The mixed systems in Mediterranean basin; its ultimate objective is to allow the farmers to make a living from locally adapted dairy sheep production systems, which represent the core of Mediterranean dairy sheep industry (Molle et al., 2008).
Mixed systems help to maximize the positive interaction between agriculture, livestock, forestry and environment from an agro-ecolog-ical approach, and they have been suggested as a strategy that can effectively ensure the sustainability of the systems as a whole (Nahed Toral et al., 2013). In addition, sheep farming has traditionally been linked to the socalled non-productive functions (Milán et al., 2003), which recognized that environmental and socioeconomic benefits and social responsibility values are enhanced both by the production and consumption (Riedel et al., 2007).
In this context, dairy livestock in the Mediterranean basin is a worthy employment opportunity for a lot of people and responds to a dryland cereal-sheep system, which is the closest approximate version of the Mediterranean system. On the other hand, the progressive concentration and intensification of the mixed system has been described by Riedel et al. (2007), Caballero (2009) and Ripoll-Bosch et al. (2012), with the consequent change in grazing towards false grazing systems, whereby the animals graze daily but most of their nutritional requirements are covered by concentrates and forage given in the stable (Castel et al., 2011;Milán et al., 2011).
Castilla La Mancha is a Spanish region with a tradition of a typical pasture-based sheep farming system under continental Mediterranean conditions. In this territory, a notorious recession of dairy sheep activity has been observed in recent decades, which has originated changes in the type and intensity of land utilization and led to environmental and landscape degradation. Consequently, there are a great diversity of farms ranging from the traditional to the highly intensive system , which they must adjust to the basic payment criteria established by the reform of the Common Agricultural Policy for 2014-2020.
It will be convenient to deep in the knowledge of livestock system diversity, its characteristics, economic, techniques, and its role to the keeping of mixed system. Therefore, this study has a double objective. Firstly, the characterization of the different types of farms in the dry land mixed system from Castilla La Mancha according to the land use, the degree of dependence on external inputs, technology and production structure. Secondly, to analyze the viability of the different types of farms with a view to suggesting measures to make dairy sheep farming more competitive.
Data collection
The study area was the Spanish region of Castilla La Mancha (38°-41°N; 1°-5°W), whose surface area of roughly 800,000 ha is distributed as follows: 70% arable land, mostly given over to rainfed crops (95%), 20% woodland and 10% natural pastureland. The land is mostly flat. Climate is Mediterranean continental with dry winters and hot and dry summers. Rainfall is concentrated in autumn and spring, and is highly irregular, annual rainfall figure varying between 400 and 1000 mm. Mean winter temperatures range around 5°C, while mean summer temperatures average 25°C (Caballero, 2009).
Information was collected via farm visits and in situ interviews which were performed in 2012 by the same person. The survey was carried out on a random sample of 157 farms, representing 17% of existing farms. The interview questionnaire included 203 questions relating to the following aspects: location and use of land (15), facilities and infrastructure (19), flock size (13), labour force (9), feeding (22), grazing (4), breeding management (19), healthcare management (10), milking management and milk quality (53), economic issues (13) and social issues (26), according to the questionnaire used to study organic dairy sheep farming by Toro-Mújica et al. (2012).
Farm typology
The development of the typology is made from the methodology proposed by Escobar and Berdegué (1990), used by Toro-Mújica et al. (2012), which consists of three stages: review and selection of variables, factor analysis and cluster analysis. 181 variables were analysed; these are related to the production and economic structure, size, use and land possession, diversification of production, organization and flock management, productivity, socio-economic aspects and farm management.
In a first stage, 27 variables were selected, those with a coefficient of variation higher than 60%. Then we analysed the correlation matrix to eliminate uncorrelated variables and the one with lowest coefficient of variation of each pair with linear dependence (Toro-Mújica et al., 2012). Through the selection process were obtained the following 10 variables: family labour (%), stocking rate [livestock unit (LU)/ha; LU is a measure of livestock and it is usually defined as equivalent to one adult dairy cow, though in this paper it has been considered that 1 sheep=0.15 LU], lamb productivity (lambs/ha), milk productivity (kg/ha), total surface area (ha), cultivated area per ewe (ha/ewe), total investment per ewe (€/ewe), ownership surface per ewe (ha/ewe), ewes (n), and grazing area (%).
In a second stage, a factor analysis (FA) was used to reduce the number of variables and summarise most of the variability. Once the factors were selected, the orthogonal varimax rotation was applied to relate more easily the selected variables to the extracted factors. The Bartlett sphericity test and the Kaiser-Meyer-Olkin index (KMO) were applied to verify polymerase chain reaction adequacy (KMO>0.7; Gelasakis et al., 2012).
In a third stage, the farms were classified into groups using cluster analysis. Firstly, hierarchical groupings were developed based on Ward's method, using the Euclidean, squared Euclidean and Manhattan distances (Köbrich et al., 2003). The optimal number of clusters was selected using the Elbow method (Gelasakis et al., 2012). The optimal clustering was selected using discriminant analysis and analysis of variance (Toro-Mújica et al., 2012). It was chosen the clustering whose discriminant function classified correctly the highest percentage of farms and generated significant differences in the largest number of original variables. Additionally, the chi square test for categorical variables was employed to highlight contrast between groups of farms.
Farm economic viability
The viability of each farm was based on its economic results, and it was calculated according to the general accounting plan. The viability focuses on the ability of the business to generate, over the long term, sufficient profits for guaranteeing the maintenance of the family unit (European Commission, 1991;Argilés-Bosch, 2007). If a farm generated a positive economic return from 2011 to 2013, it would be considered as viable, and non-viable in other situations. A t-test was used to identify the variables affecting farm viability within each group (Toro-Mújica et al., 2011). All statistical analyses were performed using the SPSS 19.0 software package (SPSS, 2010).
The dry land sheep mixed system
The sheep production has been the main source for economic activity in 80.2% of the farms. The mean flock size was 868 sheep in 1117.7 ha total farm surface, consisting of 892.3 ha of rented land and 220.4 ha of owned land. The labour force was around 3.4 annual work units (AWU), of which 57.1% was labour family (Table 1). The mean investment per ewe was 1211.7 € ( Table 1).
The 83% of the total farm surface was used for grazing and the rest corresponded to cultivated surface (177.8 ha), including rain-fed cereals, vineyard and sunflowers. On average, 64% of feed was externally sourced. The most common feeding system (58%) was a mixture of unified and concentrate, although unbalanced regarding of productivity level or physiological status. The mean consumption of concentrate was around 0.8 kg/ewe/d. The reproduction was planned in 82% of farms and it was based on an average of three season mating. The rest farms (18%) maintained the ram with the ewes permanently throughout the year ( Table 2). The mean lambing interval was 341 d (Table 1).
The mean production was of 145.3 kg/ewe per lactation and 1.4 lambs per parity, and it implied a mean of 150.8 kg of milk per ha and 1.6 lambs/ha (Table 1). The mean revenue per sheep was 336.8 €/ewe, while the mean cost was 279.4 €/ewe. This means a mean benefit of 57.4 €/ewe. The mean unit cost was 2.2 €/kg of milk.
Factor analysis
Factor analysis yielded three factors (F), [Ital J Anim Sci vol.14:2015] [page 181] explaining 80.5% of the original variance (Table 3). Table 3 shows the Fs, the variance that each explains, their eigenvalue as well as the loading factor of the different variables with the Fs. The KMO test yielded a value of 0.739, while the result of the Bartlett sphericity test was significant (P<0.05); thus confirming the adequacy of data used for FA (Köbrich et al., 2003).
Factor 1 was denominated as productivity factor, accounting for 37.1% of variance and it showed a direct positive relationship between the stocking rate, lambs and milk per surface area. F2 was related to the land use, accounting for 29.2% of the variance and it showed a positive relationship between crop area, total investment and the ownership area, and a negative relationship with the grazing area. The third factor was a size factor and it accounted for 14.1% of total variance. There was a positive relationship between the total surface area and the flock size, while a negative relationship with the family workforce.
Farm typology
Cluster analysis which presented the most significant results was the solution of three groups with Ward's method, based on the Euclidean distances ( Figure 1). Table 1 shows the main characteristics of each type.
Group I: smallholder
It comprised 62 farms (39.5%) and had the smallest size (405.5 ewes and 564.7 ha) with the lowest area in ownership (1.5% ownership Diversity and viability of mixed farms (Table 1). It was established two feeding managements according to the animal's production stage. On the one hand, the milking group, which remained stabled and the feeding system used was concentrate and forage (63% of farms), although it was unbalanced by milk production in the 82% of the farms. On the other hand, the open group, which was composed of non-pregnant, no-milking pregnant ewes, rams, replacement ewe lambs and ewe lambs put. This group made grazing (98.4%) throughout the year on large rented areas of natural pasture and fallow.
Reproductive management was planned in 72.6% of farms, consisting of the 2.3 season mating; it differed (P<0.01) from that of mixed-technifed group. For the remainder (27.4%), rams are kept with ewes during all year. The lambing interval was 344 d (Table 1). This group showed the shortest lactation length (P<0.05) and the lowest milk yield (140.4 kg/ewe) with an intermediate figure in the milk productivity (124.2 kg/ha); it differed (P<0.01) from that of mixed-technified group ( Table 1). The average litter size was 1.4 lambs/parity and the mean productivity was of 1.3 lamb/ha, which was differed (P<0.01) from the mixed technified farms (Table 1). The mean unitary cost was 2.2 €/kg of milk, intermediate for the rest of the groups, although the mean benefit (36.4 €/ewe) was the lowest in the three groups.
Group 2: large-scale farms
This group comprised 63 farms (40.1%). They are large-scale farms (1.058.7 ewes and 1.755.1 ha) with the lowest stocking rate (0.14 LU/ha). It corresponded to non-family farms (39.1% family labour) with low area in ownership (4.1%) and agriculture activity (7.6%). These farms derived most of their entrance from sheep farming (88.8%).
The cultivated area was given over largely to forage crops for livestock feeding. The feeding was balanced according to the production stage in the half of farms. The milking flock and ewes closest to the lambing were stabled and the feeding system was unifeed and concentrate (0.67 kg/ewe/d) in the 69.8% of the cases. The open group was composed of nopregnant and early-pregnant ewes, rams, replacement ewe lambs and ewe lambs put.
This group makes grazing (98.4%) throughout the year on large areas of natural pasture, so as grassland and stubble fields. Sixty-two percent of externally-sourced feed was concentrate and industrial by-products.
The reproductive management was planned at 90% of farms and comprised, on average, 3.7 season mating; it differed (P<0.01) from smallholder group. The lambing interval was 345.5 d (Table 1). Although the milk production per lactation presented the higher level of all groups (151.6 kg/ewe per lactation), the mean duration of lactation was medium in comparison to the rest of groups (137.1 d; P<0.01). Consequently, both milk (117.1kg/ha) and lamb productivity (1.2 lamb/ha) was the lowest of all groups (Table 1). To an economic level, although this group presented a lower unit cost (1.9 €/kg of milk), it obtained an intermediate benefit (50.2 €/ewe).
Group 3: mixed technified farms
It corresponded to 32 farms (20.4%) and consisted of large-scale farms (1387.4 ewes and 955.8 ha) with higher levels of technology and less use of family labour (27.0% family labour). This group combined milk production with agricultural activities (55.7% crops area), had the highest area in ownership (63.1% ownership area) and obtained the best performance in terms of productivity (268.5 kg of milk per ha and 2.9 lambs per ha).
The feeding was balanced according to the productive and reproductive stage of the flock on the 56.3% of the farms. The milking flock and ewes closest to the lambing were stabled and the feeding system was unifeed and concentrate (0.66 kg/ewe/d). The feeding for the open group was also based on pastures although as a differentiation from other groups, technological improvements are implemented as sub-divisions in the pastures area (Table 2). Forty-six percent of externallysourced feed consisted of concentrate and industrial by-products. This group had the highest stocking rate (0.35 LU/ha) due to the grazing surface (412.1 ha) was the lowest of all groups (Table 1).
The reproductive management was planned in the 87.5% of the farms and comprises, on average, 4.2 season mating. The production per lactation (142.6 kg/ewe) was in between the rest of the groups, although it showed a duration per lactation (126 d) under the rest of the groups.
In the economical aspect, this group presented the highest unit cost (2.6 €/kg of milk) while it obtained the highest economical returns (112.3 €/ewe) from the three groups.
Farm economic viability
The typological group was not associated at a great extent with the economic viability of the farm (P>0.05; Table 2). The smallholders group presented 46 viable farms (74.2%). Viable farms in group 1 owned a flock of a 37.3% higher than non-viable farms and were more productive (Figure 2). Viable farms were also differentiated by the fact that was less dependent on external food and in the number of mating seasons. Besides, the labour at nonviable farms was exclusively family-based, while viable farms employed hired labour. The large-scale farms comprised 50 viable farms (79.4%). Viable farms in group 2 owned a flock a 35% bigger and lactations were shorter and more productive (Figure 3) than in nonviable farms. Viable farms were also differentiated by its less dependence on external food.
Diversity and viability of mixed farms
The technified mixed farms comprised 27 viable farms (84.4%). Viable farms from group 3 made a less intensive use of land and get lower degrees of production per ha, although based on the offering of less external food (66%). Besides, the predominant labour was employed (Figure 4).
Discussion
According to Caballero (2001), sheep production in Castilla La Mancha was a stable system, from data coming from official records for the entire region from 1969-1995. After the entry of Spain in the EU in 1986 some structural changes took place in the sector that collects the typology of cereal-sheep farming systems elabourated by Caballero (2001). The results of this study indicate that sheep has improved its development as productive and economic activity of importance in the mixed system. Apart from this, the production has been substantially improved, especially the milk one. On the one hand, flocks are bigger in size and genetically improved, due to the official programme of milk improvement in the Manchega race (AGRAMA, 2011). On the other hand, technological improvements in the milking and reproduction management have been implemented. Currently the mixed cereal sheep system in Castilla La Mancha is immersed in a dynamic change process, where the trend to reduce the number of exploitations and remaining farms are becoming larger and more specialized in dairy livestock. This article allows to nuance this approach by showing that changes are forcing a farmer to adapt a more competitive situation with less viability of the farms and that reveal a new diversification in dairy farming models with new types of organization; in terms of production practices, work, management and partnership of family farms (Bernard de Raymond, 2013).
The interrelationship amongst natural, agricultural and farming resources that are established in the mix systems are flexible and dynamic and conditioned by the political and economic context of the moment (Argilés-Bosch, 2007). This makes diversity one of the main attributes of any mix system (Robinson et al., 2011;Peyraud et al., 2014). Diversity must be reduced by defining groups of farms with common characteristics based on the search for the largest difference between groups and the smallest difference within groups (Riveiro et al., 2013) where the multivariate statistical techniques provide a means of creating the required typologies, particularly when an exhaustive database is available (Köbrich et al., 2003).
Factor analysis (Table 3) showed that the diversity in the mixed system in Castilla La Mancha is mainly linked to land use, the degree of dependence on external inputs, technology and productive structure. These results fit with Milán et al. (2003), Gaspar et al. (2008), Castel et al. (2011), andToro-Mújica et al. (2012).
The subsequent cluster analysis allowed to identify three groups of farms (Table 1): smallholders, large-scale farms and mixed-technified farms. Caballero (2001) built a typology of farms based on the same cereal-sheep mixed system in Castilla La Mancha, where he described three productive sub-systems: with no land farms, small farms and big farms. Although the Caballero typology (2001) was focused in structural aspects, it is a referent to analyze and understand the evolution of the system.
The with no land farm would maintain small size flocks (233 ewes) that were located next to the place or in hired lands. It was a system of family subsistence and double productive aptitude. The small size farms, with 40 ha as a mean in agricultural surface, were mainly dedicated to the growing of cereals and maintained 322 ewes in mean. They were family farms oriented to mild production. Both groups were concentrated in big areas of pastures named parceled polygons ruled under the current regional Pasture and Stubble Act regulating by the Castilla La Mancha government (Caballero, 2009). The smallholders and large-scale groups identified in this study probably constitute the evolution of the farms that belong to the farms with no land and small farms identified by Caballero (2001). The main causes for this evolution are the progressive organization around the parceled polygons and the European funds that facilitate the access to land and the increase or the flock size (Ryschawy et al., 2012). Caballero (2001) also described big farms ass the ones composed by segregated polygons. These ones own their own land for agriculture (31%) and maintain flocks of 420 sheep in mean with an orientation to the production of milk and meat. The ownership of the land and Rivas et al. The smallholder group corresponds to small family that could be classified as traditional improved, according to the FAO classification (Robinson et al., 2011). This group is similar to Semi-intensive, low-investment farms described by Gelasakis et al. (2012) in Chios dairy farms, even if it has a higher average size.
The large-scale and mixed technified groups correspond to large-sized farms (1222 ewes per farm an average) and comprise 60.5% of the farms. These large-sized farms are similar to Large traditional farm reported by Riveiro et al. (2013) in Assaf sheep farms. Most part of the mixed technified farms have done heavy investments (Table 1), even higher than the reported by Riveiro et al. (2013), with a view to maximizing overall farm performance and to taking advantage of technological synergies involving both strands of activity (Milán et al., 2011;Riveiro et al., 2013). This way some farms include a specialized way similar a dairy cow systems, with a low proportion of grazing the surface, high intensification and full stabling, indicating that the trend towards specialization runs counter to more traditional management practices (grazing), which drives to an environmental unsustainable model and questionable economic viability (Nahed-Toral et al., 2013). Similarly, farms with high levels of intensification are more sensitive to the current market uncertainty (Ripoll-Bosch et al., 2012;de Rancourt et al., 2006).
Apart from this, the increase in the flock size attempts to maintain an acceptable level of income (Riveiro et al., 2013). In this study, farms with more ewes corresponded to higher surface (1,350 ha an average), mainly hired and used to pastures (Tables 1 and 2), aspect that constitutes a strength in the Manchega sheep and an advantage for these production systems (Caballero, 2001(Caballero, , 2009. These farms kept a low level of family workforce (33%), indicating that greater farm-size relates with el mayor number of employees; as a difference to the family character shown in the milk sheep farms in the Northeast of Spain by Milán et al. (2011), in Greece by Gelasakis et al. (2012) and in ecological sheep in Castilla-La Mancha-Spain by Toro-Mújica et al. (2012). Apart from these results a considerable proportion of with no land farms (39.1%) are obtained, and these ones correspond to the smallholder group.
Diversification is another way to achieve a reasonable level of income, or a strategy to face uncertainty, including agricultural crops as a complementary activity (Caballero, 2009;Riveiro et al., 2013). This option has been observed in only 13% of large-sized farms with large UAA (mixed technified).
By the other hand the classification of farms according to viability enables the evaluation of their challenges of survival (Toro-Mújica et al., 2011). Inside each group there is homogeneity and a high percentage of viable farms in which their improvements depend on a systemic focus of the productive process where grazing is the key element.
The smallholder group shows the higher percentage of non-viable farms (10%) and according to the decrease in the returns reported by de Rancourt et al. (2006), and the social aspects (that have not been considered in this analysis), even under good economic conditions this type of farms is very likely to disappear when their owner's retirement (Riveiro et al., 2013). Opposite to what it is expected, the challenges to family farming do not depend on an increase in the dimension; but they required of deep changes in the managerial functions, in what it should be done (planning), who does it (organization) and how it should be done (managing and control) , mainly in aspects such as the workforce and the implementation of the best livestock practices (housing and facilities, programming of the mating season, feeding, etc.). Unless these problems are previously analyzed and the best practices according to the structural restrictions are considered (Bernués et al., 2011), such as fragmentation and land ownership (Caballero, 2009), a great level of risk could be generated in the farm. For example, to increase the size of the flock and implement new reproductive techniques as the artificial insemination or improved genetic males would drive to higher costs and poor reproductive performance. This way, the results of a poor planning, organization, managing and control are frequently associated to the reproductive failure with percentages of empty females in comparison with the inseminated between the el 70 and the 90% .
The viable farms in the large-scale group have decided to put into practice a feeding system mainly including unified and concentration of lambing seasons. The non viable firms in the large scale group show similar problems to the smallholders groups, although they soften the organization deficiencies by means of their dimension; however they must do an effort in the managerial functions of planning, managing and control mainly in the aspects of managing the feeding and reproduction. This last one, together with the managing of information, are considered to have minor consequences for the farmers' point of view .
Mixed-technified farms have sufficient arable land to produce their own livestock feed, although in doing so farms use a diversity of organizational strategies. The advantage of the system is that it constitutes an integral model situated in the middle between agriculture and farmer. The advantage of the system is that it constitutes an integral model between the agricultural and farming activities although limited by the capacity of the surface and the dimension that will drive to a low dependence on external inputs (Rivas et al., 2013). An 84% of the mixed-technified farms of low-inputs with grazing coming from the waste of crops of these farms are viable, taking the advantages of economies of scale, and the technological adoption both are a key condition for development. The farms that are not viable in the mixed technified system must reinforce the managerial function of planning mainly in the use of the land and the implementation of technologies that improve the practice of grazing and decrease the dependence on external inputs. At the same time farms must be careful with the organization of work, especially the family workforce must be put into value to increase its productivity (Bernués et al., 2011).
Conclusions
The typology constructed allowed to identify and offer a characterization of three groups of farms. Smallholder group consists of small size family farms with high dependence on external inputs. Large-scale group corresponds to non-family farms with low productivity and agriculture activity. Mixed-technified consists of large-scale farms with higher levels of technology and less use of family labour. This group combines milk production with agricultural activities and obtains the best performance in terms of productivity.
The improvement of viability in all groups depends on the systemic focus of the productive inputs, oriented to a rational use of land and a proper adoption of technology, the organization of work and the implementation of best livestock practices. The smallholders and large-scale farms have done a great effort to Diversity and viability of mixed farms [page 186] [Ital J Anim Sci vol.14:2015] adapt the environment by transforming the structure of the family firm, by changing their life style and modernizing the reproductive techniques. The viability of both groups requires improvements in the managerial functions, mainly in planning and organization. The mixed-technified farms are those that have shown a better alignment of the use of the land and the reaching of economic results. Any effective strategy aimed at ensuring the viability and sustainability of mixed system should improve the planning in the use of land by means of the knowledge based on the best grazing practices.
The identification of a typology of farms and its classification into viable or not viable constitutes a simple technique for diagnosing and it is useful to promote improvements in the mixed systems. | v3-fos |
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} | s2 | THE IMPACT OF FOLIAR NUTRITION ON THE YIELD OF BEETROOT CROP GROWN IN HIGH FERTILITY SOIL SUMMARY The main purpose of this research is to determine the impact of soil fertility and foliar nutrition on the yield of beetroot crop grown near by the village Negorci, Gevgelija. The experiment was set up as a randomized complete block design in 2012 and 2013, with four treatments in three replications. The treatments in the experiment were as follows: 1.Control (unfertilized); 2.Foliar nutrition with Humusil fertilizer; 3.Foliar nutrition with Humustim fertilizer; and 4.Foliar nutrition with Ingrasamant foliar fertilizer. Foliar treatments of these
The main purpose of this research is to determine the impact of soil fertility and foliar nutrition on the yield of beetroot crop grown near by the village Negorci, Gevgelija. The experiment was set up as a randomized complete block design in 2012 and 2013, with four treatments in three replications. The treatments in the experiment were as follows: 1.Control (unfertilized); 2.Foliar nutrition with Humusil fertilizer; 3.Foliar nutrition with Humustim fertilizer; and 4.Foliar nutrition with Ingrasamant foliar fertilizer. Foliar treatments of these three fertilizers were performed in form of 0.3 percent solution during the vegetative period. Before the experiment was set up, determination of soil type was carried out, wherein the identified soil type was alluvial soil. Soil sampling was also performed in order to determine some chemical properties of the soil. The analysis of soil fertility showed that levels of nitrogen, phosphorus and potassium in available forms were high. After harvesting the beetroot crop and measuring the yield, it was concluded that foliar nutrition and high content of available forms of nitrogen, phosphorus and potassium in the soil, had a positive impact on the yield of all three treatments. The highest average yield of 71.68 tonnes per hectare in two years of investigation was achieved in the treatment with application of Ingrasamant foliar.
INTRODUCTION
Fertilization is one of the most important agricultural practices for ensuring good agricultural production. Controlled and well-dosed use of fertilizers keeps production of each crop sustainable. Very often, in order to achieve higher yields, fertilizers are applied in enormously high amounts. Uncontrolled use of fertilizers does not only have a negative impact on products quality, but it also leads to many environmental problems, which has long term consequences on the ecosystem in general. This is why fertilization is a very complex process which deserves greater attention.
Fertilization is an important factor in beetroot crop production technology to achieve optimum yield and root quality. The beetroot crop is a plant with high nutrient demands because of forming abundant vegetative mass and many roots at the unit area. It is a great consumer of nitrogen, phosphorus, potassium, magnesium and calcium, as well as micro elements (Fit and Hangan 2010).
Foliar nutrition is an application of water soluble fertilizers directly to the leaf. Foliar fertilizers are quickly absorbed by plants and commonly are used as nutritional supplements for the plants ) and as alternative nutrition in conditions when plants show high necessity for nutrients or in cases of deficiency in soil fertility.
Foliar nutrition is ideally designed to provide many elements in conditions that may be limiting production at a time when nutrient uptake from the soil is inefficient or nonexistent (Hiller, 1995).
The use of foliar fertilizers is becoming increasingly widespread and they are environmentally friendly and target focused, because unlike soil fertilizers, foliar fertilizers are assimilated directly into the organism in small quantities . The effectiveness of foliar fertilizers is estimated based on the assimilation and availability of the elements (Lea-Cox andSyvertsen 1995, Zhang andBrown 1999), reduction of phytotoxicity (Neuman and Prinz 1975), deficiency (Rombolà et al. 2000) and on the yield and the quality of the culture (Dong et al. 2005).
On the market there are different foliar fertilizers, which are often mixture of micronutrients and secondary nutrients. Their application is recommended in order to increase crop yield and quality of beetroot crop (Jablonski, 2003, Mousavi et al. 2007 The beetroot crop is particularly demanding in terms of soil properties and fertility. The best yields can be achieved on fertile, deep soils, which are rich in organic matter and have good water-air regime. These properties are typical for alluvial soils, meadow soils as well as chernozem, while in heavy and dense soils, deformation of the root, low yield and poor quality may occur (Lazić et al. 1998).
The beetroot crop uptakes large amounts of nutrients. The edible part of beetroot crop has good quality if it is uniformly formed, without delays or disruptions in development. It is therefore necessary nutrients to be in easily available form and in sufficient quantities. Beetroot crop has high nutrient requirements, but can contain high levels of nitrates if it is fertilize with high amounts of nitrogen. By 10 tonnes yield, beetroot crop takes out 30 kg N, 10 kg P 2 O 5 and 50 kg K 2 O from the soil (Gjurovka, 2008).
The experiment was set up as a randomized complete block design with four treatments and three replications (plots) and total size of experimental field of 96 m 2 . The size of each plot (replication) was 8 m 2 (100 plants in 0.40 m of row spacing and 0.20 m plant spacing in the row). In each treatment were included 300 plants. Investigation was carried out on alluvial soil, quite common for beetroot crop production in Gevgelija region. In order to determine the agrochemical and physical soil properties, the soil analysis were performed before setting up the experiment. The experimental field for years ago has been used for vegetable production, and was intensely fertilized with mineral and organic fertilizers. The field experiment is provided with irrigation from private wells and the relief is flat. Meteorological parameters for average temperatures and monthly rainfalls during the investigation were provided from the National Hydrometeorogical Service of Republic of Macedonia.
According to mechanical-chemical composition (Table 1), the arable layer (0-40 cm) is loam whereas physical clay fraction is represented by 55.4%, field capacity is 33.69% and with porosity of 50.90%.
In terms of pH reaction, the analyzed soil show neutral to slightly alkaline reaction, which is suitable for growing beetroot crop. Beetroot is sensitive to the soil reaction. For normal growth and development and favorable yields the best pH reaction of the soil should be ranged from 6.5 to 7.00 (Gjurovka, 2008). The acidic soils lead to lower yields and poor quality of the root (Lazić et al. 1998 x -mean; σ (SD)-standard deviation From the results of the chemical soil properties, we can conclude that there is an enormous imbalance of nutritional regime in the soil, especially the content of available nutrient elements. Namely, the content of the three basic biogenic macro elements is relatively high; especially alarming is the phosphorus content. Laboratory analyses were performed by standard methods (Džamić et al. 1996, Bormann, 2007, Pelivanoska, 2011, Mitrikeski and Mitkova 2013.
The use of soil fertilizers may have a negative effect and would further deteriorate the current soil fertility and adversely affect other components of the environment. The purpose of agricultural crop production is to get higher yields with improved quality and environment protection in the same time. These can be achieved by applying foliar fertilizers and cultivation of varieties suitable for current soil properties.
RESULTS AND DISCUSSION
Climate and soil are the most important factors that affect the yield and quality of beetroot crop (Petrov, 2014). The Gevgelija region is characterized by a warm modified Mediterranean climate (Filiposki, 1996). Precipitation and air temperature are meteorological factors that play major role in open field production. The results from our investigations on these two parameters are presented in Table 3 and 4. The total amount of precipitation from May to August during 2012 and 2013 was 204.9 and 111.8 mm respectively (Table 3). In later stages of growth longer dry periods appeared, followed by high temperatures which increased the evaporation rate, so the beetroot crop had no ability to satisfy the water requirements for normal plant development. Irrigation is an important measure for proper high and quality crop production in Republic of Macedonia (Tanaskovik et al. 2011), especially in dry periods, when soil nutrients are less available for plants. The temperature is a major climatic factor for development of beetroot crop. The optimum temperature for beetroot crop growth is 15-23 o С (Aladzajkov, 1966, Lazić et. al. 1998, Gjurovka, 2008. During the two-year field investigations, the mean daily and monthly temperatures ranged within the optimum values (Table 4). The maximum temperature values were noted in July and August, with average values of 28.4 and 27.6 0 C respectively. From the obtained data presented in Table 5, we can conclude that the beetroot yields in all investigated treatments are pretty high or more than 64 tonnes per hectare. Namely, the highest yield is achieved in treatment four with 71.68 tonnes per hectare or about 6.9 tonnes per hectare more yield compared with control treatment. If our results for yields are presented in comparative values, than treatment four shows almost 11% higher yield compared with control treatment. Treatments number two and three yielded 3 and almost 6% higher in comparison with control treatment. The results are statistically significant at 0.05 level of probability. Regarding the yields between the experimental years, there were noted differences that are result of meteorological conditions. Generally, the results in our study are higher compared with average yields in the literature data for beetroot crop in Republic of Macedonia ranging from 20 to 40 tonnes per hectare (Aladzajkov, 1966). Similar yields to average in Macedonia, but with more recent data, were obtained in Seychelles with different varieties grown on sandy-loam soil and with average yield of about 36.43 tonnes per hectare (Ijoyah et al. 2008 .60 *Values in rows followed by the same letter are not significantly different at the 0.05 probability level As we mentioned above, the results in our study shows untypical high yields in treatment without fertilization, which can be ascribed of soil fertility (high content of total and available forms of nitrogen and enormously high content of available forms of phosphorus and potassium). As a result of improper and uncontrolled fertilizers management in agricultural production in the country (Tanaskovik et al. 2011), many soil types used for vegetables production are brought into a state of impaired nutritive regime (Tanaskovik et al. 2009). Unfortunately, this was confirmed in our study, too. So, application of additional soil fertilizers in such soil condition would only have a negative impact on crop production and environment. In this case, the most economical and environmentally friendly acceptable measure is growing crops that can exploit available nutrients in the soil with proper foliar nutrition according to soil analysis and plant needs.
CONCLUSIONS
In high soil fertility conditions with previously conducted soil analysis, the application of ecological foliar fertilizers consisted by macro and micro biogenic elements and plant extracts without soil fertilization enables in average 68.98 tonnes per hectare yields. This is very important especially if we want to protect the environment from additional fertilization in high fertility soil, as well as to reduce production costs of beetroot crop. | v3-fos |
2018-04-03T04:10:51.138Z | {
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} | s2 | Physicochemical Characteristics and Composition of Three Morphotypes of Cyperus esculentus Tubers and Tuber Oils
Tuber characteristics and nutrient composition of three morphotypes of Cyperus esculentus tubers and tuber oils were determined. The mean value for length and width of the tuber and one thousand dried tuber weights ranged from 0.98 to 1.31 cm, 0.90 to 1.19 cm, and 598 to 1044 g, respectively. Tubers displayed high level of starch (30.54–33.21 g 100 g−1), lipid (24.91–28.94 g 100 g−1), and sucrose (17.98–20.39 g 100 g−1). The yellow tubers had significantly higher content in lipid compared to black ones. Levels of ascorbic acid, tocopherol, and β-carotene of the three morphotypes differed significantly. Yellow ones (morphotypes 1 and 2) were the richest in tocopherol and the poorest in β-carotene. Saturated fatty acid content of morphotype 2 was significantly lower than that of morphotypes 1 and 3. Morphotype 3 had the significantly lowest PUFA content compared to morphotypes 1 and 2. Morphotype 1 was found to be richer in Ca, Cu, and Mn contents. Al, Mg, P, S, and Si were most abundant in morphotype 2. Morphotype 3 had the highest content of Cl, K, and Zn.
Introduction
Cyperaceae is a family of monocotyledonous graminoid flowering plants known as sedges, which superficially resemble grasses or rushes. About 5,500 species have been described in the family [1] including Cyperus esculentus. Cyperus esculentus provides edible tubers commonly called tigernut, chufa sedge, nut grass, yellow nutsedge, tigernut sedge, or earth almond. Tigernut is a perennial crop cultivated particularly in tropical and subtropical areas worldwide and extensively in Africa, Asia, and some European countries for their sweetish tubers. In Africa, tigernut is mostly cultivated in the west, Ivory Coast, Ghana, Mali, Niger, Nigeria, Senegal and Togo where they are used primarily uncooked as a side dish [2].
The tubers are used fresh as a vegetable or dried as a sweet snack. They are also grinded into flour and used as a thickener, for bread and cakes or mixed with water as drink. The tubers are often considered as "health" food because they have excellent nutritional properties and prevent heart diseases and thrombosis. Tigernut is known to activate blood circulation, to reduce risk of colon cancer and diabetes, and to favor weight loss [3]. Tigernut is also known to have aphrodisiac, carminative, diuretic, emmenagogue, stimulant, and tonic effects and even some medicinal uses such as treatment of flatulence, indigestion, diarrhea, dysentery, and excessive thirst [4]. Tigernut is used as livestock food and is in southern USA ranked among the top 10 most important waterfowl foods [5]. Tigernut flour is a rich source of 2 Journal of Analytical Methods in Chemistry carbohydrate, oil, and some useful mineral elements such as iron and calcium which are necessary for body growth and development [6,7]. Three varieties have been reported on the basis of their color, namely, yellow, black, and brown varieties [8]. Tigernut was reported to be rich in carbohydrates, dietary fiber, lipids, and oleic acid [3,9]. Despite its great potentialities the tigernut remains an underutilized plant [7]. Most of the studies focused on the yellow variety while very little information exists on the physical characteristics of tigernut tubers. A better understanding of morphological parameters of the tigernut tubers as well as their link to the nutrition composition will help to identify valuable varieties and promote their use. So, this crop could contribute to the poverty alleviation among vulnerable populations, particularly rural women, in Western Africa. The aim of this study was to determine the physical traits as well as the chemical characteristics of the tubers from the three morphotypes of tigernut grown in Burkina Faso. . Five kilograms of tubers was collected in each village, immediately hand-sorted to eliminate damaged ones, and taken to the laboratory. Prior to any analysis, the samples were washed with distilled water, drained, and airdried. Each village sample was split into two parts; one part was finely ground with a Moulinex grinder robot (GT550, Zurich, Switzerland). Both parts were packing in an airtight container and stored at −18 ∘ C until analysis.
Physical Analysis.
To determine the mean length and width of the tubers, 100 tubers were per village randomly picked and their two linear dimensions were measured using a Vernier caliper with an accuracy of 0.01 mm (Canon Instruments, Japan). The thousand dried tubers weight (TSW) was obtained by counting 1000 dried tubers and weighted on an electronic balance to 0.001 g accuracy (Ohaus, USA). The variation in tubers size and color was used to classify the tigernut into different morphotypes.
Chemical Analysis.
The official methods of the Association of Official Analytical Chemists [10] were used to determine moisture, protein, crude oil, and ash contents of the tubers. Moisture (g water 100 g −1 sample) was determined by drying a 3 g ground sample at 105 ∘ C to constant weight. Nitrogen content was determined by using the Kjeldahl method and multiplied by a factor of 6.25 to determine the crude protein content (g protein 100 g −1 sample). Crude fat (g fat 100 g −1 sample) was obtained by exhaustively extracting 5.0 g of each sample in a Soxhlet apparatus using petroleum ether (boiling point range 40-60 ∘ C) as the extractant. Mineralization was performed on 3 g samples by combustion in a muffle furnace at 550 ∘ C for 8 h (g ash 100 g −1 sample) (AOAC 920.39C). Carbohydrate content was estimated by difference of mean values: 100 − (sum of percentages of ash, protein, and lipids) [11].
Starch and Sugar
Analysis. AOAC method 996.11 was used to determine starch content of Cyperus esculentus tuber flours. The assay consisted of using thermostable alphaamylase and amyloglucosidase to enzymatically hydrolyze starch into glucose that was then quantified with a spectrophotometer ( Quant, Bioteck Instruments Inc, USA). Glucose, sucrose fructose, and maltose were analyzed by HPLC according to the AOAC Official Method 982.14 [12]. Samples for HPLC sugars analysis were prepared by homogenizing 0.3 g of Cyperus esculentus flour in 3 mL distilled water and 7 mL 95% alcohol and shaken before being centrifuged at 10 000 rpm for 20 min. The clear supernatant was filtered through 0.45 m filter and degasified before analysis by HPLC. Filtered solution (20 L) was injected into HPLC 1100 Series (Agilent, Waldbronn, Germany) equipped with a G1362A refractive index detector. Sugars were separated using a commercially packed with Zobax-NH 2 column (250 × 4.6 mm (Dupont, Wilmington, DE, USA)) with a particle size of 5 m and thermostatized at 30 ∘ C. The filtered and degasified mixture of acetonitrile/water (80/20) was used as mobile phase at a flow rate of 1 mL/min for 30 min run time [13]. The sugars peaks were identified by comparing their retention times with individual standard sucrose, maltose, glucose, and fructose approximately 99% pure (Sigma-Aldrich, Steinheim, Germany) and the chromatograms analyzed using the Agilent Technologies Chemstation Software.
Vitamin
Analysis. Vitamin C was determined in tubers as previously described [14,15]. An aliquot of 25 g of tigernut was added to 25 mL of a solution containing 45 g/L metaphosphoric acid and 7.2 g/L of DL-1,4-dithiotreitol (DTT). The mixture was homogenized and centrifuged at 22,100 g for 15 min at 4 ∘ C. The supernatant was vacuum-filtered through Whatman no. 1 filter. Prior to HPLC analysis, the vacuumfiltered samples (10 mL) were passed through a Millipore 0.45 m membrane. Then, 20 L was injected into a HPLC system fitted with a reversed-phase column, C18 Spherisorb ODS2 (5 m) stainless-steel column (4.6 mm × 250 cm). The mobile phase was a 0.01% sulphuric acid solution adjusted to a pH of 2.6, at a flow rate of 1 mL/min at room temperature. Detection was performed at 245 nm with 486 Absorbance Detector (Waters, Milford, MA). Vitamin C was quantified through a calibration curve built with ACS grade ascorbic acid (>99% pure, Sigma-Aldrich, Steinheim, Germany) pure standards in the range of 0.2-50 g/mL.
To determine vitamin E ( -tocopherol) and -carotene, approximately 5 g of ground samples were extracted with 50.0 mL of hexane. The mixture was then vortexed for 5 min and filtered using 0.2 m pore size PTFE membrane. The filtered hexane fraction was directly injected into RP-HPLC system for -carotene and vitamin E analysis [16]. The RP-HPLC system (Shimadzu) consisted of an autosampler and column oven equipped with Inertsil ODS-3V (250 × 4.6 mm, 5 m) reversed-phase column. For -carotene analysis, mobile phase was acetonitrile (6 : 4, v/v, containing 0.05: BHA as antioxidant) (eluent A) and MeOH (eluent B). The following gradient was used: initial condition was 70% (A) and 30% (B) for 5 min, followed by 80% (A) and 20% (B) for 5 min, at a flow rate of 1.5 mL/min. Elution was monitored using a photodiode-array detector at 472 nm [17]. For vitamin E content, methanol mobile phase was used at a flow rate of 1.0 mL/min. The -tocopherol was detected by a Shimadzu SPD-10A (UV/VIS) detector (292 nm wavelength). Standards of -carotene (≥97.0% purity, Sigma-Aldrich, Steinheim, Germany) and DL--tocopherol (≥96% purity, Sigma-Aldrich, Steinheim, Germany) ranging from 0.5 to 6.0 g/mL and from 0.02 to 1.0 g/mL were used for calibration.
Tuber Oil Fatty Acids Analysis.
Fatty acid methyl esters were determined according to International Union of Pure and Applied Chemistry (IUPAC) method II.D.19 [18]. On hundred milligrams of extracted oils was saponified in a volumetric flask, with 1.2 mL of 0.5 M KOH in MeOH by heating and stirring under reflux for 5 min. After saponification oils were esterified by adding 1.2 mL 20% borontrifluoride through condenser and boiled for 2 min and then the flask was moved from the magnetic stirrer and fatty acid methyl esters were extracted by adding 1 mL of n-hexane. Saturated NaCl solution was added until the n-hexane is in the neck of volumetric flask, mixed carefully, flipped once or twice, and let settle for about 30 min. After separation the n-hexane phase was transferred to a vial for fatty acid methyl esters analysis. Gas chromatography (GC) of fatty acid methyl esters was performed using a Perkin Elmer GC-autosystem XL with a programmable temperature vaporizer (PTV) split-injector and a flame ionization detector (FID). Helium was used as carrier gas. The column temperature was initially maintained at 100 ∘ C for 2 min and then raised by 5 ∘ C/min to 225 ∘ C and finally held at 225 ∘ C for 16 min. The injection volume was 0.2 L with a 1 : 100 split. The PTV injector was initially maintained at 50 ∘ C and immediately after the injection raised to 270 ∘ C. The FID was kept at 250 ∘ C. The capillary column employed was CP Sil 88 (Chrompak, Varian Instruments, Walnut Creek, CA; 50.0 m × 0.25 mm and 0.2 m film thickness). The peaks were identified by comparing retention times with authentic fatty acid methyl esters. Quantification was based on the area under each fatty acid peak as compared to the total area of all fatty acid peaks.
Mineral Composition of Powered
Tubers. The elements, Mg, P, Cr, Fe, Mn, Cu, Zn, Sr, Ca, K, and Cd, in digests were measured using an atomic absorption spectrophotometer (Analyst 800, Perkin-Elmer) and/or a coupled plasma mass Spectrophotometer (ELAN DRCII Axial Field Technology, Perkin-Elmer). About 0.2 g of powered tuber was digested with 3 mL of HNO 3 (65%) and 0.5 mL of H 2 O 2 (30%) in a closed vessel microwave digestion system (MLS-ETHOS plus) and diluted to 50 mL with Millipore water. Digestion conditions for the microwave system were applied as follows: 2 min for 250 W, 2 min for 0 W, 6 min for 250 W, 5 min for 400 W, 8 min for 550 W, and vent for 8 min. A blank digest was carried out in the same way. Al, Si, S, and Cl were analysis by polarized Energy Dispersive X Ray Fluorescent (EDXRF), Spectro X-LAB 2000. Prior to analysis, 4 g of ground dried samples triplicate was pelleted by 5 tons using SpectroPess (Chemplex Industries, Inc.) and then pellets were analyzed using different excitation conditions with an EDXRF spectrometer [19]. Standard Reference Material 1568a rice flour was obtained from National Institute of Standards and Technology, Gaithersburg, USA, and was used as food reference material to evaluate the analytical methods.
Statistical
Analysis. All samples were tested at least in duplicate in each analytical technique. The values of different parameters were expressed as the mean ± standard deviation. Comparison of means was performed by one-way analysis of variance (ANOVA) followed by Wilcoxon's multiple comparison tests. Principal component analysis (PCA) was performed to compare the physical and chemical data of 3 morphotypes of Cyperus esculentus tubers. PCA was carried out using the 33 physical and chemical variables which differed significantly between morphotypes. Principal component analysis (PCA) is used in exploratory analysis. It gives graphical representations of intersample and intervariable relationships and provides a way to reduce the complexity of the data. Statistical significance was set at the 5% level of probability using JMP In 5.1 software (SAS Institute, Cary, NC, USA).
Morphological Variants.
Tubers from five collection sites were grouped into three morphological variants on the basis of their color (yellow or black) and size (big or small tuber). Then three variants were identified: (1) yellow and big (morphotype 1), yellow and small (morphotype 2), and black and big (morphotype 3) (Table 1). Thus, tuber samples from Mangodara and Tiéfora were classified as morphotype 1, those from Loropéni and Ouéléni as morphotype 2, and those from Tangora as morphotype 3 (Figure 1).
Physical
Characteristics. The tuber characteristics of the three morphotypes of Cyperus esculentus are shown in Table 1. The moisture content was not significantly different ( > 0.05) among the three morphotypes. Lengths were ranged from 0.98 ± 0.06 to 1.31 ± 0.06 cm. Morphotype 2 tubers were significantly shorter than those of morphotypes 1 and 3. Morphotypes 1 and 3 had slightly bigger tubers than approximate average length (0.63 to 1.21 cm) found for tigernuts from other countries [5]. The width of the tuber and one thousand dried tuber weights varied from 0.90 ± 0.08 to 1.19 ± 0.05 cm and from 598.00 ± 115.00 to 1044.00 ± 394.60 g, respectively. The tuber width of morphotype 2 was significantly lower than that of morphotype 3. Both morphotypes 1 and 3 had higher one-thousand-tuber weight than morphotype 2. The one-thousand-tuber weight seems to be more influenced by tuber width than length. One thousand weights of investigated tubers were far higher than those obtained for brown tubers by Coşkuner et al. [5] that showed how genetic diverse is C. esculentus cultivated around the world. Values are means ± standard deviation for = 3. Data in the same row followed by different letters are significantly different (p < 0.05).
Proximate Composition.
Crude oil contents of the three morphotypes varied from 24.91 ± 0.94 to 28.94 ± 0.37 g 100 g −1 of dry weight (DW). Crude oil content was higher in morphotypes 2 followed by morphotype 1, with morphotype 3 as the lowest (Table 1). Crude oil content of the three morphotypes reported in this paper is lower than those reported for black and brown tubers from Cameroon [20]. However, the lipid content values are similar to those of white tubers [21] and higher than the content of tigernut genotype from Spain reported by Alegría-Torán and Farré-Rovira [22]. The data reported indicate that the lipid content of tigernut is influenced by genetic material and geographical location. Protein levels in the three morphotypes ranged from 3.3±0.26 to 4.33±0.6 g 100 g −1 . The morphotype 2 protein content was significantly higher than morphotype 3. The levels of protein are not related to either colour or size. The protein content for the three morphotypes from Burkina Faso was very low compared to tubers from Cameroon [20], Nigeria [23], and Turkey [5]. The ash content of the three morphotypes was ranged between 1.81±0.24 and 2.21 ± 0.39 g 100 g −1 . Morphotype 3 had significantly higher ash content than morphotype 2. No significant difference was found between morphotype 1 and the two other ones. The ash content of the three morphotypes is lower than those reported for black, brown, and yellow tubers [5,20,21]. Morphotypes 1 and 3 had similar carbohydrate content which was higher than that of morphotype 2. Tubers from Burkina Faso are richer in carbohydrates than those from Nigeria [7] and Spain [22]. Values are means ± standard deviation for = 3. Data in the same row followed by different letters are significantly different (p < 0.05).
Starch and Other Carbohydrate Contents.
Starch, sucrose, fructose, and glucose contents of three morphotypes are reported in Table 2.
The starch content of the three morphotypes ranged from 30.54 ± 2.75 to 33.21 ± 1.1 g 100 g −1 . It appeared that starch content was not significantly different among morphotypes. However, the values for the three morphotypes were slightly higher than those reported by Coşkuner et al. [5] and similar to data of Linssen et al. [24]. The tigernuts from Burkina Faso displayed 1.6 ± 0.69 to 3.59 ± 0.72 g 100 g −1 of fructose with no significant difference among morphotypes. The sucrose and glucose contents of the three morphotypes ranged from 17.98 ± 1.03 to 20.39 ± 1.15 g 100 g −1 and from 0 to 6.79 ± 1.34 g 100 g −1 , respectively. Morphotype 3 had significantly higher sucrose than morphotype 1 and morphotype 2, while glucose content was not detected. The sucrose content was within the range previously reported [5,25]. Karacali [26] Journal of Analytical Methods in Chemistry 5 Values are means ± standard deviation for = 3. Data in the same row followed by different letters are significantly different (p < 0.05).
reported that the amount and composition of sugars vary according to fruit species, varieties, and ecological conditions, and technical and cultural practices affect the flavour. In addition, irrigation, harvest time, and storage conditions also affect the sugar composition of almond kernel [27][28][29].
Regarding the taste of sugars, sucrose is sweeter than glucose, and fructose is sweeter than sucrose [30]. Balta et al. [31] reported a positive correlation between glucose and fructose contents and the sweet taste of almond. Yellow morphotypes (morphotypes 1 and 2) had higher glucose and fructose contents than black ones; they should be sweeter.
Vitamin Contents.
The ascorbic acid, tocopherol, andcarotene contents of the three morphotypes are shown in Table 3. Vitamins contents of the three morphotypes differed significantly. The ascorbic acid levels varied from 5.48 ± 1.05 to 26.78 ± 2.51 mg 100 g −1 and were within the usual range for tubers and lower than that of nuts [32,33]. The highest content of ascorbic acid was recorded with morphotype 2, followed by morphotypes 3 and 1. Tocopherol content of three morphotypes ranged from 149.86 ± 1.94 to 270.56 ± 8.33 g 100 g −1 . The morphotype 2 tocopherol content was significantly higher than that of morphotype 1, which was also significantly higher than that of morphotype 3. The tocopherol content obtained in this study is lower than that reported in tigernut oil from Ghana [9].
-Carotene content of three morphotypes varied from 6.13 ± 0.62 to 10.05 ± 1.79 g 100 g −1 . Morphotypes 2 and 3 had the lowest and the highest content, respectively. Burmeister et al. [34] reported higher -carotene content compared to Burkinabe tubers.
Fatty Acid Composition.
Oils of the three morphotype tubers contained high amounts of monounsaturated fatty acids (MUFAs) (65.91 ± 1.75-67.75 ± 1.41%), followed by saturated fatty acids (SUFAs) (20.65 ± 0.38-22.03 ± 1.11%) and polyunsaturated fatty acids (PUFAs) (10.2 ± 0.36-12.53 ± 0.73%) ( Table 4). The SUFA content of morphotype 2 was significantly lower than that of morphotypes 1 and 3. Morphotype 3 had significantly lowest PUFA content compared to morphotypes 1 and 2. The MUFA content was not significantly different among the morphotypes. The SUFA, MUFA, and PUFA proportions were similar to those previously reported [9]. However the tigernut studied here had better Table 5). The most abundant minerals were K, P, Si, Cl, S, and Mg and their content was significantly different at < 0.05 except for S and Mg. Some contaminants such Cr, Sr, and Cd were detected at low amounts. Morphotype 1 was found to be richer in Ca, Cu, and Mn contents. Al, Mg, P, S, and Si were most abundant in morphotype 2. Morphotype 3 had the highest content of Cl, K, and Zn. The mineral compositions of the three morphotypes in the present study are different from those recorded with accessions from Niger, Nigeria, and Turkey [22,35,36]. Field observations of the soil type where the tigernuts are mainly growing showed that morphotype 1 is grown on more sandy soil, whereas morphotypes 2 and 3 are cultivated on soil with, respectively, more reddish and brownish clay. Therefore different mineral content can be due to differences in soil composition which can influence mineral uptake and storage in the tuber.
Principal Component Analysis.
Principal component analysis (PCA) is used in exploratory analysis, which gives an overview of multivariate data [37]. A PCA using 33 physical and chemical variables showed clear differences among the three morphological types of tubers and gives a good overview of the characteristics of each type ( Figure 2). The first three principal components accounted for 82.27% of the total variation among the accessions. Most of the variation was explained by the first principal component (52%), followed by the second (22%) and the third (9%) ( Table 6).
Loadings of the variables on the first two principal components show that the first component had high positive loadings from length, width, carbohydrate, sucrose,carotene, stearic acid, stearic acid, linoleic acid, total saturated fatty acids, and Zn and high negative loadings from lipids, linolenic acid, and Mn. The second component had high negative loadings from Cu, Sr, and Ca. Morphotype 1 had negative loadings in PC2 and was characterized by high Ca, Sr, Cu, and Fe contents whereas morphotype 2 showed positive scores in PC2 and had high protein, lipid, vitamin C, vitamin E, and P contents. Morphotype 3 was located in the positive side of PC1 and was characterized by the highest content of ash, -carotene, and myristic, arachidic, and linolenic acids.
Conclusion
We present in this study the physical and chemical variability of tigernuts (Cyperus esculentus) cultivated in Burkina Faso. The data revealed that three Cyperus esculentus morphotypes are important source of macronutrients (starch, fat, and Journal of Analytical Methods in Chemistry 7 sucrose) and minerals (potassium, phosphorus, silicon, chlorine, sulfur, and magnesium). Some interesting differences were noticed such as the content of carbohydrates, starch, saturated fatty acids, and polyunsaturated fatty acids. The yellow morphotypes showed the highest content of fructose, glucose, and crude oil. Black morphotype was richer in carbohydrates with high content in sucrose whereas the yellow are source of fructose and glucose. These data revealed genetic variability among cultivated tigernuts from Burkina Faso and from others grown worldwide. Thus, tigernuts from Burkina Faso displayed particular composition which could be of great interest for nutritional quality and food processing. | v3-fos |
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} | s2 | Transplanting Soil Microbiomes Leads to Lasting Effects on Willow Growth, but not on the Rhizosphere Microbiome
Plants interact closely with microbes, which are partly responsible for plant growth, health, and adaptation to stressful environments. Engineering the plant-associated microbiome could improve plant survival and performance in stressful environments such as contaminated soils. Here, willow cuttings were planted into highly petroleum-contaminated soils that had been gamma-irradiated and subjected to one of four treatments: inoculation with rhizosphere soil from a willow that grew well (LA) or sub-optimally (SM) in highly contaminated soils or with bulk soil in which the planted willow had died (DE) or no inoculation (CO). Samples were taken from the starting inoculum, at the beginning of the experiment (T0) and after 100 days of growth (TF). Short hypervariable regions of archaeal/bacterial 16S rRNA genes and the fungal ITS region were amplified from soil DNA extracts and sequenced on the Illumina MiSeq. Willow growth was monitored throughout the experiment, and plant biomass was measured at TF. CO willows were significantly smaller throughout the experiment, while DE willows were the largest at TF. Microbiomes of different treatments were divergent at T0, but for most samples, had converged on highly similar communities by TF. Willow biomass was more strongly linked to overall microbial community structure at T0 than to microbial community structure at TF, and the relative abundance of many genera at T0 was significantly correlated to final willow root and shoot biomass. Although microbial communities had mostly converged at TF, lasting differences in willow growth were observed, probably linked to differences in T0 microbial communities.
INTRODUCTION
Microorganisms colonize all plant components, and plants interact constantly with this complex microbiome. Between 5 and 20% of a plant's photosynthetic yield is transferred to its microbiome, and this occurs mainly through the roots (Marschner, 1995). As a result of this transfer, the rhizosphere supports much higher bacterial abundance and activity, not only when compared to other plant compartments, but also relative to bulk soil (Smalla et al., 2001;Kowalchuk et al., 2002). However, bacterial diversity in the rhizosphere is generally lower than is observed in bulk soil (Marilley and Aragno, 1999) while microbial community composition is distinct (Smalla et al., 2001;Kowalchuk et al., 2002;Griffiths et al., 2006;Kielak et al., 2008;Bulgarelli et al., 2012;Peiffer et al., 2013), suggesting a strongly selective environment in the rhizosphere. This selection pressure often varies between plant species (Haichar et al., 2008;Berg and Smalla, 2009) and even genotypes (Lundberg et al., 2012;Sugiyama et al., 2012). This selection pressure results from the exudation of specialized antimicrobials (e.g., flavonoids, salicylic acid, phytoalexins), or compounds that provide carbon (e.g., organic acids, aromatic compounds) and/or nitrogen (e.g., amino acids) to microbes (Badri et al., 2009). An emerging view in the microbial ecology of microbe-host systems is that the host and its microbial inhabitants are an inseparable entity, and actually function as a meta-organism or a holobiont (Bosch and McFall-Ngai, 2011;Vandenkoornhuyse et al., 2015). Interactions between plants and microbes have evolved over millions of years, and these relationships allow the plant-microbe meta-organism to minimize overall stress by, among other mechanisms, deterring pathogens (St-Arnaud and Vujanovic, 2007;Sikes et al., 2009;Mendes et al., 2011), increasing N and P uptake (Richardson et al., 2009), protecting against abiotic stress (Marasco et al., 2012;Selvakumar et al., 2012), and detoxifying the environment (Siciliano et al., 2001). Because of these intricate links, engineering of the plant host without considering the microbiome likely limits the phenotypic optimum that can be achieved (Bell et al., 2014b;El Amrani et al., 2015;Quiza et al., 2015).
Depending on its composition and activity, the plant microbiome can be either beneficial or deleterious to plant health, and shifting this delicate balance has huge implications for plant productivity. Several authors have suggested that optimizing the plant microbiome is a possible solution to the shortage of food on the planet (Morrissey et al., 2004;Glick, 2014). Manipulating the plant microbiome has the potential to reduce the incidence of plant disease (Andrews, 1992;Bloemberg and Lugtenberg, 2001), increase agricultural production , reduce the need for chemical inputs (Adesemoye et al., 2009), reduce greenhouse gas emissions (Singh et al., 2010), and increase plant-mediated removal of pollutants (Bell et al., 2014b). One approach to soil microbiome engineering is the use of blanket treatments (e.g., fertilization) to stimulate the whole microbial community, but this may lead to the stimulation of microbes that do not optimally perform targeted functions (Bell et al., 2011). Another is to introduce microorganisms to soil that are capable of performing the desired functions (i.e., bioaugmentation), like polychlorinated biphenyl- (Secher et al., 2013), polycyclic aromatic hydrocarbon- (Baneshi et al., 2014), and diesel- (Chuluun et al., 2014) degradation. However, the abundance and functional diversity of indigenous soil microbes allows them to occupy most available ecological niches, and so attempts to introduce new microorganisms have been met with limited success (Thompson et al., 2005;Gerhardt et al., 2009). Instead, disrupting microbial communities by removing specific taxonomic groups or reducing the overall microbial load may open niches for microbial colonization. Specific inhibitors like antibiotics and fungicides have been used to disrupt soil microbial communities and promote specific functions of interest (Bell et al., 2013;Qiu et al., 2014). For instance, Bell et al. (2013) used two antibiotics to inhibit specific microbial groups in diesel-contaminated soils, and found that using the two antibiotics in combination in nutrient-amended soils resulted in higher diesel degradation rates than controls or soils treated with only one antibiotic. In another study, Qiu et al. (2014) used fungicides in the rhizosphere of cucumber, which resulted in a higher incidence of disease when a pathogen was inoculated, but reduced disease incidence and increased plant growth when the pathogen was inoculated along with an antagonist bacteria. Although, the feasibility and ethics of using such approaches for modifying soil microbiomes in the field is debatable, these studies suggest potential mechanisms by which complex microbiomes can be modified. Other studies demonstrated that inoculation with microbial consortia was a more effective approach than single strain inoculation, as microorganisms appear to work synergistically to efficiently degrade petroleum hydrocarbon contaminants (Alarcón et al., 2008;Afzal et al., 2012). Further factors complicating efforts to engineer plant microbiomes include differences in the physiology and ecology of soil inhabitants, resulting in differential responses of bacterial and fungal activity, growth, and diversity to key rhizosphere parameters like pH (Rousk et al., 2009(Rousk et al., , 2010 and plant identity (Haichar et al., 2008;Berg and Smalla, 2009).
Willows (Salix spp.) have been used as model plants for phytoremediation, as they rapidly produce high amounts of biomass, including an extensive root system capable of stimulating soil microbial communities. One of the keys to effective phytoremediation with willows is the optimization of growth, biomass production, and survival in highly contaminated environments. The goal of the present study was to observe whether a complex microbiome could be transferred from one plant to another, and whether this also transferred certain characteristics of the original plant (growth, biomass production, and survival in a stressful environment). In other words, how much of the plant phenotype is related to the root-associated microbiome? Clonal willow clippings were planted for two generations in soil originating from a hydrocarbon-contaminated field site. First generation willows were planted into the unmodified soil, and soils associated with willows that showed dramatically different growth characteristics were harvested and used to inoculate gamma-irradiated soil from the same site. A second generation of willows was planted into these inoculated soils. We hypothesized that inoculation with the rhizosphere soil of large first-generation willows would result in larger second-generation willows with lower mortality than when inoculating with soil associated with smaller or dying first-generation plants.
Soil Inoculum
Soil was retrieved from an experiment in which clonal willows (Salix purpurea "Fish Creek") were planted into a homogenized highly petroleum-contaminated soil (C10-C50 concentration: 17,500 mg/kg). Most of the introduced willows died; out of 100 initial plants, only 11 were alive after 173 days. The rhizosphere of a large surviving willow (height of 128 cm, shoot fresh weight of 62.00 g, used to inoculate the LA treatment), the rhizosphere of a small surviving willow (height of 80 cm, shoot fresh weight of 43.46 g, used to inoculate the SM treatment) and the bulk soil from a pot in which the willow had died (used to inoculate the DE treatment), were harvested on 21 October 2013 by collecting the soil that remained attached to the root system after vigorously shaking the willows (for the rhizosphere) or by taking a surface soil sample in the middle of the pot (for the bulk soil). These soils represent the three different soil inocula used in subsequent experiments. Soils were transported at 4 • C and frozen at −20 • C until used for downstream steps.
Experimental Design
Fresh soil was collected at the site of a former petrochemical plant in Varennes, Quebec, Canada, within 2 m of the excavation site of the contaminated soil described above. Soil was mixed thoroughly, transferred in 20 L pails and sent to Nordion (Laval, Quebec, Canada) for gamma irradiation at a dose of 50 kGy, to disrupt the microbiome and minimize the soil microbial load. Following a previous identical irradiation of the same soil, no cultivable microorganisms could be retrieved from the soil (T.H. Bell, unpublished observations), even though bacterial, archaeal, and fungal DNA could be amplified. For each treatment type (DE, LA, and SM treatments), ∼10 kg of irradiated soil was mixed with 1 kg of the different soil inocula and distributed into ten 1 L pots. A control treatment was left uninoculated (CO treatment), resulting in four treatments with 10 replicate pots each. A willow clipping (S. purpurea "Fish Creek") was planted to a depth of 10 cm in the middle of each pot. Willow clippings were also planted in 10 pots filled with potting soil to evaluate willow growth under ideal conditions. Pots were placed in a greenhouse (February 18, 2014), and were incubated at a temperature of 20 • C during the day and 18 • C overnight. High-pressure sodium lamps (430 W) were illuminated for 18 h a day, starting at 6:00 a.m. The position of the pots on the greenhouse bench was determined using a random number generator.
Sampling
Each inoculum type (three samples) was sampled before mixing with irradiated soil and soils from the pots were sampled before planting with willow clippings (February 17, 2014, 4 treatments × 10 replicates = 40 samples at T0). Willow growth was measured on March 21, 2014 (32 days after planting), on April 17, 2014 (59 days after planting), and on May 23, 2014 (95 days after planting). Rhizosphere soils were sampled at the end of the experiment (May 28, 2014, after 100 days, 4 treatments × 10 replicates = 40 samples at TF) by collecting the soil that remained attached to the root system after vigorously shaking the willows. Willow roots and shoots (excluding the original willow cuttings) were also harvested at the end of the experiment, dried at 105 • C overnight, and weighed.
Sequence Data Treatment
Sequences were analyzed through our internal rRNA short amplicon analysis pipeline (Tremblay et al., 2015). Common sequence contaminants (i.e., Illumina adapters and PhiX spikein reads) were first removed from raw sequences using a kmer matching tool (DUK; http://duk.sourceforge.net/). Filtered reads were assembled with the FLASH software (Magoč and Salzberg, 2011). Using in-house Perl scripts, assembled amplicons were then trimmed to remove forward and reverse primer sequences that might be included in some reads. Paired-end assembled amplicons were then filtered for quality: sequences having more than 1 N, an average quality score lower than 30, or more than 10 nucleotides having a quality score lower than 10 were rejected.
OTU generation was done using a three step clustering pipeline. Briefly, quality controlled sequences were dereplicated at 100% identity. These 100% identity clustered reads were then denoized at 99% identity using USEARCH (Edgar, 2010). Clusters of less than three reads were discarded and remaining clusters were scanned for chimeras using UCHIME de novo followed by UCHIME reference using the Broad's Institute 16S rRNA Gold reference database. Remaining clusters were clustered at 97% identity (USEARCH) to produce OTUs; data were then rarefied to 1000 reads.
Taxonomy assignment of resulting bacterial and archaeal OTUs was performed using the RDP classifier with a modified Greengenes training set built from a concatenation of the Greengenes database (version 13_5 maintained by Second Genome), Silva eukaryotes 18S r118 and a selection of chloroplast and mitochondrial rRNA sequences. ITS organisms were classified using the ITS Unite database (version: sh_qiime_release_13.05.2014). Hierarchical tree files were generated with in-house Perl scripts and used to generate training sets using the RDP classifier (v2.5) training set generator's functionality (Wang et al., 2007). With taxonomic lineages in hand, OTU tables were generated and rarefied to 1000 reads. These OTU tables were used for downstream analysis.
Diversity metrics were obtained by aligning OTU sequences on a Greengenes core reference alignment (DeSantis et al., 2006) using the PyNAST aligner (Caporaso et al., 2010). Alignments were filtered to keep only the V4, V7-V8, or V6-V8 part of the alignment. A phylogenetic tree was built from alignment with FastTree (Price et al., 2010). Alpha (observed species) and beta (weighted or unweighted UniFrac and Bray-Curtis distances) diversity metrics and taxonomic classifications were computed using the QIIME software suite (Caporaso et al., 2010;Kuczynski et al., 2010).
Statistical Analyses
All statistical analyses were carried out in R v3.0.2 (R Core Team, 2013). Analysis of variance (ANOVA) and repeatedmeasures ANOVA was performed using the "aov" function, Spearman rank-order correlation analyses were performed using the "cor.test" function, Permanova was performed using the "adonis" function of the vegan library, and principal coordinate analyses were performed using the "cmdscale" function of the vegan library based on the Bray-Curtis distance calculated from the OTU matrix using the "vegdist" function of the vegan library. Since biomass could only be measured at TF, correlations and permanova analyses were carried out against the relative abundance of genera at TF, but also at T0 to evaluate whether the relative abundance of a genus, the overall community structure, or microbial diversity at T0 could be related to willow growth at TF.
Data Deposition
Raw sequence data produced in this study was deposited in NCBI under the BioProject accession PRJNA301462.
Willow Growth and Soil DNA Yields
All 40 willows planted in the contaminated soil survived over the 100 days of the experiment. However, CO willows showed delayed growth, and were smaller throughout the experiment than those that had been inoculated (Figure 2A). DE willows had significantly longer stems (P < 0.05) than the CO willows throughout the experiment, while LA willows were only significantly taller (P < 0.05) at days 59 and 95, and SM willows treatment were only significantly taller (P < 0.05) at day 59 (Figure 2A). Furthermore, at day 59, the stems of DE willows were significantly longer (P < 0.05) than those from SM willows (Figure 2A). At the end of the experiment (TF), there was a significant effect (P < 0.05) of inoculation on shoot and root biomass, with significant differences (P < 0.05) between the noninoculated controls (CO) and the inoculated treatments (DE, SM, and LA; Figure 2B). Within the inoculated treatments, the DE willows produced significantly more shoot biomass (P < 0.05), while root biomass production was comparable across the three inoculation treatments (Figure 2B). Willows planted in parallel in non-contaminated potting soil were on average 96.6 cm high, with an average root biomass of 2.81 g and an average shoot biomass of 14.92 g at TF. DNA yields from soil were on average 1.80 µg per g soil for T0 soils, 4.30 µg per g soil for the three inocula, and 5.14 µg per g soil for TF soils (Figure 1). There was a significant difference in DNA yields between T0 and TF samples (repeated-measure ANOVA: F = 89.84, P < 0.001), but no significant differences were observed between treatments or for the interaction term (P > 0.05).
Archaeal Community
At the order level, the archaeal community was very different across inoculum types, with a dominance of the E2 group in the DE inoculum, the Methanosarcinales in the LA inoculum, and the Nitrososphaerales in the SM inoculum (Figure 3A). At T0 (after mixing the inocula with the irradiated soil), the three inoculated treatments were more similar, being codominated by Nitrososphaerales, Methanobacteriales, E2 group, Methanosarcinales, and Methanomicrobiales (Figure 3A). At TF, the CO soils did not differ markedly from their T0 counterparts, while the DE and LA soils showed an increased dominance of the Methanosarcinales and the SM soils showed increased dominance by the Methanocellales (Figure 3A). The ordination resulting from principal coordinate analysis of Bray-Curtis distances based on OTU relative abundance showed high variability within each of the treatments, especially within the LA and SM rhizospheric soils, while communities from the CO treatment generally clustered together ( Figure 3B). However, inoculation appeared to have some influence, as the TF inoculated samples generally clustered on the left side of the ordination, and for the SM and LA treatments, the TF samples mostly clustered toward their initial inoculum (Figure 3B). Time and treatment had similar effects (similar F-ratios) in permanova tests (Figure 3B), and when separating T0 and TF samples, the effect of treatment was stronger at TF (Table 1). Permanova tests also revealed significant relationships between shoot biomass and archaeal community structure. A slightly stronger link was observed between shoot biomass and the TF community (higher Fratio) ( Table 1). Diversity was lower in the DE and LA inocula when compared to the SM inoculum ( Figure 3C). Repeatedmeasure ANOVA tests demonstrated that archaeal diversity was significantly influenced by treatment type, an effect that was mainly driven by significant differences between the CO, SM, and LA treatments ( Figure 3C). There was also a significant effect of time on archaeal diversity, with lower diversity in TF samples for all treatments (Figure 3C). The initial archaeal diversity (at T0) was significantly correlated with shoot biomass (r s = 0.321, P = 0.049), but not root biomass, and no correlations were significant for diversity at TF. Some of the archaeal genera identified at T0 or TF had significant positive or negative correlations with willow biomass ( Table 2). The relative abundance of Methanosarcina at T0 was significantly and positively correlated to root and shoot biomass, while its relative abundance at TF was significantly and positively correlated to root biomass ( Table 2). Other genera also showed significant correlations with shoot and root biomass and are listed in Table 2.
Bacterial Community
The bacterial inocula showed marked differences, with the inocula originating from rhizospheric soil (LA and SM treatments) dominated by Alpha-, Beta-, and Gammaproteobacteria, while the inoculum originating from bulk soil (DE treatment) was dominated by Bacteroidetes, with the Firmicutes, Alpha-, Beta-, and Gammaproteobacteria present at moderate abundance ( Figure 4A). The bacterial communities remained variable at T0, with a large dominance of Firmicutes in the CO treatment and a dominance of Proteobacteria (mainly Gammaproteobacteria) in the inoculated treatments (DE, SM, and LA; Figure 4A). After 100 days of growth (TF), the bacterial community composition of the willow rhizosphere was remarkably similar between all treatments, with a codominance of Beta-and Gammaproteobacteria (Figure 4A). This convergence of the bacterial communities at TF was also visible in the PCoA ordination of Bray-Curtis distances, in which the communities are dispersed at T0 and much more similar at TF (Figure 4B). Bacterial communities in the willow rhizosphere at TF were not especially similar to the bacterial communities of the initial inocula ( Figure 4B). Permanova showed that time was the major factor leading to differences in bacterial composition (highest F-ratio), but there were also highly significant effects of the treatments and of the interaction term. When separating the T0 and TF samples, the effect of treatment was significant for both datasets, although the F-ratio was much larger for the T0 dataset (Table 1). This was also visible in the ordinations. There was also a significant relationship between the bacterial community structure at T0 and TF and root and shoot biomass in permanova tests, with a stronger effect for T0 (higher F-ratios; Table 1). Bacterial diversity was significantly affected by time, treatment, and the interaction term ( Figure 4C). Diversity was largest in the CO and DE treatments at T0 and was at its lowest in the CO rhizosphere at TF (Figure 4C). Bacterial diversity at T0 was not significantly correlated to root and shoot biomass, but significant correlations were observed at TF between bacterial diversity, shoot biomass (r s = 0.650, P < 0.001), and root biomass (r s = 0.669, P < 0.001). A variety of bacterial genera showed significant correlations with root and shoot biomass, and the top 10 strongest positive and negative correlations are presented in Table 3. Some of the correlations were very strong, with P-values well below 1 × 10 −5 . Among the most significant positive correlations, many of the identified taxa have previously been reported to be associated with plants.
Fungal Community
The DE inoculum differed markedly from the rhizospheric inocula (LA and SM), harboring relatively more Sordariomycetes, Dothideomycetes, Chytridiomycetes, and Zygomycota, and relatively less Agaricomycetes and Pezizomycetes (Figure 5A). Differences between treatments were also visible at T0 and TF, with the CO and DE treatments differing substantially from the LA and SM treatments ( Figure 5A). Large differences in the dominant class were visible between sampling points and treatments, with the Agaricomycetes, Dothideomycetes, Pezizomycetes, Sordariomycetes, Tremellomycetes, and Zygomycota dominating or co-dominating the various treatments ( Figure 5A). In the ordination based on principal coordinates analysis of Bray-Curtis distances of OTU tables, a similar story emerged (Figure 5B). At T0, the four treatments were clearly distinct in the ordination space, with a few outliers ( Figure 5B). The rhizospheric (SM and LA) inocula and the DE inoculum were also clearly separated in the ordination space ( Figure 5B). Some of the fungal communities at TF converged toward their respective inocula, with 5/10 samples for the SM treatment, 5/10 samples for the LA treatment, and 10/10 samples for the DE treatment ( Figure 5B). The LA and SM samples that did not converge toward their initial inoculum and all the DE samples grouped together with the CO samples at TF (Figure 5B). The CO treatment did not change much through the course of the experiment and samples from T0 and TF were located together in the ordination space ( Figure 5B). The large effect of the inoculation treatments resulted in a smaller difference between the F-ratio for the effect of time and treatment in permanova tests as compared to bacteria and archaea. Separate permanova tests for the effect of treatment on T0 and TF communities revealed highly significant effects, with stronger effects (higher F-ratio) for the T0 communities (Table 1). Similarly, the relationship between root and shoot biomass and fungal community structure was stronger (higher F-ratio) for T0 communities than TF communities ( Table 1).
In terms of diversity, there was a significant effect of time, with significantly higher diversity in T0 samples than TF samples for all treatments (Figure 5C). The interaction term was also significant in ANOVA tests, which was due to the fact that the differences in diversity between treatments observed at T0 were no longer visible at TF (Figure 5C). Fungal diversity at T0 was not significantly correlated with root or shoot biomass (P > 0.05), but there was a significant negative correlation between fungal diversity at TF and shoot biomass (r s = −0.322, P = 0.045). The relative abundances of individual genera were also tested for correlation with willow biomass, and the 10 strongest positive and negative correlations are reported in Table 4. Most of the strongest positive correlations with willow biomass were fungal genera at T0, while the strongest negative correlations were with fungal genera at TF or T0 (Table 4). Sphaerosporella showed a particular pattern at TF; it was nearly absent in most samples (0-2.7%), but extremely abundant (58.2-93.7%) in the rhizosphere of the four willows that showed the highest shoot biomass (all from the DE treatment). This resulted in a significant positive Spearman correlation with shoot biomass (Table 4).
DISCUSSION
The microbiome of contaminated soils was successfully modified by gamma-irradiation followed by the introduction of various soil inocula. Bacterial and fungal communities from the four treatments were clearly distinct at the beginning of the experiment (T0), with respect to both microbial community composition and diversity. However, after 100 days of willow growth (TF), the original differences were not visible for most treatments, with the exception of the fungal communities for some samples. This convergence of the willow rhizosphere microbiome at TF suggests that the willow rapidly exerts strong selective pressures in the rhizosphere, selecting for a similar microbiome from variable starting microbiomes. This strong selective environment has been reported for other plant species, and resulted in sharp contrasts between the microbial community composition of the rhizosphere and adjacent bulk soil (Smalla et al., 2001;Kowalchuk et al., 2002;Griffiths et al., 2006;Kielak et al., 2008;Bulgarelli et al., 2012;Peiffer et al., 2013). This selective pressure often varies between plant species (Haichar et al., 2008;Berg and Smalla, 2009) and even genotypes (Lundberg et al., 2012;Sugiyama et al., 2012). Here, we observed a relatively low variability in microbiome composition between individual willows possibly because we used a clonal population of willows. This could partly explain the striking convergence in willow rhizosphere communities at TF. For willows planted in contaminated soils, this selection pressure was previously shown to result in an increased expression of microbial genes related to the degradation of hydrocarbons, as well as large shifts in the active microbial community relative to willows planted in non-contaminated soil or contaminated bulk soil (Yergeau et al., 2014;Pagé et al., 2015). Because of this overwhelming rhizosphere effect, the inoculation of a pre-selected microbiome was only effective in the short term, Unid., unidentified; OTU in the Greengenes database that was not identified at the genus level. The next lowest taxonomical level for which the OTU was identified is given.
even though we had disrupted the indigenous soil's microbiome using irradiation. Although, the experimental treatments did not produce lasting microbiome modifications, significant changes were observed in willow biomass production at TF. Many of our results suggest that microbial community composition at TF was a poor indicator of willow growth and biomass production compared with community composition at T0. Thus, the strategy of using irradiation to reduce the microbial load and open niches for microbial colonization successfully modified the starting microbiome of contaminated soil, which led to lasting differences in willow growth. Our hypothesis was that willows growing in pots inoculated with rhizospheric soil harvested from willows that had grown successfully in contaminated soils would grow more successfully than willows receiving other inoculants. In contrast to our hypothesis, willows growing in soil inoculated with bulk soil (DE treatment) performed better than those growing in pots inoculated with rhizospheric soil (LA and SM). There were no apparent differences in survival rates, as all willows survived throughout the length of the experiment. One possible explanation for the better performance of the DE treatment is that the DE inoculum was in fact bulk soil (since the willow had died) as compared to rhizospheric soil for the LA and SM inocula. As mentioned above, the rhizosphere is a strongly selective environment, which promotes a lower diversity of specialized microorganisms (Marilley and Aragno, 1999), and in fact at T0, the DE pots were more diverse in terms of the bacteria and fungi present. The willows growing in these pots were exposed to a wider diversity of organisms, which may have helped them to initially adapt to the stressful conditions created by the contaminants.
Although, the soil used to pot the second-generation willows was harvested at the exact same location as the soil used for the study that produced the first-generation willows, it should be stressed that the experimental conditions in this study were different: smaller pots, greenhouse vs. outdoor incubation, willows directly planted in soil vs. pre-growth followed by transplantation of clippings, winter vs. spring, irradiated soil vs. fresh soil. This probably explains the observed differences in survival rates, with all the second-generation willows surviving compared to an 89% mortality rate for the first-generation willows. Willows survival in contaminated soil was previously shown to differ markedly depending on field environmental conditions (Guidi et al., 2011). The different experimental conditions also likely modified the rhizospherewillow association, as well as the composition of the ideal microbiome that would allow optimal growth. Alternatively, rhizosphere communities are known to change over time (Chaparro et al., 2013b) because of shifts in plant exudates (Chaparro et al., 2013a), and the rhizosphere communities that were harvested and used as inocula (6 month old plants) were probably not optimal for willow clipping establishment in soil. Access to a more diverse microbiome might have given an advantage to the DE willows by allowing them to select the best microbiome for the growth conditions and their developmental stage. This suggests a very high specificity of rhizosphere-willow associations under stressful conditions, but a high variability in the composition of the optimal microbiome, depending on growth conditions and plant developmental stage. This further complicates efficient engineering of a beneficial microbiome. The willows from the CO treatment showed reduced growth and distinct starting microbial communities compared to the willows from other treatments. One possible explanation could be that certain key microbes required for efficient willow establishment and growth in highly contaminated environments were killed by the irradiation treatment, and could not be recruited in the CO treatment because of the lack of inoculation. Alternatively, some deleterious organisms may have survived irradiation, and rapidly colonized newly available niches. Correlation analyses highlighted some of the potentially beneficial and deleterious organisms that were highly correlated to willow biomass. Consequently, instead of trying to modify whole microbial communities, an alternative approach would be to ensure that beneficial (Hoeksema et al., 2010;Glassman and Casper, 2012;Lau and Lennon, 2012), although the relative impact of beneficial and deleterious microorganisms will differ depending on soil type, environmental conditions, and plant species. For instance, mycorrhizal fungi are generally beneficial, but can become parasitic under certain environmental conditions, especially in human-managed ecosystems (Johnson et al., 1997). Accordingly, we found a negative correlation between the mycorrhizal fungi genus Rhizophagus and shoot biomass. Alternatively, the correlations between willow biomass and microbial relative abundance could be indirect, through the effect of the microorganisms on other soil organisms or soil physico-chemical characteristics.
The lack of inoculation in the CO treatment also resulted in significantly lower bacterial diversity in the willow rhizosphere at TF. In fact, bacterial diversity at TF was strongly and positively correlated to willow biomass. High community evenness and diversity have been shown to result in healthy soils, high levels of nutrient cycling, increased plant productivity, and reduced stress and disease incidence (Elliot and Lynch, 1994;van Bruggen and Semenov, 2000;Wittebolle et al., 2009;Crowder et al., 2010). A lack of plant community evenness has been associated with reduced plant productivity, possibly due to niches being left vacant and the loss of certain ecosystem services (Wilsey and Potvin, 2000). One way to optimize the willow microbiome might be to provide a soil bacterial community with high diversity and evenness, to allow the willow to select its preferred rhizosphere organisms for optimal growth. This may help to avoid pressures that could lead to selection of suboptimal communities, such as microbial priority effects. However, polluted environments rarely contain diverse or even microbiomes, and one key to effective phytoremediation may be to restore soil bacterial evenness by, for example, soil fertilization, mixing, or aeration before the introduction of plants. Indicative of the importance of restoring soil quality, the willows planted in the contaminated soils only grew to a fraction of the size of those that were grown in parallel in nutrient-rich, well-aerated potting media.
In contrast to bacteria and archaea, the diversity of fungi showed a weak but significant negative correlation with willow shoot biomass and some fungal communities had converged toward the composition of their respective inocula by the end of the experiment. The difference between fungal and bacterial and archaeal communities could be due to the more intimate nature of the relationship between fungi and plants, as many obligate symbionts and pathogens of plants are found in the fungal domain. Previous studies of willows growing in contaminated soil highlighted the stronger link between fungal communities and willow cultivar identity (Bell et al., 2014a) and between fungi and willow growth and zinc uptake (Bell et al., 2015) as compared to bacterial communities. Fungal diversity was also enhanced significantly more by willow introduction than was bacterial diversity, suggesting that phytoremediation may have a disproportionate direct effect on fungi (Bell et al., 2014a). Fungi and bacteria can also be antagonists in the soil environment (De Boer et al., 2005;Rousk et al., 2008;Bonfante and Anca, 2009;Schrey et al., 2012), and competition between these groups has been shown to reduce key soil functions (Siciliano et al., 2009) and microbial growth (Mille-Lindblom et al., 2006;Meidute et al., 2008). Taken together, these results indicate that the physiological and ecological differences between fungi and bacteria may require domain-specific microbiome engineering strategies.
The relative abundance of certain genera at T0 appeared to play a key role in willow growth. For many of the genera (especially fungi) with the strongest positive correlations with willow growth, it was often their relative abundance at T0 that was most strongly correlated to final willow characteristics. Furthermore, the microbial communities of the different treatments were often dissimilar at T0, closely mirroring eventual differences in willow growth, while the TF communities were more similar to each other, and less strongly related to differences in willow growth. This data strongly implies that the microbiome composition at T0 plays a role in determining eventual willow growth in stressful environments. This is in line with our recent results that show that willow growth and Zn accumulation after 16 months of growth in the field were more strongly related to the abundance of the ectomycorrhizal fungus Sphaerosporella brunnea at 4 months than to its abundance at 16 months (Bell et al., 2015).
CONCLUSIONS
Modifying the soil microbiome through gamma-irradiation followed by soil inoculation resulted in short-term shifts in microbial communities, but lasting effects on plant growth characteristics. Our study demonstrated the potential for modifying target plant characteristics through manipulation of the plant-associated microbiome, even though this did not occur as we had hypothesized. This study also highlights several key factors that should be considered when engineering the plant rhizosphere microbiome, including the presence and abundance of keystone species, diversity and evenness of the initial inoculum, ecological differences between fungi and bacteria, environmental conditions, and the plant growth stage that the inoculum originates from. | v3-fos |
2017-08-27T08:29:06.615Z | {
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} | s2 | A METHOD FOR DETECTING AND TYPING OF SALMONELLA BY MULTIPLEX PCR
Today in Ukraine’s market is increasing the volume of trade with livestock products. Also the number of catering services and grocery shops selling ready-made food is growing throughout the country. Th e veterinary service should have time to check the quality of all of these products. Only traditional bacteriological methods of isolation and identifi cation of pathogens of toxicoinfection, which is not enough in terms of increasing turnover of products, are used today. Th e one of the most dangerous toxicoinfections is salmonellosis. Typing diff erent Salmonella species gives an answer about the source of infection. Th e aim of our work was to develop a system of identifi cation of Salmonella and typing among them fi ve serovars based on the polymerase chain reaction (multiplex PCR). We performed analysis of the nucleotide sequences of the fi ve members of the genus Salmonella, on the basis of which a primer designed for the identifi cation of any member of the genus Salmonella with simultaneous typing Salmonella enteriса ser. Enteritidis, Salmonella enteriса ser. Typhimurium, Salmonella enterica ser. Тyphi, Salmonella enterica ser. Dublin, Salmonella enterica ser. GallinarumPullorum by multiplex PCR. Th e protocol of multiplex PCR was optimization with simples positive DNA matrix.
INTRODUCTION
Salmonellosis -one of the most dangerous diseases that is caused by serotypes of bacteria of the genus Salmonella, which have mechanisms for habitat and parasitism in the gastrointestinal tract (Althouse et al., 2003;Chiu et al., 2010).
According to the current classifi cation, S. enterica is divided into six subspecies: Salmonella enterica subspecies enterica, Salmonella enterica subspecies salamae, Salmonella enterica subspecies arizonae, Salmonella enterica subspecies diarizonae, Salmonella enterica subspecies houtenae and Salmonella enterica subspecies indica, which diff erentiate by the biochemical activity and represent the number of subtypes I, II, IIIa, IIIb, IV , and VI , respectively. Salmonella enterica subspecies enterica is mostly isolated in the majority of cases of Salmonella infection from animal and human (Althouse et al., 2003;Battistuzzi et al., 2004).
Salmonella contamination occurs through the consumption of contaminated food: eggs and egg products, milk and dairy products, meat birds and other animals. Another way of infection is the transfer of infections through tap water, in addition, the sources of infection can be the open water (Bailey, 1998). According to the FAO, 20% of poultry products in the world are contaminated with Salmonella, and they can persist for a long time in the animal facilities because they can form a surface fi lm (Vestby et al., 2009; http://www. fao.org/docrep/012/i1133e/i1133e00.htm). Annually on the planet are registered 21 million cases of typhoid fever, and about 216 thousand cases (Zhou and Pollard, 2010).
Worldwide, the monitoring of the incidence of salmonellosis in which tracked various options for its manifestation. As well as a comparison of Salmonella strains isolated from humans and animals (Chiu et Analysis of antigen alleles H1 (i, g, m, r or z10) allowed fast typed serological variants enteritidis, hadar, heidelberg and typhimurium (Hong et al., 2008).
To date, Ukraine has not yet widespread methods of rapid diagnosis of salmonellosis. Typing of the pathogen is an essential component of diagnosis, because it can give an answer about the alleged source of infection. For this reason, the aim of our work was the development of the national test system based on the polymerase chain reaction, which would like to identify and typed some key members of the genus Salmonella (Gerylovich, 2011).
METHODS AND MATERIALS
Th e objects of our study were Salmonella spp., Salmonella enterica ser. Enteritidis, Salmonella enterica ser. Typhimurium, Salmonella enterica ser. Typhi, Salmonella enterica ser. Dublin, Salmonella enterica ser. Gallinarum-Pullorum. For the construction of genus-and species-specifi c primers electronic databases of sequences of essential genes in Salmonella contained in the international database GenBank (http://www.ncbi.nlm.nih.gov/genbank/) were analyzed.
Multiple alignment of selected sequences, and their subsequent analysis to select PCR primers was performed using the computer program Bio Edit (v.7.2.4).
Th e protocol of polymerase chain reaction has been developed on the basis of the primer systems with a certain temperature, the selection of components for the formulation of the multiplex PCR and the identifi cation of the genus Salmonella spp. and typing of the fi ve listed above serotypes (Elnifro, 2000;Kaderali, 2007).
One-day-old cultures of Salmonella from the museum sector study mycoplasmoses and salmonellosis are grown for meat -peptone medium were used as the source of positive DNA-matrix.
Extraction of total nucleic acid was carried out using micro columns. To 450 μl of Extraction buff er was added 100 μl of Salmonella culture. Aft er lysis of the containments from the tubes were transferred to microcolumns and centrifuged. Th is was followed by washing with ethanol followed by extraction of total nucleic acid of TE-buff er.
DNA concentration was calculated by spectrophotometery at 260 nm.
RESULTS AND DISCUSSIONS
Th e nucleotide sequences of the major genes were analyzed. Th e greatest breadth of sample homogeneity and sequenced portions of the gene was detected in invA for all members of the genus Salmonella. In the computer analysis of the gene sequences invA was selected 22 pairs of oligonucleotides -potential pairs of primers for PCR. Th e PCR product limited by size of 387 bp in length, and olygonucleotides were called Salm3_4.
For Salmonella enterica ser. Enteritidis specifi c motifs were found in the gene SefA. Sequence analysis of this gene allowed to establish the potential 6 primer pairs. Th e primers fl anking portion length 299 bp were selected.
Th e gene fl iC demonstrated specifi city for Salmonella enterica ser. Typhimurium. Th e primers fl anking region 420 bp were choosed.
Gene viaB contained specifi c motives for Salmonella enterica ser. Typhi. Accordingly, on this basis was chosen area, which limited the targeted gene fragment length 738 bp.
For the genome of Salmonella enterica ser. Dublin serospecifi c motifs were found in SeD_A1104 gene. When bioinformatics studies were identifi ed primers fl anking the product of 203 bp.
Finally, gene SG0266 was elected by containing specifi c motifs for Salmonella enterica ser. Gallinarum-Pullorum. Specifi c primers fl anking length of 97 bp region were selected in analyzed area. Aft er synthesis of primers, we performed optimization of the PCR protocol. As the positive control for PCR we used DNA extracted from the oneday-old culture of Salmonella which have been stored in the museum NSC " IECVM ".
Th e obtained DNA matrix concentration aft er measuring with a spectrophotometer, we have led to the same concentration and then put PCR.
Th e fi rst stage was carried out testing each primer pair using the standard composition of the reaction mixture at diff erent temperatures.
Multiplex PCR protocol could be applied in the laboratories for identification and typing of Salmonella in the shortest possible time. Also, the system can be convenient for monitoring Salmonella contamination of various objects, while typing their main representatives.
ACKNOWLEDGE
Th e authors thank senior researcher studying pathology of reproduction Bolotin Vitaly I., and Roxana Sanchez-Ingunza, DVM, PhD Research Microbiologist Egg Safety and Quality Research Unit USDA, ARS, RRC 950 College Station Road Athens, GA 30605 USA for assistance in the Science. | v3-fos |
2018-04-03T05:32:57.038Z | {
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} | 0 | [] | 2015-12-02T00:00:00.000Z | 17867900 | {
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} | s2 | US-like isolates of porcine epidemic diarrhea virus from Japanese outbreaks between 2013 and 2014
Since late 2013, outbreaks of porcine epidemic diarrhea virus (PEDV) have reemerged in Japan. In the present study, we observed a high detection rate of PEDV, with 72.5 % (148/204) of diarrhea samples (suckling, weaned, and sows) and 88.5 % (77/87) of farms experiencing acute diarrhea found to be positive for PEDV by reverse transcription PCR. Sequencing and phylogenic analyses of the partial spike gene and ORF3 of PEDV demonstrated that all prevailing Japanese PEDV isolates belonged to novel genotypes that differed from previously reported strains and the two PEDV vaccine strains currently being used in Japan. Sequence and phylogenetic analysis revealed prevailing PEDV isolates in Japan had the greatest genetic similarity to US isolates and were not vaccine-related. Unlike vaccine strains, all prevailing field PEDV isolates in Japan were found to have a number of amino acid differences in the neutralizing epitope domain, COE, which may affect antigenicity and vaccine efficacy. The present study indicates recent PEDV isolates may have been introduced into Japan from overseas and highlights the urgent requirement of novel vaccines for controlling PEDV outbreaks in Japan.
Background
Porcine epidemic diarrhea (PED) is a highly contagious and devastating viral enteric disease characterized by vomiting, acute onset of severe watery diarrhea, and dehydration. PED has a high infectivity and a particularly significant mortality in piglets (Pensaert and de Bouck 1978). The porcine epidemic diarrhea virus (PEDV), an enveloped, single-stranded RNA virus belonging to the Alphacoronavirus genus of the Coronaviridae family, is responsible for PED. The PEDV genome is approximately 28 Kb in length and is composed of seven open reading frames (ORF) that encode four structural proteins, namely, spike (S), envelope (E), membrane (M), and nucleocapsid (N), and three major non-structural proteins, including replicases 1a and 1b, and ORF3 (Song and Park 2012). Of the structural protein, the PEDV S protein plays a pivotal role in regulating interactions with specific host cell receptors to mediate viral attachment and entry. Moreover, the S protein is associated with the induction of host neutralizing antibodies, growth adaptation in vitro, and attenuation of virulence in vivo (Song and Park 2012). Thus, study of the S glycoprotein has been essential in understanding the genetic relationships between PEDV strains, the epidemiological status of PEDV in the field, and the development of vaccines (Song and Park 2012;Chen et al. 2012); (Temeeyasen et al. 2014).
In addition to the S glycoprotein gene, the ORF3 gene has received a large amount of attention in the aspect of PEDV virulence. ORF3 gene plays a role in encoding an ion channel protein (Wang et al. 2012) and it has been suggested to be an important determinant for virulence of this virus (Song and Park 2012). The virulence of PED can be reduced by altering the ORF3 gene through cell culture adaptation (Park et al. 2008), and variation in ORF3 was reported to be associated with viral attenuation in the natural host (Song et al. 2003). Also, vaccine-derived isolates with unique continuous deletions of 49 and 51 ORF3 nucleotides have been confirmed (Chen et al. 2010;Park et al. 2008). Therefore, these unique deletions in the ORF3 gene can be used to differentiate between field and attenuated vaccine strains. Moreover, ORF3 gene variation may represent a useful tool in molecular epidemiological studies of PEDV (Park et al. 2008(Park et al. , 2011Song et al. 2003;Chen et al. 2010).
In Japan, the first outbreak of PED-like disease was reported in late 1982 and early 1983 (Kusanagi et al. 1992;Takahashi et al. 1983), and was followed by pandemics between late 1993 and 1996 (Sueyoshi et al. 1995;Tsuda 1997). Afterwards, there have been sporadic PED outbreaks in intervals of several years. Since late 2013, numerous diarrhea epidemics, suspected to be caused by PED, have occurred in pigs throughout Japan. These epidemics were characterized by severe diarrhea, dehydration, and vomiting in pigs of all ages. Mortality rates were particularly high among suckling pigs. Up to the end of August 2014, more than 410,000 of 1,286,000 pigs from 817 infected farms have died of PED in Japan based from the report of Ministry of Agriculture, Forestry and Fisheries (MAFF) (http://www.maff.go.jp). However, there have been few studies investigating the re-emergence of PEDV in Japan. This study aimed to evaluate the genetic characteristics and molecular epidemiology of the emergent Japanese PEDV isolates using genome analysis and phylogenetic analysis of the partial S gene and ORF3.
PEDV detection
A total of 72.5 % (148 of 204) of samples (suckling, weaned, and sows) from 77 pig farms (88.5 %) experiencing acute diarrhea in six prefectures were found to be positive for PEDV by RT-PCR. PEDV-positive samples were identified from the following prefectures: Miyazaki (n = 107), Kagoshima (n = 9), Aichi (n = 15), Akita (n = 1), Hokkaido = 7), and Aomori (n = 9). To investigate the heterogeneity of the recent Japanese isolates and their genetic relationship with modified live vaccines, in addition to 2 PEDV vaccine strains (P5-V and 96-P4C6) used in Japan, representative isolates were selected for sequencing of the partial S gene and full ORF3 gene.
Sequence and phylogenetic analysis of the partial S gene
The partial S gene, including the CO-26K equivalent (COE) domain, of 80 PEDV samples from 69 PEDVinfected farms were amplified, purified, and sequenced. The partial S sequences were aligned at nucleotides 1477-2116 (amino acids 493-705) of the full S gene. Identical nucleotide sequences were distinguished and excluded, resulting in the identification of 23 individual sequences from the total of 80 field PEDV isolates (Table 1). However, sequencing revealed high genetic variation between nucleotides 1815 and 1944 (amino acid residues 605-648). A total of 20 nucleotide substitutions were detected, leading to 13 amino acid changes, within the partial S gene (Fig. 1).
The COE domain (amino acids 499-638) of the S protein consists of 140 aa and contains epitopes that are capable of inducing PEDV-neutralizing antibodies (Chang et al. 2002). Compared to the two vaccine strains (P-5V and 96-P4C6), all Japanese field strains had 3 different amino acids at positions 517 (A → S), 549 (T → S), and 594 (G → S) within the COE domain. Furthermore, differences in amino acids were found at the following 10 sites within the COE domain of the S protein: 500 , and 632 (L → F) as shown in Fig. 1.
To investigate the heterogeneity of prevailing PEDV strains in Japan, phylogenetic tree of 23 partial S genes of PEDV field strains and two vaccine strains were constructed together with 4 previously reported Japanese PEDV strains (NK, KH, MK, 83P-5) and reference strains from other countries available in GenBank.
Pairwise alignment of field Japanese PEDV isolates demonstrated high nucleotide and amino acid sequence identity between strains (99.1-100.0 and 97.2-100 %, respectively). Notably, 42 field PEDV isolates collected from 3 prefectures in this study had identical partial S gene sequence (100 % nucleotide homology). Japanese
Sequence and phylogenetic analysis of the ORF3 gene
To investigate the genetic relationship between recent Japanese field isolates, and modified live vaccine strains and reference strains, the nucleotide sequences of the ORF3 genes of 28 recent PEDV isolates and 2 vaccine samples (P5-V and 96-P4C6) were sequenced and analyzed (Table 1). Sequencing data revealed the ORF3 genes of all 28 PEDV samples were 675 bp in length and (Table 1). Sequence analysis revealed that the ORF3 genes of the Japanese field isolates were relatively well-conserved. Only 5 point substitutions were observed at nt 24, 51, 189, 302, and 501, with only the substitution at nt 302 resulting in a non-synonymous substitution of T to I at residue 100. Phylogenetic analyses revealed that, based on the ORF3 gene, all PEDV isolates could be divided into three groups namely: G1, G2, and G3 (Fig. 3). Notably, all Japanese field isolates clustered closely with US isolates and recent South Korea isolates, forming a separate subcluster within G1. On the other hand, the vaccine strains, P5-V and 96-P4C6, which have been used to prevent PEDV infection in Japan, were found within G3, which are therefore genetically distant from prevailing field isolates.
DNA sequence homology of 99.6-100 % was observed between ORF3 genes of recent Japanese isolates that had the highest DNA identity (99.4-100 %) with the commonly observed on PED-vaccinated farms, leading to the loss of high numbers of pigs. As a result, the genetic characteristics and origins of prevailing PEDVs in Japan, the efficacy of PEDV vaccines being used in Japan in protecting previously well pigs from prevailing PEDVs, and the genetic differences between vaccine strains and field PEDV isolates remain critically important questions that have yet to be fully elucidated. We therefore performed this study to address these important issues regarding PED.
In this study, 88.5 % (77 of 87) of pig farms in six prefectures (Miyazaki, Kagoshima, Aichi, Hokkaido, Aomori, and Akita) were confirmed as infected with PEDV, and 72.5 % (148 of 204) of samples were found to be positive for PEDV. This result demonstrates a high prevalence of PEDV infection in Japanese pig herds.
The PEDV spike glycoprotein has a high degree of variability and contains several epitopes (Chang et al. 2002;Sun et al. 2008). Among these epitope sites, the COE domain (aa 499-638) is an important region capable of inducing PEDV-neutralizing antibodies (Chang et al. 2002). In comparison with vaccine strains (P-5V and 96P4C6) commonly used in Japan, all the field isolates were found to have 3-7 different residues in the COE domain, particularly at these 3 positions (517, 549, and 594). Notably, the amino acid at these three sites were all serine, one of few major amino acids that are capable of generating new O-linked glycosylation or phosphorylation. Netphos 2.0 server (http://www.cbs.dtu.dk/services/ NetPhos) and NetPhosBac 1.0 Server (http://www.cbs. dtu.dk/services/NetPhosBac-1.0) were used for prediction of phosphorylation site. The result showed that phosphorylation was generated from serine residues at the position 517 and 549 of the field Japanese isolates. On the other hand, using BepiPred 1.0 Server (http://www. cbs.dtu.dk/services/BepiPred) to predict the location of linear B cell epitopes, no remarkable difference between the field PEDV isolates and the vaccine strains were found. Therefore, further research is needed to determine whether these amino acid differences may affect the antigenicity of prevailing PEDV isolates and consequently influence the efficacy of the vaccines currently used on Japanese pig farms.
In May 2013, PEDV was detected for the first time in the United States. Subsequently, US strain-like PEDVs were reported in South Korea in late 2013 , and Germany in May 2014 (Hanke et al. 2015). The result of phylogenetic and genetic analysis of the partial S gene demonstrated that prevailing Japanese PEDV isolates had been previously unreported in Japan, shared the greatest similarity with US strainlike strains, and may have been introduced into Japan via unknown routes.
To date, two distinct PEDV strain types have been identified in US: the highly virulent US PEDV (US prototypes) (Stevenson et al. 2013) and the S INDEL PEDV variant, which contains insertions and deletions in the N-terminal region of the S protein, reported to cause milder disease in the field (Vlasova et al. 2014;. Interestingly, isolate 14JM-140 was grouped in the same cluster as the S INDEL variant (OH851, IOW106, KNU-1406) with 100 % nucleotide identity observed between these strains. Clinical signs recorded on PEDV-infected farms demonstrated that only 24 piglets (out of a total of 400 pigs on the farm) had disease manifesting as diarrhea, with 4 piglets dying at the time of PED onset. This finding suggests the Japanese field isolate 14JM-140 may, in fact, be the S INDEL PEDV variant. This PEDV variant is prevalent and associated with low morbidity and mortality in PED outbreaks in Japan, although more extensive genome sequencing is required to clarify this finding.
ORF3 is an accessory gene thought to influence virulence and cell culture adaptation and has been used as a viral target in attempts to reduce PEDV virulence. Generally, ORF3 has utility as a valuable tool in the study of PEDV molecular epidemiology and for differentiating between field and vaccine-derived isolates. Our study revealed that the ORF3 gene of the Japanese vaccine strains, P5-V and 96P4C6, have unique deletions (49 and 4nt, respectively) that can lead to reading frame-shift and coding of truncated polypeptides. This genetic characteristic can be used to differentiate between field and attenuated-derived vaccine PEDV. Moreover, the finding of 49nt deletion in ORF3 gene of P5-V in this study is different from the result of a previous study (Park et al. 2008) in which authors reported that P5-V have 51nt deletion in ORF3 gene. This difference may be due to the genetic variation of P5-V during the time of the study. The results of the present study demonstrated that no deletion were observed in the Japanese field isolates, suggesting that they are not vaccine-related. Phylogenetic analysis further demonstrated that Japanese field isolates had greatest genetic similarity with US strains.
Conclusions
This study demonstrated a high detection rate of PEDV on pig farms in Japan. All recent Japanese PEDV isolates were found to have previously unreported genotypes that differed from Japanese strains prior to 2013 as well as vaccine strains currently being used in Japan and had the greatest genetic similarity with US isolates, as compared with other countries. These findings suggest that prevailing PEDV isolates may have been introduced into Japan from overseas. The distant genetic relationship and amino acid differences in the neutralizing epitope COE domain between recent PEDV isolates and the vaccine strains may be responsible for unsuccessful PED control in Japan. Therefore, the development of new vaccines with greater protection against PEDV outbreaks in Japan is required.
Sample collection
A total of 204 samples were collected from suckling pigs, weaned pigs, and sows at 87 pig farms (farrow-to-finish and farrow-to-wean) experiencing acute diarrhea from six prefectures from north to south of Japan between December 2013 and October 2014. The number of samples from each prefecture was as follows: Miyazaki (n = 134), Kagoshima (n = 14), Aichi (n = 28), Akita (n = 3), Hokkaido (n = 10), Aomori (n = 15). One to 10 fecal samples, intestinal samples, or intestinal contents, were obtained from each outbreak of diarrhea. Fecal samples were taken from animals showing signs of diarrhea at the time of collection. Samples of intestine and intestinal content were collected from animals that have died due to severe diarrhea within 3 h. All the samples were temporarily preserved in ice boxes at time of collection, kept in icebox containing dry ice during transportation, and stored at freezer (−70 °C) when it arrived at the Laboratory of Veterinary Pathology, Univeristy of Miyazaki, using cryogenic freezing systems. Samples of two vaccine strains, P-5V (produced by Nisseiken Co., Ltd) and 96-P4C6 (produced by Kaketsuken Co., Ltd), were collected from commercial vaccine bottles used in pig farms in Japan.
RNA isolation
Specimens from sick pigs were homogenized and diluted five times in Dulbecco's Modified Eagle's Medium with a low concentration of glucose. Samples were then centrifuged at 5000 rpm for 10 min at 4 °C. Supernatants were stored and subsequently used for RNA extraction. For each PEDV sample, total RNA was extracted from 100 to 300 µL aliquots of supernatant using ReliaPrep ™ RNA Cell Miniprep kits (Promega Corpoation, WI, USA) in accordance with the manufacturer's instructions.
One tube RT-PCR reaction was performed using AccessQuick ™ RT-PCR System kits (Promega Corpoation, WI, USA). Exactly, 4 µL of RNA template was mixed with a reaction mixture, which contained 12.5 µL of AccessQuickTM Master Mix (2×), 0.5 µL of each specific primer (10 µM), and 0.5 µL of AMV reverse transcriptase (5 u/µL). Then, 7 µL of nuclease-free water was added to reach the total volume reaction of 25 µL. The RT-PCR reaction were done using Takara PCR Thermal cycler (Japan). Following a reverse transcription step of 45 °C for 45 min and an incubation step of 94 °C for 2 min, 35 cycles were performed as follows: 94 °C for 30 s, 53 °C for 30 s, and 72 °C for 1 min. Cycles were followed by a terminal 10 min extension step at 72 °C. The last stage was preserving the PCR products at 4 °C. The RT-PCR products were visualized by electrophoresis in a 1.5 % agarose gel containing Ethidium Bromide.
Amplification of the partial S gene and ORF3 gene
A primer pair was designed for amplifying the full ORF3 gene of PEDV with the following sequences: forward primer (ORF3-F), 5′-GTCCTAGACTTCAACCTTAC-GAAG-3′; and reverse primer (ORF3-R), 5′-AACTAC-TAGACCATTATCATTCAC-3′. The predicted size of the ORF3 PCR product was 740 bp. For the application of the partial S gene and the ORF3 gene of PEDV, RT was first performed using random primers and OligodT primers from Reverse Transcription System Kits (Promega, Madison, WI, USA). Complimentary DNA was immediately used to amplify the partial S gene (primer pair P1/ P2) and ORF3 gene (primer pair ORF3-F/ORF3/R) using GoTaq ® Green Master Mix Kits (Promega, Madison, WI, USA) under the following condition: denaturation at 94 °C for 2 min; 35 cycles of denaturation at 94 °C for 30 s, annealing at 53 °C for 30 s, and extension at 72 °C for 1 min. PCR products were purified using FastGene Gel/PCR Extraction Kits (NIPPON Genetics Co., Ltd, Japan), according to the protocol of the commercial kit's instruction.
Sequencing
All sequencing reactions were carried out in duplicate and sequences were determined in both direction with BigDye ® Terminator v3.1 Cycle Sequencing Kits and an ABI PRISM 3130xl Genetic Analyzers (Applied Biosystems, CA, USA). The resultant nucleotide sequences were deposited in GenBank under the following accession numbers: KT968486-KT968518. Nucleotide and deduced amino acid sequences were edited, aligned (MUSCLE algorithm), and analyzed using BioEdit version 7.2.5 and molecular evolutionary genetics analysis (MEGA) software version 6.0 (Tamura et al. 2013). Phylogenetic trees based on the nucleotide sequences of the partial S gene and ORF3 gene were constructed with maximum likelihood method using Hasegawa-Kishino-Yano substitution model with discrete Gamma distribution, and bootstrap tests of 1000 replicates in the MEGA v.6 program. | v3-fos |
2015-03-21T21:52:17.000Z | {
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} | s2 | Detection of Avibacterium paragallinarum by Polymerase chain reaction from outbreaks of Infectious coryza of poultry in Andhra Pradesh
Aim: This study was carried out for the detection of Avibacterium paragallinarum from outbreaks of infectious coryza of poultry Materials and Methods: The polymerase chain reaction (PCR) was standardized for the diagnosis of infectious coryza by using infectious coryza Killed vaccine, ventri biologicals, Pune as source of DNA of A. paragallinarum. Five outbreaks of infectious coryza from Andhra Pradesh were investigated in the present study. A total of 56 infra orbital sinus swabs and 22 nasal swabs were tested by PCR. Results: PCR analysis showed 56 positives (71.7%) for infectious coryza out of total 78 samples tested. Of 56 infra orbital sinus swabs tested, 47 were positive (83.9%) and 9 nasal swabs (40.9%) out of 22 tested had given positive results for infectious coryza. Samples collected from birds at acute stage of disease and samples collected before treatment with antibiotics were given better results on PCR. Conclusion: For preventing the economic losses associated with the disease, an early, accurate and rapid diagnosis is essential. PCR is a rapid and highly sensitive diagnostic technique which can substitute conventional cultural examination.
Introduction
A group of respiratory diseases, often called as respiratory disease complex which produces closely resembling symptoms, mixed infections of respiratory system with multiple etiologies are contributing to the complexity in the proper diagnosis and differentiation of respiratory diseases. Infectious coryza is a respiratory disease of chickens caused by the bacterium, Avibacterium paragallinarum primarily affecting upper respiratory tract, including the involvement of nasal passages, infra orbital and paranasal sinuses.
Infectious coryza is a cosmopolitan disease, which has been reported from all around the world where chickens are raised including India. The economic losses associated with infectious coryza results from poor growth performance in growing birds including broilers, marked reduction (10-40%) in egg production in layers and increased culling rates in meat chickens. Chronically infected birds or recovered healthy birds act as reservoirs of infection in a population and makes the disease endemic in an area [1,2].
The disease is recognized as a cause of significant loss to the poultry industry all over the world. For reducing the economic losses associated with this disease, early, rapid and accurate diagnosis is essential.
In developing countries, conventional diagnosis of infectious coryza is based on clinical signs, demonstration of satellite colonies by cultural examination and confirmation is by biochemical tests. However, the factors like simultaneous occurrence of combined respiratory infections, occurrence of NAD independent strains, overgrowth of fast growing bacteria, which are masking the growth of A. paragallinarum, requirement of special media for culturing, presence of different biovars, etc. makes the confirmatory diagnosis difficult. Hence, nucleic acid based techniques are the best alternative tools in the easy and rapid confirmatory diagnosis.
The present study was taken up to detect A. paragallinarum by Polymerase chain reaction from outbreaks of Infectious coryza of poultry in Andhra Pradesh
Ethical approval
All samples were collected as per standard collection procedure.
Collection of samples
The samples used in the study were collected from suspected outbreaks of infectious coryza from Guntur, Krishna, West Godavari and Chittoor districts of Andhra Pradesh according to the method described previously [3] in which 56 samples were infra orbital sinus swabs and 22 were nasal swabs. Samples consisted of swabs from three commercial poultry farms and two backyard flocks of Aseel chicken of different age groups with no history of vaccination against infectious coryza. Swabs were collected aseptically and soaked in 30% glycerol-phosphate buffered saline [4]. The samples were transported to the laboratory in ice pack at the earliest and stored at −20°C.
DNA extraction
The standard phenol-chloroform method described previously [5] was employed for the extraction of A. paragallinarum DNA with necessary modifications. Briefly, 567 μl of sample was mixed with 30 μl of 10% Sodium Do-decyl Sulfate (SDS) and 3 μl of proteinase-K (20 μg/ml) and incubated at 37°C for one hour. Equal volume of phenol: Chloroform solution was added and vortexed properly and centrifuged at 13000 rpm for 10 minutes at 4°C. The supernatant was taken out carefully and the phenol-chloroform extraction was repeated. Final supernatant was taken and mixed with 2.5 volume of chilled absolute ethanol and 1/10th volume of 3M Sodium acetate (pH-5.2) and kept at −20°C for overnight. The tube was centrifuged at 13000 rpm for 10 min, the pellet was washed with 70% chilled ethanol, air dried and dissolved in 30 μl of tris-ethylenediaminetetraacetic acid (TE) buffer and stored at −20°C until use.
The purity of the extracted DNA was assessed by spectrophotometer. The DNA was diluted in TE buffer and absorbency at 260 nm and 280 nm was recorded. The ratio of the absorbance at 260 and 280 nm was calculated. The sample giving a ratio of 1.8 or above was considered as pure DNA and used for further steps of the study [5]. Quantification of DNA was carried out by using Ethidium bromide binding assay and U.V. spectrophotometer reading as per the procedure out lined previously [5]. The DNA was diluted to 5 ng per μl of TE buffer. The DNA extracted from the infectious coryza killed vaccine (Ventri Biologicals, Pune) was used as standard DNA in the present study. It was used for standardization of polymerase chain reaction (PCR) protocol and as positive control in PCR test for field samples.
PCR
The primers described by previous works were used in the present study [6]. The sequence was TGA GGG TAG TCT TGC ACG CGA AT (23 bp) for forward primer and CAA GGT ATC GAT CGT CTC TCT ACT (24 bp) for the reverse primer. The Red Dye PCR Master mix (Genei, Bangalore) was used for PCR reaction which contains premixed dNTPs, Taq polymerase, MgCl 2 and buffer at optimum concentrations. The gel loading dye was also incorporated to the master mix. About 25 μl reactions were used and the protocol was initially standardized for optimizing the concentration of components of the reaction mixture in the PCR assay and then by varying the annealing temperature and cycling conditions [6] using Kyratec Supercycler SC200 thermocycler. The PCR product was stored at -20°C until use.
The standardized protocol was used in PCR for field samples collected. The reaction volume used was 25 μl in which 12.5 μl of red dye master mix along with 3 μl of target DNA, 0.5 μl each of primers and 8.5 μl of molecular biology grade water were used. Initially the tubes were exposed to 94°C for 2.5 min for denaturation. Then 30 cycles of denaturation at 94°C (1 min), annealing at 58°C (1 min), extension at 72°C (2 min) was carried out. The reaction was at 72°C for 10 min for final elongation before bringing to the final holding temperature of 4°C.
The PCR amplified product was analyzed by electrophoresis in two percent agarose gels and visualized by ethidium bromide staining. About 10 μl of the PCR product along with gel loading dye was loaded to the wells. The electrophoresis was performed at a voltage of 5 Volt/cm of the gel. After sufficient migration, the gels were taken to gel documentation system (Alpha Innotech) and the results were recorded. Appropriate positive and negative controls were included in the PCR reaction.
Results
During the present study, five suspected outbreaks of infectious coryza from Andhra Pradesh were investigated which included outbreaks in commercial poultry and native Aseel chicken. The birds were showing signs of acute upper respiratory tract infections like coughing, sneezing, nasal discharge, facial edema, edema of wattle and comb and lacrimation and conjunctivitis. Anorexia and prominent infra orbital sinus swelling were observed. Most prominent features of infectious coryza are an acute inflammation of the upper respiratory tract including the involvement of nasal passages and sinus with a serous to mucoid nasal discharge, facial edema and conjunctivitis [ Figures-1-3].
Outbreaks were reported from two layer farms which were following multi-age farming with a morbidity of 25-30% and the mortality of 5% to 10%. Morbidity of 40% and mortality of 10% were recorded along with reduced growth rate in the broiler farm from which was a small scale farm with a flock size of 20, 000. Poor hygienic and biosecurity measures were observed and this farm had the history of infectious coryza outbreak in the previous batch also. Generally, infectious coryza is characterized by high morbidity and low mortality with a drop of 10-40% in egg production. The higher production losses could be because of the stress on the birds, climatic conditions, presence of opportunistic pathogens, bio security and hygiene of the farm, parasitism etc. The Chronic or healthy carrier birds were recognized as the main reservoir of the infection and the multi-aged farms are at a higher risk of infectious coryza because of this reason. During the post-mortem examination, there was no characteristic feature of any other respiratory viral pathogen. Infra orbital sinus swelling typical to infectious coryza was very evident. The commercial flocks were vaccinated against Newcastle disease (ND), Infectious Bronchitis, Infectious Bursal Disease. The Aseel flocks were vaccinated against ND. No attempt was made to isolate any viral pathogens.
DNA extraction
The presence of DNA extracted from vaccine was confirmed by agarose gel electrophoresis followed by ethidium bromide staining. When viewed under UV transilluminator, a single band of DNA was observed in the gel, just below the well in all the samples. The A260/A280 ratio of 1.8 or more was obtained for all the samples from vaccine.
Standardization of PCR
PCR was carried out as described under materials and methods. The size of the amplified product was analyzed by agarose gel electrophoresis using standard DNA molecular size marker. The size of the amplified product was 500 bp, which was the size of the amplicon defined by selected primers. No amplification was observed in negative control indicating that amplicon was specific to bacteria A. paragallinarum.
Screening of field samples for infectious coryza by applying PCR
The standardized protocol was used to screen the field samples. The results of PCR analysis showed 56 positives (71.7%) for infectious coryza out of total 78 samples tested. Out of 56 infra orbital sinus swabs tested, 47 were positive (83.9%) and 9 nasal swabs (40.9%) out of 22 tested had given positive results for infectious coryza [ Figure-4]. Samples from Vijayawada outbreak gave 100% (15 out of 15) positivity for infra orbital sinus and 57% (four out of seven) positives for nasal swabs. Samples from Tenali showed 93.3% (14 out of 15) positivity for infra orbital sinus and 60% (three out of five) positivity for nasal swabs. Outbreak from Tirupati showed 83.3% (10 out of 12) positivity for infra orbital sinus swabs and all the nasal swabs were negative. Samples collected from BN Kandriga showed 80% (eight out of 10) positivity for infra orbital sinus swabs and 50% positivity for nasal swabs. All the samples tested from Dwarapudi gave negative results in PCR [ Table-1
Discussion
Infectious coryza is an upper respiratory tract disease of poultry with considerable economic impact, particularly in multi aged farms. The isolation and identification of the causative agent, of A. paragallinarum is difficult and demanding. The conventional diagnosis of infectious coryza is based on the appearance of typical clinical signs, isolation of satellitic organisms and further biochemical characterization [3,7]. But the dependence or the hemophilic nature of (requirement of V factor or NAD) A. paragallinarum is complicated by many facts. A. paragallinarum is a slow growing organism which will take 36-48 h or even more time to show detectable colonies. But the vigorous growth of the bacteria, which are in co-infection will mask the growth of the A. paragallinarum and the satellitic growth may not be appreciated. Two nonpathogenic, hemophilus bacteria named Avibacterium avium and Avibacterium volatinum, which are the part of normal flora of the chicken show satellitic colony growth similar to that of A. paragallinarum on blood agar. The reports of emergence of NAD-independent A. paragallinarum, which will not show satellitic growth again complicated this conventional method of identification [6].
Diagnosis of the infectious coryza can be more complicated when it co-occurs with other pathogens, especially bacteria like Pasteurella multocida, Ornithobacterium rhinotracheale, Salmonella species etc. [8,9]. Further complications can be contributed by the presence of opportunistic pathogens like Escherichia coli, Pseudomonas, Proteus, Staphylococcus species, Streptococcus species, Corynebacterium etc. during the cultural examination of samples from suspected infectious coryza cases [10][11][12][13]. Typical isolates of the A. paragallinarum have strict nutritional demands when grown in-vitro, meaning that complex media with costly ingredients such as NAD, oleic albumin complex, chicken serum and thiamine must be used to obtain pure cultures [3]. Some complex media, like supplemented test medium agar (TM/SN) and Hemophilus maintenance medium described previously are proven useful for characterization tests following isolation but not suitable for isolation [14].
The difficulties associated with conventional culture method and biochemical characterization of infectious coryza made the molecular technique, PCR attractive. There was no standard culture of A. paragallinarum readily available in the country and obtaining it from other countries was very difficult due to strict biosecurity norms adopted in the country. Hence, DNA of A. paragallinarum were isolated from infectious coryza killed vaccine, produced by ventri biologicals, Pune which contains page reference strains 0083 (A-1), and Modesto (C-2). The primers used in the present study were described by previous workers [6] and it was successfully used by many others worldwide [12,[15][16][17]. A 30 cycle PCR reaction with annealing temperature of 58°C for 1 min was found to be optimum for amplification of 500 bp products.
The samples collected from fresh outbreaks within two to three days of onset of clinical signs where the birds were at acute stage of disease and before the commencement of antibiotic treatment (samples from Vijayawada and Tenali) showed more percentage of positive results than samples collected from the flocks which were ailing from the disease for few weeks and those with antibiotic treatment (ciprofloxacin/enrofloxacin). Samples from the flock from Dwarapudi, which were at the convalescent stage of disease due to effective antibiotic treatment showed all negative for PCR test. Samples from the acute stage of the disease for accurate diagnosis of infectious coryza were recommended by previous workers [3]. Antibiotic treatment significantly reduced the capacity of both conventional cultural examination and PCR test to detect A. paragallinarum [4]. The better performance of PCR against cultural examination for field samples probably reflects the difficulties in obtaining samples of good enough quality to ensure the growth of fragile A. paragallinarum in-vitro [4]. The false negative results and expense of test can be significantly reduced, if the PCR test is being applied as a flock test as recommended by previous workers [18] by pooling of samples from two to three birds instead of examining samples from individual birds separately.
Two flocks of Aseel chicken, one was backyard flock and the other was exclusively reared for cockfighting found to have suffering from infectious coryza. The flock from BN Kandriga, which was a [21]. Four isolates of A. paragallinarum were obtained from native Kampung chickens of Indonesia and observed that infectious coryza can be present in less intensive production systems [15]. The potential importance of infectious coryza in less intensive system was supported by the fact that infectious coryza killed more chicken than any other disease, including Newcastle disease, in Thai village chickens [22]. Poor housing, parasitism and inadequate nutrition might be the predisposing factors of infectious coryza [7]. The disease in Aseel chicken can pose a serious threat to our backyard poultry wealth and also can act as a source of infection to the commercial poultry. Hence, the occurrence of the infectious coryza in Aseel and other indigenous breeds of chicken must be closely monitored and vaccination must be carried out if it is found to be necessary.
Conclusion
In the present study, three infectious coryza outbreaks were investigated in commercial poultry and two from Aseel chicken. All the outbreaks showed similar symptoms with varied intensity. The birds were showing signs of acute upper respiratory tract infections like coughing, sneezing, nasal discharge, facial edema, edema of wattle and comb and lacrimation and conjunctivitis. PCR was standardized for rapid and accurate diagnosis of infectious coryza and field samples were screened. The disease, infectious coryza which was considered to be a disease of commercial chicken was diagnosed in native Aseel chicken and also in commercial chicken from Andhra Pradesh. The PCR was as an easier and rapid diagnostic tool for infectious coryza and found to be highly sensitive while screening the field samples. | v3-fos |
2016-03-22T00:56:01.885Z | {
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} | s2 | Determination of Phenolic Compounds and Antioxidant Activity in Leaves from Wild Rubus L. Species
Twenty-six different wild blackberry leaf samples were harvested from various localities throughout southeastern Poland. Leaf samples were assessed regarding their phenolic compound profiles and contents by LC/MS QTOF, and their antioxidant activity by ABTS and FRAP. Thirty-three phenolic compounds were detected (15 flavonols, 13 hydroxycinnamic acids, three ellagic acid derivatives and two flavones). Ellagic acid derivatives were the predominant compounds in the analyzed leaves, especially sanguiin H-6, ellagitannins, lambertianin C, and casuarinin. The content of phenolic compounds was significantly correlated with the antioxidant activity of the analyzed samples. The highest level of phenolic compounds was measured for R. perrobustus, R. wimmerianus, R. pedemontanus and R. grabowskii. The study showed that wild blackberry leaves can be considered a good source of antioxidant compounds. There is clear potential for the utilization of blackberry leaves as a food additive, medicinal source or herbal tea.
Introduction
Many plants look similar to one another, especially wild plants. In Poland, 63 species of blackberries occur in the wild, but only a few of them have nutritional and healing properties [1,2].
Blackberry leaf has many traditional uses, and it is officially approved in Germany for treating certain health conditions. Blackberry leaves can be made into tea or used as a mouthwash and gargle solution, according to Flora Health [1]. Tannins in blackberry leaf are responsible for some of the beneficial effects, although tannins can cause liver damage if taken in large amounts over long time frames. One should consult a qualified health-care provider before using blackberry leaf supplements. Commission E, the German regulatory agency for herbs, has approved blackberry leaf tea for relieving non-specific acute diarrhea. Tannins in the leaves can alleviate this problem, according to Flora Health. Commission E advises taking 4.5 grams of blackberry leaves daily as a tea or other internal supplement. The University of Maryland Medical Center (UMMC) lists a standard dosage of blackberry leaf tea for relieving diarrhea as 1 heaped teaspoon of dried leaves per cup of hot water, drinking 1/2 cup per hour. The UMMC recommends talking to a doctor before taking blackberry leaf for treating diarrhea, because certain types of diarrhea can be worsened by herbal treatment [3].
Martini et al. [4] evaluated the effects of R. ulmifolius on Helicobacter pylori bacteria, using leaves and isolated polyphenols. H. pylori is a common cause of gastrointestinal ulcers and stomach inflammation. It has developed some resistance to antibiotics, and antibiotics for treating H. pylori infection are not readily available in developing countries. The leaf extract and all of the polyphenols had antibacterial effects against H. pylori. The most important phenolic compounds in blackberry leaves are ellagitannins, which show high antioxidant and free radical scavenging activities. For this reason, their potential effects in preventing oxidative related diseases, such as cardiovascular diseases, have been widely studied. In vitro studies show that ellagitannins, at concentrations in the range of 10-100 µM, show some relevant anti-atherogenic, anti-thrombotic, anti-inflammatory and anti-angiogenic effects, supporting the molecular mechanisms for vascular health benefits [5]. There is clear potential for the use of blackberry leaves in the food, cosmetic and pharmaceutical industries.
Among common fruits and vegetables, blackberry is one of the richest in anthocyanins, flavonol glycosides, and other phenolics, which contribute to the high antioxidant capacity of its berries. However, data on the chemical composition of Rubus species leaves are scarce. Although the content of leaf phenolics is affected by environmental conditions and the level of maturity at harvest, it is very important to know the chemical composition and the antioxidant capacity of different Rubus species in order to selectively use them in the pharmaceutical and alimentary industries.
So far, to our knowledge, there have been no comparative studies on the chemical composition of leaves of a large number of Rubus species. Consequently, the purpose of this study was to identify a broad range of phenolic acids and flavonoids and their contents in leaves of 26 species belonging to the Rubus genus, and to compare them. This is the first paper about flavonoids and the phenolic acid composition of numerous members of the multispecies Rubus genus.
Peak Identification and Assignment
Identification and peak assignment of phenolic compounds in blackberry leaves was based on comparison of their retention times and mass spectral data with those of standards and published data ( Table 1). Thirty-three phenolic compounds were detected in wild blackberry leaves. Fifteen of them were flavonols: five kaempferol (MS 2 ion at m/z 285.0187) and 10 quercetin (MS 2 ion at m/z 301.0277) derivatives. By comparing their mass spectral data with those reported previously [6][7][8], these flavonols were tentatively identified as monoglucosides of two quercetin [9,11] reported the presence of these kaempferol derivatives in blackberry samples.
Two flavones were detected in wild blackberry fruit extracts: luteolin-3-O-glucuronide (MS ion at m/z 461.0710 with MS fragmentation ion at m/z 285.0187) and apigenin-3-O-glucuronide (MS ion at m/z 445.0710 with MS fragmentation ion at m/z 269.0450). These compounds had maximum absorption at shorter wavelengths (340 nm and 338 nm) than flavonols, which indicated their presence in the analyzed samples.
Nine phenolic acid derivatives were detected in the blackberry leaf extracts. Among them were: neochlorogenic, chlorogenic acid and p-coumaric acid, identified by comparison with standard compounds. Two caffeoyl hexosides were found with m/z 341.0849 and an MS/MS fragment at 179.0349, obtained after the loss of 162 amu (hexose moiety) [10,12]. The caffeoyl dihexose and caffeic acid derivatives were identified with m/z 503.1190 and m/z 459.094, respectively. These two compounds had a spectrum characteristic for caffeic acid derivatives, with ëmax at 324 nm. The p-coumaroylquinic acid was identified with m/z 337.0937 and fragmentation m/z 191.0553 (as quinic acid) and m/z 163.0380 (as p-coumaric acid).
Some ellagitannin and ellagic acid derivatives were identified in Rubus leaves. Ellagic acid (MS ion at m/z 300.9999) and ellagic acid pentoside (MS ion at m/z 433.0777), rhamnoside (MS ion at m/z 447.0527) and methyl ellagic acid pentose (MS ion at m/z 477.1082) were identified in blackberry extracts based on mass spectral data and comparison of their retention times with those of standards and published data (Table 1) [10,12,13]. Three ellagitannins-sanguiin H-6 (MS ion at m/z 1869.0851), lambertianin C (MS ion at m/z 1401.3730) and ellagitannins hexoside (casuarinin) (MS ion at m/z 935.0760)-were identified in wild blackberry leaf based on maximum absorption at 240 nm, mass fragmentation spectral data m/z 633.0750 (galloyl-hexahydroxydiphenoyl-glucose; galloyl-HHDP-glucose) and m/z 300.9999 (ellagic acid), and published data [14,15]. Sanguiin H-6 (comprising four hexahydroxydiphenoyl, two galloyl and two glucosyl units) is the major ellagitannin in berries and their products [16]. Lambertianin C consists of six hexahydroxydiphenoyl, three galloyl and three glucosyl moieties [17]. Lambertianin C is relatively abundant in Rubus fruit [18]. Rt-retention time.
Phenolic Compounds from Wild Blackberry Leaves
Analysis of the extracted phenolic compounds of 26 samples is presented in Figure 1. The total content of flavonoid derivatives, phenolic acids and ellagitannins was calculated as the sum of compounds resulting from UPLC-PDA analysis. The total content of phenolic compounds extracted from leaves of wild blackberry was highly diverse and ranged from 83.02 mg/g dry matter (dm) for R. austroslovacus to 334.24 mg/g dm for R. perrobustus. The R. pomobustus, R. wimmerianus, R. grabowskii, and R. pedemontaneus samples had the highest content of phenolics. The R. austroslovacus, R. nessensis, and R. caesius samples had the lowest content. Among particular groups of phenolic compounds, the largest was composed of ellagitannins-from 51.59 mg/g dm for R. austroslovacus to 255.01 mg/g dm for R. wimmerianus. Blackberries, especially their leaves, are known for their high content of ellagitannins, which determine their value in the prevention of diseases [5]. The average content in all analyzed samples was 165.84 mg/g dm.
The second important group of bioactive compounds contained in the leaves of wild blackberries was composed of flavonoid derivatives of quercetin, kaempferol, luteolin and apigenin. The content of these compounds ranged from 8.68 mg/g dm in the leaves of R. macrophyllus to 61. 27 Gudej and Tomczyk [19] found the highest flavonoid aglycone content after hydrolysis in the wild leaves of R. nessensis (1.06% dm), and the lowest in the wild leaves of R. fruticosus (0.34% dm), respectively. These compounds also play an important role as substances with a high antioxidant activity and in the prevention of many diseases [20]. In nine species of wild blackberry leaves, quercetin-3-O-glucuronide was not detected, and the largest amount of this compound was in R. crispomarginatus (28.08 mg/g dm).
The next group of polyphenols in blackberries is composed of phenolic acids, derivatives of caffeic acids, p-coumaric acids and ellagic acids. The amount of these compounds found ranges from 8.62 mg/g dm in leaves of R. nessensis to 43.14 mg/g dm in leaves of R. pericrispatus. The average from all samples of blackberry leaves was 28.74 mg/g dm. Among these compounds, the content of ellagic acid and its derivatives is especially valuable, because these compounds are assigned anti-tumor activity [21].
Among derivatives of caffeic acid, in the majority of species, the content of neochlorogenic acid was higher than that of chlorogenic acid. In R. parthenocissus the value of neochlorogenic acid was 22.07 mg/g dm, and that of chlorogenic acid only 0.41 mg/g dm. Among derivatives of ellagic acid, ellagic acid rhamnoside was found in the smallest amounts in the leaves of analyzed R. praecox, i.e., 0.01-0.21 mg/g dm, while in R. bifronus, this compound was not detected. Similarly, small amounts of methyl ellagic acids pentose (from 0.03-0.77 mg/g dm) were found, and in five species these compounds were not detected.
Antioxidant Activity
Antioxidant activity of wild blackberry leaf extracts, as measured by FRAP and ABTS°+ methods, is presented in Figure 2. The tested extracts from the leaves of wild blackberry species were characterized by diverse antioxidant activity. The lowest FRAP activity was observed for samples of extracts from the leaves of R. pericrispatus < R. plicatus < R. nessersis < R. macrophyllus and the lowest ABTS°+ activity for R. nessersis and R. caesius (Figure 2). The last two species are among those having the lowest contents of phenolic compounds too (Figure 1). In contrast, the highest FRAP abilities were exhibited by the species R. pedemontanus (192.91 mmol TE/g dm) and R. parthenocissus (192.53 mmol TE/g dm).
Both are among the species with a very high content of phenolic compounds (Figure 1). The sample from the leaves of R. pedemontanus species also showed the highest ability of ABTS radical scavenging (212.69 mmol TE/g dm). Mullen et al. [17] reported that sanguiin H-6 was a major contributor to the antioxidant capacity of raspberries fruits, together with Vitamin C and the anthocyanins. The correlation observed between antiradical activity measurements and ellagitannins indicated that phenolics of high molecular weight were major contributors to antioxidant capacity.
Significant positive correlations were found between the results of antioxidant assays (FRAP and ABTS°+) and ellagitannins (Pearson correlation = 0.614 and 0.725, respectively) and with total phenolic compounds (Person correlation = 0.608 and 0.737, respectively). The correlation coefficients between the other phenolic compounds and antioxidant activity were weak. Our results indicated that these compounds contributed markedly to the total antioxidant capacity of the leaf samples studied. This can be attributed to the structures of ellagitannins characterized by the presence of several hydroxy functions in ortho position, which exhibit a greater ability to donate a hydrogen atom and to support the unpaired electron as compared to phenolics of low molecular weight [22]. The leaves of blackberries are rich in phenolics, which have antioxidant and anticancer properties [23,24]. Wang et al. [6] found that the leaves from blackberry, raspberry, and strawberry plants had high antioxidant capacities and total phenolics content compared to their fruit tissues; therefore, they reported that Rubus leaves have great capacities as free radical scavengers and peroxide decomposers. The obtained results enabled the estimation of the leaf content of phenolics and antioxidant activity across a wide range of species of wild blackberry. These may be used in the preparation of infusions in preventative medicine [23]. Oliveira et al. [25] reported that Cydonia oblonga Miller leaves had a very high total phenolics content, varying from 4.9-16.5 g/kg dm, and were characterized by higher relative contents of kaempferol derivatives than fruits (pulps, peels, and seeds). Tavares et al. [26] demonstrated that the ingestion of wild blackberry species attenuated degenerative processes in the brain, with these benefits ascribed to the phenolic components.
Cluster Analysis
Cluster analysis is an unsupervised data analysis method, meaning that prior knowledge of the sample is not required. HCA enables interpretation of the results in a fairly intuitive, graphic way.
Cluster analysis of the different blackberry leaf samples, according to their phenolic compounds (33 variables), was used as an additional exploratory tool to assess heterogeneity among different quality parameters of Rubus leaves. Generally, HCA showed 11 clear similarity clusters (Figure 3). The highest similarity of blackberry species was obtained between R. nessensis and R. austroslovacus. The lowest similarity (below 30%) was obtained between R. radula, R. fasciculatus, R. gracilis, R. glivicensis, R. montanus, R. subcatus, R. crispomarginatus and R. praecox. The rest of the analyzed Rubus leaves showed similarities between 36% and 74%.
Plant Material
Twenty six different wild blackberry leaf samples were collected in September and October 2013 from various localities throughout southeastern Poland (Table 4). Leaves were directly frozen in liquid nitrogen and freeze-dried (24 h; Alpha 1-4 LSC, Christ, Germany). The homogeneous powders were obtained by crushing the dried tissues using a closed laboratory mill to avoid hydration. Powders were kept in a refrigerator (−80 °C) until extract preparation, no longer than 7 days.
Extraction Procedure by Pressurized Liquid Extraction (PLE)
The Speed Extractor E-916 (BUCHI Labortechnik AG Switzerland) was used for pressurized solvent extraction. Blackberry leaf powders (0.3 g) were mixed with 1 g of diatomaceous earth and placed into 10 mL extraction cells containing a cellulose paper filter at the bottom of each cell. The cells containing the samples were placed into the accelerated solvent system (ASE system), pre-filled with extraction solvent, pressurized and then heated. The extraction conditions and process were as follows: firstly, a static time of 5 min, followed by a flush elution with a 60% volume, followed by a nitrogen purge of 60 s, then the samples were extracted twice. The extraction was conducted under the following conditions: solvent: 50% methanol acidified with 1% acetic acid; extraction volume: 25 mL; temperature: 50 °C; pressure: 100 bar. As a result, six samples were processed in one run in exactly the same conditions. Extraction was repeated five times. The diluted extracts were filtered through a hydrophilic PTFE 0.20 µm membrane (Millex Samplicity Filter, Merck, Damrstadt, Germany) and then subjected to UPLC-PDA-MS analysis.
Identification of Polyphenols by the Liquid Chromatography-Mass Spectrometry (LC-MS) Method
Identification of the polyphenol of extracts was carried out using an ACQUITY Ultra Performance LC TM system (UPLC TM ) with binary solvent manager (Waters Corporation, Milford, MA, USA) and a Micromass Q-Tof Micro mass spectrometer (Waters, Manchester, UK) equipped with an electrospray ionization (ESI) source operating in negative mode. For instrument control, data acquisition and processing, MassLynx TM software (Version 4.1) was used. Separations of individual polyphenols were carried out using a UPLC BEH C18 column (1.7 μm, 2.1 × 100 mm, Waters Corporation, Milford) at 30 °C. Samples (10 μL) were injected and elution completed in 15 min, with a sequence of linear gradients and isocratic flow rates of 0.45 mL·min −1 . The mobile phase was composed of solvent A (4.5% formic acid, v/v) and solvent B (100% of acetonitrile). The program began with isocratic elution with 99% A (0-1 min), then a linear gradient was used until 12 min, lowering A to 0%; from 12.5-13.5 min, returning to the initial composition (99% A), and then holding constant to re-equilibrate the column. Analysis was carried out using full scan, data-dependent MS scanning from m/z 100-1500. The mass tolerance was 0.001 Dalton and the resolution was 5.000 Leucine enkephalin was used as the internal reference compound during ESI-MS accurate mass experiments and was permanently introduced via the LockSpray channel using a Hamilton pump. The Lock Mass Correction was +/−1.000 for Mass Window. All TOF-MS-chromatograms are displayed as Base Peak Intensity (BPI) chromatograms, and scaled to 12,400 counts per second (cps) (=100%). The effluent was led directly to an electrospray source with a source block temperature of 130 °C, desolvation temperature of 350 °C, capillary voltage of 2.5 kV and cone voltage of 30 V. Nitrogen was used as desolvation gas, with a flow rate of 300 L·h −1 .
The characterisation of the individual components was carried out via retention time and accurate molecular masses. Each compound was optimized to its estimated molecular mass [M−H] − in the negative mode before and after fragmentation. The data obtained from UPLC/MS were subsequently entered into the MassLynx 4.0 ChromaLynxTM Application Manager software. Based on these data, the software is able to scan different samples for the characterised substances.
Analysis of Antioxidant Activity
The ABTS°+ activity of the sample was determined according to the method of Re et al. [27]. The total antioxidant potential of the sample was determined using a ferric reducing ability of plasma (FRAP) assay by Benzie et al. [28] as a measure of antioxidant power. A standard curve was prepared for all analyses, using different concentrations of Trolox. All determinations were performed in triplicate using a Shimadzu UV-2401 PC spectrophotometer (Kyoto, Japan). The results were corrected for dilution and expressed in milimoles of Trolox per gram dm (mmol TE/g dm). | v3-fos |
2019-04-04T13:07:24.662Z | {
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} | 0 | [] | 2015-09-12T00:00:00.000Z | 62889980 | {
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} | s2 | Effect of EDTA on Cadmium and Zinc Uptake by Sugarcane Grown in Contaminated Soil
Corresponding Author: Pantawat Sampanpanish Environmental Research Institute, Chulalongkorn University, Bangkok 10330, Thailand and Center of Excellence on Hazardous Substance Management, Bangkok 10330, Thailand Email pantawat.s@chula.ac.th Abstract: The effect of EDTA on cadmium and zinc uptake by sugarcane (Saccarumofficinarum L.) grown in contaminated soil was investigated. Sugarcane was grown in pots for 1 month and EDTA was added at concentration levels of 0(control), 0.5, 1 and 2 millimole per 1 kilogram of soil. Plants were harvested at 2, 4, 6 and 8 months. Soil samples were analyzed to determined levels of cadmium and zinc. Plants were separated into 5 parts: Leaves, bagasses, underground stem, root and juice, including the phytotoxicity. Moreover, the plants were also analyzed for cadmium and zinc accumulation. This result shows that the concentration of EDTA at 1 millimole per 1 kilogram of soil had the highest cadmium accumulation in the root of sugarcane at 21.87, 44.68, 57.52 and 41.97 mg kg −1 , at the contact time, respectively. Furthermore, the root showed the most efficient sugarcane uptake compared to the underground stem, bagasses, leaves and juice (root > undergroundstem > bagasses > leaves > juice). The EDTA concentration at 2 millimoles per 1 kilogram of soil has maximum zinc accumulation in various parts of sugarcane. The harvested time at 2 months showed zinc uptake much higher than for leaves and bagasses, while the maximum accumulation of zinc was found in roots and the underground stem at 4 months.
Introduction
Heavy metal pollution in soil has become a wide spread global problem, which can threaten ecosystems and human health. In northwest Thailand, cadmium (Cd) contamination in paddy field water and soil has become a growing concern. This affects agricultural products, especially rice, garlic and soybean. Cadmium contamination in soil and plants has increased to such an extent that it does not meet the safety standard set by the codex committee for food additives and contaminants (Codex, 2007). This causes are attributed to mining and human activity which have an impact on human health and the food chain (Luc et al., 2012). At presently there are numerous remediation technologies used to clean up heavy metal contamination in water, soil and sedi-ments. These techniques include in situ physical and chemical processes (soil flushing, solidification and stabilization), thermal processes, ex situ physical and chemical processes (soil washing, chemical reduction and oxidation) and other processes including excavation and off-site disposal (Sampanpanish et al., 2006). Thus, alternative energy plants were selected for cultivation in Cd contaminated areas, owing to the energy crisis in Thailand. Sugarcane has been used as a raw material for ethanol production and, for this reason, has replaced rice farming in many areas (Tananonchai, and Sampanpanish, 2014). A chelating agent was proposed to improve the efficiency of conventional phytoremediation of metal polluted soils by solubiliting target metals from the soil (Salt et al., 1995) and making them more available for plantuptake and translocation to the shoots and leaves (Lombi et al., 2001). EDTA has been used the most widely for phytoremediation because it has strong chelating ability with different metals and increases the bioavailability in soil to plants (Salt et al., 1998). The objectives of this study were to determine the effect of EDTA on total Cd and Zn in contaminated soil and leachate at different EDTA application rates as well as determine the efficiency of total Cd and Znuptake by sugarcane grown in contaminated soil.
Soil Preparation
Contaminated soil was collected in Maesot district, Tak province, Thailand from a 0-30 cm surface layer. It was air dried at room temperature before separation through a 2-mm sieve. Soil texture was determined using hydrometer methods (Bouyoucous, 1951). The pH was measured by a pH meter (soil: Water = 1:1) (Thomas, 1996). Cation Exchange Capacity content (CEC) was determined with ammonium saturation and distillation (Hendershot et al., 1993). Electrical Conductivity (EC) was measured by a conductance meter (soil: Water = 5:1). Organic Matter content (OM) was determined by the Walkley-Black method (Nelson and Sommers, 1996). Available phosphorus was determined with Bray II sollution (Bray and Kurtz, 1945). Available Potassium was determined by ammonium acetate 1 N pH 7.0 extractions (Tan, 2005). The total Cd and Zn contents in soil were determined by USEPA method 3052 (USEPA, 1996) and analyzed using an Atomic Absorption Spectrometer (AAS). A Perkin Elmer AAs model AAnalyst 800 (Perkin Elmer Instruments LLC, Unberlingen, Germany) was used.
Pot Preparation
The Cd contaminated soil was sepeated into at 10 kg batches and placed in plastic plots (a dry weight soil). These were then covered with plastic bags. Plastic was also placed under the pots to collect drainage water which was then returned to the pots to prevent the loss of metals through leaching. After this, each pot was planted with an underground stem (setts). A month later, the first application of EDTA was conducted. The EDTA was added at concentration levels of 0(control), 0.5, 1 and 2 millimoles per 1 kilogram of soil. The plants were prepared by cutting pieces of mature sugarcane stems (setts), LK 92-11 ecotype, obtained from Kampangpetch province. The USEPA method 3052 was used for the analysis of background cadmium and zinc in plant (setts) samples. The result showed that cadmium and zinc contents in setts were non-detected. Soil, sugarcane and leachate water samples were harvested at 2, 4, 6 and 8 months. An analysis was made to determine levels of cadmium and zinc in the soil and in five plant parts: Leaves, bagasses, underground stem, root and juice.
Sample Preparation and Analysis
Soil was dried at 105°C for 24-48 h to achieve aconstant weight. It was then crushed to pass through a 2-mm sieve and thoroughly mixed to homogenize. To determine the available cadmium and zinc in the soil sample, it was air-dried for 72 h, then crushed to pass through a 2-mm sieve and finally mixed to homogenize before analysis. Sugarcane samples were cleaned and washed with tap water twice and rinsed with deionized water. Next, they were cut into five parts: Leaves, bagasses, underground stem, root and juice. Samples were dried at 105°C for 24-48 h to achieve aconstant weight and dry matter yields were determined. Sugarcane juice was analyzed by digestion in a mixture of 10:1:4 (v/v/v) of HNO 3 : H 2 SO 4 : HClO 4 (Jackson, 1973). Available cadmium and zinc in soil were estimated by DTPA extraction method (0.005 M DTPA +0.01 M CaCl2) (Lindsay and Norvell, 1978). Total cadmium and zinc in soil and sugarcane (leaves, bagasses, underground stem, root and juice) were determined using the USEPA method 3052 (USEPA, 1996). Leachate water was analyzed by the USEPA method 3015A (USEPA, 1998). The digested solution was analyzed by an Atomic Absorption Spectrometer (AAS).
Statical Analysis
The variance and significance of cadmium and zinc in soil, sugarcane and leachate water samples were analyzed by Analysis Of Variance (ANOVA). In cases where the data varies, the difference was compared by Duncan's New Multiple Range Test (DMRT). Statistical analysis of data was performed using the Statistical Package for Social Science (SPSS) software.
Soil Properties
The contaminated soil was collected in Maesot district, Tak province, Thailand. The soil background properties were determined and are presented in Table 1. Soil texture is loam with pH value of 7.6 which is considered neutral. The background cadmium and zinc in soil were 136.47 and 4,137.43 mg kg −1 , respectively. The contamination levels of heavy metals in soils have been reported for different countries. The USEPA (1990) and Alloway (1995) reported that cadmium contaminated soil at 2 and 12 mg kg −1 would be zinc accumulated at 200 and 720 mg kg −1 , respectively. Table 2 shows that cadmium and zinc accumulation inleachate water increased when EDTA rates increased. It was found that the highest amounts of cadmium and zinc accumulated in 2 mmol kg −1 of soil. Cadmium accumulation was found at 0.17, 0.22, 0.28 and 0.37 mg kg −1 and zinc at 1.17, 1.25, 1.62 and 2.00 mg kg −1 at harvested time of 2, 4, 6 and 8 months, respectively. The cadmium and zinc concentrations inleachate water increased with the increase in harvesting time. Figure 1 shows the effect of EDTA concentration levels at 0(control), 0.5, 1 and 2 mmol kg −1 on cadmium and zinc accumulation in soil. The results tend to suggest that EDTA decreased cadmium and zinc concentrations in soil slightly because of its uptake to accumulate in plant tissues. Cadmium and zinc accumulation in soil was lowest at 8 months. The accumulation of cadmium in soil at 8 month was 102.36, 102.05, 96.08 and 98.34 mg kg −1 and zinc were 3,200.76, 3,116.97, 3,031.52 and 3,005.63 mg kg −1 for EDTA applied at the rate of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively. The concentrations of total cadmium and zinc in soil were lowest at 0.5, 1 and 2 millimole per 1 kilogram of soil as compared to non-EDTA soil (0 mmol kg −1 of soil). Madrid et al. (2003) also found EDTA to be highly effective at mobilizing metals in soil making it easy for uptake by plants.
Effect of EDTA on Availability of Cadmium and Zinc in Soil
Availability or bioavailability is the proportion of total metals that are available for incorporation into biota or taken up by plants (John and Leventhal, 1995). This study shows that the level of available cadmium and zinc tended to decrease when havesting time increased (Fig. 2). However, statistical analysis by ANOVA indicated that there was no significanted difference in the available cadmium and zinc concentration in soil throughout the harvesting time and when adding EDTA of 0(control), 0.5, 1 and 2 mmol kg −1 of soil. The highest available cadmium concentrations in the soil were 27.81, 29.31, 30.11 and 30.34 mg kg −1 for EDTA applied at the rate of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively at 2 months. While, available zinc concentration highest at 2 months were 78.02, 81.77, 85.25 and 102.05 mg kg −1 for EDTA applied at the rate of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively.
Effect of EDTA on Cadmium Accumulation in Different Parts of Sugarcane
The effect of EDTA on cadmium accumulation in different parts of sugarcane is illustrated in Fig. 3. The result shows that EDTA at 1 mmol kg −1 of soil produced maximum cadmium accumulation in different parts of sugarcane. The highest cadmium accumulation in leaves was 7.21, 8.24, 12.45 and 11.16 mg kg −1 for EDTA rates of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively, at 4 months (Fig. 3a) and 9.71, 10.40, 14.13 and 12.75 mg kg −1 in bagasses, respectively at 4 months ( Fig. 3b). At the same time, the highest cadmium accumulation in underground stems was 11.07, 11.59, 16.76 and 15.76 for EDTA rate, respectively (Fig. 3c). The highest cadmium accumulation in roots was 49.09, 50.65, 57.52 and 52.27 mg kg −1 for EDTA applied rate, respectively at 6 months (Fig. 3d). Moreover, this result shows lower cadmium contamination in juice among 0.15-0.23 mg kg −1 (Fig. 3e). In their study, Chen and Cutright (2001) found EDTA at 0.5 g kg −1 tended to increase cadmiumin the shoot of Helianthus annuus from 34 to 115 mg kg −1 , demonstrating the total removal efficiency at 59 µg/plant. The cadmium accumulation in different parts of sugarcane were highest in roots followed by underground stems>bagasses>leaves> juice. This result conforms with the research of Segura et al. (2006) who noted that highest cadmium accumulation was in the root of sugarcane (Saccharum spp.) at 0.23 mg kg −1 , followed by stems and leaves which was equal to 0.20 and 0.13 mg kg −1 , respectively.
The Effect of EDTA on Zinc Accumulation in Different Parts of Sugarcane
The effect of EDTA on zinc accumulation in different parts of sugarcane is reported in Fig. 4. The result shows the highest zinc accumulation in leaves at 62.11, 66.20, 79.66 and 87.18 mg kg −1 at 2 month for EDTA rate of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively (Fig. 4a), while EDTA at 2 mmol kg −1 in soil produced maximum zinc accumulation in the leaves: 87.18, 36.65, 35.09 and 26.67 mg kg −1 , at harvest time, respectively. The highest zinc accumulation in bagasses was 111.58, 281.30, 320.00 and 378.16 mg kg −1 , respectively at 2 months (Fig. 4b). EDTA at 2 mmol kg −1 of soil produced maximum zinc accumulation in the bagasses of 378. 16, 144.78, 115.70 and 65.90 mg kg −1 , at harvest time, respectively. Figure 4c shows that the highest cadmium accumulation in underground stems was 114.40, 116.06, 125.00 and 151.12 for EDTA applied at the rate of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively at 4 months, while EDTA at 2 mmol kg −1 of soil produced maximum zinc accumulation in the underground stems at 130.21, 151.12, 89.27 and 69.95 mg kg −1 , of harvest time, respectively. The highest zinc accumulation in roots was 1,003.62, 1,069.34, 1,165.75 and 1,169.98 mg kg −1 for EDTA applied at the rate of 0(control), 0.5, 1 and 2 mmol kg −1 of soil, respectively at 4 months. However, the maximum zinc accumulation in the root at EDTA 2 mmol kg −1 was 849.56, 1,169.98, 762.15 and 538.33 mg kg −1 , at harvest time, respectively (Fig. 4d). Moreover, this study found that the EDTA had produced zinc accumulate in juice among 10.91-12.88 mg kg −1 (Fig. 4e). Note that the result shows zinc accumulation in different parts of sugarcane tends to be highest in roots followed by bagasses> underground stems> leaves> juice. Weihong et al. (2009) reported that with EDTA at 0.8 mmol kg −1 , shoot and root of Vetiveriazizanioides tend produce an increase of zinc accumulation at 7.3 and 37.4%, respectively. Kabata-Pendias and Pendias (2000) reported that roots tend to contain more zinc than shoots and leaves, particularly if plants are grown in zinc-rich soil. Our findings were similar to the results obtained by Oprea et al. (2010) and Ranjan et al. (2012).
Conclusion
The effect of EDTA on cadmium and zinc uptake by sugarcane (Saccarumofficinarum L.) grown in contaminated soil was investigated. This result shows that soil cadmium and zinc contamination tends to decrease when harvesting times increase. In contrast, at increased harvesting time, cadmium and zinc accumulation increasing in plants while EDTA did not affect sugarcane growth. However, the results show that EDTA at 1 mmol kg −1 in soil produced the highest cadmium accumulation in various parts of sugarcane. Two mmol/kg of EDTA in soil resulted in maximum zinc accumulation in various parts of sugarcane. Thus, the EDTA increased cadmium accumulation of sugarcane in the order: Root > underground stem > bagasses> leaves> juice, while EDTA produced an increase in zinc accumulation in sugarcane as follows: Root> bagasses> underground stem > leaves > juice. | v3-fos |
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} | s2 | The Pathogenic Role of Persistent Milk Signaling in mTORC1- and Milk-MicroRNA-Driven Type 2 Diabetes Mellitus
Milk, the secretory product of the lactation genome, promotes growth of the newborn mammal. Milk delivers insulinotropic amino acids, thus maintains a molecular crosstalk with the pancreatic β-cell of the milk recipient. Homeostasis of β-cells and insulin production depend on the appropriate magnitude of mTORC1 signaling. mTORC1 is activated by branched-chain amino acids (BCAAs), glutamine, and palmitic acid, abundant nutrient signals of cow´s milk. Furthermore, milk delivers bioactive exosomal microRNAs. After milk consumption, bovine microRNA-29b, a member of the diabetogenic microRNA-29-family, reaches the systemic circulation and the cells of the milk consumer. MicroRNA-29b downregulates branched-chain α-ketoacid dehydrogenase, a potential explanation for increased BCAA serum levels, the metabolic signature of insulin resistance and type 2 diabetes mellitus (T2DM). In non-obese diabetic mice, microRNA-29b downregulates the anti-apoptotic protein Mcl-1, which leads to early β-cell death. In all mammals except Neolithic humans, milk-driven mTORC1 signaling is physiologically restricted to the postnatal period. In contrast, chronic hyperactivated mTORC1 sig-naling has been associated with the development of age-related diseases of civilization including T2DM. Notably, chronic hyperactivation of mTORC1 enhances endoplasmic reticulum stress that promotes apoptosis. In fact, hyperactivated β-cell mTORC1 signaling induced early β-cell apoptosis in a mouse model. The EPIC-InterAct Study demonstrated an association between milk consumption and T2DM in France, Italy, United Kingdom, Germany, and Sweden. In contrast, fermented milk products and cheese exhibit an inverse correlation. Since the early 1950´s, refrigeration technology allowed widespread consumption of fresh pasteurized milk, which facilitates daily intake of bioactive bovine microRNAs. Persistent uptake of cow´s milk-derived microRNAs apparently transfers an overlooked epigenetic diabetogenic program that should not reach the human food chain.
INTRODUCTION
The worldwide rising prevalence of type 2 diabetes mellitus (T2DM) has been attributed to rising rates of obesity and poor lifestyles, genetic and developmental susceptibility to disease [1]. According to the US National Diabetes Statisitics Report 2014 [2] 29.1 million people or 9.3% of the U.S. population have diabetes mellitus.
Notably, since the 1960´s there is a steady increase in the prevalence rate of T2DM in industrialized countries [7]. Shortly prior to the 1960's, the refrigerator and widespread cooling technology was introduced into most households and food stores of developed countries. Cooling technology allows daily access to fresh pasteurized cow´s milk, whereas in former times and less developed countries primarily fermented milk and milk products have been consumed due to the unavailability of cooling facilities.
The pathogenesis of age-related diseases of civilization such as obesity, T2DM, metabolic syndrome, cancer, neurodegenerative diseases and early aging have all been related to persistently increased activation of the nutrient-sensitive kinase mechanistic target of rapamycin complex 1 (mTORC1) [8][9][10][11][12][13][14]. Remarkably, milk is the only and sufficient nutrient system of all mammals that allows appropriate postnatal growth. It has recently been recognized that milk is not "just food" but represents a sophisticated signaling system of mammalian evolution that adequately activates mTORC1 of the cells of the milk recipient to drive controlled species-specific growth [15]. Milk contains abundant essential branched-chain amino acids (BCAAs: leucine, isoleucine, and valine) and glutamine that are important nutrient signals that communicate with pancreatic -cells of the milk recipient to promote mTORC1-mediated insulin synthesis and secretion. Insulin itself is an important growth hormone that activates mTORC1 of insulin-dependent cells facilitating anabolism and growth of the newborn organism. Notably, it is not the carbohydrate content of milk and skim milk that exerts strong insulinotropic effects, but the insuli-notropic amino acids that operate as nutrient signals stimulating insulin secretion. In all mammals, except humans since the Neolithic revolution, this insulinotropic signaling system is restricted to the postnatal growth phase and has not been designed by evolution for lifelong use. Downregulation of intestinal lactase expression resulting in lactose intolerance after the weaning period is thus the original genetic makeup of humans and all other mammals.
It is the intention of this review to provide evidence that persistent abuse of mTORC1-activating and microRNAtransmitting bovine milk is a major overlooked pathogenic and epigenetic factor promoting the epidemic of T2DM.
It will be demonstrated that persistent and excessive cow´s milk consumption provides and mediates abundant nutrient and growth factor signals that overactivate -cell mTORC1 signaling of the human milk recipient promoting endoplasmic reticulum (ER)-stress and early -cell apoptosis.
Milk Provides BCAAs Activating mTORC1
Milk proteins provide highest amounts of essential BCAAs, especially leucine [44]. Leucine plays a pivotal role for activating mTORC1 [39]. Of all animal proteins, whey proteins contain the highest amount of leucine (14%) [44], and in comparison to meat (8% leucine), whey proteins un- Fig. (1). Schematic working model representing the potential crosstalk bewteen milk signaling and persistent -cell mTORC1 hyperactivation promoting endoplasmic reticulum (ER)-stress and early -cell apoptosis. Milk is a rich source of branched-chain amino acids (BCAAs). Leucine (Leu) and glutamine (Gln) synergistically activate -cell mTORC1. mTORC1 activation is important for insulin synthesis. Insulin synthesis is further promoted by whey-stimulated secretion of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1(GLP-1). Milk-derived exosomal microRNA-29b (miR29b) may represent a shutoff mechanism of mitochondrial BCAA catabolism that increases BCAA plasma levels enhancing BCAA-driven -cell mTORC1 activation. Persistent milk-mediated -cell mTORC1 activation promotes ER-stress leading to early -cell apoptosis. ER-clearance is impaired by mTORC1-mediated inhibition of autophagy further promoting -cell apoptosis. ER-stress in a vicious cycle via activating transcription factor 4 (ATF4)-mediated upregulation of L-type amino acid transporter (LAT) augments leucine-mTORC1 signaling. Further enhancement of -cell apoptosis may result from milk miR29b-mediated inhibition of anti-apoptotic Mcl-1. Milk miR-21-mediated inhibition of FoxO1 may increase -cell proliferation and may increase oxidative stress further promoting -cell apoptosis. See list of abbreviations. dergo fast intestinal hydrolysis, thus operate like an i.v.amino acid infusion [45][46][47][48][49].
Milk Provides Glutamine Activating mTORC1
Milk protein (8.09 g glutamine/100 g) in comparison to beef protein (4.75 g glutamine/100 g) provides 70% more glutamine [49]. In the -cell, glutamine is an important activator of mTORC1. Glutamine functions as a gatekeeper for cellular leucine uptake via the L-type amino acid transporter (LAT) and is a precursor of the glutaminolysis pathway that activates mTORC1 [16,[50][51][52]. Leucine is an allosteric activator of glutamate dehydrogenase (GDH), the key-regulating enzyme of the glutaminolysis pathway [50][51][52]. This intimate interplay of glutamine and leucine maximizes the flux through GDH in pancreatic -cells, which is important for mTORC1-S6K1-dependent insulin secretion [52]. Thus, leucine and glutamine should be regarded as milk´s amino acid messengers that activate -cell mTORC1 signaling during the postnatal period of mammalian life.
Additionally, whey-derived amino acids directly exert inulinotropic effects on pancreatic -cells [16,18,19]. Milk protein consumption in comparison to meat protein intake thus results in significant hyperinsulinemia [63]. Furthermore, i.v.-infusion of bovine -casomorphin 4, a bovine milk protein peptide that is generated in the intestinal tract, has been shown to stimulate μ-receptors of -cells and substantially increases insulin secretion in dogs [64]. Thus, milk intake may also stimulate neuroendocrine regulatory networks of the -cell that augment insulin secretion.
Milk Stimulates IGF-1 Secretion Activating mTORC1
A meta-analysis confirmed that continued milk consumption increases serum levels of insulin-like growth factor-1 (IGF-1) [65]. The European Prospective Investigation into Cancer and Nutrition (EPIC) confirmed a relationship between milk intake in 2,109 European women with increased IGF-1 serum levels [66]. A 20% increase in serum IGF-1 levels has been observed in prepubertal children previously not used to milk consumption after a daily intake of 710 mL of ultra-heat treated (UHT) milk for 4 weeks [67]. A recent study including 193 overweight adolescents aged 12-15 years drank either 1L/day of skim milk, whey, casein or water for 12 weeks. All milk-based-drinks contained 35 g milk protein/L. IGF-1 significantly increased with skim milk and tended to increase with casein compared to the pre-test control group [68]. Casein in comparison to whey protein has been shown to differentially enhance hepatic IGF-1 synthesis [55]. Notably, per capita cheese comsumption, the major dairy source of casein, increased in Germany from 5 kg in 1950 to 24.4 kg in 2013 [69].
Milk Provides Palmitic Acid Activating mTORC1
Bovine milk contains about 3.5 to 5% total lipid. About 98% of the lipid is composed of triacylglycerols, transported in milk fat globules [70]. The major fatty acid of total fatty acids of milk lipids is palmitate (C16:0) with 32.3 wt% [70,71]. Palmitate like BCAAs activates mTORC1 at the lysosomal compartment [43].
Thus milk, the promoter of postnatal growth of mammals, activates mTORC1 of the milk recipient either by transfer or induction of pivotal mTORC1 activating signaling pathways.
MILK´S SOFTWARE: EXOSOMAL MICRORNAS
In 2013, Melnik and colleagues [15] hypothesized that milk functions as a genetic transfection system of the milk recipient by transfer of exosomal bioactive bovine milk mi-croRNAs to modulate early metabolic programming. The microRNA regulatory network appears to represent milk´s epigenetic software that augments mTORC1 signaling and cell cycle progression to optimize growth conditions of the newborn mammal. Valadi et al. [72] were the first who demonstrated that exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Thus, secreted exosomal microRNAs have been appreciated as important players of gene regulation and intercellular communication [73][74][75].
MicroRNAs bind through partial sequence homology to the 3´-untranslated region (UTR) of target mRNAs and cause either translational block or mRNA degradation [76].
Recently, Witwer and Hirschi [77] challenged the hypothesis that diet-derived foreign microRNAs, especially plant-derived xenomirs, might be absorbed and could regulate vertebrate metabolism and function. The caveat of Witwer and Hirschi [77] is primarily based on repeated negative results evaluating the intestinal uptake of plant-derived mi-croRNAs [78][79][80], which could not confirm the reported intestinal absorption of rice-derived MIR168a [81].
In mammals however, microRNAs enclosed by membranous microvesicles (exosomes) play a pivotal role for horizontal microRNA transfer [82]. Milk is apparently mam-mal´s longest distance interindividual exosomal signaling system that allows maternal-neonatal communication for metabolic regulation of the newborn. In fact, breast milk in comparison to all other human body fluids contains the highest amounts of total RNAs [83]. It has been suggested that bovine and human milk exosomal microRNAs may be trans-ferred to the infant to promote immune regulatory functions [84][85][86]. MicroRNA-containing exosomes of 30-100 nm diameter have been identified in human breast milk, cow´s milk, bovine whey and colostrum [87][88][89]. Exosomes from bovine colostrum and mature milk are able to deliver mi-croRNAs into cultured cells thereby increasing cytoplasmic microRNA levels [89]. Recently, Baier et al. [90] provided evidence that microRNAs of commercial pasteurized cow´s milk are absorbed by adult human subjects in biologically meaningful amounts from nutritionally relevant doses of cow´s milk and affected gene expression of human peripheral blood mononuclear cells, HEK-293 kidney cell cultures and mouse liver cells. The authors estimated that the 245 microRNAs of bovine milk may modulate the transcription of more than 11,000 human genes [90]. The lipid bilayer of milk exosomes protects their microRNA cargo against harsh degrading conditions like low acidic pH of 1-2 and RNasemediated degradation [86,91]. Boiling of milk, however, results in complete microRNA degradation [92]. Recently, Howard et al. [93] studied the influence of homogenization, pasteurization, microwave treatment and storage at 4°C of commercial whole milk, fat reduced (2%) milk and skim cow´s milk on microRNA recovery. Notably, more than 50% of microRNA-29b was still detectable after pasteurization and homogenization of whole and 2% fat milk in comparioson to raw milk [93]. Nearly one third of microRNA-29b was recovered in skim milk after these procedures [93]. Storage of 2% fat milk for 15 days did not affect microRNA-29b concentrations [93]. Thus, raw cow´s milk contains the highest amounts of bioactive microRNAs, whereas pasteurized refrigerated commercial milk still contains substantial amounts of bioactive microRNAs [90,93].
Furthermore, microRNA-21 induces adipogenic differentiation and proliferation of human adipose tissue-derived mesenchymal stem cells [106,107], thus promotes fat mass accretion. MicroRNA-21 orchestrates high glucose-induced signals to TORC1, resulting in renal cell pathology in T2DM [108]. Moreover, microRNA-21 has been demonstrated to promote renal injury in a mouse model of T2DM [109]. Thus, excess intake of bovine milk microRNA-21 may overstimulate -cell mTORC1 activation and may contribute to renal mTORC1-driven pathology in T2DM.
The rate-controlling step of BCAA catabolism is catalyzed by the multienzyme mitochondrial branched-chainketoacid dehydrogenase (BCKD) [143]. About half of the BCKD catalytic activity resides in skeletal muscle, whereas a considerable portion of activity also resides in adipose tissue [143]. The BCKD complex is composed of the branchedchain keto acid dehydrogenase (BCKDHA), the dihydrolipoamide branched-chain transacylase (DBT), and the dihydrolipoamide dehydrogenase (DLD) [143,144]. Notably, the DBT forms the core of the BCKD complex [145]. Mersey and coworkers [146] provided evidence that human mi-croRNA-29b controls the expression of the BCKD complex at the level of mRNA translation. Human microRNA-29b recognizes the mRNA of DBT, which forms the core of the BCKD complex and provides the binding site for all other proteins in the BCKD complex including the branched-chain -keto acid dehydrogenase kinase (BCKDK) [146,147]. Thus, microRNA-29b, a major microRNA of bovine milk [86,92], suppresses BCAA catabolism. Intriguingly, Baier and coworkers [90] demonstrated that bovine microRNA-29b, which is identical to their human ortholog (www.mirbase.org), increased in substantial amounts and in a dose-dependent manner in healthy milk consumers. Furthermore, microRNA-29b increased in peripheral blood mononuclear cells (PBMCs) associated with a doubling of cellular microRNA-29b levels six hours after oral exposure
MicroRNA-29b: Milk´s Inhibitor of BCAA Catabolism?
to commercial cow´s milk [90]. Remarkably, milk consumption evoked 30% changes in microRNA-29b target gene expression in human PBMCs [90]. From these data, it is conceivable to suggest that bovine microRNA-29b may modify mRNA levels of its target DBT mRNA, which translates the functionally most important core component of the BCKD complex (Fig. 1).
Why should milk inhibit BCAA catabolism? There is good reason to believe that milk provides a regulatory epigenetic microRNA program that rescues valuable essential BCAAs from mitochondrial oxidation in order to favor their incorporation into important functional and structural proteins required for growth and development. Leucine, isoleucine and valine are among the most hydrophobic amino acids, which are crucial determinants for hydrophobic clefts of enzymes and are important for the insertion of proteins such as receptors into cell membranes [143]. Hydrophobic residues are crucial for oxygen binding in hemoglobin and myoglobin and substrate binding of various enzymes [148]. Remarkably, surfactant protein B contains 37% of BCAAs (17.7% leucine) [149]. Leucine-rich transcription factors such as leucine zippers are most important for adequate regulation of transcription and cell signaling [150]. It is thus conceivable, that BCAA catabolism should be attenuated during the process of postnatal growth and development. From this perspective, it makes sense that milk provides a signal to switch off BCAA catabolism in order to increase BCAA levels for the formation of vitally important BCAAdependent proteins. Notably, in stored and refrigerated whole milk and 2% fat milk more than 50% of microRNA-29b is preserved compared to unprocessed raw milk [93].
There is accumulating evidence that commercial milk consumption is associated with increased body mass index and obesity in humans and in a recently reported mouse model, which demonstrated increased mTORC1-S6K1 activation during bovine milk consumption [33,[151][152][153][154][155]. In addition, milk-mediated transfer of microRNA-21, which induces adipogenesis [106,107], may function as a further mechanism that promotes the development of obesity, the most common comorbidity of T2DM. It has recently been demonstrated in db/db mice that long-term inhibition of mi-croRNA-21 reduced obesity [156].
Remarkably, BCKD component transcripts were significantly lower in subcutaneous adipocytes from obese versus lean Pima Indians [139]. Moreover, mRNA abundances for BCAA catabolic enzymes were markedly reduced in omental white adipose tissue of obese persons with metabolic syndrome compared with weight-matched healthy obese subjects [139]. Lynch and Adams [157] recently concluded that attenuated mitochondrial BCAA metabolism, which appears to be a critical metabolic deviation in T2DM, is either caused by altered gene expression, mutations, or epigenetic factors that affect gene expression. Notbably, BCKDHA (branchedchain -keto acid dehydrogenase), the gene encoding the regulated unit of BCKDC is one of the primary susceptibility genes identified that affected the risk of both T2DM and obesity [158].
Nevertheless, genetic mutations cannot explain the worldwide and steady rise in diabetes prevalence. Thus, an epigenetic modifier such as a very common dietary factor may promote BCAA dysregulation of human beings. Bovine milk microRNA-29b-attenuated BCAA catabolism may be the missing overlooked epigenetic factor that is responsible for the epidemic of T2DM.
Palmitate, the major fatty acid of milk fat, significantly increases the expression of microRNA-29a in myocytes [163]. MicroRNA-29a targets and suppresses mRNA of insulin receptor substrate-1 (IRS-1) and attenuates IRS-1 expression. Ectopic expression of microRNA-29a thus impairs insulin signaling and glucose uptake in myocytes through a substantial decrease in IRS-1. Intriguingly, bovine milk contains microRNA-29a [89], thus presents a putative exogeneous source of microRNA-29a-mediated suppression of insulin signaling. The suppression of skeletal muscle insulin signaling via milk-derived microRNA-29a transfer may spare insulin for more important anabolic purposes as skeletal muscle activity is rather low during the nursing period. Increased circulating blood levels of palmitate in obesity may induce palmitate-mediated microRNA-29a expression in skeletal muscle, which may be fortified by milk-derived palmitate as well as direct transfer of bovine milk mi-croRNA-29a into the systemic circulation of the milk consumer. MicroRNA-29a and let-7-family of bovine milk may thus promote microRNA-driven insulin resistance [159,164].
BCAA-MTORC1-S6K1-MEDIATED INSULIN RE-SISTANCE
Fatty acids and their metabolites have been implicated in the development of insulin resistance and T2DM. However, metabolomics technologies revealed that BCAAs and related metabolites are more strongly associated with insulin resistance than many common lipid species. Nevertheless, in animal feeding studies, BCAA supplementation required the background of a high-fat diet to promote insulin resistance [136].
MILK ACCOMPANIES THE LIFELONG MARCH TO DIABETES
Accelerated fetal growth and increased birth weight are well-known risk constellations increasing the risk of T2DM and obesity later in life [175][176][177]. As medicine and nutritional sciences still regard milk as a source of valuable proteins, vitamins, and calcium, an increase (4 servings per day) of either milk or dairy products is recommended by most societies of gynecology and obstetrics during pregnancy [178]. Data from 50,117 mother-infant pairs of the Danish National Birth Cohort collected from 1996-2002 showed an increase of placental weight and birth weight across the whole range of milk intake [179]. The Generation R Study, a population-based prospective cohort study from fetal life until young adulthood in Rotterdam, investigated 3,405 mothers during pregnancy [180]. Maternal milk consumption of >3 glasses (450 mL of milk) per day was associated with greater fetal weight gain in the third trimester of pregnancy, which led to an 88 g higher birth weight than that with milk consumption of 0 to 1 glass per day [180]. Notably, this association was limited only to milk, whereas protein intake from nondairy food or cheese was not associated with increased birth weight. A possible explanation for this finding is the presence of biologically active microRNAs in milk and their potential absence in processed and fermented milk products such as cheese [93]. Jiang et al. [94] recently detected increased levels of microRNA-21 in placental tissue of mothers with macrosomal infants. Bovine microRNA-21 transfer to the pregnant mother by milk consumption may overstimulate trophoblast mTORC1, which controls nutrient and BCAA transfer to the fetus [181][182][183][184][185][186]. A recent literature review provided translational evidence that milk consumption during pregnancy but not fermented dairy products increased placental and birth weight [187].
After birth, high protein infant formula feeding maintains exaggerated BCAA-mTORC1 signaling associated with rapid weight gain [188][189][190][191]. Infant formula with higher protein versus formula with lower protein content has been linked to increased mTORC1 signaling [188,189], which is associated with higher weight gain velocity [190,191]. Importantly, rapid weight gain in infancy has been related to an increased risk of T2DM [192]. Data derived from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 confirmed that milk consumption in children increased body mass index (BMI) [151] and induced earlier onset of menarche [193]. Increased BMI and early onset of menarche are both explained by milk-mTORC1-mediated anabolism, which obviously accelerates human growth trajectories. Remarkably, early onset of menarche is a wellknown risk factor for the development of T2DM recently confirmed in a systematic review and meta-analysis [194]. Thus, there is good reason to assume that persistent bovine milk signaling deviates the physiological human axis of mTORC1 signaling during intrauterine and extrauterine life.
MTORC1 INDUCES ENDOPLASMIC RETICU-LUM-STRESS-MEDIATED -CELL APOPTOSIS
To maintain appropriate -cell mass and -cell homeostasis, a physiological level of mTORC1 signaling is required [195]. In order to adapt to the increased metabolic burden of obesity and insulin resistance, -cells increase mass by proliferation, neogenesis and hypertrophy to enhance -cell function [195]. There is substantial evidence that ER-stress of chronically overacticated -cells results in early -cell apoptosis, the hallmark of T2DM [196][197][198]. Studies in humans indicate that glucose intolerance appears after 20% reduction in -cell mass, while overt diabetes develops with 65% reduction [199]. Pancreatic -cells have a heavy engagement in insulin synthesis (> 50% of total protein synthesis) and express high levels of the ER-stress transducers eukaryotic translation initiation factor 2-alpha kinase 3 (EIF2AK3) and endoplasmic reticulum-to-nucleus signaling 1 (ERN1), which induce the unfolded protein response (UPR) [197]. Recent evidence supports the concept that hyperactivation of the UPR is closely related to -cell dysfunction and apoptosis [196,197].
ER-stress and -cell dysfunction have been related to increased lipotoxicity [198]. The saturated fatty acid palmitate, the most abundant fatty acid of milk lipids, has been implicated to play a major role in -cell apoptosis [199]. Glucose amplifies fatty acid-induced ER-stress in pancreatic -cells via activation of mTORC1 [200]. Notworthy, palmitate and BCAAs are both able to activate mTORC1 on lysosomal compartments [43].
Apparently, in a vicious cycle, ER-stress via induction of eIF2 -P/activating transcription factor-4 (ATF4) signaling stimulates the expression of LAT thereby enhancing intra-cell leucine levels that further stimulate mTORC1 signaling during ER-stress [204,206] (Fig. 1). Han et al. [207] demonstrated that ER-stress via ATF4 and DNA damage-inducible transcript 3 (DDIT3) upregulation increased protein synthesis leading to cell death.
ER-stress stimulates autophagy as an adaptive response to clean up terminally misfolded proteins from the ER [198] (Fig. 1). It is well established that mTORC1 is a negative regulator of autophagy [208,209]. Remarkablly, it has been shown that stimulation of autophagy improved ER-stressinduced diabetes in a mouse model [210]. Furthermore, inhibition of mTORC1 during ER-stress increased autophagy and attenuated apoptosis [211].
Thus, persistent milk-mediated overstimulation of -cell mTORC1 may promote chronic ER-stress promoting -cell apoptosis, the hallmark of T2DM. In fact, persistent mTORC1 activation of -cells in -cell TSC2 -/mice resulted in a biphasic response with hyperinsulinemia and hypoglycemia at young ages (4-28 weeks) and hypoinsulinemia and hyperglycemia due to enhanced -cell apoptosis in adult mice [212]. These findings are in accordance with the observations of Ozcan et al. [203], who found enhanced UPR signaling in cells lacking TSC2. This experimental constellation thus resembles chronic milk-mediated mTORC1 hyperactivation, which apparently provides a most critical mechanism promoting early death of -cells in milk consuming societies (Fig. 1).
ARE MILK-DERIVED MICRORNAS DIABETO-GENIC?
It is predicted that more than 30% of human genes are regulated by microRNAs. There is most recent scientific interest in the influence of microRNAs in the regulation of insulin signaling pathways and insulin resistance in type 1 and type 2 diabetes [213][214][215][216][217]. As milk promotes insulin secretion and mTORC1-driven growth, it is most conceivable that milk-derived exosomal microRNAs that reach the systemic circulation [90] may be taken up by the pancreatic -cell to modify translation during the period of lactation and milk feeding.
The -cell must respond immediately to changes of blood glucose levels and thus has an intimate connection to the systemic blood circulation. To facilitate this connection, the -cells of the islets of Langerhans are embedded in a dense capillary network. Notably, islet capillaries show about ten times more fenestration than those within the exocrine tissue and are highly permeable [218][219][220]. Endothelial cell fenestrae produce a pore of about 100 nm in diameter and allow rapid passage of macromolecules [220].
There is recent evidence that -cells release microRNAcontaining exosomes [221,222]. It is thus conceivable, that milk exosomes, which have a size of 50-100 nm, may reach the -cells from the systemic circulation. The purpose of milk-mediated exosomal microRNA signaling may be the stimulation of -cell growth and insulin secretion during the postnatal growth period, which requires an adaptation of the infant´s -cell mass to fulfill increased insulin demands. However, persistent milk-driven microRNA signaling may deteriorate -cell homeostasis.
Notably, the microRNA-29 family, which consists of mi-croRNA-29a, b, and c, has been identified as diabetic mi-croRNA markers [223]. MicroRNA-29a has been identified as one of the microRNAs that was upregulated in the serum of children with type 1 diabetes [224]. microRNA-29 has pro-apoptotic functions and is involved in renal and cardiovascular injury [225], common complications of T2DM.
MicroRNA-29b downregulates the expression of the antiapoptotic protein myeloid cell leukemia 1 (Mcl-1) [226]. In non-obese diabetic (NOD) mice, upregulation of microRNA-29a, b, and c caused pancreatic -cell death via suppression of Mcl-1, an essential member of the pro-survival Bcl-2 family genes [227]. Thus, the microRNA-29-Mcl-1 axis may thus play a role in the pathogenesis of diabetes and may contribute to -cell dysfunction in prediabetic NOD mice [227]. Furthermore, studies on microRNA expression in skeletal muscles of Goto-Kakizaki (GK) rats, a non-obese model of T2DM, identified upregulated microRNA-29a and mi-croRNA-29b in these diabetes animals compared to control animals [228]. Intriguingly, increased urinary levels of mi-croRNA-29a, b, and c have been detected in patients with T2DM [229]. Thus, upregulation of the microRNA-29 family may be involved in the pathogenesis of type 1 and type 2 diabetes.
EPIDEMIOLOGY OVERLOOKS THE IMPACT OF MILK´S MICRORNAS
The majority of epidemiological studies show that "dairy consumption" in general is inversely related to the risk of T2DM [231][232][233][234][235]. Rice and coworkers recommend the intake of more than three servings of dairy per day to reduce the risk of T2DM [236]. It is of most critical concern that most cohort studies do not accurately differentiate milk from other fermented dairy products. There are only few studies that selectively analyse the association between milk consumption and T2DM [237][238][239][240][241][242]. Surprisingly, milk, the starting material of all other processed dairy products does not convincingly exhit diabetes-protective effects as observed with fermented or processed milk products such as yoghurt. Liu et al. [237] prospectively examined the incidence of T2DM in 37,183 women in relation to the number of skim milk and whole milk servings and found no significant decrease in diabetes risk. Elwood et al. [238] studied 2,375 men of the Caerphilly cohort. Milk intake showed no significant trend with incident diabetes. Villegas et al. [239] investigated 64,191 women of the Shanghai women cohort and reported a significant decrease in diabetes risk in women consuming > 200 g milk/day versus none. Kirii et al. [240] analysed 59,796 men and women of a Japanese cohort and found no significant risk for diabetes for milk consumption in men, whereas women exposed to > 200 g milk/day showed a trend to lower diabetes risk, although not reaching statisitical significance. The Physicians´ Health Study [241] (21,660 men) exhibited a significant increase in diabetes risk. Less than 1 serving of whole milk/week was associated with a diabetes prevalence of 1.7% and > 2 servings/week with 2.6% (p<0.001), respectively. For skim/low fat milk the diabetes percentages were 1.6 and 2.3 (p<0.001) respectively [241].
The worldwide largest prospective study investigating the type of dairy product intake and incident T2DM is the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct study [242], a nested case cohort within 8 European countries (n=340,234). Although, the pooled hazard ratios (HRs) demonstrated only a slight but not sig-nificiant increase of diabetes risk in relation to increased milk intake, HRs of individual countries showed substantial variations. Higher diabetes risks (HR > 1) were observed in the French, Italian, UK, German and Swedish cohorts, whereas the Netherlands and Denmark exhibited HR=1 (Fig. 2). Only Spain (UHT milk consumption > 96% of total milk consumption [243]) exhibitied a HR < 1 [242]. Sluijs et al. [242] convincingly concluded that the findings for milk and diabetes risk remain inconclusive and require further research of the associations with various types of milk.
Differences in heat exposure and time during milk processing may modify the biological activity of bovine mi-croRNAs. High temperature short time (HTST) pasteurization (72°C, 15 sec), and UHT processing (140°C, 14 sec) may have different effects on the bioactivity of milk´s exosomal microRNAs. Furthermore, milk processing by the consumer prior to use (boiling or microwave treatment) is also of critical importance to evaluate milk microRNAmediated effects on human health [93].
DISCUSSION
"Milk and sugar" are the inseparable and most common food items on everyman´s table in Western societies. It is known for a long time, that the addition of milk to a low glycemic carbohydrate meal exaggerates the insulinemic response comparable to that of a hyperglycemic carbohydrate meal [244]. Thus, milk intake is an overlooked metabolic burden of the -cell that increases ER-stress. However, in comparison to glucose, milk´s origin and function differ. Milk is the secretory product of the lactation genome of a mammalian species that executes a sophisticated growth program designed to upregulate anabolic mTORC1 signaling of the milk recipient, the species-specific newborn mammal. Milk maintains an intimate molecular crosstalk with the pancreatic -cell via stimulation of incretin signaling and trans-fer of abundant insulinotropic BCAAs that increase insulin synthesis and secretion by upregulation of -cell mTORC1 activity. Furthermore, milk provides a microRNA signaling software. By transfer of the bovine exosomal microRNA-29 family, milk apparently attenuates BCAA catabolism, a meaningful metabolic deviation that favors BCAA incorporation into functionally important proteins during postnatal development. However, this metabolic deviation increases BCAA-mTORC1-driven -cell ER-stress as well as BCAA-mTORC1-S6K1-driven insulin resistance of peripheral tissues.
In mammals, milk signaling generally is limited to the physiological nursing period, except the Neolithic Homo sapiens, who introduced milk consumption 8000-10,000 years ago into his food chain [245,246]. Noteworthy, humans of the early Neolithic period consumed preferentially fermented milk and milk prodcuts [245,246]. Whereas lactase persistence in most Europeans resulted from LCT mutations during the early Neolithic period [247], most Asian populations are still lactose intolerant. However, the dairy industry is able to bypass physiological lactose intolerance in humans by treating milk with exogeneous microbial lactase ( -galactosidase) [248].
The Chinese transition to the Western dietary lifestyle is reflected by the Hong Kong Dietary Survey [249]. In this cohort, a dietary pattern with "more meat and milk products" was associated with a 39 % greater risk of diabetes [249]. In Europe as well, higher animal protein (milk protein plus meat protein) consumption has been associated with a higher prevalence of T2DM compared to plant-derived protein intake [250].
Most recent evidence has been provided that fermentation such as in yoghurt or cheese production destroys or attenuates the exosomal microRNA signaling of milk [93].
HR
Populations that gained mutations of the lactase gene resulting in lactase persistance have lifelong access to fresh milk containing both the amino acid hardware and microRNA software of milk. Modern populations experienced a further boost of "milk doping" and growth acceleration by the widespread distribution of refrigeration technology since the early 1950´s. With the intention to preserve valuable bioactive ingredients of milk such as vitamins, pasteurized fresh milk prodcuts reached the daily food chain of the modern consumer. This unnoticed change exposed people of technologically developed societies to daily microRNA signaling of milk [15,90,93]. Indeed, since the introduction of the refrigerator into our households the prevalence of diseases of civilization increased progressively. Persistent "abuse" of an mTORC1 sigaling system designed by mammalian evolution to operate only during the early postnatal growth phase of life may be a key mTORC1-dependent mechanism promoting age-related diseases of cilvilization such as obesity, T2DM, cancer, and neurodegenerative diseases [8][9][10][11][12][13][14][15]. The presented concern about the association of milk consumption and diseases of civilization is in accordance with recent results of Michaëlsson et al. [251], who reported a higher mortality in two large Swedish cohorts of men and women with high intake of milk but not fermented or processed dairy products. Furthermore, the authors observed a correlation between milk intake and serum levels of the inflammatory cytokine interleukin 6 (IL-6) [251], which is also increased in patients with T2DM [252]. Experimental evidence underlines that exposure of -cells to IL-6 induces early -cell death [253]. Milk-mediated IL-6 signaling may be the connecting piece that links milk consumption with low grade inflammation that promotes -cell failure and early -cell apotosis [3][4][5]. Remarkably, -cells express IL-6 receptors, which after ligand binding induce phosphorylation of signal transducer and activator of transcription-3 (STAT3) [254].
Milk´s biological function as a BCAA-and microRNAdonating system for mTORC1-driven growth may explain accelerated ageing and increased mortality with persistent milk consumption [251]. As early as 1934, McCay and Crowell [259] provided translational evidence that slower growth favours longevity of various animal species.
Remarkably, comorbidities of T2DM such as ischemic heart disease have been associated with milk consumption [260], whereas populations with a high prevalence of lactose malabsorption, whose milk intake is low, have a reduced risk of ischemic heart disease than populations with low (<30%) lactose malabsorption [261]. In another large recent Swedish cohort study, subjects with lactose intolerance had decreased risks of lung, breast, and ovarian cancer [262]. Increased whole milk intake has also been associated with prostate cancer-specific mortality among U.S. male physicians [241]. Activated mTORC1 signaling plays a pivotal role in the initiation and progression of prostate cancer [263,264]. Thus, persistently over-activated mTORC1, milk´s crucial biologi-cal function, accelerates aging and the onset of age-related diseases of civilization [8][9][10][11][12][13][14][15].
Evidence accumulates that the widely prescribed antidiabetic drug metformin functions as an inhibitor of mTORC1 signaling [265]. Intriguingly, the mTORC1 inhibitor metformin not only controls T2DM, but also reduces the risk of cancer [266], and apparently prolongs life span in humans [267]. Metformin thus counteracts milk-mediated activation of mTORC1.
From the perspective of evolutionary biology, milk consumption represents a novel human behavior that could exert adverse long-term health effects [151]. Continued overstimulation of mTORC1 signaling in humans due to persistent consumption of milk may accelerate aging of the -cell associated with -cell apoptosis. Half a century ago, the antagonistic pleiotropy theory solved the mystery of aging by postulating genes beneficial early in life at the cost of aging [268]. Early in life, milk via mTORC1 activation drives a developmental program, which persists later in life as an aimless quasi-program of aging and age-related diseases [268]. In this regard mTORC1 signaling works as pacemaker of aging [269]. In order to prevent age-related diseases such as T2DM Kapahi et al. [269] suggested to reduce mTORC1 signaling: "with TOR less is more" (Fig. 3).
Refrigeration technology has been implemented into
Western households since the 1950´s. This technological achievement allows daily and widespread access to bioactive bovine microRNAs that may affect more than 11,000 human genes [90]. This unnoticed change in human nutrition apparently plays a major role in the pathogenesis of mTORC1driven T2DM and its mTORC1-driven comorbidities. It is of critical concern that in Western societies milk-driven mTORC1 signaling starts already during fetal life (maternal milk consumption during pregnancy), is further promoted by high protein infant formula feeding, maintained by school milk intake during adolescence, and continued into adulthood and senescence.
Despite the lack of sound evidence powered by randomized controlled trials [270], industry-associated authors still proclaim milk as a "source of healthy nutrition" preventing diseases of civilization such as T2DM [271,272]. Future randomized controlled trials have to differentiate the health effects of pasteurized, HTST versus UHT milk and fermented dairy products in relation to their microRNA bioactivity, especially of the diabetogenic microRNA-29 family.
At present, no epidemiological study has considered the impact of biologically active milk microRNAs in relation to obesity and T2DM. The adipogenic and diabetogenic risk of fresh pasteurized milk has to be differentiated from UHT milk and fermented milk products such as yoghurt. Notably, Howard et al. [93] detected only trace amounts of mi-croRNA-29b in yoghurt. The inactivation of diabetogenic microRNAs during the fermentation process may explain the reduced risk of T2DM in association with yoghurt intake [273,274]. Hyperactivated -cell mTORC1 signaling in combination with milk-derived diabetogenic microRNAs superimposed by high glucose and palmitate-driven mTORC1 signaling may in a synergistic fashion accelerate ER-stress and early -cell apoptosis resulting in its final clinical outcome: type 2 diabetes mellitus ( Table 1).
CONFLICT OF INTEREST
The author confirms that this article content has no conflict of interest.
ACKNOWLEDGEMENTS
Declared none. | v3-fos |
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} | s2 | Molecular Genetic Analysis and Evolution of Segment 7 in Rice Black-Streaked Dwarf Virus in China
Rice black-streaked dwarf virus (RBSDV) causes maize rough dwarf disease or rice black-streaked dwarf disease and can lead to severe yield losses in maize and rice. To analyse RBSDV evolution, codon usage bias and genetic structure were investigated in 111 maize and rice RBSDV isolates from eight geographic locations in 2013 and 2014. The linear dsRNA S7 is A+U rich, with overall codon usage biased toward codons ending with A (A3s, S7-1: 32.64%, S7-2: 29.95%) or U (U3s, S7-1: 44.18%, S7-2: 46.06%). Effective number of codons (Nc) values of 45.63 in S7-1 (the first open reading frame of S7) and 39.96 in S7-2 (the second open reading frame of S7) indicate low degrees of RBSDV-S7 codon usage bias, likely driven by mutational bias regardless of year, host, or geographical origin. Twelve optimal codons were detected in S7. The nucleotide diversity (π) of S7 sequences in 2013 isolates (0.0307) was significantly higher than in 2014 isolates (0.0244, P = 0.0226). The nucleotide diversity (π) of S7 sequences in isolates from Jinan (0.0391) was higher than that from the other seven locations (P < 0.01). Only one S7 recombinant was detected in Baoding. RBSDV isolates could be phylogenetically classified into two groups according to S7 sequences, and further classified into two subgroups. S7-1 and S7-2 were under negative and purifying selection, with respective Ka/Ks ratios of 0.0179 and 0.0537. These RBSDV populations were expanding (P < 0.01) as indicated by negative values for Tajima's D, Fu and Li's D, and Fu and Li's F. Genetic differentiation was detected in six RBSDV subpopulations (P < 0.05). Absolute Fst (0.0790) and Nm (65.12) between 2013 and 2014, absolute Fst (0.1720) and Nm (38.49) between maize and rice, and absolute Fst values of 0.0085-0.3069 and Nm values of 0.56-29.61 among these eight geographic locations revealed frequent gene flow between subpopulations. Gene flow between 2013 and 2014 was the most frequent.
Introduction
Rice black-streaked dwarf virus (RBSDV), a member of the genus Fijivirus in the family Reoviridae, causes maize rough dwarf disease (MRDD) and rice black-streaked dwarf disease (RBSDD), which lead to severe yield losses in maize and rice in East Asia [1,2]. Variability, codon usage and nucleotide composition bias, recombination, selection pressure, and population genetic structure can each affect the evolution of a virus [3][4][5][6][7]. Therefore, we investigated the population codon usage bias and genetic structure of RBSDV in 111 MRDD and RBSDD isolates (S1 Table) sampled from eight geographic locations in 2013 and 2014. These locations were mainly in the Yellow and Huai River summer maize-growing regions of China, where the MRDD prevailed, including Henan, Shandong, Jiangsu, Hebei provinces and Beijing.
RBSDV has icosahedral, double-layered particles with a diameter of 75-80 nm that contain ten linear dsRNAs (S1-S10) that range in size from 1.8 to 4.5 kb [2,[8][9][10][11]. The dsRNA S7 is comprised of two ORFs designated S7-1 and S7-2 that encode the proteins P7-1 and P7-2, respectively. P7-1 is a nonstructural protein comprised of 363 amino acids (with a molecular mass of 41.0 kDa) that causes male sterility due to nondehiscent anthers in Arabidopsis [12]. P7-2 is a nonstructural protein comprised of 309 amino acids with a molecular mass of 36 kDa that interacts with SKP1, a core subunit of SCF ubiquitin ligase [13]. Although P7-1 and P7-2 exhibit many characteristics consistent with a role in virus replication, the genetic structure and codon usage bias of their encoding dsRNAs have not yet been elucidated. Further, the interactions of host plants with RBSDV should be examined to gain insights into the evolution of the S7 dsRNA.
Studying the nucleotide composition of these viral molecules, and the extent and causes of biases in their codon usage is essential to understanding the evolution of RBSDV, particularly to detect any interplay between the virus and the cells or immune responses of its hosts [4]. Studies have revealed complicated patterns of nucleotide composition and codon usage bias (CUB) in some viruses, but the forces shaping their evolution have not been illuminated [4]. Codon usage bias refers to the phenomenon wherein synonymous codons do not appear with equal frequencies in protein sequences. Synonymous codon usage has been studied in a wide variety of organisms, including prokaryotes, eukaryotes, and viruses [14]. CUB occurs in higher organisms, microorganisms, and in some human and animal viruses [15][16][17][18]. Among plant viruses, there have been studies on sobemovirus [19], citrus tristeza virus [20], and soybean dwarf virus [21]. However, there has been little research into CUB in RBSDV or other reoviruses to date [22].
However, analyses of the genetic structure and codon usage bias of the RBSDV S7 dsRNA had not previously been performed. In the present study, the genetic structure and codon usage bias of 111 RBSDV S7 sequences from maize and rice hosts from eight geographic locations in 2013 and 2014 were analysed. Our findings provide further insights into the evolution of RBSDV based on molecular genetic analysis of the S7 dsRNA.
Sampling of virus isolates
Maize and rice plants with symptoms of rough dwarf disease of Beijing (I) were collected from the experimental field of Chinese Academy of Agricultural Sciences. In Tangshan (II), plants were collected together with Wen-Yue Tong of Tangshan Agricultural Reseach Institutes. In Baoding (III), plants were collected together with Dr. Jie Shi and Dr. Bo Li of Hebei Academy of Agriculture and Forestry Sciences. In Jinan (IV), plants were collected together with Dr. Zhao-Dong Meng and Dr. Qi Sun from Shandong Academy of Agricultural Sciences. In Jining (V), plants were collected together with Zhao-Wen Sun of Jining Agricultural Reseach Institutes. In Zhengzhou (VI), plants were collected together with Dr. Shuang-Gui Tie and Dr. Xiao-Hua Han of Henan Academy of Agricultural Sciences. In Yancheng (VII) and Nanjing (VIII), plants were collected together with Dr. Yan-Ping Chen of Jiangsu Academy of Agricultural Sciences. In this study, our maize and rice plants were not cultivated on private land. Our study involved no specific permissions for these locations/activities, because our plant materials were all collected together with the scientific researchers of local institutions in the experimental fields of every academy of agricultural sciences. Our study did not involve endangered or protected species.
A total of 111 maize or rice plants with symptoms of maize rough dwarf disease or rice black-streaked dwarf disease were collected from eight areas in which these diseases prevailed in 2013 and 2014 (S1 Table). Nine plants were collected from Beijing, 21 from Hebei, 33 from Shandong, 25 from Henan, and 23 from Jiangsu. Rice plants were also harvested from near the same locations in which maize was also cultivated in Baoding (III), Jining (V), Zhengzhou (VI), and Nanjing (VIII). These virus-infected plant leaves were frozen in liquid nitrogen and stored at -80°C. A total of 76 maize isolates from eight geographic locations (from I through VIII), and 35 rice isolates from four geographic locations (II, V, VI, and VIII) (S1 Table) were processed and used for analyses of RBSDV S7 sequences.
RNA extractions, RT-PCR, and sequencing RBSDV dsRNA was extracted from individual maize and rice isolates following previously described methods [9,33,34]. The quality and integrity of the dsRNA were assessed on 1.2% native agarose gels and the dsRNA concentrations were estimated using a NanoDrop 2000 spectrophotometer (Thermo Scientific, USA). First-strand cDNA was synthesized using a Fast Quant RT Kit (TIANGEN, China), and PCR products were amplified with two pairs of S7-specific primers (S2 Table) using KOD-Plus-Neo enzyme (TOYOBO, Japan). These products were then sequenced at the AuGCT DNA-SYN Biotechnology Company (Beijing, China) using the dideoxy chain-termination method. For partial S7 sequences, three independent PCR reactions were sequenced to confirm sequencing quality. The sequence data was assembled and analyzed using DNAMAN and Jemboss1.5 software (EMBOSS, Cambridge, UK) [35].
Analysis of codon usage bias in S7-1 and S7-2 sequences
Codon usages in P7-1 and P7-2 were assessed using the program Codon W 1.4.4 (http:// sourceforge.net/projects/codonw/). The effective number of codons (Nc value) represents the bias towards synonymous codons but does not pertain to amino acid composition or codon number [36,37]. Nc values for different genes or isolates ranged from 20 (when one codon is used per amino acid) to 61 (when all possible codons are used equally). Highly expressed genes tend to have high codon bias with low Nc values [38]. GC3 S denotes the frequency of G+C, and the expressions A3 S , U3 S , G3 S , or C3 S indicate the frequencies of A, U, G, or C, respectively, at synonymous third-base positions.
The codon adaptation index (CAI) was used to measure the extent of codon bias in expressed genes [39,40], S7-1 and S7-2 in the present study. The value of CAI ranges from zero to one, where a value of one indicates high codon usage bias and potential expression level [40]. The codon bias index (CBI) was used to estimate the proportion of preferred codons [41]. When the CBI value is one, only preferred codons are used for all triplets in the mRNA, which would indicate a nonrandom process. In contrast, negative values for CBI indicate that nonpreferred codons are used more often than expected.
To determine the preferred codons for the S7-1 and S7-2 sequences, the value for relative synonymous codon usage (RSCU) was calculated using 111 sequences from 111 isolates. RSCU is the ratio of the observed to the expected codon frequency, assuming that all synonyms for that amino acid have an equal chance of being used. There is positive codon usage bias when the value of RSCU is greater than one, and relatively negative codon usage bias when RSCU is less than one. When RSCU equals one, a codon has been chosen randomly [42].
Five percent of the total genes with the highest and lowest CAI values were defined as the high-and low-expression datasets respectively, and were selected to determine optimal codons. Codon usage was compared using a Chi-squared contingency test of groups, defining codons whose frequency of usage was significantly higher (P < 0.01) in the high-expression dataset than in the low-expression dataset as the optimal codons [43].
Sequence variants and nucleotide diversity in S7 sequences
Nucleotide or amino acid sequence alignments among these 111 viral isolates from 2013 and 2014 were performed using the MegAlign program in DNAStar5.01 software (Madison, USA) [2,44] set to default settings. The nucleotide sequences for S7 across these 111 viral isolates were aligned using MEGA 6.06 [45]. Sliding-window analyses of nucleotide diversity (π) in S7 sequences was performed using a 200-bp window in 100-bp steps with TASSEL 3.0 software [46]. Nucleotide diversities for S7 sequences were calculated for these isolates either grouped by geographic location, host, and year, or for all isolates combined.
Detection of genetic recombination within and phylogenetic analyses of S7 sequences
Nucleotide and amino acid sequences were aligned using CLUSTAL W in MEGA 6.06 with default settings [45]. Possible recombination sites within S7 sequences were examined using the software RDP 4.22 with the RDP, GENECONV, BOOTSCAN, Maximum Chi SQUARE (MAXCHI), CHIMAERA, Sister Scanning (SISCAN), and 3Seq algorithms in the default configurations, except that the 'linear sequence' and 'disentangling overlapping signals' options were selected [47]. Recombination events were validated only if they were detected by more than two methods. The default parameter for the number of simulated datasets was 100 and the P-value cutoff was 0.05. Phylogenetic trees were constructed using the neighbor-joining (NJ) method in MEGA 6.06 software [45] for the S7 sequences from these 111 isolates. The number of bootstrap replicates was set to 1000. Only bootstrap values greater than 50% are shown.
Detection of selection pressure on S7 nucleotide sequences
The Ka/Ks ratio was used to estimate the level of selection pressure on S7, where Ka is the average number of nonsynonymous substitutions per nonsynonymous site and Ks is the average number of synonymous substitutions per synonymous site. The average values of Ka and Ks were calculated using MEGA 6.06 software [45] according to the methods described in previous studies [48,49]. When the Ka/Ks ratio is greater than one, the gene is considered to be under positive or diversifying selection. If the Ka/Ks ratio is one, selection is neutral. However, if the Ka/Ks ratio is less than one, the gene is under negative or purifying selection.
Tajima's D, Fu & Li's D, Fu & Li's F statistical tests, and haplotype diversity were estimated using the software DnaSP 5.0 [50]. Tajima's D [51], Fu and Li's D, and Fu & Li's F tests [52] hypothesize all mutations to be selectively neutral. The frequencies and numbers of haplotypes indicate the haplotype diversity in the population.
Estimation of genetic differentiation and gene flow
To detect genetic differentiation between different subpopulations, three permutation-based statistical tests, Ks à , Z (the rank statistic), and Snn (the nearest-neighbor statistic), were performed. Because these three tests can powerfully detect genetic differentiation, they are particularly effective for datasets in which mutation rates are high and sample size is small [53,54]. The level of gene flow between subpopulations was measured by estimating Fst (the component of genetic variation between populations or the normalized variation in allele frequencies among populations) and Nm (the product of the effective size of each population [N] and the rate of migration among populations [m]) [55]. Fst ranges from zero to one for undifferentiated to fully differentiated populations, respectively. An absolute value of Fst of greater than 0.33 normally suggests that infrequent gene flow has taken place. Genetic drift that can result in substantial local differentiation can be indicated if the value of Nm is less than one, but not if the value of Nm is greater than one [56]. The statistical tests for genetic differentiation and estimation of Fst were performed using DnaSP 5.10 [50].
Nc plots (a plot of Nc versus GC3s) were used to understand the relationship between nucleotide composition and codon bias in S7-1 and S7-2 ( Fig 1A). Nc should fall on a continuous curve between Nc and GC3s if GC3s is the only determinant of Nc. The Nc values for S7-1 ranged from 42 to 47 and those for S7-2 ranged from 38 to 41, indicating that there are very significant differences in codon bias between S7-1 and S7-2 (P < 0.01). The relationships between nucleotide composition and codon bias for both S7-1 and S7-2 are independent of years ( Fig 1B), hosts (Fig 1C), and geographical locations (Fig 1D). A small number of points lie on the standard curve towards GC-poor regions in the Nc plot for S7-1, but no points lie on the standard curve in Nc plot for S7-2. However, most of the points with low Nc values lie below the standard curve (Fig 1A), which suggests that S7-1 and S7-2 have additional codon usage bias independent of GC3s. In fact, points for S7-2 mostly lie far away from the standard curve in comparison with those for S7-1, which indicates that mutational bias had a weaker effect on codon usage variation in S7-2 than in S7-1.
Correspondence analysis of relative synonymous codon usage and optimal codons
Further evidence that mutational bias and other factors are responsible for codon usage variation in S7-1 and S7-2 came from correspondence analysis (CA) of the RSCU values for the two ORFs. The first two major axes explain fractions of the total variation (37.76% and 14.60% in S7-1; 38.96% and 9.64% in S7-2), and the next two axes account for 12.78% and 10.54% of the total variation in S7-1 and for 9.18% and 8.08% of the total variation in S7-2, respectively. The first and second axes for S7-1 and S7-2 were clustered in the plot (Fig 2); however, the majority of data for S7-1 and S7-2 do not cluster completely. S7-1 was scattered around the first axis, S7-2 concentrated mostly in a region located at the first quadrant of the two axes. However, the difference between S7-1 and S7-2 in this analysis was not significant (P > 0.05).
To detect correlations along the first two major axes for both CAI and Nc, correlation coefficients were calculated among values of these parameters. The separation of codons on the first axis appeared to be largely due to differences in the frequencies of codons that end with G/C or A/U. The S7-1 on axis one were strongly correlated with the C3s value (r = 0.9560, P < 0.0001) and Nc (r = 0.9234, P < 0.0001), and significantly negatively correlated with the U3s (r = -0.9516, P < 0.0001) and G3s (r = -0.8720, P < 0.0001) values ( Table 1). The S7-2 on axis one were strongly correlated with the GC3s value (r = 0.9241, P < 0.0001) and CAI (r = 0.7650, P < 0.0001), and significantly negatively correlated with the A3s (r = -0.9214, P < 0.0001) and GC (r = -0.8919, P < 0.0001) values (Table 1). For S7-2, values of CAI were significantly correlated or negatively correlated with Nc and certain codons (GC3s, GC, C3s, A3s, G3s) (|r| > 0.7, P < 0.0001) ( Table 1). But the value of CAI in S7-1 was uncorrelated with Nc or other parameters.
To determine the optimal codons used in S7-1 and S7-2, the average RSCU values in highand low-expression datasets were determined (S3 Table). Six codons were identified as the optimal codons in S7-1 and S7-2, according to the Chi-square test. Most optimal codons ended with G (41.67%) or U (33.33%), indicating that codon usage in RBSDV-S7 was biased towards synonymous codons ending with G or U.
Nucleotide diversity across S7 in 111 viral isolates
In the present study, 76 maize isolates with typical rough dwarf disease symptoms and 35 rice isolates with typical black-streaked dwarf disease symptoms were collected from eight locations in 2013 and 2014 (S1 Table). A total of 486 nucleotide mutation sites, including 194 singleton variable sites and 292 parsimony-informative sites, were detected among the S7 sequences across these 111 viral isolates, with an average of one mutation site per five base pairs. Fourteen amino acid changes were detected in P7-1, with an average of one mutation site per 26 amino acids, and 69 amino acid changes were detected in P7-2, with an average of one mutation site per four or five amino acids.
Recombination and phylogenetic analysis
One recombination event within S7 was detected in maize isolate 13IIIM-2 from Baoding using three different methods (Maxchi, Chimaera, SiSscan). The breakpoint positions were located at nucleotide (nt) 1242 in ORF S7-2 and at nt 2192 in the 3' UTR of 13IIIM-2 within the major and minor parental sequences for isolates 13VIIM-4 and 13VR-2. A phylogenetic tree was constructed from these 110 isolate sequences to determine the evolutionary relationships among these RBSDV S7 isolates. The recombinant in the present study was not included, because the phylogenetic algorithm we used cannot accommodate recombinants (Fig 4). Based on S7 sequences, these 110 isolates could be classified into two main groups, designated A and B, that were independent of year, host, and geographical origin (Fig 4). Both groups A and B could be further clustered into two subgroups (groups AI and AII; and BI and BII). Subgroup AI included seven isolates from 2013 and nine isolates from 2014; subgroup AII included four isolates from 2013; subgroup BI included four isolates from 2013 and six isolates from 2014; subgroup BII included 31 isolates from 2013 and 49 isolates from 2014.
Selection pressure and neutrality tests
To analyze possible selection pressure on RBSDV S7, the ratios of nonsynonymous to synonymous sites (Ka/Ks) were calculated for maize and rice hosts from eight geographic locations in 2013 and 2014 ( Table 2). The Ka/Ks ratios for S7-1 and S7-2 suggest that both S7-1 and S7-2 were under negative and purifying selection ( Table 2). There was no significant difference in Ka/Ks ratios for S7-1 or S7-2 between 2013 and 2014, with S7-1 values of 0.0181 and 0.0177, and S7-2 values of 0.0510 and 0.0569, respectively. And there were no significant differences in Ka/Ks ratios for S7-1 and S7-2 between hosts or between geographic locations. However, Ka/ Ks ratios for S7-1, which ranged from 0.0147 to 0.0370, were significantly lower than those for S7-2, which ranged from 0.0328 to 0.0702 (P < 0.01). This result suggests that S7-1 and S7-2 each experienced different levels of selection, and that selection pressure on S7-1 was greater than that on S7-2.
Values for Tajima's D, Fu and Li's D, and Fu and Li's F, as well as haplotype, were evaluated using DnaSP version 5.10 ( Table 3). The values for Tajima's D, Fu and Li's D, and Fu and Li's F were all negative for year, host, and geographic location except in locations I and IV. The Pvalues for Tajima's D, and Fu and Li's D, and Li's D and F were less than 0.01 in the entire population of 111 isolates and less than 0.05 in the maize, location VI, and location VIII subpopulations. This result suggests that the RBSDV populations were expanding (P < 0.01). The maize, location VI, and location VIII subpopulations were in a state of significant expansion (P < 0.05). The other subpopulations were also expanding, but not significantly. The values of haplotype diversity for S7 ranged from 0.8330 to 1.000 in different subpopulations. Such high values for haplotype diversity also indicate that the RBSDV populations were expanding.
Genetic differentiation and gene flow between subpopulations
In the present study, genetic differentiation and gene flow between RBSDV subpopulations, including years, hosts, and geographic locations, were analyzed. The P-values for Ks à , Z, and Snn calculated from RBSDV S7 subpopulations derived from 2013 or 2014 and the subpopulations derived from maize or rice were greater than 0.05. These results suggest that genetic differentiation was not significant between subpopulations defined as years or hosts (Table 4). However, genetic differentiation of six particular groups of subpopulations reached significant or very significant levels (Table 4). These six groups were derived from the combinations of locations I and III, I and VII, I and VIII, III and V, III and VII, and IV and VII. Neighbor-joining phylogenetic tree based on the nonrecombinant nucleotide sequence of S7 from different RBSDV isolates. The number of bootstrap replicates was set to 1000. Only bootstrap values > 50% are shown. Red lines represent the isolates that clustered into subgroup AI; pink lines represent the isolates that clustered into subgroup AII; black lines represent the isolates that clustered into subgroup BI; blue lines represent the isolates that clustered into subgroup BII. The absolute values of Fst for subpopulations based on years, hosts, and geographic locations were less than 0.33, indicating gene flow between subpopulations of RBSDV (Table 4). Gene flow was the most frequent across years, because the absolute Fst values for subpopulations comprised of 2013 and 2014 were the smallest. The absolute values of Nm for subpopulations comprised of 2013 and 2014, maize and rice hosts, and 24 groups based on geographic locations (except for combined locations I + III, I + VII, IV + VII, and V+VII) were greater than one (Table 4). This result suggests that gene flow occurred between years or parts of geographic locations. The absolute values of Nm were greater than four in some subpopulations, such as 2013 and 2014, hosts maize and rice, and combined geographic locations I and V, II Table 2. Nonsynonymous-to-synonymous substitution ratio for S7-1 and S7-2 sequences from RBSDV.
Discussion
MRDD is a serious viral plant disease in the Yellow and Huai River summer maize-growing region of China, in which winter wheat is also grown [57][58][59]. Maize and rice are infested naturally by the small brown planthopper (SBPH) viral vector that overwinters on winter wheat [60,61]. The SBPH also migrates between regions in China and infects maize or rice [1,62], so variation in the virus could occur during migration and reproduction of this vector. The genetic diversity of the virus might be supported by its frequent transmission by the SBPH vector in maize and rice hosts in these eight geographic locations in 2013 and 2014. In the present study, the levels of nucleotide diversity observed in these isolates were similar in maize and Genetic Analysis and Evolution of Rice Black-Streaked Dwarf Virus rice, independent of geographic locations or years. However, the differences in observed nucleotide diversity among years or parts of geographic locations reached significant levels (P < 0.05). So it is possible that the distinct levels of nucleotide diversity in these two years and eight geographic locations may be greater than that in the two hosts. High levels of adaptation of codon usage have been reported for several viruses including those in the family Flaviviridae, which infect humans, and in other viruses that infect bacteria and humans [63,64]. A detailed comparative analysis was performed to evaluate the level of codon usage bias occurring in RBSDV S7 sequences. In general, RBSDV S7 exhibits a low degree of codon usage bias (average Nc, S7-1: 45.63, S7-2: 39.96), thus mutational bias is likely to be the major force driving codon usage bias in RBSDV S7. The nucleotide composition of these genes provided evidence of mutation as the major factor influencing the codon usage bias between S7-1 and S7-2 but not towards convergence. This result is consistent with previous reports showing that mutational bias is the major force that affects codon usage in other viruses [20,65,66]. Previous studies have shown that protein secondary structure and genomic architecture also influence codon usage bias in plant viruses [67]. Combining information from the conserved sequence of RBSDV S7 and its codon usage pattern, an RNA interference (RNAi) vector could be constructed to use to transform maize for disease resistance.
Previous studies have shown that the RBSDV population in China can be organized into three groups based on S8 sequences [1], or into two groups based on S9 [32] and S10 sequences [1,2], regardless of host or geographic origin. In the present study, 111 Chinese S7 isolates also clustered into two groups without regard to host or geographic location. This result also conforms with the results of a previous study on RBSDV S9 [32]. However, in the present study, years influenced the grouping to some degree. Within subgroup A, AI was widely distributed, while AII was comprised of the isolates from only 2013. Some isolates from 2014 clustered into subgroup BII. These results provided direct evidence of the irrelevance of hosts or different geographic locations but the relevance of years in regard to genetic variation among RBSDV isolates. Correspondence analysis of relative synonymous codon usage revealed a relationship between the phylogeny and the first and second axes of S7-1 and S7-2. These results suggest that the phylogenetic clusters are correlated with the values for CAI, Nc, GC3s, GC, AC3s, and G3s.
Population genetic structure is a significant aspect influencing the evolution of plant viruses and several studies of the genetic structure of plant virus populations have been reported. However, genetic structure had rarely been studied in S7 sequences from RBSDV or other segments of similar viruses harboring two ORFs. Frequent gene flow events were detected between the subpopulations comprised of two years, two hosts, and most of the geographic locations analysed, especially among year and host subpopulations in China. These results suggest that gene flow between years was more frequent than that between hosts, and that gene flow between geographic locations was the lowest. Because only S7 sequences were investigated in the present study, more evidence from other segments of RBSDV should be gathered to verify this hypothesis.
In conclusion, the genetic structure and codon usage bias of RBSDV S7 sequences were determined for 111 Chinese isolates from maize and rice hosts obtained from eight geographic locations in 2013 and 2014. Genetic variation and genetic structure were analysed for the RBSDV S7 dsRNA sequence that is comprised of two ORFs. Further, the present study represents the first time that codon usage bias in RBSDV has been analysed. These results should help elucidate the evolution of this virus and promote further exploration of the relationship between this virus and its hosts.
Supporting Information S1 Fig. Basic characteristics of codon usage in S7-1 and S7-2. (a) Values for Nc, CAI, CBI, GC3s, and GC in S7-1 and S7-2 in data for two years, two hosts, and eight geographic locations are shown. (b) Values for G3s, A3s, C3s, and U3s in S7-1 and S7-2 in data for two years, two hosts, and eight geographic locations are shown. (TIF) S1 | v3-fos |
2019-03-31T13:44:41.414Z | {
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} | s2 | Petroleum Hydrocarbon-induced Changes in Juice of Citrus sinensis following Chronic Exposure
Aim: The aim of this study was to investigate the effect of chronic exposure to petroleum hydrocarbon pollution (PHC) on some biochemical parameters of the fruit juice of Citrus sinensis. Place and Duration of study: This study was carried out at Ebocha-Egbema and Uvuru Mbaise in Imo state (Niger Delta Area), Nigeria between October 2008 and October 2011. Methodology: Acidity (pH), concentrations of ascorbic acid (AA), glutathione (GSH), citric acid, glucose and the activity of lactate dehydrogenase (LDH) in the juice of just-ripe orange fruits ( Citrus sinensis ) from the two environments were investigated by standard methods. The estimated values were analyzed using student t-test and the results expressed as mean ± standard deviation. Results: The results obtained revealed that there was no significant (p ≥ 0.05) difference in the mean pH values, ascorbic acid and glucose concentrations of the fruit juice from the two areas studied. Mean concentrations of glutathione and citric acid in the juice from Ebocha (0.44±0.09 and 18.80±1.14mg/l) were significantly (p ≤ 0.05) lower than the values in the juice from Uvuru (0.66±0.10 and 21.43±2.02 mg/l), respectively. The results also showed that the mean activity of lactate dehydrogenase was significantly higher in the juice from Ebocha (7.033+/-1.73 U/l) than in that from Uvuru (5.344±1.74 U/l). Conclusion: The findings of this study are suggestive of a possible alteration in the metabolic activities of Citrus sinensis trees evident in its fruit juice due to the PHC pollution in Ebocha in the Niger Delta.
INTRODUCTION
While petroleum exploration and production is Nigeria's most crucial economic lifeline, the environmental consequences in the Niger Delta Area have been very glaring in terms of their negative impact. Petroleum provides a relatively cheap and convenient source of energy as compared to other fuels such as coal and electricity [1]. However, crude oil occurs with gas in such a way that the gas must be separated out before the oil could be reached. It is expensive to capture and liquefy the gas for transportation, so the oil producing companies in Nigeria chose rather to burn it off into the atmosphere by what is known as gas flaring. The most glaring site in gas production flow station is the ten-meter-high flame that burns continuously from vertical pipes at the many facilities owned by the oil companies. This gas flaring releases huge volumes of greenhouse gases into the atmosphere, while emitted sulphur dioxide returns to the soil as acid rain [2,3]. In addition, accidental spills during transportation of crude oil further contribute to the pollution of the environment. Inhabitants of the region have consistently complained of health problems, mainly respiratory tract diseases as well as damage to wild life and vegetations [2,4]. The environment of Ebocha-Egbema in the Niger Delta has been shown to be polluted as a result of the oil activities (gas flaring and oil spillage), which have gone on there for over five decades [5]. It has also been shown that the pollution in Ebocha has had adverse effects on some biochemical parameters of the native fowl (Gallus domesticus) native to that environment [6]. However, there is no information on whether the effect is the same in plants. The present study was therefore designed to investigate the effect of chronic exposure to petroleum hydrocarbon (PHC) pollution on some biochemical parameters of the fruit juice of the citrus plant (Citrus sinensis) native to the Ebocha-Egbema environment in the Niger Delta Area.
Sample Collection and Extraction of Fruit Juice
Ten fresh and apparently healthy ripe orange fruits each were selected by radom and distance distribution selection from five (5) different trees that have existed for many years in Ebocha. The same was also done from Uvuru Mbaise. The trees from the two environments were of the same age bracket. The fruits were spread on a paper on the floor to reduce the rate of deterioration of the biochemical components of the fruits. The fruit juice was extracted using manual juice press method.
Determination of Biochemical Parameters
The pH of juice was measured using digital pH meter standardized with a buffer solution as described by Walter [7]. Ascorbic acid concentration was determined using the method of Roe and Kuether [8]. Ascorbic acid was converted to dehydroascorbic acid by shaking with Norit and this was coupled to 2,4dinitrophenyl hydrazine in the presence of thiourea (a mild reducing agent).This was determined according to the method described by Raja et al. [9]. Citric acid concentration was determined by titimetric method as was described by Haleblian et al. [10]. Glucose concentration was estimated based on glucose oxidase method as described by Trinder [11]. Assay of lactate dehydrogenase activity was carried out using lactate dehydrogenase (LDH) liquid reagent kit supplied by Teco Diagnostics, U.S.A.
Statistical Analysis
Each reading was taken in triplicate. All data were expressed as mean ± standard deviation and analysed for statistical significance using students't-test.
RESULTS AND DISCUSSION
The results obtained are presented in Figs. 1-6 below. Values obtained revealed no significant (p≥0.05) difference between the mean pH of the juice from Ebocha and that of the juice from Uvuru. (Fig. 1). This could be attributed to the metabolic flexibility of plants by which they are able to adapt to stress [13]. Gehl and Colman [14] stated that plants use energy to maintain their pH. This energy in stressed plants is acquired by anaerobic metabolism [15]. The increased production of lactate in anaerobic metabolism which should result in marked decrease in pH is counter balanced by the conversion of lactate to glucose by gluconeogenesis to sustain glycolysis and energy production [16]. However, there might be a slight decrease in pH, but the low concentration of citrate as a result of reduction in tricarboxylic acid cycle (TCA) and electron transfer chain (ETC) due to reactive intermediates from PHC pollution tends to balance this decrease [17,13]. The results revealed that there was no significant (p≥0.05) difference between the mean concentrations of ascorbic acid in the juice from Ebocha and Uvuru (Fig. 2). There is no information in literature to explain this finding. However, it could be a peculiarity with citrus fruits. This is because organisms exposed to situations such as environmental pollution, produce a lot of free radicals which cause chain reactions of oxidations in living organisms [18]. As a water-soluble antioxidant, ascorbic acid in conjunction with vitamin E, a fat-soluble antioxidant and the enzyme glutathione peroxidase, help to quench free radical chain reactions that lead to oxidative stress [19]. Since ascorbic acid is a product of citrus plants, it could be that it was being replaced as fast as it was used to scavenge free radicals; thus, resulting in no significant (p≥0.05) different, (Fig. 2).
The mean concentration of glutathione in the juice from Ebocha was found to be significantly (p≥0.05) lower than the value obtained for the juice from Uvuru (Fig. 3). This could also be as a result of the antioxidant function of glutathione by which it scavenges free radicals induced by the pollution in the environment. This is in accordance with the report of Foyer et al. [19], that glutathione is associated with stress resistance owing to its redox-thiol group. Nwaogu et al. [5] also reported a reduction in the mean concentration of glutathione in the native fowl (Gallus domesticus) following chronic exposure to petroleum hydrocarbon pollution, although, the organisms used were not the same. Ascorbic acid (mg/l)
Fig. 2. Mean values of ascorbic acid concentrations of orange fruits from Ebocha and Mbaise
The present study revealed that the mean concentration of citric acid in the juice from Ebocha was significantly (p≤0.05) lower than the mean concentration of citric acid in the juice from Uvuru (Fig. 4). This could be because the plants from Ebocha, which is a polluted environment, were carrying out the citric acid stage of respiration at a slower rate than the plants from Uvuru. Free radicals due to PHC pollution inhibit the ETC and prevent oxygen from being reduced to water, thereby limiting the TCA cycle as well, since it does not proceed in the absence of oxygen [17]. Consequently, the concentration of citrate also is decreased. In addition, oxaloacetate, which condenses with acetyl Co-A to form citric acid, is directly gluconeogenic. This further reduces the concentration of citric acid because the plant (in this study) was utilising oxaloacetate in gluconeogenesis to maintain glucose availability for glycolysis. Citric acid has antioxidant properties by which it helps to preserve the flavour of fruit juices [20]. This might also account for the lower value obtained for citric acid in the juice from Eboch because the chronic exposure to PHC pollution would have had some effect on the flavour of the juice. Results obtained did not show any significant (p≥0.05) difference in the mean glucose concentrations of juice from the two environments (Fig. 5). According to Murray et al. [21], the glucose is metabolized in both aerobic and anaerobic situations. However, due to the blocking of oxidative phosphorylation by free radicals, the plant shifted to anaerobic respiration, but glucose metabolism in anaerobic respiration yields only little energy [13]. In order for plants to meet up with its energy demands, glycolysis had to proceed at a much faster pace leading to increased availability of lactate and depletion of glucose [17]. The plant subsequently resorted to gluconeogenesis to refurnish its depleting store of glucose so as to sustain glycolysis and energy production, and thereby using up the accumulating lactate [16]. This could explain why there was no significant (p≥0.05) difference in the mean glucose concentrations in the juice from both environments.
The mean activity of lactate dehydrogenase was found to be markedly higher in the juice from Ebocha than in the juice from Uvuru (Fig. 6) This could be because Ebocha is a polluted environment [6], and plants tend to shift to anaerobic metabolism under free radicalproducing stress conditions, which is regarded as an adaptive phenomenon to maintain the capacity for ATP synthesis [13,15,22,23,24]. During anaerobic respiration, pyruvate is reduced to lactate. This results in the production of high concentrations of lactate and an increase in the activity of lactate dehydrogenase. This result agrees with the finding of Jian et al. [25] that during water logging, the LDH activity in adventitious-root-retained seedlings was higher than that in the control. It also corroborates the findings of Hoffman et al. [26] that LDH activity in barley gradually increased under hypoxic stress. Achuba [27] showed that maize and cowpea seedlings had marked increase in LDH activity following exposure to refined petroleum products (kerosene, diesel, gasoline). Stephen Onodjede [28] also noted an increase in LDH activity of fowls native to Warri in Niger Delta with chronic PHC pollution when compared to that of fowls from Ughara, an unpolluted environment.
CONCLUSION
The present study revealed that the chronic exposure to PHC in the Niger Delta did not affect the concentration of ascorbic acid in the juice of Citrus sinensis native to that environment. However, the concentrations of glutathione and citric acid were markedly reduced. The activity of LDH was significantly (p≤0.05) increased. Based on these findings, it was concluded that the chronic exposure to PHC pollution in the Niger Delta has induced some changes in the metabolic activities of Citrus sinensis fruit native to that area. | v3-fos |
2019-03-31T13:42:25.201Z | {
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} | s2 | Genomics Approaches to Dissect the Genetic Basis of Drought Resistance in Durum Wheat
A better knowledge of the genetic basis of the mechanisms underlying the adaptive response to drought will be instrumental to more effectively deploy marker-assisted selection (MAS) to improve yield potential while optimizing water-use effi ciency. Genomics approaches allow us to identify and clone the genes and QTLs that underlie the adaptive response of durum wheat to drought. Linkage and association mapping have allowed us to identify QTLs for traits that infl uence drought resistance and yield in durum and bread wheat. Once major genes and QTLs that affect yield under drought conditions are identifi ed, their cloning provides a more direct path for mining and manipulating benefi cial alleles. While QTL analysis and cloning addressing natural variation will increasingly shed light on mechanisms of adaptation to drought and other adverse conditions, more emphasis on approaches relying on resequencing, candidate gene identifi cation, ‘omics’ platforms and reverse genetics will accelerate the pace of gene/QTL discovery. Genomic selection provides a valuable option to improve wheat performance under drought conditions without prior knowledge of the relevant QTLs. Modeling crop growth and yield based on the effects of major QTLs offers an additional opportunity to leverage genomics information. Although it is expected that genomics-assisted breeding will enhance the pace of durum wheat improvement, major limiting factors are how to (i) phenotype genetic materials in an accurate, relevant and high-throughput fashion and (ii) more effectively translate the deluge of molecular and phenotypic data into improved cultivars. A multidisciplinary effort will be instrumental to meet these challenges.
Introduction
Among all abiotic stresses most affected by climate change, drought is the major one curtailing global wheat production. Although conventional breeding has steadily increased crop productivity under drought conditions and across a broad range of environmental constraints, the present rate of increase in wheat productivity is insuffi cient to meet food security globally. Genomics-assisted crop improvement provides novel opportunities to enhance the yearly rate of increase in wheat yield while advancing our understanding of the genetic and functional basis of the adaptive response to water-limited conditions (Habash et al. 2009 ;Fleury et al. 2010 ;Able and Atienza 2014 ; ). This chapter illustrates how genomics approaches have been applied to genetically dissect durum wheat performance under water-scarce conditions and, more in general, how this information might help to mitigate the negative effects of drought on wheat productivity. In view of the genetic and functional similarity shared by durum and bread wheat, a number of relevant examples for the latter have also been considered.
Dissecting the Genetic Basis of Drought Resistance in Durum Wheat
The genetic basis of grain yield and the morpho-physiological traits that determine durum wheat performance under drought involves a myriad of quantitative trait loci (QTLs) of widely different effects, mostly too small to be detected experimentally. One of the reasons accounting for the modest impact of genomics-assisted breeding on the release of drought-tolerant cultivars is that screening conditions adopted under controlled conditions (e.g. growth chamber) usually provide a rather poor surrogate of the dynamics of the drought episodes that crops are exposed in the fi eld (Passioura 2007 ;Tuberosa 2012 ). Additionally, the high context-dependency of QTL effects according to the genetic background and environment (Maphosa et al. 2014 ) further limits the effectiveness of marker-assisted selection (MAS) for improving fi eld performance under drought conditions. Until the introduction of association mapping, QTL identifi cation has been pursued via linkage mapping based on the evaluation of biparental populations of recombinant inbred lines (RILs). Notably, the availability of maps obtained with different crosses and sharing common polymorphisms allows for the construction of a consensus map ) that in turn enables an even more accurate comparative analysis (e.g. meta-analysis) of QTL positions.
Association mapping (AM) based on sets of unrelated accessions provides additional opportunities to identify the loci (genes and/or QTLs) for target traits. In durum wheat, the evaluation of a panel of elite accessions characterized by high LD (>1 cM) has allowed for a genome-wide search using a limited number of markers (Maccaferri et al. 2005(Maccaferri et al. , 2011. Although AM has mostly targeted traits with a genetic basis less complex than drought tolerance (e.g. resistance to biotic stress), some studies have targeted drought-adaptative traits and grain yield in durum wheat grown under varying water regimes (Sanguineti et al. 2007 ;Maccaferri et al. 2011 ;Canè et al. 2014 ;Graziani et al. 2014 ).
Notwithstanding the clear advantages of AM as compared to biparental linkage mapping, a major limitation of the former is the high rate of false positives (i.e. Type-I error rate) due to the presence of hidden population structure. Additionally, for highly integrative and functionally complex traits such as yield, particularly under drought conditions, the effectiveness of AM is reduced by the fact that different genotypes may show similar phenotypes due to trait compensation (e.g. yield components), which inevitably undermines the identifi cation of signifi cant markertrait association. Although the number of studies is clearly too limited to draw more certain conclusions on the validity of AM in identifying QTLs for yield, the results reported by Maccaferri et al. ( 2008Maccaferri et al. ( , 2011 in durum wheat suggest that the identification of yield QTLs under different water regimes should also be pursued via biparental mapping. This is particularly true whenever the investigated trait (e.g. yield under drought conditions) is strongly infl uenced by fl owering time, in which case the overwhelming effects on yield of this phenological covariate will overshadow the effects due to the action of yield per se QTLs, hence reducing the possibility of identifying them.
QTLs for Drought-Adaptive Traits
On the discovery side, the past two decades have witnessed remarkable progress in several areas as shown also by the manuscripts in this special issue. The pivotal role of phenotyping in drought-related research is now universally recognized and receiving renewed attention (Tuberosa 2012 ;Araus and Cairns 2014 ). This revival in phenotyping has been sparked by the recent availability of new phenotyping technologies and highly automated platforms coupled with a better appreciation of the role of phenotyping in accelerating the response to selection for drought resistance, either through conventional or non-conventional approaches.
Dehydration avoidance and dehydration tolerance are the main mechanisms that contribute to maintain yielding ability under water-limited conditions (Blum 1988 ). Deep rooting and osmotic adjustment -classifi ed under dehydration avoidanceenable the plant to maintain better hydration while other biochemical and physiological features (e.g. accumulation of molecular protectants, remobilization of stem water-soluble carbohydrates, etc.) classifi ed under dehydration tolerance enable the plant to sustain metabolism even under severely dehydrated conditions. Notably, most genes induced under extreme dehydration have been shown to belong to metabolic pathways with doubtful functional signifi cance under the water-limited fi eld conditions encountered by wheat (Passioura 2007 ). Conversely, exploitation of naturally occurring variation for yield and/or drought-adaptive traits has allowed for slow albeit unequivocal progress in wheat performance under drought conditions (Reynolds and Tuberosa 2008 ).
Given the quantitative nature of abiotic stress tolerance, QTLs have been the main target of studies attempting to identify the loci regulating the adaptive response of crops to environmentally constrained conditions. In very few cases, major QTLs affecting yield and other drought-adaptive traits across a broad range of soil moisture conditions have been identifi ed (Quarrie et al. 2005 ;Maccaferri et al. 2008 ).
QTLs for Root Architecture and Size
Among the traits that affect the water balance of the plant, roots play a key role in conditions of limited soil moisture (Richards 2008 ). Roots show a high level of morphological and developmental plasticity, a peculiarity that allows plants to adapt to moisture-limited conditions (de Dorlodot et al. 2007 ;Den Herder et al. 2010 ). An example is provided by root aerenchyma and root angle, root features that are receiving increasing attention for their effects on the response to drought and other abiotic stresses (Christopher et al. 2013 ). Other root features remain much more challenging to investigate, particularly under fi eld conditions, such as in the case of root depth, a trait that has repeatedly shown a key role in crop adaptation to drought conditions when residual moisture at maturity is mainly available in deeper soil layers (Blum 2009(Blum , 2011Watt et al. 2013 ). In bread wheat, soil coring down to 2 m depth revealed a broad range of genetic variation in deep root traits and showed that root features of highperforming genotypes were superior to those of low-performing genotypes or commercial varieties (Wasson et al. 2014 ). Since direct measuring of root depth remains an unresolved challenge, large-scale phenotyping for this trait can only be addressed through the use of proxies (e.g. canopy temperature depression) that through aerial remote sensing allow for monitoring the water status of a large number of genotypes in the fi eld (Lopes and Reynolds 2010 ;Lopes et al. 2014 ).
In wheat, root metaxylem diameter is another feature that has shown an association with yield under drought conditions (Schoppach et al. 2014 ). Notably, selection for higher water-use effi ciency (WUE) has shown merits in Australian environments where the crop prevalently grows on moisture stored in the soil prior to planting. Under these conditions, a wheat plant using water conservatively is able to complete grain fi lling with greater amount of water available in the soil. The adoption of this conservative strategy led to the release of two cultivars ('Drysdale' and 'Rees'; Condon et al. 2004 ) characterized by yield increases of up to 23 % when compared with control cultivars. The fi nal effects of root architecture and size on yield will depend on the distribution of soil moisture and the level of competition for water resources within the plant community.
A most challenging aspect is to defi ne the most desirable root ideotype able to optimize yield according to the prevailing dynamics of soil moisture profi le but also accounting for the concurrent presence of gradients in the soil profi le for other abiotic factors (e.g. salinity, toxic elements, high pH, etc.) that may impair plant growth. Therefore, each root ideotype should be established based upon the prevailing soil features in the target environment, a good understanding of the root architectural features that limit water uptake, and the metabolic cost required to develop and functionally sustain the root system. Along this line, loci that affect root growth under particular abiotic (e.g. boron toxicity) and biotic (e.g. nematode resistance) constraints are interesting targets for MAS aimed at improving drought resistance through a more vigorous root system of wheat grown in problematic soils.
QTLs for Carbohydrate Accumulation and Relocation
In wheat, the accumulation of carbohydrates and their relocation to the ear are key factors for optimizing yield under adverse environmental conditions (Blum 1998 ;Reynolds et al. 2009 ). In bread wheat, QTLs for stem reserve, water-soluble carbohydrates (WSC) remobilization and leaf senescence have been reported across well-watered and waterstressed conditions (Snape et al. 2007 ;Rebetzke et al. 2008 ;Bennett et al. 2012 ;Zhang et al. 2015 ). Although these studies showed an important role for WSC in assuring stable yield and grain size, Rebetzke et al. ( 2008 ) concluded that the small effects of many independent WSC QTLs may limit their direct use for MAS. A combined QTL analysis for yield of several wheat populations evaluated across different environments and seasons enabled Snape et al. ( 2007 ) to identify QTLs showing stable and differential expression across irrigated and non-irrigated conditions. Variation for stem water-soluble carbohydrate reserves was associated with the chr. 1RS arm of the 1BL/1RS translocated (from rye to wheat) chromosome, and was positively associated with yield under both irrigated and rainfed conditions, thus contributing to general adaptability (Snape et al. 2007 ). The benefi cial role of this translocation on wheat performance under drought-stressed conditions has already been reported (Ehdaie et al. 2003 ).
QTLs for Other Traits of Interest for the Control of Water
Balance Measurement of traits such as stomatal conductance, canopy temperature and leaf rolling provides indications of water extraction patterns and the water status of the plant. Therefore, measuring these traits together with soil moisture may help in selecting deep-rooted germplasm in environments where water is available at depth (Blum 1988 ;Reynolds et al. 2009 ). Stomatal conductance integrates important environmental and metabolic cues and allows the plant to modulate and optimize its transpiration and WUE (Brennan et al . 2007 ). A study conducted on a series of successful bread wheat cultivars released from 1962 to 1988 showed a strong and positive correlation between stomatal conductance and grain yield ( r = 0.94; Fischer et al. 1998 ), suggesting that the more modern cultivars extract more water from the soil. These results indicate the possibility of raising the yield potential using stomatal conductance as proxie and suggest the value of identifying the relevant QTLs. Canopy temperature is an integrative trait that reports on the water balance at the leaf and whole-plant level, thus providing a proxie of the capacity of the plant to extract soil moisture (Blum 1988(Blum , 2009Reynolds and Tuberosa 2008 ). Canopy temperature depression (CTD) is mainly useful in hot and dry environments, with measurements preferably made on recently irrigated crops in cloudless and windless days at high vapour pressure defi cits (Blum 1988 ;Reynolds et al. 2009 ). Under these circumstances, CTD can be a good predictor of grain yield in bread wheat ( r varying from 0.6 to 0.8; Reynolds et al. 2009 ), where yield progress has been associated with cooler canopies, hence higher transpiration (Fischer et al. 1998 ). Genetic gains in yield have also been reported in response to direct selection for CTD (Reynolds et al. 2009 ).
QTLs for Yield Under Different Water Regimes
As global climate change intensifi es, the identifi cation of loci with consistent per se effects on yield (i.e. not loci for fl owering time) across a broad range of soil moisture regimes becomes increasingly important to raise yield potential (Maccaferri et al. 2008 ;Pinto et al. 2010 ;Reynolds et al. 2011 ;Turner et al. 2014 ). Major QTLs for grain yield and its components across a broad range of soil moisture regimes have all been reported in bread wheat (Quarrie et al. 2005 ;Kirigwi et al. 2007 ;Snape et al. 2007 ) with only one notable exception in durum wheat where Maccaferri et al. ( 2008 ) searched for QTLs for grain yield in RILs evaluated in 16 environments with a broad range in grain yield values (from 0.56 to 5.88 t ha −1 ), mainly consequent to different soil moisture availability. Two major QTLs on chr. 2BL and 3BS ( QYld.idw-2B and QYld.idw-3B , respectively) showed highly signifi cant and consistent effects in eight and seven environments, respectively. In both cases, an extensive overlap was observed between the LOD profi les for grain yield and plant height, but not with those for heading date, thus indicating that the effects of these two QTLs on yield were not due to escape from drought, a well-known factor in determining yield under terminal drought stress conditions that typically characterize Mediterranean environments (Araus et al. 2008 ). Accordingly, this population was originally chosen because it had shown limited variability in fl owering time. For plant height and grain yield, a strong epistasis between QYld.idw-2B and QYld.idw-3B was detected across several environments, with the parental combinations providing the higher performance. These two QTLs evidenced signifi cant additive and epistatic effects also on ear peduncle length and kernel weight (Graziani et al. 2014 ). As a prerequisie to positional cloning, progeny derived from the cross of isogenic lines have been evaluated for fi ne mapping of both QTLs (Maccaferri et al. unpublished).
Improving Drought Resistance via Marker-Assisted Selection
Several factors limit the possibility of obtaining reliable QTL data and, most importantly, their deployment in breeding programs through MAS (Tuberosa et al. 2007 ). Among such factors, the environment dependence of QTL expression is of utmost importance in order to obtain reproducible data and effectively assess the value of a particular QTL. This aspect is particularly relevant for stress tolerance traits since the effect of the same QTL can markedly differ according to the prevailing environmental conditions (Collins et al. 2008 ). Although many studies have described QTLs that infl uence tolerance to drought, MAS has so far contributed marginally to the release of drought-resistant cultivars. Improving crop performance under waterlimiting conditions via MAS may also require considering QTLs for tolerance to abiotic (e.g. high boron) and biotic (e.g. nematodes) factors that impair root growth and functions. A common feature of cereal responses to drought near fl owering and during early stages of seed growth is a reduction of reproductive fertility due to partial sterility and/or early abortion. This loss of fertility has been attributed to different factors acting alone and more likely on reproductive fertility. The QTL approach attempts to dissect out the genetic and physiological components affecting source-sink relationships under abiotic stress and to what extent these may infl uence yield (Miralles and Slafer 2007 ). Major QTLs for seed weight and grain yield at different moisture conditions have been identifi ed in durum wheat (Maccaferri et al. 2008 ) and are being introgressed in different genetic backgrounds. In bread wheat, Fleury et al. ( 2010 ) have implemented a strategy where a specifi c environment is targeted and appropriate germplasm adapted to the chosen environment is selected, based on extensive defi nition of the morpho-physiological and molecular mechanisms of tolerance of the parents. This information was then used to create structured populations and develop models for QTL analysis, MAS and positional cloning.
Future Perspectives
Increasing attention has been devoted to the use of crop modeling for elucidating the genetic basis of genotype × management × environment (G × M × E) interaction at the level of the entire genotype and, more recently, at the level of single loci (Ludwig and Asseng 2010 ;Richards et al. 2010 ;Tardieu and Tuberosa 2010 ;van Eeuwijk et al. 2010 ;Parent and Tardieu 2014 ). The objective is to predict, via modeling, yield differences among genotypes grown under different environmental conditions (Cooper et al. 2009 ;Tardieu and Tuberosa 2010 ). The benefi ts accrued by modeling studies are expected to increase as the complexity of the genetic control of traits increases provided it is possible to account for the effects of genetic interactions for predicting trait variation (Cooper et al . 2009 ). Ultimately, modeling aims to predict the best combinations of QTL alleles able to optimize yield. The main underlying assumption of the modelling approach is that yield and other functionally complex traits can be analyzed and improved by dissecting it into simpler processes, and then by re-assembling such processes to reconstruct via modelling higher order of plant functionality and ultimately yield itself. Models have been used to generate an index of the climatic environment (e.g. of drought stress) for breeding program trials. In wheat grown in northern Australia, this has shown that mid-season drought generates large genotype by environment interaction (Chapman 2008 ).
With only a few exceptions as listed above, the vast majority of loci that affect crop yield per se have a rather small effect, particularly under drought conditions. Therefore combining the favorable alleles by MAS to achieve a signifi cant improvement quickly becomes impractical and would excessively constrain the potential for achieving yield gain due to the action of other loci. In this case, MAS for mapped QTLs (Randhawa et al. 2013 ) can be replaced by genome-wide selection (Bernardo 2010 ;Storlie and Charmet 2013 ). Nowadays, genome selection is facilitated by the availability of large numbers of markers, particularly Single Nucleotide Polymorphysms (SNPs; Wang et al. 2014 ) that are amenable to high-throughput profi ling at very low cost.
Conclusions
The release of cultivars better adapted to a broader range of environmental conditions will become an increasingly important goal of breeding projects worldwide. Compared to conventional breeding practices, the contribution in this direction of molecular breeding has somehow fallen short of expectations (Blum 2014 ;. Nonetheless, genomics approaches and sequence-based breeding will expedite the dissection of the genetic basis of abiotic stress tolerance while providing unprecedented opportunities to tap into wild relatives of wheat. To what extent this will actually impact the release of improved cultivars will largely depend on a more complete and comprehensive understanding of the adaptive response of crops to abiotic stress and our capacity to integrate this information into breeding programs via modeling or other approaches such as genomic selection. In view of the complexity of yield, particularly under drought, we foresee that genomic selection will provide the most effective way to raise the yield potential to the levels required to keep up with the fast-increasing demand in food worldwide. However, MAS will remain a valid option for major loci (genes and/or QTLs) as long as their effects will be suffi ciently predictable and economically viable (Tuberosa and Pozniak 2014 ). Additionally, QTL cloning will become a more routine activity thanks to a more widespread utilization of high-throughput, accurate phenotyping (Tuberosa 2012 ), sequencing and the identifi cation of suitable candidate genes via 'omics' profi ling. Ultimately, reducing wheat vulnerability to drought will require a multidisciplinary and integrated approach that will eventually allow breeders to more effectively select drought-resistant cultivars. Open Access This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. | v3-fos |
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} | s2 | Energy Value of Cassava Products in Broiler Chicken Diets with or without Enzyme Supplementation
This study investigated the metabolizable energy (ME) intake, net energy of production (NEp), heat production (HP), efficiencies of ME use for energy, lipid and protein retention as well as the performance of broiler chickens fed diets based on cassava chips or pellets with or without supplementation with an enzyme product containing xylanase, amylase, protease and phytase. The two products, cassava chips and pellets, were analysed for nutrient composition prior to feed formulation. The cassava chips and pellets contained 2.2% and 2.1% crude protein; 1.2% and 1.5% crude fat; and 75.1% and 67.8% starch, respectively. Lysine and methionine were 0.077%, 0.075%, and 0.017%, 0.020% protein material, respectively, while calculated ME was 12.6 and 11.7 MJ/kg, respectively. Feed intake to day 21 was lower (p<0.01) on the diet containing cassava chips compared to diets with cassava pellets. Enzyme supplementation increased (p<0.01) feed intake on all diets. Live weight at day 21 was significantly (p<0.01) reduced on the diet based on cassava chips compared to pellets, but an improvement (p<0.01) was noticed with the enzyme supplementation. Metabolizable energy intake was reduced (p<0.01) by both cassava chips and pellets, but was increased (p<0.01) on all diets by enzyme supplementation. The NEp was higher (p<0.01) in the maize-based diets than the diets containing cassava. Enzyme supplementation improved (p<0.01) NEp in all the diets. Heat production was highest (p<0.01) on diets containing cassava pellets than on cassava chips. It is possible to use cassava pellets in diets for broiler chickens at a level close to 50% of the diet to reduce cost of production, and the nutritive value of such diets can be improved through supplementation of enzyme products containing carbohydrases, protease, and phytase.
INTRODUCTION
The world production of cassava was 262.6 million tonnes in 2012, with a steady increase in production over previous years (FAO, 2012). Thailand is the second largest producer of cassava in the world but significantly, most of its production is processed into starch or animal feed, unlike the output from African producers where cassava is an important human food. Cassava chips and pellets are the key cassava products used in animal feeding, which can replace some or all of the cereal grain in diets for poultry (Iji et al., 2011). These cassava products are also exported to Europe and other parts of the world. A study by Brum et al. (1990) showed that up to 66.7% of maize in broiler diets can be replaced by cassava meal without compromising growth performance. Other researchers have reported variable responses of diets containing cassava products such as chips and pellets in broiler diets (Obikaonu and Udedibie, 2006). These inconsistencies may be due to differences in cultivars or product processing prior to feeding or poor digestion of the main carbohydrates in cassava.
There is a need for research on cassava and its byproducts with the aim of maximizing their energy value for broiler chickens. In particular, the utilization of energy in cassava products by poultry has not been extensively studied under controlled environments. The use of biotechnology in the form of microbial enzymes holds great potential for maximizing carbohydrate digestion and energy value of cassava products in poultry feeding. Microbial enzymes have been employed in diets containing various cereal grains (Bedford, 1996;Cowieson et al., 2006) but few investigations have been carried out in diets containing cassava. This is an area that needs to be investigated, in order to position cassava as an alternative source of energy in poultry diets. The current study assessed the carbohydrate digestion and energy value of cassava products in broiler chicken diets with or without microbial enzyme supplementation.
Birds and housing
A total of 384 one-day-old male Cobb-500 broiler chicks were used in a 3×2 factorial arrangement to compare diets with two cassava products (chips and pellets) or maize, with or without a combination of exogenous feed enzymes (Avizyme 1502, with active enzymes xylanase (600 Units/g), protease (8,000 Units/g) and amylase (800 Units/g); and Phyzyme XP, a phytase feed enzyme. Both enzymes were supplied by Feedworks, Australia Pty Ltd.
Each treatment had 8 replicates, with eight chicks per replicate. The chicks were reared in floor cages in an environmentally controlled house up to day 16. The birds were moved to apparent metabolizable energy (AME) cages in a climate-controlled room and excreta were collected for three days from 18, 19, and 20 days of age. The room temperature was initially set at 32°C and was gradually reduced to 25±1°C by 21 days. Experimental diet and drinking water were offered ad libitum to the birds. The experiment was approved by the Animal Ethics Committee of the University of New England (Approval No.: AEC09/100).
Diets
Balanced diets were formulated (Table 1) to contain the cassava products or maize as primary energy source in the diet with or without enzyme supplementation to meet NRC (1994) recommendations. The ingredients in particular whole maize grain as well as cassava chips and pellet were ground through a hammer mill before mixing. All experimental diets were iso-caloric and iso-nitrogenous; relevant diets were supplemented with exogenous enzymes (Avizyme 1502, 0.5 g and Phyzyme XP, 0.1 g per kg of each diet) and all diets were further pelleted using a cold pelleting process. Each diet was incorporated with titanium dioxide (TiO 2 ) at a rate of 0.05% as an indigestible marker to enable measurement of nutrient digestibility as well as for AME.
Data collection
Feed leftover and body weights (BW) were recorded on days 7, 14 and 21 for the determination of average feed intake (FI), BW, and feed conversion ratio (FCR) on a floor cage (replicate) basis. On day 7 and 21, one or three birds (respectively) from each cage were randomly selected, weighed and euthanized by cervical dislocation. Weights of the small intestine, proventriculus and gizzard with content, liver, pancreas, spleen and bursa of Fabricius were recorded. Ileal digesta (from Meckel's diverticulum to the ileo-caecal junction) were collected on day 21 and pooled by replicate. Digesta were stored at -20°C prior to freeze-drying and ground through a small coffee grinder for analyses of starch, gross energy (GE) and crude protein (CP).
Preparation of carcass samples
At 21 day, two birds per replicate were killed and the whole intact body was frozen immediately and later processed. Both chicks from the same cage were processed together. After chopping and coarse-grinding individual chickens, they were thoroughly mixed and two subsamples (around 250 g each, wet weight) were taken, finely ground and freeze-dried as described by Olukosi et al. (2008). The two subsamples were mixed together after drying and ground again. Hence chemical analysis was on one sample from each cage and not from individual chickens. The AME was measured using the marker (TiO 2 )-based faecal collection method on samples collected between 18 and 21 days of age. The representative excreta sample was collected from each cage over three days, pooled and mixed thoroughly, subsample, freeze-dried, and analysed for the marker and GE.
Chemical analysis
Excreta, diet and ileal digesta samples were analysed for GE with the purpose of determining the metabolizable energy (ME). The ME content of cassava chips and pellets were calculated according to the equation (ME [kcal/kg] = 53+38×[% CP+2.25×% ether extractable fat {EE}+1.1×% Starch+% Sugar]) developed by Carpenter and Clegg (1956). Samples were dried at 105°C in a drying oven for 24 h for DM determination. Gross energy was determined in a bomb calorimeter (IKA -WERKE bomb calorimeter [C7000, GMBH & CO., Staufen, Germany]) using benzoic acid as a calibration standard. The nitrogen content of the diets, ground carcass and ileal content were determined according to the Dumas combustion technique as described by Sweeney (1989) (1994). The amylose/amylopectin ratio was determined with a Megazyme amylose/amylopectin assay kit (Megazyme International Ireland, Bray Business Park, Bray, Ireland) using the selective quantitative precipitation reaction of con-canavalin A (Con A) for amylopectin (Gibson et al., 1997) and by the colorimetric method of iodine binding for amylose (Chrastil, 1987). Insoluble and soluble non-starch polysaccharides (NSPs) were analyzed by gas chromatography (VARIAN, CP-3800, Walnut Creek, CA, USA) as the alditol acetate derivatives of monosaccharide based on the method developed by Englyst and Hudson (1993), and Theander and Westerlund (1993).
Minerals were analysed by inductively coupled plasma method (Vista MPX-radial) following the protocol of Anderson and Henderson (1986). Concentrations of amino acids were determined using pre-column derivatisation amino acid analysis with 6-aminoquinolyl-Nhydroxysuccinimidyl carbamate followed by separation of the derivatives and quantification by reversed phase high performance liquid chromatography according to Cohen and Michaud (1993) and Cohen (2001).
Titanium dioxide concentrations in the diets, ileal digesta and excreta samples were measured after ashing the samples and treating the ash with boiling 7.4 M Sulphuric acid according to the method of Short et al. (1996). The concentrations of the TiO 2 marker and of nutrients in the feed and ileal digesta were used to calculate the digestibility coefficient of protein, GE, and starch, using the following equation: The ground carcass samples were analysed for GE, diethyl EE and nitrogen (N). The data were used to calculate AME, nutrient retention, net energy of production net energy of production (Nep), heat production (HP) and efficiencies of utilization of metabolizable energy for protein, fat and energy retention as described by Olukosi et al. (2008). All laboratory samples were analysed in duplicate.
Calculations
AME ( MJ/kg) was calculated as follows: Where GE i is gross energy (MJ/kg) in feed; GE o is the gross energy (MJ/kg) in excreta, T i is the concentration of titanium in the diets and T o is the concentration of titanium in the excreta.
NEp was calculated as follows: Initial GE of carcass (kJ) = Carcass GE (kJ/g)×BW of bird (g) Final GE content of carcass (kJ) = Carcass Ge (kJ/g)×BW of bird (g) NEp (kJ) = (2) -(1) The HP, which consists of the heat increment of feeding and fasting HP was calculated as the difference between NEp and ME intake by this equation: HP (kJ) = MEI -NEp, where ME intake (MEI) was calculated using the following formula: MEI (kJ) = ME (kJ/g)×FI (g) Energy retained as fat (RE f ) and as protein (RE p ) was calculated as follows: RE f (kJ) = Carcass fat (g)×38.2 kJ/g RE p (kJ) = Carcass crude protein content (g)×23.6 kJ/g The values 38.2 and 23.6 kJ/g are energy values per gram of fat and protein, respectively, and were according to Larbier and Leclercq (1992).
Because excreta was collected for the last 3 days and the ME intake for killed chicken at day 21 was calculated using FI for days 0 to 21.
Efficiency of ME use for energy retention (K RE ) = NEp/MEI Efficiency of ME use for lipid retention (K REf ) = RE f /MEI Efficiency of ME use for protein retention (K REp ) = REp/MEI
Statistical analysis
Data for each day of sampling were analysed separately. The performance data such as FI, BW, FCR, relative weight of visceral organs, nutrient digestibility and parts yield characteristic were analysed using the general linear models procedure of SPSS options, Version 18.0.0 (SPSS Inc, 2010) for the main effects of diets, and enzyme effects with their interactions. Separation of means within a significant effect was done by Duncan's multiple range test through post hoc procedure of SPSS. Significance levels were set at p≤0.05 unless otherwise specified.
Nutrient composition of cassava products
The chemical composition of the cassava chips and cassava pellets is presented in Table 2. The crude protein, ME, total starch, resistant starch and amylopectin contents were higher in cassava chips than in cassava pellets (2.2%, 12.6 MJ/kg, 75.1%, 39.7%, and 57.8% vs 2.1%, 11.7 MJ/kg, 67.8%, 31.1% and 49.8%, respectively). On the other hand, the crude fat, amylose, total insoluble and soluble NSPs contents were higher in cassava pellets than in the chips (1.5%, 17.9%, 5.4%, and 0.83% vs 1.2%, 17.3%, 3.9%, and 0.78%, respectively). The concentrations of Ca and phosphorus were similar in the two products. However, potassium was higher in cassava chips than in pellets (0.71% vs 0.55%). The lysine and alanine contents were slightly higher in cassava chips than in cassava pellets (0.077% and 0.114% vs 0.075% and 0.112%, respectively). Conversely, cassava pellets were higher than chips in the other amino acids such as methionine, threonine, arginine, histidine, tyrosine and glycine.
Feed intake, body weight gain, and feed efficiency Birds fed on the diets containing cassava chips significantly (p<0.01) ate less than those fed on the diets containing maize or cassava pellets up to 7 days of age (Table 3). The enzyme supplements increased (p<0.01) FI on all the diets; and birds fed on diets containing cassava pellets had increased FI compared to birds fed diets with cassava chips or maize. Similarly, BW at day 7 was significantly reduced (p<0.01) on the diet based on cassava chips but increased (p<0.01) by diets with enzyme supplementation. Subsequently, there was a significantly poorer (p<0.01) FCR in groups with cassava chips compared to the maize based control diet. However, the FCR of birds improved (p<0.05) on all diets with microbial enzyme supplementation compared to unsupplemented diets. Feed intake up to day 21 was lower (p<0.01) on the diet containing cassava chips than on diets with maize or cassava pellets (Table 4). The enzyme supplements improved (p<0.01) the FI of birds on all the diets. Body weight at day 21 was also significantly reduced (p<0.01) on the diet based on cassava chips, and improved (p<0.01) by the enzyme supplements. There was a significantly poorer (p<0.01) FCR in groups with the cassava products compared to the maize-based diet, but this tended (p = 0.08) to be improved by enzyme supplementation. There was an increase in BW with the inclusion of enzymes in all diets.
Visceral organ weight
At day 7, the relative weight of the small intestine was significantly (p<0.01) lower on the diet containing maize; and the highest relative weight was observed in chickens fed diets based on cassava pellets ( Table 5). Irrespective of energy source, there was no significant change in the relative weight of small intestine of birds with or without enzyme supplementation. The relative weight of gizzard was significantly (p<0.01) lower in chicks on the diets containing cassava pellets than on diets cassava chips at 7 days of age. However, this tended (p = 0.08) to be reversed by enzyme supplementation. There were no significant changes in the relative weight of liver, pancreas, spleen, bursa of Fabricius and yolk sac due to diet or enzyme supplementation.
At day 21, the relative weight of the small intestine was significantly (p<0.01) lower on the diet containing maize and the highest relative weight was observed in chickens fed on diets based on cassava pellets (Table 6). There was a significant (p<0.05) increase in the relative weight of the small intestine in chickens fed diets without supplemented compared to enzyme supplemented diets. The interaction between cassava product/maize and enzyme supplementation on the relative weight of the small intestine was significant (p = 0.037); with the lowest relative weight in the enzyme-supplemented maize-based diet. The relative weight of gizzard was significantly (p<0.001) lower on the diets containing cassava pellets than on diets with maize or cassava chips at this age. However, the effect of enzyme supplement was absent on the weight of this organ at 21 d.
The relative weight of the proventriculus was not changed by either cassava product. The interaction between diet and enzyme supplement was significant on the relative weight of proventriculus; it was significantly (p<0.01) lower in birds fed the diet containing cassava pellet with enzyme supplementation than in those without enzyme supplement. The relative weight of liver was lower (p<0.01) on the diet containing maize than on the diets containing cassava pellets. However, the interaction between diet and enzyme was significant (p<0.01) on the relative weight of liver and pancreas. There were no significant changes in the relative weight of spleen and bursa Fabricius.
Metabolizable energy intake and utilization
Metabolizable energy intake was reduced (p<0.001) in birds fed both cassava chips and pellets without enzyme supplementation but was increased (p<0.001) in all the diets with enzyme supplementation (Table 7). A similar trend was observed for NEp, generally being higher (p<0.01) on the maize-based diets than on diets containing cassava, and enzyme supplementation improving (p<0.01) NEp in all diets. The highest estimated HP was observed in birds fed diets containing cassava pellets and it increased (p<0.01) by enzyme supplementation in all diets. More energy was retained as protein and fat in birds fed the maize-based diets than diets containing cassava products (p<0.01) and this was increased (p<0.01) in all diets as a result of enzyme supplementation. The efficiencies of utilization of ME for energy and lipid retention were reduced (p<0.01) with the inclusion of cassava products compared to the maize diet, but these were unaffected by enzyme supplementation, within diet.
Digestibility of nutrients
At 21 days of age, the ileal digestibility of protein, GE and starch was not significantly affected by diet and enzyme supplementation (Table 8). In general, protein, energy and starch digestibility tended to increase in diets Table 7. ME intake, net energy production (NEp), heat production (HP), energy retained and efficiencies of ME use for energy, lipid and protein retention in broiler chicks on the different diets to 21 days 1 when supplemented with the microbial enzymes.
Growth performance of broiler chickens
The primary aim of the present study was to evaluate two cassava products, chips and pellets, as replacement for maize, with or without enzyme supplementation, in broiler chicken diets. The nutrients in cassava chips and pellets were apparently used less efficiently for growth than nutrients in maize. Overall, gross response on the cassavabased products was inferior to that on the maize-based diets. Generally cassava starch is more digestible than maize starch, the former being higher in amylopectin (Gomes et al., 2005). However, cassava is lower in protein and diets may require supplementation with synthetic amino acids to meet the growth requirement of poultry.
The pellets performed better than chips in terms of FI, BW and FCR. This is in agreement with Burn et al. (1990), who reported that up to 66.7% of maize in broiler diets can be replaced by cassava meal without adversely affecting growth performance of broilers. Addition of these microbial enzymes to diets increased overall productivity such as FI, BW gain and FCR on the maize (control), cassava pellets and cassava chips diets. This is in agreement with the results of Akinfala et al. (2009), who observed a beneficial effect of feed additives, including baker's yeast, as well as enzymes (hemicellulases) in cassava-based diets fed to broiler chickens. Similarly, Acamovic (2001) suggested that the utilization of cassava in broiler diets can be enhanced with enzyme supplementation, as is commonly found with cereal grains. In the current study, the FI was reduced when birds were fed-high fibre cassava-based diets without supplementation of enzymes. This could be due to the inability of the birds to digest the fibre, which would then create a gut fill sensation and subsequent depression of appetite. High levels of fibre also reduce the transit time of food through the digestive system (Connell, 1981). Additionally, a reduction of growth due to a lower density of digestible nutrients in cassava products compared to maize may be related to the reduction on FI.
In a previous study by Obikaonu and Udedibie (2006), birds fed on a diet based on cassava ensiled peel meal had similar FI and BW gain compared to a control group, whereas the FCR of birds on sun-dried cassava peel meal was poor. Microbial digestion of fibre occurs during ensiling, similar to the effect of microbial enzymes in the diet. However, the digestibility of starch was not significantly improved due to microbial enzyme supplementation of the diets based on cassava pellets or chips.
In this study, the relative weight of visceral organ, in particular small intestine, gizzard, proventriculus, liver and pancreas were increased in chicks on both cassava chips and cassava pellet diets at both ages, day 7 and 21. This is in partial agreement with the result of Borin et al. (2006), who reported that the weight of above mentioned organs increased with an increase in cassava leaf meal. Cassava leaves tend to be higher in fibre than root meals and root chips are less processed than pellets, and may contain fibre in relatively large quantity.
Energy utilization of broiler chickens
In this study, the ME content of the experimental diets were similar, but ME intake was reduced on diets containing cassava chips or pellets, which may be due to high fibre contents of the two diets when compared to maize. However, ME intake was increased in all diets when supplemented with microbial enzymes. This agrees with results by Iji et al. (2011), who reported that NEp and HP were reduced by cassava pulp but were increased by enzyme supplements similar to those used in the present study.
The benefit of enzymes was likely related to an increase in the rate of nutrient digestibility and changes on the ability of the bird to adapt to higher fibre levels. Phytic acid, in particular can adversely affect energy utilization and the availability of other nutrients in poultry diets (Ravindran et al., 2005). Besides, increased activity of gut microflora on the dietary factors can lead to energy wastage (Choct et al., 1996) or availability as well as digestibility of other nutrients (Smits et al., 1997). Le Goff and Noblet (2001) also reported that most of the variation in digestibility of feed energy is related to the presence of dietary fibre.
In the current study, broilers on the maize-based control diets showed higher NEp, with high HP when supplemented with microbial enzymes. This group of birds also attained heavier BW than those on cassava-based diets. This improvement in NEp and performance of birds is evidence of more efficient utilization of energy on these diets due to improvement in nutrient and energy availability (Olukosi et al., 2008).
Heat production of birds varied significantly between treatments and was higher the on maize-based control and cassava pellets diets than on the cassava chips only when supplemented with enzymes. This increase in HP on the former two diets may be due to higher FI, in particular protein intake (Johnson, 2007). The maize-based control diets also resulted in increased efficiencies of ME use for energy, lipid and protein retention, which is supported by the findings of Boekholt et al. (1994) who reported that when protein is not limiting in the diets of broilers, extra energy available in the diets is used for both fat and protein accumulation. Conversely, the rate of deposition of energy and fat was reduced in birds on the cassava chips diets but protein deposition was higher on cassava pellets diets.
In general, more energy was retained as lipid than protein on the maize-based control diet, which may be due to differences in the energy to protein ratios between maize and cassava products-based diets. Lesson and Summers (1997) have reported that abdominal fat of birds increases with age whereas protein accretion decreases. This is related to the maturity of birds and is found commonly in most strains (Lesson, 1995). In the current study, the proportion of the retention of lipid was found to be higher than that of protein as birds in the test age group (0 to 21 d) are still in the actively growing phase of production (Bregendhl et al., 2002). The efficiency of utilization of ME for energy, protein and fat retention was affected by dietary treatment, the ME being more efficiently used for energy deposition and less for protein and fat disposition. It is unclear what this implies but such energy may be deposited as fat as the birds becomes older. On a technical note, some of our values of HP and NEp do not exactly add to ME intake. This deviation was around 5% and may be due to minor over-estimation of energy intake or discrepancy in bomb calorimetry. Overall, this error would not greatly alter the results.
This study suggests that cassava pellets or chips could be used to replace maize in broiler diets at up to 50%, with enzyme supplementation of such diets. This was supported by the fact that the cassava products had no adverse effects on carcass weight, abdominal fat and carcass composition. However, the commercial use of the products would depend on price, and the cost of protein sources, synthetic amino acids and pigments. The diets would need to be supplemented with appropriate microbial enzymes. | v3-fos |
2016-05-12T22:15:10.714Z | {
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} | s2 | Contrasting responses of root morphology and root-exuded organic acids to low phosphorus availability in three important food crops with divergent root traits
Available phosphorus (P) is one of the most important factors affecting crop production worldwide. Study on improving plant P uptake is hence of global importance. We have investigated the responses of root morphology and root-exuded organic acids to low P availability in three important food crops (barley, canola and potato) with divergent root traits using a hydroponic culture system. Results showed that plants evolved divergent adaptations of root morphology and exudation as a response to low P availability. These results could underpin future efforts to improve P uptake of the three crops which are important for future sustainable crop production.
Introduction
Phosphorus (P) deficiency is one of the major limitations for crop productivity globally. In modern agriculture, mineral P fertilizers are extensively used, and large economic benefits have been generated. However, P fertilizers have also been added in amounts that far exceed the amount of P removed at harvest: up to 90 % of P applied as fertilizer may be strongly sorbed to the soil to become less available to plants, or eroded and lost in run-off (Gerke et al. 1994;Smith and Schindler 2009;Andersson et al. 2013). As a consequence, high P input has produced many problems, such as eutrophication and hypoxia of waterways (Withers et al. 2001) as well as eutrophication of oligotrophic natural terrestrial systems . Hence, it is important to understand P-acquisition mechanisms and genetically improve crop plants to be able to acquire P more efficiently, which would enable reduced P-fertilizer application.
Higher plants have developed various responses to low P availability, including modified gene expression, morphological responses especially in root architecture (e.g. reduced primary root length, more lateral roots and root hairs) and physiological modification of the rhizosphere by root exudation and pH changes, as well as metabolic responses (Raghothama 1999;Lynch 2011). To improve P-acquisition efficiency, understanding changes in root structure and activities under various P availabilities is necessary. During the past decades, three main types of changes have been revealed: (i) changes in root morphology, such as root length, root hairs, root distribution and root diameter (Williamson et al. 2001;Ló pez-Bucio et al. 2002;Lambers et al. 2006;Desnos 2008); (ii) modification of root physiology, important for release of water and protons into soil and exudation of nucleases, acid phosphatases and carboxylic acids to change soil properties and mobilize organic and inorganic P sources (Read et al. 2003;Lambers et al. 2006Lambers et al. , 2008Prieto et al. 2012) and (iii) colonization by arbuscular mycorrhizal fungi, since P uptake by the mycorrhizal hyphae is the dominant pathway for P acquisition when plant roots are colonized by arbuscular mycorrhizal fungi (Smith et al. 2003). Finally, these factors might not operate alone but interact with each other to improve P uptake.
Although significant progress has been made in understanding plant processes associated with soil P mobilization and acquisition, each plant species is different and likely responds to P supply differently. Furthermore, there are a number of issues that are not well understood, such as the complex coordination of root morphology, and physiological and biochemical responses under variable P availability (Shen et al. 2011). Root exudation represents a significant carbon cost to plants, and root exudates are influenced by plant age, species and genotype, root structure and environmental factors including both biotic and abiotic stressors (Badri and Vivanco 2009). Phosphorus deficiency increases the release of organic acids (OAs) by roots of certain plants (Ló pez-Bucio et al. 2000), which could play a key role in mobilizing P from mineral surfaces and from oxides and hydroxides of Al and Fe, as well as Ca-phosphates (Neumann and Römheld 2001;Ryan et al. 2001;Neumann et al. 2014).
In this study, we aimed to investigate contrasting responses of root morphology and root exudation with regards to acquiring P. Therefore, we selected three economically important crops with different root systems as plant materials: barley, canola and potato. Barley, a typical monocot, has a wide-ranging network of fibrous roots, whereas the dicots (canola and potato) tend to have a long tap-root with thick lateral roots. Barley and potato are capable of forming an arbuscular mycorrhizal symbiosis to acquire soil P, while the non-mycorrhizal canola cannot do this (Brundrett 2009;. We compared the root structure and root-exuded OAs of these three crop plants under different P supply using hydroponic culture. We hypothesized that under low P, (1) canola has a more developed root system with longer roots, greater root surface area and more lateral roots, or increased root exudates to compensate for its lack of mycorrhizas; (2) barley and potato exude less OAs than canola and thus save carbon for releasing other compounds to promote rhizosphere microbial activity and (3) compared with canola and barley, potato releases the least OAs and stores most of its belowground carbon resources in tubers as starch. The information generated in this study will be of value for a more sustainable production of canola, barley and potato.
Plant material and experimental design
Canola (Brassica napus cv. MARIE), barley (Hordeum vulgare cv. HEDER) and micropropagated seedlings of potato (Solanum tuberosum cv. PIMPERNEL) were selected for this study. Hydroponic culture experiments were conducted in the greenhouse of the Norwegian University of Life Sciences (NMBU). Germinated canola and barley seeds were first grown in full-strength nutrient solution containing 1.5 mM KCl, 2 mM Ca(NO 3 ) 2 , 1.0 mM MgSO 4 , 1 mM H 3 BO 3 , 1 mM MnSO 4 , 1 mM ZnSO 4 , 0.5 mM CuSO 4 , 0.37 mM Na 2 MoO 4 and 50 mM Fe-EDTA. Phosphorus was added as KH 2 PO 4 in a concentration of 1 or 50 mM, designated as low P availability (P1) and P sufficient (P50), respectively (concentrations used by Cheng et al. 2014). Five-day-old uniform seedlings without seed residues were then carefully transferred to 1-L plastic pots (one plant per pot) filled with nutrient solution containing P1 or P50, with pH adjusted to 5.8 + 0.2. Solutions were replaced every third day; at the same time, pots were rearranged randomly. For potato, 10 cm heights of tissue culture-derived seedlings were selected for hydroponic culture, and no root tuber was produced in this 4-week experiment. Plants were grown at 25 8C/16 8C day/night temperature with a 16-h photoperiod at a light intensity of 200 + 20 mmol m 22 s 21 and 50 -75 % relative humidity. Three independent replications were carried out.
Root exudate collection
Root exudates were collected as described by Khorassani et al. (2011). Briefly, after plants had been grown hydroponically under P1 or P50 for 2 and 4 weeks, whole root systems of intact plants were carefully washed with deionized water to remove the nutrient solution. Then the whole root system was placed into ultrapure Milli-Q water (Millipore, Billerica, MA, USA) in a container to collect root exudates; the volume varied from 20 to 50 mL depending on the size of the root system. The roots were kept in the water for 2 h (between 10:00 and 13:00) under the same controlled-climate conditions as described for plant growth. Neumann and Römheld (2001) reported that roots are not harmed by Milli-Q water and no significant degradation of the exudates occurs in a short time period of 2 h. As Valentinuzzi et al. (2015) reported, water is the most effective and suitable trap solution to collect exudates like OAs, especially in a short time period such as 2 h. Micropur (0.01 g L 21 , Katadyn Products, Kemptthal, Switzerland) was then added to the solution to inhibit the activity of microorganisms (Cheng et al. 2014). The collected root exudates were immediately frozen at 220 8C. Before analysis with liquid chromatography triple quadrupole mass spectrometry (LC-MS/MS), collected root exudate samples were filtered with Phenex regenerated cellulose syringe filters (pore size: 0.45 mm, filter diameter: 15 mm) (Phenomenex, Torrance, CA, USA), and 0.2 mg deuterium-labelled succinic acid was added to each sample to be used as an internal standard (IS).
Determination of OAs released from roots
The OA analysis was performed using a Waters Alliance 2695 LC system coupled to a Quattro Ultima Pt triple quadrupole mass spectrometer (Micromass, Manchester, UK), equipped with an electrospray ionization (ESI) source. The auto-sampler in the LC system cooled the samples to 5 8C. The injection volume was 50 mL and sample constituents were separated using an Acquity XSelect HSS T3 (50 × 3 mm, 2.5 mm) analytical column (Waters, Milford, MA, USA) at a column oven temperature of 40 8C and a sample run time of 6 min. The trifunctional alkyl C18-bonded phase used for the HSS T3 sorbent is compatible with the 100 % aqueous mobile phase; so, aqueous formic acid (0.08 M, pH 2.4) was used as the sole mobile phase solution at a flow rate of 0.3 mL min 21 . Electrospray ionization conditions were as follows: capillary voltage of 3.0 kV, source temperature of 120 8C, desolvation temperature of 350 8C, cone gas flow of 80 L h 21 and desolvation gas flow of 620 L h 21 . The cone voltage, collision energy and selection of product ions were optimized for each OA for maximum intensities. Two characteristic fragmentations of the OA precursor ion ([M2H] 2 ) were monitored. The most abundant product ion was used for quantification, and the second product ion was used for verification of the OA (Table 1). The optimal quantifier ions in our MS system were identical to the quantifier ions used by Erro et al. (2009). For malonic acid, which has a small molecular mass, only one product ion was used. Pure OA standards (citric acid (.99 %), L-(2) malic acid (.99.5 %), succinic acid (.99.5 %), malonic acid (99 %), L-(+)-tartaric acid (.99.5 %) and deuteriumlabelled succinic acid-2,2,3,3-d 4 (98 %)) were purchased from Sigma-Aldrich (St Louis, MO, USA). The OAs were mixed in Milli-Q water in the range 0.05-2.0 mg mL 21 , containing a fixed amount (mg mL 21 ) of the IS deuteriated succinic acid. Internal standard calibration was performed using weighted (1/x) quadratic regression analysis of the peak area ratios (analyte/IS) versus the concentration ratios. Limits of quantification were 0.015-0.04 mg mL 21 , corresponding to signal-to-noise ratios of 15.
Plant harvest and measurements of root morphology
Plants were harvested 28 days after transfer to hydroponics, and roots and shoots were sampled separately for subsequent analysis. The total number of green leaves and senesced leaves was recorded. Root length and root surface area were measured using WinRHIZO (EPSON 1680, WinRHIZO Pro2003b, Regent Instruments Inc., Quebec, Canada). Shoot and root dry weight (DW) were measured separately after being oven-dried for 48 h at 65 8C.
Statistical analyses
Data were statistically analysed by R software (version 3.1.3; software and commanders were downloaded from the NMBU library). Two-way ANOVAs were used to study main effects of P level, species and their interaction on all the parameters involved in this study. For multiple comparisons to determine which of the six P/species combinations were significantly different from each other, post hoc pair-wise Tukey honest significant difference tests were used after ANOVA. For all analyses, the significance a level of 0.05 was used.
Plant growth at different P availability
After 4 weeks of P1 treatment, a 65 % lower total dry biomass was found in barley and .87 % lower biomass in AoB PLANTS www.aobplants.oxfordjournals.org canola and potato, compared with plants grown under P50; no significant differences were found between these three crops at a low P level, while canola and potato showed 102 and 68 % more biomass than barley at P50, respectively ( Fig. 1A; Table 2). The root : shoot DW ratio increased considerably in plants grown under P1, with .70 % increase in barley, and .300 and 400 % increase in canola and potato, respectively; at P50, barley showed a significantly greater ( 100 %) root/shoot ratio than canola and potato ( Fig. 1B; Table 2). Consistent with the results for biomass, the number of total leaves was decreased by 42 -53 % at P1 compared with that at P50 for all three crops; potato (with an average of 38 leaves at P50 and 18 leaves at P1) had more leaves than canola (12 leaves at P50 and 7 leaves at P1) and barley (13 leaves at P50 and 7 leaves at P1) under both P50 and P1 conditions ( Fig. 1C; Table 2). Low P availability also led to earlier leaf senescence in all three species, especially in potato (.53 % senescent leaves), with many shed leaves after 3 weeks, while there was almost no leaf senescence in potato at P50 (Fig. 1D; Table 2).
Root morphology
Changes in root morphology varied significantly among the studied crop species (Figs 2 and 3; Table 2). Under P1, compared with P50, barley showed a marked reduction in total root length (44 %) and root surface area (58 %), whereas canola showed a significant increase in total root length (37 %), but a decrease in number of root tips (45 %). Total root length in potato and root surface area in canola did not change significantly. For potato, the number of root tips almost doubled under P deficiency. At P1, canola and potato showed 58 and 49 % greater total root length than barley, respectively; canola had 18 % greater root surface area than potato, and potato had 57 % greater root surface area than barley, but the average number of root tips decreased in the order potato (1892) . barley (883) . canola (627). On the other hand, barley showed 36 and 55 % greater root length than potato and canola, respectively, and 55 % greater root surface area than canola and potato at P50. These three crops had almost the same number of root tips at P50.
Root exudate analysis
Three OAs-citric, malic and succinic acids-were detected in the root exudates of both P1 and P50 plants ( Fig. 4; Table 2). All these three OAs were found in canola and barley exudates, while citric acid was not detected in potato root exudates ( Fig. 4A and D). Under P1 treatment, the greatest amounts of total OAs (citric + malic + lowest amount of OAs (11 nmol plant 21 h 21 ). When root exudates were collected on the 15th day (just after solutions were replaced), P-deficient canola plants exuded over 400 % more citric acid and 1300 % more malic acid than the plants with sufficient P supply ( Fig. 4A and B). However, succinic acid exudation at P1 in canola was only 25 % of that at P50 (Fig. 4C). The exudation of all three OAs increased in the P1 treatment of barley, but for citric and succinic acids, this increase was not significant ( Fig. 4A -C). Canola roots exuded over three times more citric acid than barley roots under P deficiency (Fig. 4A). For potato, the amounts of released malic and succinic acid were in general only 10 -50 % of those for barley or canola (except for succinic acid at P1), and no significant differences between P1 and P50 were found ( Fig. 4B and C). When root exudates were collected on the 28th day (just before harvesting), the three studied OAs released by roots in all studied crops decreased dramatically, with 30 -70 % reduction compared with those collected on the 15th day ( Fig. 4D -F
Phosphorus status in shoots and roots
Unsurprisingly, the P concentrations and P contents in both shoot and root tissues were significantly higher (between 3 and 81 times) for plants supplied with P50 compared with those of plants supplied with P1 ( Fig. 5; Table 2). Under P50 supply, the P concentrations and P contents in shoots decreased in the order barley . potato . canola ( Fig. 5A and B), while in roots, the order was potato . barley . canola ( Fig. 5C and D). The shoot and root P concentrations varied from 4 to 8 mg g 21 DW, comparing well with a P concentration in agricultural crops that generally varies from 1 to 5 mg P g 21 DW (Anonymous 1999). This shows that 50 mM was a P concentration sufficient for plant growth. Under P1 conditions, potato had the highest P concentrations and P contents in shoots, although no statistically significant difference was found in shoot P content. Canola had shoot P concentrations equal to those of barley, but it had a P content that was only 45 % as high due to having only 55 % as much shoot biomass (Figs 1A and 5A and B). In root tissues, potato and canola had almost the same P concentrations, which were 121 % higher (P , 0.05, Student's t-test) than in barley (Fig. 5C), and potato roots showed the greatest P content (0.06 mg versus 0.03 mg P in barley and canola), but these differences were not significant (Fig. 5D).
Discussion
Phosphorus availability and uptake directly affect crop productivity. Understanding the relationships between root architecture, exudates and P availability was thus the main objective of this study. To understand the complex adaptive responses of root morphology and root exudates to low P availability, we carried out hydroponic culture experiments on canola, barley and potato, three crop species with different root systems. Although a hydroponic culture system does not reflect natural growth conditions for plants compared with a soil experiment, it is widely used (Gahoonia et al. 2000; Dechassa and Schenk ) and useful for studying root architecture, including tiny root tips, and for collecting root exudates for biochemical analysis of OAs. Furthermore, the effects of plantplant interactions were minimized in our system, since we grew a single plant per pot. Contrasting responses of root morphology and root-exuded OAs to low P availability in these three important food crops were revealed. These results could underpin future efforts to improve P uptake of the three crops.
The role of root morphology in improving P uptake Root architecture plays an important role in P uptake. Previous studies have shown that at reduced P availability, most species allocate more biomass to roots and allocate root biomass in shallow soil horizons, as well as increase root length and develop more and longer root hairs and lateral roots; some even produce cluster roots, thereby promoting P uptake (Nielsen et al. 2001;Lambers et al. 2006Lambers et al. , 2015Brown et al. 2013). In this study, our results showed a pronounced increase in root/shoot biomass ratio for the three studied species (Fig. 1B) under low P supply, which corresponds well with previous reports (Hermans et al. 2006;Hammond and White 2008). However, we found some differences in root traits like root length, lateral root numbers and root surface area among different crops (Fig. 3): under low P availability, barley showed a 44 % reduction in root length, 58 % smaller root surface area and 21 % lower root tip number; canola showed a 37 % increase in root length and a 45 % reduction in root tips and potato showed a doubling of the number of root tips, compared with under P50 conditions. However, Steingrobe et al. (2001) observed enhanced root-length production at a low P supply in barley in a field experiment, which differs from our results. This could be due to the two different methodologies used (i.e. we used a hydroponic culture, whereas Steingrobe et al. performed field experiments involving a more complicated environment around the roots). Moreover, the effects of micropropagated plantlets on root systems are not clear so far. Phosphorus uptake by plants is dependent on the surface area and length of the root system and on lateral roots to explore a large soil volume (Richardson et al. 2009;Balemi and Negisho 2012;Lambers et al. 2015). In our study, as we used KH 2 PO 4 as P source, root morphology plays a dominant role in P acquisition. At P50, barley had greater shoot P concentrations and P contents than canola and potato ( Fig. 5A and B), probably due to its significantly longer total root length and greater root surface area, enabling greater P uptake ( Fig. 3A and B), because these three crops had the same root tip number (Fig. 3C). Another explanation is its smaller biomass and higher root/shoot ratio ( Fig. 1A and B), resulting in higher shoot P concentrations compared with those of canola and potato. On the other hand, potato showed a significantly greater root P concentration and P content than barley and canola did at P50 (Fig. 5C and D), suggesting that potato roots may have a greater P uptake capacity than barley and canola. Further studies are needed to reveal the mechanisms for this. In addition, under low P supply, canola roots showed greater root length and larger root surface area than barley and potato, while potato showed a remarkable increase in root tips compared with that at P50, and hence had greater root P concentrations and contents than canola and barley (Fig. 3). This also suggests that root tips had a major effect on improving P uptake, as found by Fitter et al. (2002). However, no significant differences were found in root P concentrations and P contents under P1, which could be due to the very limited P supply. Our results for potato root architecture agree with those of McArthur and Knowles (1993a), who reported that root growth in potato is less influenced by P deficiency than either leaf or stem growth. Furthermore, they found a greater root colonization level of arbuscular mycorrhizal fungi for P-stressed potato plants, and P uptake by roots was enhanced by different kinds of arbuscular mycorrhizal fungi at all levels of P supply (McArthur and Knowles 1993b). Brundrett (2002) reviewed the major influence that root morphology characteristics such as cortex cell properties and root features like root length/biomass ratio, root branching and root hairs have on mycorrhiza formation. Highly mycorrhiza-dependent plants tend to have coarser root systems and would not be as responsive to changes in nutrient availability. Hence, these root traits of potato, especially abundant root tips, might favour mycorrhizal colonization.
The possible role of root exudation in low-P responses
Root exudation of OAs is considered as an important mechanism to mobilize P sources and alleviate P starvation, because OAs can replace organic and inorganic P that is bound to soil particles (Lambers et al. 2006). The fact that those plants that release more OAs could take up more P from growth media and soil has also been confirmed using genetically modified plants (Lü et al. 2012;Wang et al. 2013). However, root exudates are influenced by many factors (Dechassa and Schenk 2004). We used the most suitable and effective trap solution-waterto collect the exudates (Valentinuzzi et al. 2015), but we could not completely avoid some microbial breakdown, so the root-exuded OAs were possibly somewhat underestimated in our data (Kuijken et al. 2015).
Great differences in OA exudates were found among species in our system (Fig. 4). For canola, the absolute rate of citric acid exudation corresponded well with that reported by Hoffland et al. (1989). Furthermore, an increase in citric and malic acids and a decrease in succinic acid were found for canola under P starvation, which compares well with the results of Hoffland et al. (1989), except that malic acid was the dominant OA. On the other hand, no OAs were induced by P deficiency from canola roots, as reported by Ligaba et al. (2004) using the same system.
For barley, citric, acetic and fumaric acids were detected in root exudates of two cultivars under P deficiency by Gahoonia et al. (2000) using a hydroponic culture, but they only showed a difference between two cultivars; no information about the difference between P supply and P deficiency was given. Our results showed no significant difference in citric acid exudation in barley between P-sufficient and P-deficient plants, but there was an increase in malic acid exudation in the P deficiency treatment (Fig. 4A, B and E), thus showing that there are differences in the types and quantities of OAs that are released from different crop species and varieties in response to P starvation.
For potato, few references about OA exudates can be found in the literature, but the increase in succinic acid exudation in response to P deficiency was in accordance with the results of Dechassa and Schenk (2004), while the absolute value in our results was lower ( 0.002 versus 0.36 nmol (cm root) 21 h 21 ). The reason for this difference is unclear.
The decrease in the OA amounts released by roots of P-stressed plants after 4 weeks ( Fig. 4D-F) suggests that root exudation was influenced by plant age (Dechassa and Schenk 2004;Badri and Vivanco 2009).
Citric acid has the strongest ability to release soil P (Ryan et al. 2001), malic acid is 10 times less effective than citric acid in mobilizing soil P and succinic acid complexes metal cations only very weakly and, hence, has only a relatively weak ability to release soil P (Nagarajah et al. 1970;Jones and Darrah 1995). Therefore, canola, with its relatively rapid exudation of citric acid, is likely to have the greatest ability among the investigated crops to mobilize insoluble soil P. These results provide good evidence to support our Hypothesis (1), but the effect of root exudates on P uptake could not be assessed in this study, because P was only added to the system as aqueous KH 2 PO 4 . Further investigation is required to reveal the effect of root exudates (OAs) on P mobilization and uptake from soil.
Conclusions
Using a hydroponic culture system and various analytical methods, we have tested our hypotheses that canola, a dicot oilseed crop; potato, a tuber-producing dicot and barley, a monocot, respond differently under various levels of P availability. Our results revealed that the non-mycorrhizal AoB PLANTS www.aobplants.oxfordjournals.org species, canola, showed rapid rates of carboxylic acid exudation, which, together with its greater root length and root surface area, could allow canola to acquire poorly available P forms and explore a larger soil volume. The monocot and mycorrhizal species barley showed a reduction in root length and root surface area as well as low amounts of root exudates; in soil, this would result in a low P-uptake capacity. Potato released only trace amounts of root exudates but produced double the number of root tips under low-P conditions, which would benefit its P uptake in soil. Hence, our study indicates that plants evolved divergent adaptations of root morphology and exudation as a response to low P availability. The results and information generated in this study are valuable for future effective utilization of P and improving the productivity of the three important crops.
Sources of Funding
This study was supported by the core funding of the strategic institute program on 'Opportunities for sustainable use of phosphorus in food production' at the Norwegian Institute of Bioeconomy Research.
Conflict of Interest Statement
None declared. | v3-fos |
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} | s2 | Identification, Phylogeny, and Transcript of Chitinase Family Genes in Sugarcane
Chitinases are pathogensis-related proteins, which play an important role in plant defense mechanisms. The role of the sugarcane chitinase family genes remains unclear due to the highly heterozygous and aneuploidy chromosome genetic background of sugarcane. Ten differentially expressed chitinase genes (belonging to class I~VII) were obtained from RNA-seq analysis of both incompatible and compatible sugarcane genotypes during Sporisorium scitamineum challenge. Their structural properties and expression patterns were analyzed. Seven chitinases (ScChiI1, ScChiI2, ScChiI3, ScChiIII1, ScChiIII2, ScChiIV1 and ScChiVI1) showed more positive with early response and maintained increased transcripts in the incompatible interaction than those in the compatible one. Three (ScChiII1, ScChiV1 and ScChiVII1) seemed to have no significant difference in expression patterns between incompatible and compatible interactions. The ten chitinases were expressed differentially in response to hormone treatment as well as having distinct tissue specificity. ScChiI1, ScChiIV1 and ScChiVII1 were induced by various abiotic stresses (NaCl, CuCl2, PEG and 4 °C) and their involvement in plant immunity was demonstrated by over-expression in Nicotiana benthamiana. The results suggest that sugarcane chitinase family exhibit differential responses to biotic and abiotic stress, providing new insights into their function.
Phylogenetic analysis of chitinase gene family. Among the 17 differentially expressed chitinase unigenes, a total of 9 members was predicted to have full-length sequences with open reading frames (ORFs). The assembled sequence of ScChiVII1 based on homologous cloning method according to the predicted S. bicolor chitinase gene (XM_002460419.1) was added. To study the phylogenetic relationships of the chitinase family genes in sugarcane, a multiple alignment analysis was performed. The 10 genes with ORF structures were classified into seven types (class I ~ VII) based on the similarity of their amino acid sequences with 21 biotic stress resistance-related chitinases of other plant species from NCBI 17,18 . As shown in Fig. 1, they were segregated into two branches, one comprising classes III and V, and the other one including the classes I, II, IV, VI and VII. The 10 sugarcane chitinase genes were named by classification system of the chitinase in the phylogenetic tree and described as ScChiI1 (gi32815041), ScChiI2 (gi34957207), ScChiI3 (Sugarcane_Unigene_BMK.68059), ScChiII1 (gi35992663), ScChiIII1 Unigene ID Yacheng05-179 log 2 fold change (T/CK) * ROC22 log 2 fold change (T/CK) * BLAST annotation 24 hpi 48 hpi 120 hpi 24 Sequence analysis of chitinase gene family. In order to gain insight into the diversification among the above 10 chitinases from sugarcane and 21 from other plant species, several features of the predicted proteins were analyzed. The typical domains of chitinase, including chitin binding domain (CBD), chitinase domains of glycoside hydrolase family 18 and family 19, were shown in Fig. 2. In addition, the signal peptide, isoelectric point (pI) and the number of amino acids (aa) were also presented in Fig. 2. We found that not all chitinases contained signal peptide at their N-termini, such as ScChiI3 and O. Sativa chitinase (294979698) in class I and Momordica charantia chitinase (AAM18075.1) in class V. The length of the ORFs in sugarcane chitinases ranged from 238 aa to 325 aa. The average ORF length was 291 aa. The isoelectric point (pI) in different members was not identical in the same class, as some were acidic and others were basic. The sugarcane chitinases, including classes I, II, IV, VI and VII members, have a lysozyme-like domain in their structures which may exhibit lysozyme activity. Class I members ScChiI1 and ScChiI2 both contained the N-terminal signal peptide, following the chitin binding domain (CBD) which was rich in cysteines (9) and a glycoside hydrolase family 19 chitinase domain. Though the protein domain of ScChiI3 lacked a signal peptide and the CBD structure and was different from those of ScChiI1 and ScChiI2, they sharing 63.96% amino acid sequence identity. A spacer hinge region, rich in proline (3, 12 and 13) and glycine (5, 6 and 5) residues, was found between the CBD and the glycoside hydrolase family 19 chitinase domains of ScChiI1, ScChiI2 and ScChiI3. Class II chitinase ScChiII1 lacked the CBD and the hinge region, but contained a N-terminal signal peptide and a glycoside hydrolase family 19 chitinase domain (amino acids 34 ~ 223), sharing a high degree of homology (70.82%) with class I members. Like class I protein, class IV chitinase ScChiIV1 consisted of the CBD, hinge region and glycoside hydrolase family 19 chitinase domain. However, there was only 59% identity in the catalytic domain among class I and class IV. The class VI chitinase ScChiVI1, which lacked the duplicated CBDs in its N-terminal region which was different from chitinase (P11218) in Urtica dioica endochitinase 36 , had a signal peptide, a hinge region (1 prolines and 6 glycines) and a glycoside hydrolase family 19 chitinase domain. Class VII chitinase ScChiVII1 lacked the CBD and the hinge region, and its amino acid sequences were 47.57% homology to class I and Class II chitinases. Unlike Tissue-specific expression of chitinase family genes in sugarcane. qRT-PCR was performed to determine the expression patterns of these putative chitinase genes in different sugarcane above-ground tissues. As shown in Fig. 3, the expression of chitinase genes belonging to classes I, II, III, V and VII was detected in all of the four sugarcane tissues including leaf, bud, stem pith and stem epidermis. Compared with the other three tissues, the chitinase genes with the highest expression levels in stem pith were ScChiI1, ScChiI2, ScChiI3, ScChiIII1, ScChiIII2, ScChiV1 and ScChiVII1. ScChiII1 showed the highest level of transcripts in sugarcane tissues with transcripts most abundant in leaf. Transcripts of ScChiIV1 and ScChiVI1 accumulated to the highest level in bud tissues. These results showed a certain degree of tissue specificity in sugarcane chitinase family genes (Fig. 3).
Accumulation of chitinase gene mRNAs in sugarcane post inoculation with S. scitamineum. qRT-PCR was used to examine the expression patterns of the 10 sugarcane chitinase family genes during sugarcane-smut interaction (Fig. 4). It was seen that all 10 transcripts were induced by infection of S. scitamineum but different patterns were evident.
During the incompatible interaction using Yacheng05-179, one smut resistant sugarcane genotype, early transcriptional elevation of ScChiI1, ScChiIII1, ScChiIII2 and ScChiVI1 was observed at 24 hpi (Fig. 4A). The transcript of ScChiIII1 reached the maximum at 24 hpi, while the maximal accumulation of the other 3 genes was observed at 168 hpi. ScChiI2 and ScChiV1 transcripts decreased at 24 hpi and 48 hpi, but increased to the peak at 120 hpi and again reduced at 168 hpi. Although the ScChiI3 and ScChiIV1 accumulation decreased at initial stage (from 0 hpi to 48 hpi), they gradually elevated at the later stage (from 120 hpi to 168 hpi). ScChiII1 was up-regulated from 48 hpi to 168 hpi. In contrast, ScChiVII1 demonstrated a down-regulation during the incompatible interaction.
During the compatible interaction using ROC22, a popular genotype which is susceptible to S. scitamineum, transcripts of ScChiI1, ScChiII1 and ScChiIII2 were observed to be elevated as early as 24 hpi, suggesting rapid response to the infection of smut pathogen (Fig. 4B). Their expression values were accumulated to the maximal levels at either 24 hpi or 48 hpi. Transcripts of ScChiI2 and ScChiIV1 maintained almost at the same level after inoculation. ScChiI3 was down-regulated compared with that at 0 hpi. The transcripts of ScChiIII1, ScChiV1, ScChiVI1 and ScChiVII1 peaked at 48 hpi. The data indicated that all genes except ScChiVI1 had the lowest expression level at 168 hpi during the compatible interaction. Gene expression in response to different defense-related signal compounds. Transcript accumulation of chitinase genes in sugarcane plantlets under different phytohormone treatments, including SA, MeJA (methyl jasmonate) and ABA stresses, were examined by qRT-PCR (Fig. 5). The results revealed that all three signal compounds up-regulated ScChiI2, ScChiIII2 and ScChiV1, while ScChiIII1 was down-regulated. ScChiI1, ScChiIV1 and ScChiVII1 were up-regulated by MeJA and ABA but down-regulated by SA. In addition ScChiVI1 was down-regulated by MeJA and ABA but up-regulated by SA. ScChiI3 was up-regulated by SA and MeJA but suppressed by ABA. ABA treatment down-regulated ScChiII1 while ScChiVII1 was up-regulated. These results suggest that the transcription of individual chitinase genes respond differently to SA, MeJA and ABA. Functional characterization of three chitinase genes, ScChiI1, ScChiIV1 and ScChiVII1, during pathogen infection. Based on the information of differentially expressed chitinase genes post S. scitamineum infection, the full-length cDNA sequences of three chitinase genes, ScChiI1, ScChiIV1 and ScChiVII1, were isolated from sugarcane. The sequence data of ScChiI1, ScChiIV1 and ScChiVII1 were submitted to GenBank under accession number of KF664182, KF664178 and KF664179, respectively. The ORF fragment was recombined into the plant expression vector of pCAMBIA 2300 containing the 35S promoter and the GFP reporter gene. Their subcellular localization was characterized by transient expression of the target gene and GFP in N. benthamiana leaves with Agrobacterium-mediated transformation method 37 . Infiltrated leaves observed under a confocal laser scanning microscope showed that 35S::ScChiI1::GFP, 35S::ScChiIV1::GFP and 35S::ScChiVII1::GFP fusion proteins were located in cytoplasm and plasma membrane, plasma membrane, cytoplasm and plasma membrane, respectively (Fig. 6). In addition, the mock of 35S::GFP was shown in the nucleus, cytoplasm and plasma membrane cells.
Chitinase genes have been reported to be induced not only by biotic but also by abiotic stress 12,38 . The expression patterns of ScChiI1, ScChiIV1 and ScChiVII1 in Yacheng05-179 plantlets were investigated after treatment with 25% PEG (polyethylene glycol), 250 mM NaCl (sodium chloride), 100 μ M CuCl 2 (copper chloride), and low temperature (4 °C) (Fig. 7). This showed induction of high levels of ScChiIV1 transcripts with all four abiotic treatments. PEG, NaCl and CuCl 2 appeared to cause an increase of accumulated ScChiI1 transcripts post stress, while low temperature caused slightly decrease at 12 h. The expression of ScChiVII1 was up-regulated by low temperature and down-regulated by NaCl. In response to PEG and NaCl stresses, the level of ScChiVII1 transcript reduced slightly at 6 h and 12 h, but increased at 12 h and 24 h, respectively.
Transient expression of ScChiI1, ScChiIV1 and ScChiVII1 induces a defense response in N.
benthamiana. To test whether the target genes can induce hypersensitive response (HR) and immunity in plant, ScChiI1, ScChiIV1 and ScChiVII1 genes were transiently over-expressed in N. benthamiana leaves. After 48 h post infiltration, a typical HR symptom with deeper DAB staining was found in the leaves expressing 35S::ScChiI1, 35S::ScChiIV1 and 35S::ScChiVII1, respectively (Fig. 8). The bronzing color after over-expressing ScChiI1 was the darkest. Furthermore, the expression levels of seven immunity associated marker genes including the HR marker genes NtHSR201 and NtHSR203, the JA-associated genes NtPR-1a/c and NtPR2 and NtPR3, and the ethylene synthesis depended genes NtEFE26 and NtAccdeaminase, were increased post 24 h infiltration. These results suggest that ScChiI1, ScChiIV1 and ScChiVII1 were involved in cell death responses.
Discussion
Many plants contain multiple chitinase isozymes. They have been categorized into seven classes (class I ~ VII) based on their primary structure, substrate specificity, mechanisms of catalysis and sensitivity to inhibitors 17,18 . On the basis of the annotations of O. sativa and Arabidopsis genomic sequences, 37 and 24 chitinases were found in O. sativa and Arabidopsis, respectively 24 . Analysis revealed that each cluster had distinct amino acid characteristics. Krishnaveni et al. 39 had observed three antifungal chitinases, CH1, CH2 and CH3, from S. bicolor. Four cDNAs encoding acidic and basic isoforms of chitinases were isolated from Cladosporium fulvum-infected tomato leaves 40 . We have previously reported cloning and identification of one class III and one class VII chitinases from sugarcane post S. scitamineum inoculation 22,34 . The current study of the sugarcane chitinase family indicated the presence of at least 17 expressed genes induced by smut pathogen.
Chitinase isozymes are a diverse group of enzymes with different characteristics, such as enzymatic activities, primary sequence, pI and cellular localization 41 . Based on the domain architecture of chitinases classes I~VII in sugarcane and other plants, not all chitinases contained a signal peptide, and the CBD structure was absent in ScChi VI1 (class VI). According to the most popular classification system described earlier 17,18,42 , class I chitinases contain three domains: a cysteine-rich N-terminal CBD, a proline-and glycine-rich hinge region and a highly conserved C-terminal catalytic domain. Class II chitinases are generally extracellular which lack the CBD and the hinge region, but their amino acid sequences in the catalytic domain are nearly identical to class I chitinases (more than 65%). Class III lacks CBD and has little sequence identity to the class I and class II catalytic domain, while Class IV contains the CBD, hinge region and catalytic domain, but displays deletion in the catalytic domain. Class V chitinases has little sequence similarity with the other chitinases, but more similar to bacterial chitinases, such as those from Bacillus circulans and Serratia marcescens. Class VI chitinases possess the duplicated CBDs in their N-terminal regions, while Class VII chitinases lack the CBD and the hinge region. In this study, seven types of sugarcane chitinases coincided with the former classification 17,18,42 . In Fig. 1, although ScChiV1 and the chitinase proteins from Momordica charantia (AAM18075.1) and Scientific RepoRts | 5:10708 | DOi: 10.1038/srep10708 N. tabacum (CAA54373.1) were not at the consistent branch of the phylogenic tree, it was assigned to the class V subfamily containing the same domain of glycoside hydrolase family 18. Nearly all sugarcane chitinases, except ScChiI 3, contained the N-terminal targeting domain which may involve in directing them to either the vacuole or the apoplast (Fig. 2). Like other plant species 43 , sugarcane chitinases of classes I, II, IV, VI and VII have the glycoside hydrolase family 19 domain belong to class PR-3 family, and class III and class V possess the glycoside hydrolase family 18 domain belong to PR-8 and PR-11 families, respectively. Chitinases including class I, II, IV, VI and VII were predicted to contain a lysozyme like domain 44 , suggesting that most sugarcane chitinases possess lysozyme activity.
According to previous reports, the only route of invasion of the smut pathogen is via sugarcane buds 45 . Previous studies also revealed that plant chitinases are developmentally regulated, indicating a role in the specific physiological processes 18,46 . In this study, transcripts of sugarcane chitinase genes differently accumulated in the noninfected sugarcane above-ground tissues (Fig. 3). Seven chitinase genes expressed at high expression levels in stem pith, suggesting specific roles in stem pith. ScChiII1 showed the highest expression level in sugarcane and its transcript was most abundant in leaf. Considering the significantly higher expression of ScChiIV1 and ScChiVI1 in sugarcane buds than in other tissues, it suggests that ScChiIV1 and ScChiVI1 may play a positive role in sugarcane smut resistance.
In the present study, during S. scitamineum infection (0 hpi ~ 168 hpi), the expression of at least 10 sugarcane chitinases was induced. However they showed different expression patterns in the incompatible/compatible interactions. In Yacheng05-179, four chitinase genes, ScChiI1, ScChiIII1, ScChiIII2 and ScChiVI1, rapidly responded to smut pathogen inoculation at initial stage (from 0 hpi~24 hpi) (Fig. 4), and reached maximal accumulation at 168 hpi. Conversely, in ROC22, almost all the target genes (except ScChiVI1) had lower expression levels at 168 hpi (Fig. 4). These results suggest that sugarcane chitinase genes are pathogen-inducible and are involved in disease resistance. Previously, a class III sugarcane chitinase gene ScChi was shown to be induced after challenge in the incompatible interaction (Yacheng05-179 vs. S. scitamineum) and its expression remained higher than that in a compatible interaction (Liucheng03-182 vs. S. scitamineum) 22 .
In plants, levels of chitinases are regulated by biotic and abiotic stress, such as pathogen infection, cold, drought, heavy metals, salt, and plant hormones 12,22,38 . As reported, SA, JA and ethylene are considered as the defense signal compounds for systemic acquired resistance (SAR) and induced systemic resistance (ISR), two types of plant induced resistance 21 . In plant responses to environmental stress, the reaction of the signaling molecule JA is the fastest, and plays an important part in resistance reaction. JA-related gene expression has been reported to be up-regulated and cause JA accumulation under biotic and abiotic stress 47 . Previous studies suggested that ABA affects plant response to biotic stress mainly via interaction with other stress responsive pathways 48 . In our study, the expression levels of sugarcane chitinase genes could be differentially modulated by SA, MeJA and ABA (Fig. 5). Exogenously applied SA resulted in an increase accumulation of ScChiI2, ScChiI3, ScChiIII2, ScChiV1 and ScChiVI1 transcripts. Application of MeJA increased the expressions of ScChiI1, ScChiI2, ScChiI3, ScChiII1, ScChiIII2, ScChiIV1, ScChiV1 and ScChiVII1. The exogenous application of ABA increased the levels of ScChiI1, ScChiI2, ScChiIII2, ScChiIV1, ScChiV1 and ScChiVII1 transcripts.
Full-length cDNA sequences of three sugarcane chitinase genes, each one of class I chitinase ScChiI1, class IV chitinase ScChiIV1 and class VII chitinase ScChiVII1, were isolated from smut resistant genotype Yacheng05-179. These three genes were pathogen-inducible post S. scitamineum infection (Fig. 4), and were up-regulated by MeJA and ABA but down-regulated by SA (Fig. 5). Protein localization revealed that 35S::ScChiI1::GFP and 35S::ScChiVII1::GFP fusion proteins were located in cytoplasm and plasma membrane, while 35S::ScChiIV1::GFP was located in plasma membrane (Fig. 6). ScChiI1 and ScChiIV1 were up-regulated by PEG, NaCl and CuCl 2 stresses, while ScChiVII1 was not (Fig. 7). ScChiIV1 and ScChiVII1 transcripts were increased under 4 °C low temperature stress, but ScChiI1 was not (Fig. 7). However, all these genes induced defense responses in N. benthamiana by transient expression (Fig. 8). These results suggest that the different sugarcane chitinases have individual functions in response to various environmental stresses.
Although functions of sugarcane chitinases genes are not fully understood, some chitinases in plant species have been shown to inhibit the growth of chitin-containing fungi, both in vitro 49 and in vivo 14,15 . Data were normalized to the GAPDH expression level. All data points were the means ± SE (n = 3). Different lowercase letters indicated a significant difference, as determined by the least-significant difference test (p-value < 0.05). PEG, polyethylene glycol; NaCl, sodium chloride; CuCl 2 , copper chloride.
Scientific RepoRts | 5:10708 | DOi: 10.1038/srep10708 When compared with wild-type plants, in many cases, transgenic plants constitutively expressing chitinases showed enhanced resistance to fungal infection or delayed development of disease symptoms 50,51 . The transgenic Musa acuminata expressing the O. sativa chitinase gene exhibited resistance to black leaf streak disease caused by the pathogenic fungus, Mycosphaerella fijiensis 26 . In our previous work, a close relationship between the expression of sugarcane class III chitinase gene ScChi (KF664180) and plant immunity was demonstrated from inoculation experiments and the validation of in vitro antibacterial activity. There was also a report of smut resistance improvement in sugarcane varieties ROC22 and ROC10 by introduction of a β -1,3 glucanase together with the modified class I chitinase gene from N. tabacum 52 . From the characteristics of the 10 sugarcane chitinase genes obtained here, the possible contribution of all these genes for plant defense against pathogen attack is suggested. However, the conclusive validation and precise functional determination of these genes by genetic transformation into sugarcane is still in progress. The transcripts analysis of the immunity associated marker genes, including the hypersensitive response marker genes NtHSR201 and NtHSR203, the jasmonate associated genes NtPR-1a/c and NtPR2 and NtPR3, and the ethylene synthesis depended genes NtEFE26 and NtAccdeaminase. NtEF1-α was used to normalize the transcript levels. Mock: the Agrobacterium strain carrying 35S::00. All data points are the means ± SE (n = 3). Different lowercase letters indicate a significant difference, as determined by the least-significant difference test (p-value < 0.05).
Plant materials and inoculation with
Scientific RepoRts | 5:10708 | DOi: 10.1038/srep10708 of spores 37 to eliminate the effect of wounding. At 0 hpi, 24 hpi, 48 hpi, 120 hpi and 168 hpi, one biological replicate consisting of five buds for each group were excised, immediately frozen in liquid nitrogen and then stored at − 80 °C.
Tissue distribution study.
For tissue distribution study, one biological replicate with six healthy 10 month old plant of Yacheng05-179 was selected. The samples were collected from the youngest fully expanded leaf (+1 leaf) with a visible dewlap (the collar between the leaf blade and sheath), buds, stem pith and stem epidermis. These samples were fixed in liquid nitrogen and kept at − 80 °C until RNA extraction 37 . Abiotic stress treatments. To investigate the expression of sugarcane chitinase family genes in response to stress factors, 4 month old tissue cultured plantlets of Yacheng05-179 were grown in water for one week and then exposed to various chemical stimuli 37
According to the results of previous researches by Kirubakaran et al. 28 , Rahul et al. 33 and Singh et al. 17 , along with the information from bioinformatic analysis and their expression profile under the stresses of MeJA, ABA and SA indicated in this study, three out of ten chitinase genes, ScChiI1, ScChiIV1 and ScChiVII1 were chosen for further study. Based on the sequences of the above predicted chitinase genes, the primers used to clone the target genes were designed. Amplification of ScChiI1 (gi32815041) was performed with primers ScChiI1: FW-ACATACATAGTTGCTTGCYTTGC and RV-CCTTTTGCTTTATTCATTGCTC on first-strand cDNA template of Yacheng05-179 under 4 °C low temperature treatment for 24 h. ScChiIV1 (Sugarcane_Unigene_BMK.56580) and ScChiVII1 were amplified with primers ScChiIV1: FW-GCACCGCAGCAACGAA and RV-CGGAGCCATGCAAGGAG, ScChiVII1: FW-AAGATGAAGCGGAAGACG and RV-GCTAAAACAGACCCATTGTG, on first-strand cDNA template of Yacheng05-179 post 48 h S. scitamineum inoculation. These PCR products were gel-purified, cloned into the pMD18-T vector (TaKaRa, China) and sequenced (Shenggong, China).
Sequence analysis of chitinase genes. ORF analysis was performed with the ORF Finder (http:// www.ncbi.nlm.nih.gov/gorf/gorf.html). The pI was calculated with the ProtParam tool (http://www. expasy.ch/tools/protparam.html). SignalP 4.0 Server (http://www.cbs.dtu.dk/services/SignalP/), NCBI Conserved Domains (http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) and SMART (http://smart. embl-heidelberg.de/) programs were employed to scan for the signal peptides and the motifs on the primary structure of the deduced protein sequences. Subcellular location of the putative proteins was predicted with PSORT Prediction (http://psort.hgc.jp/form.html). ClustalW software was used to perform multiple alignment of sugarcane chitinases with other previously published plant chitinases 17,18 . Based on this alignment, a phylogenetic tree was constructed according to the neighbor-joining (NJ) method (1,000 bootstrap replicates) using the MEGA 5.05 program.
Transcript level analysis. Expression patterns of sugarcane chitinase family genes in different tissues and their response to biotic and abiotic stress were analyzed by qRT-PCR, which followed the instructions of the SYBR Green Master (ROX) (Roche, China) on a 7500 real time PCR system (Applied Biosystems, USA). The GAPDH (glyceraldehyde-3-phosphate dehydrogenase) gene (Table 2) was used as an internal control. According to sequences of ScChiI1 ~ ScChiVII1, the specific primers (Table 2) were designed using the Beacon Designer 8.12 program. The qRT-PCR reaction system (20 μ L) contained 10 μ L FastStart Universal SYBR Green PCR Master (ROX), 1.0 μ L of first-strand cDNA (10 × diluted) and 0.5 μ M of each primer. PCR with distilled water as template was performed as control. The qRT-PCR reaction condition was held at 50 °C for 2 min, 95 °C for 10 min, 40 cycles of 95 °C for 15 s and 60 °C for 1 min. At the end of the PCR reaction, a melting curve was established. Each qRT-PCR was conducted in triplicate. The 2 −Ct method was adopted to analyze the qRT-PCR results 53 . For calculating gene expression level during developmental stages, the tissue exhibiting the lowest expression level was served as control. For the abiotic stress treatments, unstressed sample was used as control. During the biotic stress, gene expression profile was calculated by the expression level of the inoculated sample of S. scitamineum minus the level of the mock at each corresponding time point to eliminate any effect of wounding. Data points in qRT-PCR time course were plotted as means ± SE of three replicates.
The role of three chitinase genes in response to pathogen infection. Subcellular location assay
with Agrobacterium-mediated transformation was followed from Su et al. 22 . ORF fragments of ScChiI1, ScChiIV1 and ScChiVII1 were inserted into the vector of pCAMBIA 2300-GFP and transformed into the competent cells of A. tumefaciens strain EHA105, respectively. The subcellular localization of the fusion protein was visualized using a confocal laser scanning microscope Leica TCS SP5 (Germany) equipped with 10 × lense.
As reported, cell death presented at the infected site is the most efficient method to restrict pathogen growth and development 54 . The stimulation of reactive oxygen species (ROS) and defense-related hormones, induction of R gene expression and ion fluxes are the common response of cell death 55,56 . For the transient expression of the target gene in N. benthamiana, overexpression vectors pCAMBIA 1301-ScChiI1, pCAMBIA 1301-ScChiIV1 and pCAMBIA 1301-ScChiVII1 were constructed to analyze their defense responses. Agrobacterium strain EHA105 carrying the recombinant vector was transiently expressed in N. benthamiana leaves. Each treatment was carried out in three replicates. DAB (3,3'-diaminobenzidinesolution) was used to stain H 2 O 2 produced in agroinfiltrated leaves 22 . The leaves were incubated in 1.0 mg/mL DAB-HCl solution in the dark overnight and destained by boiling in 95% ethanol for 5 min. The bronzing color of the leaves for H 2 O 2 detection was photographed. qRT-PCR analysis of the expression of seven immunity associated marker genes were conducted post 24 infiltration, including the hypersensitive response marker genes NtHSR201 and NtHSR203, the jasmonate associated genes NtPR-1a/c, NtPR2 and NtPR3, and the ethylene synthesis depended genes NtEFE26 and NtAccdeaminase ( Table 2) 22 . NtEF1-α ( Table 2) was used to normalize the transcript levels. | v3-fos |
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} | s2 | Optimization of Fermentation Medium for Extracellular Lipase Production from Aspergillus niger Using Response Surface Methodology
Lipase produced by Aspergillus niger is widely used in various industries. In this study, extracellular lipase production from an industrial producing strain of A. niger was improved by medium optimization. The secondary carbon source, nitrogen source, and lipid were found to be the three most influential factors for lipase production by single-factor experiments. According to the statistical approach, the optimum values of three most influential parameters were determined: 10.5 g/L corn starch, 35.4 g/L soybean meal, and 10.9 g/L soybean oil. Using this optimum medium, the best lipase activity was obtained at 2,171 U/mL, which was 16.4% higher than using the initial medium. All these results confirmed the validity of the model. Furthermore, results of the Box-Behnken Design and quadratic models analysis indicated that the carbon to nitrogen (C/N) ratio significantly influenced the enzyme production, which also suggested that more attention should be paid to the C/N ratio for the optimization of enzyme production.
Introduction
Lipases (triacylglycerol ester hydrolase EC 3.1.1.3) catalyze the hydrolysis of triglycerides into fatty acids and glycerol [1,2] and under certain conditions can also catalyze the synthesis of esters through transesterification, thioesterification, and aminolysis [3][4][5]. Lipases exist widely in nature environment, especially in bacteria, yeasts, and filamentous fungi. In recent years, the interest in microbial lipases production has been increasing, because of their large potential in industrial applications for the synthesis of biopolymers and biodiesel, the production of enantiopure pharmaceuticals, agrochemicals, and flavour compounds [2,6]. Both high-level production and the safety of the process and products are required to broaden the industrial application of lipases [6].
Aspergillus niger is one of the most important industrial microbes, which can produce more than 30 species of enzymes such as lipase [7][8][9][10][11], amylase [12,13], cellulase [14,15], pectinase [16], and glucose oxidase [17,18]. It has been widely used to produce extracellular enzymes and organic acid for decades [19,20]. The microorganism is Generally Recognized as Safe (GRAS) by the United States Food and Drug Administration [19]. Because of its excellent protein secretion capability, mature fermentation, and posttreatment process and safety, A. niger becomes one of the most important species in industrial application [21]. A. niger enzymes such as lipase could be utilized as auxiliary material or additive in food, medicine, and feed industry [19]. Maximization of the lipase yield is a prerequisite for the immense potential of A. niger lipase. The composition of fermentation medium has significant effect on microorganism metabolism [22], which is desired to optimize for the maximum yields of lipase.
Response Surface Methodology (RSM) is a mathematical and statistical method that can overcome some drawbacks like time consumption and high cost. It is widely used to solve multiple variable problems in different biotechnological a Corn starch hydrolyzate (hydrol), a less expensive nutrient source for industrial medium, contains 50-60 g/L glucose and is rich in trace elements. The value of hydrol was 30, 40, and 50 g/L. b 40 g/L soybean meal was supplemented in the analysis of sodium nitrate. The concentration of sodium nitrate was set as 8, 10, and 12 g/L, respectively.
processes [13,[23][24][25][26][27]. RSM has been successfully applied to evaluate and optimize the effect of process parameters in the production of lipase. Hatzinikolaou et al. [24] used RSM to study the effect of carbon and nitrogen sources on the extracellular lipase production from A. niger. A maximum lipase activity of 42.4 U/mL was obtained in the optimum medium with a combination of corn oil and peptone. Also using RSM, Kaushik et al. [23] reported that sunflower oil, glucose, peptone, agitation rate, and incubation temperature were the most influential parameters in the production of extracellular lipase from A. carneus. A 1.8-fold increase in production, with the final yield of 12.7 IU/mL, was obtained under the optimum medium and operation. Box-Behnken Design (BBD) is a RSM suitable for fermentation optimization in shake flasks, in which the most influential parameters can be determined by the minimum numbers of experiments [25]. In this study, we aimed to improve the yield of lipase production through optimization of the fermentation medium composition for A. niger G783, which is an industrial production strain. In this paper, the influential parameters were determined and optimized by a series of single-factor experiments and BBD method, respectively, which can also evaluate the effect and relationship of different medium components.
Strains and Chemicals.
A. niger G783, a genetic stability lipase high-yielding industrial production strain, was genetically engineered by physical and chemical mutagenesis from A. niger CICC 2475 (China Center of Industrial Culture Collection), which was preserved in Shenzhen Leveking Bio-Engineering Co., Ltd. Glucose, sucrose, corn starch, dextrin, soybean meal, peptone, beef extract, yeast extract, salt, and agar were obtained at analytical grade from chemical suppliers in China. Olive oil and soybean oil were purchased from local markets (Shenzhen, China).
Strain Cultivation.
The inoculum was produced in YPD medium in slant. Shake flasks of 250 mL containing 25 mL of seed medium were incubated in a shaker (220 rpm) at 30 ∘ C, for 20-32 h. Lipase production was carried out with a 2% (v/v) inoculum of A. niger G783 in 500 mL shaken flasks with 50 mL of FM1 and incubated at 30 ∘ C in a shaker (220 rpm) for about 48 h. The broth was refrigerated at 4 ∘ C and centrifuged at 10,000 rpm for 10 minutes, and the supernatant was obtained as crude enzyme solution that was used for lipase activity analysis.
Single-Factor Experiment.
To determine the influential parameters on the lipase production, we carried out a singlefactor experiment. The value of the factors was set based on FM1 medium. The medium was divided into five components, primary carbon sources, secondary carbon sources, nitrogen sources, oils, and inorganic salts. The composition of components and the experimental sequence for the singlefactor experiment are shown in Table 1. Fermentation was performed in 500 mL shake flasks with 50 mL medium and incubated at 30 ∘ C in a shaker (220 rpm) for about 48 h. The broth was refrigerated at 4 ∘ C and then centrifuged at 10,000 rpm for 10 minutes. The supernatant was obtained as crude enzyme solution that was used for lipase activity analysis. All components were analyzed independently, and every test was performed in triplicate. The influential factors and levels for the enzyme activity were evaluated.
BBD Design.
Box-Behnken Design (BBD), one of RSM design, with a three-level factorial design was used as the experimental design model to optimize the influential parameters for enhancing lipase production. According to the results of single-factor experiment, the levels of the variables and the experimental design (according to Design-Expert Table 2: Coded levels and real values (in parentheses) for the BBD and lipase activity achieved after fermentation by A. niger G783.
Run
Corn starch (g/L) Table 2. The lipase activities in volume were associated with simultaneous changes in corn starch concentration (8, 10, and 12 g/L), the soybean meal concentration (30,35, and 40 g/L), and the soybean oil concentration (5, 10, and 15 g/L) of fermentation medium. In this study, 17 experiments planned with the BBD design were carried out for building quadratic models, with five replications of the center points to estimate the experimental errors accordingly. The corresponding fermentation was performed in 500 mL shake flasks with 50 mL medium and incubated at 30 ∘ C in a shaker (220 rpm) for about 48 h. The broth was refrigerated at 4 ∘ C and centrifuged at 10,000 rpm for 10 minutes, and the supernatant was obtained as crude enzyme solution that was used for lipase activity analysis. A software named "Design-Expert 8.0" was used to analyze the experimental results, build the regression model, and predict the optimal processing parameters [28].
2.6. Lipase Activity Assay. Lipase activity in the fermentation broths was analyzed according to a slightly modified NaOH titration method [29]. The assay mixture contained 5 mL of the olive oil emulsion, 4 mL of 50 mmol/L glycine-NaOH buffer (pH 9.4), and 1 mL of enzyme solution. The reaction was preceded at 36 ∘ C for 15 minutes and stopped by adding 20 mL of 95% ethanol and 10 mL 30% NaCl. One unit of the lipase activity was defined as the amount of enzyme required to release 1 mol of fatty acid per minute under assay condition [30]. of A. niger G783, the levels of the variables were set to be close to the central point in the single-factor experiments. As shown in Table 1, the levels of the variables were designed and the single-factor experiments were performed as the following sequence: primary carbon source, secondary carbon source, nitrogen source, oil, and inorganic salt. The optimum variable and level that were determined in every step would be used in the next steps. As carbon catabolite repression (CCR) existed in Aspergillus sp. [31,32], two types of carbon source, primary and secondary carbon sources, are thought to play different roles in the metabolism of Aspergillus sp. Therefore, these carbon sources were analyzed independently. Glucose, maltose, corn starch hydrolyzate (hydrol), sucrose, and glycerol were selected as the primary carbon source, while corn starch, modified starch, and dextrin were selected as secondary carbon source ( Table 1). As shown in Figure 1, higher lipase activity was obtained when glucose was used as primary carbon source. Using glucose as the primary carbon source was significantly higher than using maltose, sucrose, or glycerol. However, the lipase activity obtained from hydrol was not significantly different than using glucose, because the major content of hydrol was glucose. This result suggested that glucose was the best primary carbon source for lipase production. Moreover, the lipase production was similar to each other between 15 and 25 g/L glucose. To make sure the carbon source is enough, 25 g/L glucose was used as the primary carbon source in the following studies. For the three types of secondary carbon source, corn starch was the best secondary carbon source on the lipase production ( Figure 2). Among the concentration range of 5-15 g/L corn starch, the best condition was 10 g/L corn starch. Thus, the amounts of carbon sources were designed as 25 g/L glucose and 10 g/L corn starch in FM1.
Result and Discussion
During fermentation, the availability of precursors for protein synthesis [33] and the nitrogen source [34] are both important in the production of extracellular enzymes. Nitrogen source would also significantly affect the pH of the medium. To obtain an insight for the effect of different nitrogen sources, various inorganic and organic nitrogen sources were investigated in lipase production. As shown in Figure 3, the activity of lipase has no significant difference when using peptone, beef extract, and soybean meal with or without NaNO 3 , respectively. However, lipase activity decreased significantly when yeast extract was used as nitrogen source. Thus, soybean meal was selected as nitrogen source because of its low cost and the ease of accessibility. Since the soybean meal was assumed to contain most of the necessary nutrients that lipase production needs, no other nitrogen supplements were necessary [26]. Herein, the lipase activity was not significantly different when supplemented with sodium nitrate, which suggested that sodium nitrate can be omitted. Oils could be served as carbon source and inducer of lipase synthesis during A. niger fermentation [35]. Figure 4 showed that olive oil and soybean oil were both outstanding for lipase production, compared to lard oil, peanut oil, and sunflower oil. As it is of low cost and easily acquired, soybean oil was selected to replace olive oil. Although the effect of sodium phosphate monobasic and calcium carbonate on the lipase production was greater than potassium sulfate ( Figure 5), all inorganic salts chosen in the single-factor experiments are essential for the basic metabolism of A. niger. The results indicated that the concentration of inorganic salts should be 1.5 g/L NaH 2 PO 4 , 0.2 g/L K 2 SO 4 , and 5 g/L CaCO 3 , respectively. Based on the results of single-factor experiments, a new fermentation medium (FM2) was established as follows (per liter): 25 g glucose, 10 g corn starch, 40 g soybean meal, 10 g soybean oil, 12 g NaNO 3 , 1.5 g NaH 2 PO 4 , 0.2 g K 2 SO 4 , 5 g CaCO 3 , and pH 7.2.
BBD Model Fitting and Data Analysis.
According to the single-factor experiments, three influential factors ( : corn starch, : soybean meal, and : soybean oil) in FM2 for G783 fermentation were selected for BBD design and quadratic models analysis ( Table 2). Parameters of the BBD design were set as follows: factor = 3, liver = 3, and runs = 17 (including 5 replications of the center points), and lipase activity was set as response value ( (1) a Coefficient of determination ( 2 ) = 0.9828, CV = 2.29%. A model with an value of 43.89 implies that the model is significant, which could occur due to noise. Values of "Prob. > " less than 0.01 indicate that model terms are significant. In this case, , , , , 2 , 2 , and 2 are significant model terms. The "Predicted 2 " of 0.9431 is close to the "Adj. -Squared" of 0.9602, which corrects the 2 values for the number of terms and for the sample size in the model. The "adequate precision" value of 22.523 indicates an adequate signal. The lack of fit is insignificant and the model is adequate. This model can be used to navigate the design space. The variance analysis results were listed in Table 3. This model processes high reliability, high fitting degree, and deviation with coefficient of determination 2 = 0.9826 and adequate precision of 22.523. Furthermore, the value of this model was significant ( < 0.01) and the lack of fit was not significant ( = 0.9057 > 0.05), which indicated that the residual might be caused by random error and this model is adequate. On the whole, this model could be used for evaluation, optimization, and prediction of lipase fermentation process. The variance analysis of three factors ( , , and ) showed that , , , 2 , 2 , and 2 have significant effect on enzyme production ( < 0.05) as listed in Table 3. This model predicted that these three factors were significant affecting the lipase production. In the medium, corn starch, soybean meal, and soybean oil are the major source for supply carbon or nitrogen resource to maintain the normal microbe metabolism and protein synthesis. Additionally, various amounts of these three factors also affect the carbon to nitrogen ratio (C/N), which could affect the metabolic pathway of the microorganism. We discussed about the effect of C/N ratio thereinafter. Therefore, the concentrations of corn starch, soybean meal, and soy oil bean in the medium have significant effect on enzyme production.
Earlier studies by Gombert et al. [36] and Dinarvand et al. [37] have optimized C/N ratio in the medium for enzyme production. Comparing to metabolite production (C/N ratio = 300) [38], lower C/N ratio medium is beneficial to enzyme production (C/N ratio <14) [36,37]. Dinarvand et al. [37] indicated that both organic and inorganic nitrogen sources can improve cell growth and synthesis of enzymes. High productivity of enzymes was obtained under low C/N ratio condition, carbon limitation, and rich nitrogen. The C/N ratio in this BBD study was set to 6.6-8.3 within an appropriate range for enzyme production. As shown in Figure 6(a), the interaction between factors (corn starch) and (soybean meal) was significant, which indicated that C/N ratio (corn starch/soybean meal) was important for lipase production. This result suggested that more attention should be paid to C/N ratio in the optimization of enzyme production. As shown in Figures 6(b) and 6(c), the interactions of and or and were not significant. Although soybean oil not only induces the lipase synthesis but also is used as carbon source [35], our results suggested soybean oil did not significantly affect the C/N ratio. After derivation of the quadratic equation and calculation (according to Design-Expert 8.0), the concentrations of three factors in the optimum medium for maximum lipase activity production were predicted as 10.5 g/L corn starch, 35.4 g/L soybean meal, and 10.9 g/L soybean oil. Therefore, the optimum fermentation medium (FM3) was predicted as follows (per liter): 25 g glucose, 10.5 g corn starch, 35.4 g soybean meal, 10.9 g soybean oil, 12 g NaNO 3 , 1.5 g NaH 2 PO 4 , 0.2 g K 2 SO 4 , and 5 g CaCO 3 , pH adjusted to 7.2. The maximum lipase activity was predicted at 2,096 U/mL.
Validation Experiments.
Validation experiments were carried out in triplicate to confirm the predicted optimal conditions. Initial fermentation medium (FM1), single-factor optimum medium (FM2), and BBD optimum medium (FM3) were investigated and evaluated to validate the predicted optimal conditions ( Table 4). The final lipase activity of A. niger G783 in FM3 was 2,171 ± 41 U/mL with a slight increase compared to the predicted value. Considering the experimental error, this result was consistent with predicted value, which suggested that the model built by BBD in this study is valuable for optimization of the fermentation medium. Moreover, the lipase activity was significantly improved in FM3 compared to the other two media, especially the initial medium (FM1). This statistical optimization study on A. niger fermentation medium is important for industrial lipase production. This study also provided helpful experiences for industrial production strain improvement.
Conclusions
Medium component significantly affects the revenue in industrial scale fermentation, due to the effect on feedstock cost and product yield. In this study, we successfully demonstrated sequential single-factor experiments and BBD strategy could be used for optimization of fermentation medium for the industrial production strain. Due to its effect on the C/N ratio, corn starch, soybean meal, and soybean oil were selected as factors in BBD design to predict the optimal conditions. Statistical analysis from BBD suggested that the C/N ratio was important for A. niger lipase production. Using the predicted condition, the optimum lipase activity of A. niger G783 was up to 2,171 ± 41 U/mL, which was 16.4% higher than using the initial medium. This optimal fermentative medium formula could be used for the future upscale lipase production using A. niger. This study also provided helpful experiences for industrial production improvement. | v3-fos |
2016-03-01T03:19:46.873Z | {
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} | s2 | Studies on Chemical Composition, Antimicrobial and Antioxidant Activities of Five Thymus vulgaris L. Essential Oils
This study is aimed at assessing the essential oil composition, total phenolic content, antimicrobial and antioxidant activities of Thymus vulgaris collected in five different area of the Campania Region, Southern Italy. The chemical composition of the essential oils was studied by GC-flame ionization detector (FID) and GC/MS; the biological activities were evaluated through determination of MIC and minimum bactericidal concentration (MBC) and evaluation of antioxidant activity. In total, 134 compounds were identified. The oils were mainly composed of phenolic compounds, and all oils belonged to the chemotype thymol. The antimicrobial activity of the five oils was assayed against ten bacterial strains. The oils showed different inhibitory activity against some Gram-positive pathogens. The total phenol content in the essential oils ranged from 77.6–165.1 mg gallic acid equivalents (GAE)/g. The results reported here may help to shed light on the complex chemotaxonomy of the genus Thymus. These oils could be used in many fields as natural preservatives of food and as nutraceuticals.
. Chemical composition of the essential oils isolated from the aerial part of Thymus vulgaris collected at the campus of the University of Salerno (S), Frigento (F), Contrada la Francesca (LF), Morigerati (M) and Zungoli (Z).
Minimum Inhibitory Concentrations
The minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC) values of the five essential oils against ten selected microorganisms are reported in Table 2. The five essential oils showed different inhibitory activity against the Gram-positive pathogens. Among the Gram-negative bacteria, E. coli was affected by the oil of Frigento (F). Staphylococcus epidermidis was the more sensitive bacterial strain.
Total Phenolic Content
The concentration of total phenols was determined in the five essential oils of T. vulgaris plants. In Figure 1, the results of the colorimetric analysis are given; they were derived from the absorbance values of the oil solutions compared to the standard solutions of gallic acid equivalents (standard curve equation: y = 0.00119x − 0.00532, r 2 = 0.9996). The total phenol content of the five oils ranged from 77.6-165.1 mg gallic acid equivalents (GAE)/g of sample (essential oil). The essential oil from Zungoli contained significantly higher total phenols (165.1 mg GAE/g) than the other oils.
Free Radical-Scavenging Capacity
The antioxidant activity of T. vulgaris essential oils was assessed by DPPH assay, evaluating the H-donating or radical scavenging ability of the oils using the stable radical 2,2-diphenyl-1-picrylhydrazyl (DPPH) as a reagent. Table 3 shows the concentrations that led to 50% inhibition (IC50) for three of the studied thyme oils (data for essential oils from Zungoli and Morigerati are unavailable). Ascorbic acid was used as a standard antioxidant. In this study, the IC50 values of the studied oils were less than the value of the reference antioxidant ascorbic acid (IC50 values of 3.10 ± 1.13 μg/mL) [7]. The essential oil composition of the five T. vulgaris populations appeared similar, and the oils belonged to the same chemotype. Indeed, the five oils were characterized by high percentages of phenols and can be classified as oils belonging to the thymol chemotype. The variations between the main compounds of thyme essential oil can be explained by the biosynthetic relationship between the two phenols.
The metabolic pathway for the carvacrol and thymol formation begins with the autoxidation of γ-terpinene to p-cymene and the subsequent hydroxylation to thymol [8]. In the literature, it was reported that Thymus vulgaris has a chemical polymorphism with six different chemotypes that show spatial segregation in nature: phenolic chemotypes (thymol and carvacrol) and non-phenolic chemotypes (geraniol, α-terpineol, linalool and trans-thujan-4-ol/terpinen-4-ol) [9].
The different antimicrobial activity of these oils might be due to the little variation in their chemical profile. In the literature, it was reported that various chemical compounds have direct activity against many species of bacteria, such as terpenes and a variety of aliphatic hydrocarbons (alcohols, aldehydes and ketones). The lipophilic character of their hydrocarbon skeleton and the hydrophilic character of their functional groups are of main importance in the antimicrobial action of essential oils components, and the importance of the hydroxyl group of phenolic structures has been confirmed.
Moreover, the aldehyde group conjugated to a carbon-to-carbon double bond is a highly electronegative arrangement, which may explain their activity, suggesting a proportional increase of the antibacterial activity with electronegativity. The activity increased with the length of the carbon chain. Secondly, there is some evidence that minor components have a critical part to play in antibacterial activity, possibly by producing a synergistic effect between other components. This has been found for sage, some species of Thymus and oregano [10]. The appreciable total phenol contents of the five essential oils can also contribute to the antimicrobial activity. Ahmad and coworkers [3] reported that synergistic and additive interactions occur between the major and minor constituents present in the essential oil of Thymus vulgaris, and in this way, the antimicrobial efficacy of the essential oil could be enhanced.
Our data concerning total phenolic content are in line with previous research [11,12], which reports that the phenolic compounds are the main compounds in the thyme essential oil. The variation of the total phenolic content may be due to environmental conditions, such as soil composition and nitrogen content, which can modify the constituents of the plant [13,14].
The moderate antioxidant activity of the essential oil from the campus of the University of Salerno is probably due to the high amount of oxygenated compounds (phenolic compounds, 75.5%; oxygenated monoterpenes, 6.4%; oxygenated sesquiterpenes, 7.4%) and to the total phenolic content (112.3 mg GAE/g of sample). Our results are in agreement with previous studies, which showed that greater antioxidant potential of several Thymus species' essential oils could be related to the nature of the phenolic compounds and their hydrogen ability. Besides, such activity could be ascribable to the oxygenated compounds, such as carvacrol and thymol. Moreover, the activities of essential oils of Thymus species depend on several structural features of the molecules and are primarily attributed to the high reactivity of the hydroxyl group substituent [15]. Moreover, the essential oils that contain oxygenated monoterpenes and/or sesquiterpenes have been reported for their greater antioxidative properties [1].
Isolation of the Volatile Oils
One hundred grams of fresh aerial parts of each sample were ground in a Waring blender and then subjected to hydrodistillation for 3 h according to the standard procedure described in the European Pharmacopoeia [16]. The oils were solubilized in n-hexane, dried over anhydrous sodium sulfate and stored under N2 at +4 °C in the dark until tested and analyzed. The calculated essential oil yield was expressed in % (v/w), based on the weight of the fresh plant material. All extractions were done in triplicate.
GC-FID Analysis
The gas chromatography-flame ionization detector (GC-FID) analysis was carried out on a Perkin-Elmer Sigma-115 gas chromatograph equipped with a flame ionization detector (FID) and a data handling processor. The separation was achieved using an apolar HP-5 MS fused-silica capillary column (30 m × 0.25 mm i.d., 0.25-μm film thickness); column temperature: 40 °C, with 5 min initial hold, then to 270 °C at 2 °C/min and, finally, at 270 °C for 20 min; injection mode: splitless (1 μL of a 1:1000 n-pentane solution). Injector and detector temperatures were 250 °C and 290 °C, respectively. Analysis was also run by using a fused silica HP Innowax polyethylene glycol capillary column (50 m × 0.20 mm i.d., 0.25-μm film thickness). In both cases, helium was used as the carrier gas (1.0 mL/min). The relative essential oil contents of the components were obtained by peak area normalization, without calculating response factors.
GC/MS Analysis
The gas chromatography-mass spectroscopy (GC/MS) analysis was performed with an Agilent 6850 Ser. II apparatus, fitted with a fused silica DB-5 capillary column (30 m × 0.25 mm i.d., 0.33-μm film thickness), coupled to an Agilent Mass Selective Detector MSD 5973; ionization energy voltage: 70 eV; electron multiplier voltage energy: 2000 V. Mass spectra were scanned in the range 40-500 amu, with a scan time of 5 scans/s. The gas chromatographic conditions were as reported in the previous paragraph; transfer line temperature: 295 °C.
Identification of the Essential Oil Components
The identification of the essential oil constituents was based on the comparison of their Kovats retention indices (RIs), determined relative to the tR values of n-alkanes (C10-C35) on both capillary columns with those in literature [17][18][19][20] and their mass spectra with those of authentic compounds available in our laboratories or those listed in the NIST 02 and Wiley 275 mass spectral libraries [21]. For some compounds, the identification was confirmed by coinjection with an authentic sample (Table 1).
Determination of Minimum Inhibitory Concentration and Minimum Bactericidal Concentration
The antibacterial activity was evaluated by determining the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC) using the broth dilution method [22]. . The strains were maintained on Tryptone Soya agar (Oxoid, Milan, Italy); for the antimicrobial tests, Tryptone Soya broth (Oxoid, Milan, Italy) was used. In order to facilitate the dispersion of the oil in the aqueous nutrient medium, it was diluted with Tween 20, at a ratio of 10%. Each strain was tested with sample that was serially diluted in broth to obtain concentrations ranging from 100 μg/mL down to 0.8 μg/mL. The sample was previously sterilized with a Millipore filter of 0.20 μm. The samples were stirred, inoculated with 50 μL of physiological solution containing 5 × 10 6 microbial cells, and incubated for 24 h at 37 °C. The MIC value was determined as the lowest concentration of the sample that did not permit any visible growth of the tested microorganism after incubation. The control containing only Tween 20 was not toxic to the microorganisms. As positive controls, cultures containing only sterile physiological solution Tris buffer were used. MBC was determined by subculture of the tubes with inhibition in 5 mL of sterile nutrient broth. After incubation at 37 °C, the tubes were observed. When no growth was observed, the sample denoted a bactericidal action. The oil sample was tested in triplicate. Chloramphenicol was used as the standard antibacterial agent.
Determination of Total Phenolics
The total phenolic content was determined following the microscale protocol for Folin-Ciocalteu colorimetry, an alternative protocol for small sample volumes [23]. Each oil sample (20 μL, dissolved in ethanol, to obtain a final concentration of 50 mg/5 mL), a gallic acid calibration standard (50 mg/mL; 100 mg/mL; 250 mg/mL; 500 mg/mL) or blank (distilled water) was taken in a test cuvette. The absorbance was determined at room temperature at k = 765 nm using a Cary UV/Vis spectrophotometer (Varian Cary 50 MPR). The quantification was based on a standard curve generated with gallic acid; the results were expressed as mg gallic acid equivalents (GAE)/g of essential oil. A methanolic solution of gallic acid was tested in parallel as a reference compound.
Antioxidant Activity
The antiradical activity of the extracts under investigation was determined using the stable 1,1-diphenyl-2-picrylhydrazyl radical (DPPH), according to the method reported by Brand-Williams and coworkers [24] with some modifications to adapt the procedure using 96-well microplates [25]. In its radical form, DPPH has an absorption band at 517 nm, which disappears upon reduction by an antiradical compound. Briefly, an aliquot (7 μL) of the MeOH solution containing different amounts of the oils was added to 280 μL of DPPH solution (7.6 × 10 −5 M), prepared daily, kept in the dark when not used. An equal volume (7 μL) of the vehicle alone was added to control tubes. Absorbances at 517 nm were measured on a Multiskan Spectrum Microplate Spectrophotometer (Thermo Fischer Scientific, Vantaa, Finland) 0, 10, 20, 30, 40, 50 and 60 min after starting the reaction. For preparation of the standard curve, different concentrations of DPPH methanol solutions (5-40 μg/mL) were used. Moreover, the solution of ascorbic acid was used for a calibration curve of DPPH reduction and as a chemical reference in comparison to the antioxidant capacities of the oils. Ascorbic acid was obtained from Fluka (Buchs, Switzerland). Ascorbic acid is an effective antioxidant [26]. Ascorbic acid was solved in methanol to have the following final concentrations (5 μg/mL, 2.5 μg/mL, 1.25 μg/mL, 0.625 μg/mL, 0.3125 μg/mL). The DPPH concentration (μg/mL) in the reaction medium was calculated from the following calibration curve, determined by linear regression (r 2 : 0.9974): Absorbance (λ517) = 0.00186 + 0.0187 × [DPPH] The IC50 value was defined as the concentration of sample that reduced the initial DPPH concentration by 50%, as compared to the negative control.
Statistical Analysis
Data from the determination of total phenolics were analyzed in GraphPad Prism 6.0 for correlation and significance (one-way ANOVA and Dunnett's multiple comparison post-test). Data on antioxidant activity are expressed as the mean ± SD of five experiments.
Conclusions
The results reported here may help to shed light on the apparently complex chemotaxonomy of the genus Thymus. All five samples belong to the thymol chemotype, showing a homogeneity of prevalent monoterpenes in the oils. This finding seems to be related to the circum-Mediterranean distribution of this chemotype, which is the only one with the characteristic flavor and aroma of true thyme. Moreover, this study focused on the phenolic fraction and the effectiveness of T. vulgaris essential oils as an antimicrobial and antioxidant. Therefore, these oils could be used in many fields as natural preservatives of food and as nutraceuticals.
Conflicts of Interest
The authors declare no conflict of interest. | v3-fos |
2018-04-03T02:43:50.329Z | {
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} | 0 | [] | 2015-03-11T00:00:00.000Z | 16979520 | {
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} | s2 | Preventive Effects of a Fermented Dairy Product against Alzheimer’s Disease and Identification of a Novel Oleamide with Enhanced Microglial Phagocytosis and Anti-Inflammatory Activity
Despite the ever-increasing number of patients with dementia worldwide, fundamental therapeutic approaches to this condition have not been established. Epidemiological studies suggest that intake of fermented dairy products prevents cognitive decline in the elderly. However, the active compounds responsible for the effect remain to be elucidated. The present study aims to elucidate the preventive effects of dairy products on Alzheimer’s disease and to identify the responsible component. Here, in a mouse model of Alzheimer’s disease (5xFAD), intake of a dairy product fermented with Penicillium candidum had preventive effects on the disease by reducing the accumulation of amyloid β (Aβ) and hippocampal inflammation (TNF-α and MIP-1α production), and enhancing hippocampal neurotrophic factors (BDNF and GDNF). A search for preventive substances in the fermented dairy product identified oleamide as a novel dual-active component that enhanced microglial Aβ phagocytosis and anti-inflammatory activity towards LPS stimulation in vitro and in vivo. During the fermentation, oleamide was synthesized from oleic acid, which is an abundant component of general dairy products owing to lipase enzymatic amidation. The present study has demonstrated the preventive effect of dairy products on Alzheimer’s disease, which was previously reported only epidemiologically. Moreover, oleamide has been identified as an active component of dairy products that is considered to reduce Aβ accumulation via enhanced microglial phagocytosis, and to suppress microglial inflammation after Aβ deposition. Because fermented dairy products such as camembert cheese are easy to ingest safely as a daily meal, their consumption might represent a preventive strategy for dementia.
Introduction
With aged populations growing rapidly around the world, cognitive decline and dementia are becoming an increasing burden not only on patients and their families, but also on national healthcare systems. Alzheimer's disease is a progressive irreversible brain disorder, symptoms of which include memory loss, confusion, impaired judgment and loss of language skills, and the number of affected individuals is rising sharply. Because cognitive function declines in accordance with an accumulation of Amyloid β (Aβ) in the brain, Aβ deposition is a crucial part of the pathology [1].
Recent pathological and immunological studies revealed that chronic inflammation following Aβ deposition in the brain is closely associated with Alzheimer's disease pathology [2][3][4]. Microglia play unique immunological roles including the removal of apoptotic cells and waste such as Aβ through phagocytosis, as well as host defense against virus infection in the central nervous system [5][6]. In the Alzheimer's brain, however, microglia infiltrate the region around the Aβ plaques, become excessively activated, and produce large amounts of inflammatory cytokines and chemokines, such as tumor necrosis factor-α (TNF-α), macrophage inflammatory protein-1α (MIP-1α), reactive oxygen (ROS) and nitric oxide (NO) [7][8][9]. These products, which are chronically generated by microglia, after Aβ deposition are toxic to neurons and cause neuronal cell death [7,[10][11].
Numerous reports suggest that controlling microglial activities is effective in the prevention and cure of Alzheimer's disease and cognitive decline [12][13][14]. Epidemiological studies suggest that prolonged use of nonsteroidal anti-inflammatory drugs (NSAIDs), including the common medication ibuprofen, significantly reduce the risk for Alzheimer's disease [15][16]. Consistent with epidemiological research, chronic ibuprofen treatment was found to significantly suppress microglial inflammation and the development of Aβ pathology in a transgenic model mouse of Alzheimer's disease [17]. However, side effects in the gastrointestinal tract, liver and kidney caused by inhibiting cyclooxygenase I preclude the widespread use of NSAIDs in preventing the disease. Therefore, alternative treatments to Alzheimer's disease and cognitive decline need to be explored and, as a result, preventive approaches based on diet, exercise and learning are attracting increasing attention.
Several recent epidemiological studies suggest that consumption of fermented dairy products may reduce the risk of cognitive decline in the elderly and prevent dementia including Alzheimer's disease [18][19][20]. However, the underlying mechanism and the active compounds remain to be elucidated.
In the present study, the preventive effects of fermented dairy products were evaluated using a transgenic mouse model of Alzheimer's disease, with a particular focus on microglial activities. In addition, after animal evaluation, compounds in dairy products were screened to identify components capable of enhancing microglial Aβ phagocytosis and anti-inflammatory activity.
B6SJL-Tg mice were maintained in the experimental facility at the University of Tokyo, and the experiments were approved by the Animal Care and Use Committee of the University of Tokyo and conducted in strict accordance with their guidelines. Pregnant C57BL/6J mice, 8-week-old C57BL/6J mice, and 6-week-old CD-1 mice were maintained in Kirin Company Ltd, and the experiments were approved by the Animal Experiment Committee of Kirin Company Ltd and conducted in strict accordance with their guidelines. All efforts were made to minimize suffering.
Preparation of Penicillium candidum-fermented dairy product sample Penicillium (P.) candidum-fermented dairy products (camembert cheese) were prepared according to a general manufacture procedure. In brief, sterilized milk was fermented with Lactococcus lactis to reduce the pH, and treated with calf rennet. The aggregated curds were fermented by P. candidum. The fermented products were then freeze-dried and delipidated with n-hexane (Wako, Tokyo, Japan) to remove triglyceride. The nutrient composition of the extracted samples was calculated by Japan Food Research Laboratories (Tokyo, Japan).
AIN-93G and AIN-93M diets (Oriental Yeast) containing 2% (w/w) fermented sample were prepared by a conventional procedure, and each diet with or without sample was adjusted to contain the same calories according to the nutrient composition of the extracted sample.
Preparation of lipid extract
The surface and inside of dairy product fermented with or without P. candidum were crushed in a mortar after lyophilization, and extracted with n-hexane, chloroform and then with methanol. For gas chromatography mass spectrometer (GC/MS) analysis, the lyophilized samples were suspended in methanol containing 1N KOH, and saponified at 80°C for 2 hours. The lipid fraction was obtained as previously described [22] with some modifications. Vehicle (chloroform: water = 10:9) was added to the fraction (final ratio: approximately 1:1:0.9, v/v/v; chloroform:methanol:water), which was then vortexed for 20 min and centrifuged at 3000rpm for 10 min. The lower phase was dried under a stream of N 2 at 40°C, dissolved in acetone, and filtered through a Polytetrafluoroethylene membrane disc (Millipore, MA, USA).
GC/MS conditions
The analysis for primary fatty acid amides using GC/MS has been previously described [23]. An Agilent Technologies Network GC/MS system (7890 GC with 5975 mass detector) was used for the analysis with an HP-5MS capillary column (0.25 mm internal diameter, 0.25 μm film thickness, 30 m long, Agilent Technologies). The temperature was initially held at 80°C for 1 min, raised up to 280°C at a rate of 30°C per min, and then held at 280°C for 23 min. The total run time was 30.7 min. Helium was used as a carrier gas with a flow of 1.2 ml/min. Ionization was obtained by electron impact (electron energy, 70 eV). The temperature of the injection port and the transfer line was 250°C. Splitless injection was used with a volume of 1 μl.
In vivo anti-inflammatory assay
Six-week-old CD-1 male mice were orally given 50 mg/kg of oleamide dissolved in vehicle including 5% ethanol, 5% cremophor and 90% saline, once a day for 3 days. We confirmed that 10 ml/kg oral administration of vehicle did not induce inflammation in the brain (data not shown; n = 7 mice in each group). Thirty minutes after the last administration, the mice were deeply anesthetized with sodium pentobarbital (Kyoritsu Seiyaku, Tokyo, Japan) and injected intracerebroventricularly with 0.25 mg/kg of LPS (L7895, Sigma). LPS or distilled water (for sham-operated controls) was injected by hand into the cerebral ventricle in a volume of 3 μL as described previously [24][25][26][27]. Briefly, a micro-syringe with a 27-gauge stainless steel needle, 2 mm in length, was used for micro injection. The needle was inserted unilaterally 1 mm to the right of the midline point equidistant from each eye, at an equal distance between the eyes and the ears and perpendicular to the plane of the skull (anteroposterior, − 0.22 mm from the bregma; lateral, 1 mm from the bregma). LPS was delivered gradually within 30 s. The needle was taken out after waiting 30 s. All mice exhibited normal behavior after they recovered from the anesthetic. Three hours later, the mice were euthanized, the cerebral cortex and hippocampus in one hemisphere were homogenated in RIPA buffer, and the concentration of TNF-α (eBioscience) and MIP-1α (R&D systems) in the supernatants was quantified by ELISA. The hippocampus in the other hemisphere was dissociated with papaine, stained for microglia with the above-mentioned antibodies, and analyzed by flow cytometry as previously described.
Phagocytosis of 6-carboxyfluorescein-labeled Aβ 1-42 by microglia Microglial phagocytosis of 6-carboxyfluorescein-labeled Aβ 1-42 (Aβ-FAM, AnaSpec, CA, USA) was evaluated by a plate-based assay. Microglial cells isolated from newborn mice were plated at a density of 50,000 cells per well in a PDL-coated 96-well plate and incubated with 500 nM Aβ-FAM for 24 hours after either oleic acid (Sigma-Aldrich) or oleamide (Sigma-Aldrich) pretreatment for 12 hours. After the medium was removed, extracellular Aβ-FAM was quenched with 0.2% trypan blue, pH 4.4. Cellular fluorescence was measured at 485 nm excitation/535 nm emission using a plate reader (Molecular Device, CA, USA).
In vivo phagocytosis assay
Eight-week-old C57BL/6J male mice were orally given 0, 10 or 50mg/kg of oleamide dissolved in vehicle including 5% ethanol (Wako), 5% cremophor (Sigma-Aldrich) and 90% saline (Otsuka) once a day for 3 days (n = 5 mice in wach group). Three hours after the last administration, microglia in the brain were isolated by MACS, and the phagocytotic activity of the microglia was measured using Aβ-FAM as described above. Populations of CD206-and CD11b-positive cells and the expression of cell markers were analyzed using a flow cytometer after staining with 2 μg/ml of anti-CD36-APC antibody (BioLegend), and 2 μg/ml of anti-CD11b-APC-Cy7 antibody (BD Pharmingen).
Statistical analysis
All values were expressed as the mean ± SEM. Data from the production assays for cytokines, chemokines, neurotrophic factors and synaptophysin, and from in vitro antagonist assays were analyzed by two-way ANOVA, followed by the Tukey-Kramer test. Data from the in vitro assays were analyzed by one-way ANOVA, followed by Dunnett's test or Student's t test. All statistical analyses were performed using the Ekuseru-Toukei 2012 software program (Social Survey Research Information, Tokyo, Japan).
Intake of the fermented dairy product substantially reduces Aβ burden and inflammation
The amount of soluble Aβ 1-42 in the brain of 5xFAD transgenic mice was significantly decreased by 17% in the group fed with the dairy sample (Fig. 1A). The insoluble Aβ 1-42 in cerebral cortex detected immunohistochemistry was decreased by 21% in the sample group but the reduction was not significant (Fig. 1B, C, D). Pathological staining examination by immunohistochemistry revealed that the Aβ1-42 burden was reduced by 21% in the cerebral cortex but 12.5% in the hippocampus. Iba-1-positive microglia had massively infiltrated and engulfed Aβ 1-42 (Fig. 1E), and produced MIP-1α (Fig. 1F). The enhanced production of MIP-1α in the transgenic mice was significantly suppressed by administration of the dairy product (Fig. 1H).
Intake of the fermented dairy product increases hippocampal neurotrophic factors and synaptophysin
The production of BDNF and GDNF in the hippocampus was significantly lower in the transgenic mice than in wild-type mice. In contrast, the production of these factors was significantly higher in the mice fed with dairy product than in the control mice ( Fig. 2A, B, respectively). The expression of synaptophysin, a neuronal synapse marker was correlated with the productions of neurotrophic factors. (Fig. 2D). There were no significant differences in the amount of NGF (Fig. 2C) and synaptophysin.
Anti-inflammatory activity of extracts from the surface of the dairy product
The surface and inside part of the dairy product fermented with or without P. candidum were separately treated with methanol after triglyceride removal by n-hexane and chloroform. The weight of the methanol extract, which mainly contains fatty acids, was increased only on the surface of fermented dairy products (data not shown). The extract from the surface of the fermented dairy product suppressed the production of TNF-α by microglia in a concentration-dependent manner, whereas the extracts from the inside of the product and those without fermentation did not (Fig. 3A).
P. candidum fermentation generates oleamide
Gas chromatography-mass spectrometry showed a peak identical to oleamide in the extract from the surface of the dairy product fermented with P. candidum (Fig. 3B). The mass spectrum of this peak (Fig. 3C) corresponded to the reference standard of oleamide (Fig. 3D). Oleamide (Fig. 3E) is fatty acid oleic acid (Fig. 3F), and was not detected in dairy products that had not been fermented with P. camdidum.
Oleamide has microglial anti-inflammatory activity in vitro
Oleamide suppressed microglial TNF-α production in a concentration-dependent fashion, and enhanced microglial anti-inflammatory activity more strongly than oleic acid (Fig. 4A). The ratios of MIP-1α-positive microglia to CD11b-positive microglia and TNF-α-positive microglia to CD11b-positive microglia were significantly lower after oleamide treatment (Fig. 4B, C, respectively). Microglia treated with oleamide also showed a lower expression of the inflammatory cell markers CD68 and CD80 in CD11b-positive microglia (Fig. 4D, E, respectively). In addition, oleamide significantly suppressed TNF-α production in microglia derived from the Aβ-deposited brain of Alzheimer's disease model mice (Fig. 4F).
Oleamide enhances microglial anti-inflammatory activity in vivo
Intracerebroventricular injection of LPS significantly increased the production of TNF-α and MIP-1α, but there was no significant difference between the sham and vehicle-treated groups and the group given 50 mg/kg of oleamide and LPS in either the hippocampus (Fig. 5A, C, respectively) or the cerebral cortex (Fig. 5B, D, respectively). Flow cytometric analysis revealed that the production of TNF-α and MIP-1α in CD11b-positive microglia was significantly lower in the group administered oleamide (Fig. 5E, F, respectively). In addition, the expression of I-A/I-E and CD68 was significantly reduced (Fig. 5G, H, respectively) and that of PDL-2 was significantly increased (Fig. 5I) in the group of mice given oleamide.
Oleamide enhances microglial phagocytosis in vitro and in vivo
Oleamide at concentrations of 100-1000 nM was found to enhance microglial phagocytosis of Aβ 1-42 in a concentration-dependent manner in vitro, whereas oleic acid did not show activity at all (Fig. 6A). In addition, oral administration of 50 mg/kg of oleamide significantly enhanced the brain microglial phagocytosis of Aβ (Fig. 6B) and significantly enhanced the expression of CD36 in CD11b-positive microglia in the hippocampus (Fig. 6C).
Discussion
In the present study, the preventive effects of ingesting a fermented dairy product on Alzheimer's disease, which have previously been reported only epidemiologically, were investigated in a mouse model of Alzheimer's disease. In mice fed with the fermented dairy product, the deposition of Aβ in the brain was significantly reduced. Microglia play a crucial role in maintaining the brain environment by removing waste products such as amyloid, aged synapses and apoptotic cells via phagocytosis [28][29][30][31]. The results of the present study suggest that ingredients in the fermented dairy product contribute to the activation of microglial phagocytosis, resulting in a reduction of Aβ in the brain. In Alzheimer's disease, chronic inflammation in the brain exacerbates the pathological condition and cognitive decline because inflammation is toxic to neurons and suppresses the production of neurotrophic factors such as BDNF, GDNF and NGF [32][33][34][35]. In the present study, the inflammation induced by Aβ deposition in the transgenic mice was suppressed when the mice were fed with the fermented dairy product. In addition, the production of chemokine (MIP-1α) was remarkably increased in the hippocampus of the transgenic mice and significantly reduced by ingestion of the fermented dairy product. It has been reported that MIP-1α and TNF-α produced by microglia exacerbate the Alzheimer's pathology [36][37]. The production of both BDNF and GDNF in the hippocampus was also significantly reduced in the model mouse, whereas their production in mice fed with the fermented dairy product was significantly recovered to the levels observed in wild-type mice. It has been suggested that suppression of inflammation contributes to the production of neurotrophic factors, the survival of neuronal synapses and the retention of cognitive function. In the brain, immunological phenomena are mainly regulated by microglia; as a result, it seems likely that some components of the fermented dairy product may regulate the microglial inflammatory response, leading to a suppression of the pathology.
In the transgenic mouse model of Alzheimer's disease, intake of the fermented dairy product showed preventive effects on development of the disease. Phagocytosis of Aβ by microglia may be essential for clearance of Aβ in Alzheimer's disease; however, excessively activated microglia also produce several neurotoxic products, such as ROS, NO, cytokines and chemokines, leading to neuronal death [7][8][9]. Therefore, our results suggest that some ingredients in the fermented dairy product may enhance microglial anti-inflammatory activity and phagocytosis.
Our findings revealed that a certain dairy substance generated during fermentation with P. candidum is crucial for microglial regulation because the fatty acid extract had high anti-inflammatory effects. In general, linoleic acid and linolenic acid in dairy products are known to have an anti-inflammatory effect. In the present study, linoleic acid and linolenic acid were also identified, but oleamide as a novel ingredient with anti-inflammatory properties was identified from the dairy product fermented with P. candidum. As compared with linoleic acid and linolenic acid, oleamide has much higher anti-inflammatory activity. In addition, oleamide was identified as a potent dual-active component capable of enhancing both phagocytosis and antiinflammatory activity. Oleamide is also known as an endogenous substance that binds to cannabinoid (CB) receptors as an agonist [38][39]. However, no previous studies have reported that dairy products contain oleamide. Oleamide is the amide of oleic acid, and is synthesized from oleic acid and ammonia by enzymatic amidation [40]. Oleic acid is abundant in dairy products, and ammonia is generated during the fermentation and maturation of cheese. It is also reported that oleamide is converted from oleic acid via the amidation activity of lipase in a bacteria [41]. These reports suggest that oleamide is generated in the dairy product from oleic acid during fermentation with P. candidum. In support of this, in the present study oleamide was detected mainly on the surface part of camembert cheese, where P. candidum grows well, but was not detected in the dairy product without P. candidum fermentation.
As mentioned above, oleamide has high anti-inflammatory activity. A previous study using an LPS-stimulated murine microglial cell line (BV-2) showed that oleamide suppressed the production of NO and PGE2 [42]. Another study revealed that oleamide suppressed microglial C, respectively). D and E, Expression of CD68 and CD80 in CD11b-positive cells (D and E, respectively). F, Isolated microglia from the brain of 6-month-old 5xFAD transgenic mice were stimulated with 5 ng/ml LPS and 0.5 ng/ml IFN-γ after pretreatment with oleamide, and TNF-α in the supernatant was measured by ELISA. Error bars represent the means ± SEM of 3 wells per group. *p < 0.05 and **p < 0.01. doi:10.1371/journal.pone.0118512.g004 Fig 5. Effect of in vivo treatment with oleamide on microglial anti-inflammatory activity. CD-1 mice (n = 7/group) were orally given 50 mg/kg of oleamide once a day for 3 days and then injected intracerebroventricularly with either saline or 0.25 mg/kg of LPS. A and B, Quantification of TNF-α in the cerebral cortex and hippocampus, respectively. C and D, Quantification of MIP-1α in the cerebral cortex and hippocampus, respectively. E and F, The ratio (%) of TNF-α-positive or MIP-1α-positive cells to CD11b-NO production via CB2 receptors, which are mainly expressed on the surface of immune cells (monocytes, macrophages, and B cells). In the present study, oleamide suppressed the productions of MIP-1α and TNF-α, which were predominantly produced in the brain of the Alzheimer's model mice. Oleamide was also found to have an in vivo anti-inflammatory effect in the brain of the Alzheimer's model mouse. In addition, orally administered oleamide was found to have a potent anti-inflammatory activity on microglia in the LPS-stimulated brain by suppressing the inflammatory cell markers I-A/I-E and CD68, up-regulating the anti-inflammatory cell marker PDL-2, and reducing the inflammatory factors MIP-1α and TNF-α. Therefore, the regulation of microglial activity with oleamide might contribute to the effective prevention of Alzheimer's disease. Effect of treatment with oleamide on microglial phagocytosis. A, Aβ phagocytotic activity was measured in vitro using isolated microglia pretreated with either oleic acid or oleamide. The value is the ratio of fluorescence to the vehicle. Error bars represent the means ± SEM (n = the number of wells when we examined phagocytosis of Aβ1-42) B and C, Effect of treatment with oleamide in vivo on microglial phagocytotic activity. After the oral administration of 0, 10, or 50 mg/kg of oleamide once a day for 3 days and isolation of microglia from the brain, phagocytotic activity and the expression of CD36 were measured. B, Cellular Aβ-FAM was measured after isolated microglia were treated with 500 nM Aβ-FAM for 5 hours and quenched extracellular Aβ-FAM. C, Expression of CD36 in CD11b single-positive cells. Error bars represent the means ± SEM of 5 mice per group. *p < 0.05 and **p < 0.01. On the other hand, oleamide activates PPAR-γ receptors in cells [43], and its agonist enhances the phagocytotic activity of monocytes [44]. PPAR-γ has recently been receiving increasing attention as a target for Alzheimer's disease therapy [45][46][47], so activation of PPAR-γ might be involved in the enhancement of microglial phagocytosis by oleamide. Further studies will elucidate the mechanism of oleamide activate microglial phagocytosis. Oleic acid has no effects on microglia phagocytosis; therefore, amidation of oleic acid must be crucial for this activity. In addition, orally administered oleamide enhanced microglial phagocytosis in the brain and increased the expression of CD36, which is important for uptake of Aβ [46].
In summary, it has been revealed that oleamide in fermented dairy product enhances microglial phagocytosis and suppresses inflammation. Oleamide might prevent Alzheimer's disease by regulating microglia to a phenotype preferable for maintaining the brain environment. Although camembert alone might not prevent dementia, a well-balanced diet that combines camembert with agreeable foods like red wine or fish is expected to reduce the risk of dementia. Red wine and fish have been proven to contain resveratrol and omega-3 fatty acids respectively, which are beneficial for preventing Alzheimer's disease. Recent reports suggesting that a Mediterranean diet is associated with lower risk of dementia are supportive of a food culture that combines dairy products with wines and fish dishes [48][49]. Fermented dairy products such as camembert cheese are easy and safe to consume frequently, and might helpful for dementia prevention. | v3-fos |
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} | s2 | Recent trends and perspectives of molecular markers against fungal diseases in wheat
Wheat accounts for 19% of the total production of major cereal crops in the world. In view of ever increasing population and demand for global food production, there is an imperative need of 40–60% increase in wheat production to meet the requirement of developing world in coming 40 years. However, both biotic and abiotic stresses are major hurdles for attaining the goal. Among the most important diseases in wheat, fungal diseases pose serious threat for widening the gap between actual and attainable yield. Fungal disease management, mainly, depends on the pathogen detection, genetic and pathological variability in population, development of resistant cultivars and deployment of effective resistant genes in different epidemiological regions. Wheat protection and breeding of resistant cultivars using conventional methods are time-consuming, intricate and slow processes. Molecular markers offer an excellent alternative in development of improved disease resistant cultivars that would lead to increase in crop yield. They are employed for tagging the important disease resistance genes and provide valuable assistance in increasing selection efficiency for valuable traits via marker assisted selection (MAS). Plant breeding strategies with known molecular markers for resistance and functional genomics enable a breeder for developing resistant cultivars of wheat against different fungal diseases.
Introduction
Wheat is a major staple food for mankind in many parts of the world with 714 million tons produced during 2013 (http://www.agri-outlook.org). It is cultivated on 15.4% of the arable land in the world in almost all countries, except the humid and high-temperature areas in the tropics and high-latitude environments. Accounting for a fifth of humanity's food, wheat is the second only to rice which provides 21% of the food calories and 20% of the protein for more than 4.5 billion people in 94 developing countries (Braun et al., 2010). It contributes 30% of the world's edible dry matter and 60% of the daily calorie intake in several developing countries (FAOSTAT, 2015). Wheat is produced for a wide range of end-users and it is a critical staple food for a large proportion of the world's poor farmers and consumers. Due to consistent increase in the world population, there is a need of 60% increase in wheat production to meet the requirement of developing world till 2050 Rosegrant and Agcaoili, 2010).
Increasing wheat yield potential in the developing world is a primary aim for food security concern (Duveiller et al., 2007). Today, the most challenging task for wheat breeders is to increase grain yield as well as to improve the grain quality of crop for end products (Goutam et al., 2013). These two aspects must be cope up with the strategies employed for enhancing the tolerance against biotic (Keller et al., 2008;Todorovska et al., 2009) and abiotic stresses (Kamal et al., 2010) in addition to the enhanced capability to adapt to various climate changes (Olmstead and Rhode, 2011). Amongst the most important diseases in wheat (derived from fungi, virus, and bacteria), rust diseases (leaf, stem, and stripe) caused by fungus, powdery mildew and Karnal bunt have been reported to produce devastating consequences on wheat quality and production (Keller et al., 2008;Goyal and Prasad, 2010). Cereal rust fungi are highly variable for virulence and molecular polymorphism. Leaf rust, caused by Puccinia triticina is the most common rust of wheat on a worldwide basis (Kolmer, 2013). Leaf rust has potential to cause losses of up to 50% and because of its more frequent and widespread occurrence, leaf rust probably results in greater total annual losses worldwide than stem and stripe rusts . However, management of fungal diseases using conventional plant protection and breeding strategies is quite easy and effective tool, but, it results into different types of environmental pollutions as it involves the use of various ecohazardous chemicals. Identification and selection of resistant genes through breeding practices is also time-consuming and slow process. Moreover, disease management by host resistance, employment of stable diseases resistance and development of homozygous and resistant cultivars are also time consuming methods (Sharma, 2003;Keller et al., 2008).
To overcome these problems, molecular marker technology is the novel genetic tool for developing high yielding disease resistant cultivars (Landjeva et al., 2007;Varshney et al., 2007). Molecular markers could tag the presence of important resistance genes and allow breeders to identify the resistance genes rapidly and accurately. They also provide significant assistance for increasing selection efficiency through indirect selection for valuable traits via marker assisted selection (MAS). Thus, MAS offers a potential tool for assisting conventional plant breeding approaches to select phenotypic traits for screening disease resistant crop plants (Todorovska et al., 2009). Therefore, existing plant breeding techniques along with available molecular markers (Gupta et al., 2010) and functional genomic tools (Gupta et al., 2008) can help a breeder for developing superior wheat cultivars resistant against fungal diseases in order to minimize yield losses (Goyal and Prasad, 2010). Different types of markers such as random DNA markers, gene targeted markers (Gupta et al., 2010) and functional markers have been reported for facilitating identification of genes responsible for individual traits and for improving potential of using MAS in wheat breeding programs (Gupta et al., 2008). DNA-based molecular markers like RFLP (Hartl et al., 1993;Ma et al., 1993Ma et al., , 1994Autrique et al., 1995;Paull et al., 1995;Nelson et al., 1997), RAPD (Penner et al., 1995;Procunier et al., 1995;Demeke et al., 1996;Qi et al., 1996;Dweikat et al., 1997;Dubcovsky et al., 1998;Shi et al., 1998), STS (Schachermayr et al., 1994(Schachermayr et al., , 1997Key concepts (1) DNA marker It is a gene or DNA sequence with a known location on a chromosome that can be used to identify individuals or species. A genetic marker may be a short DNA sequence, such as a sequence surrounding a single base-pair change (single nucleotide polymorphism, SNP), or a long one, like minisatellites.
(2) Fungal disease An abnormal growth and/or dysfunction of a plant caused by fungi, which disturbs the normal life process of the plant.
(3) Marker assisted selection (MAS) MAS is a process whereby a marker (morphological, biochemical or one based on DNA/RNA variation) is used for indirect selection of a genetic determinant or determinants of a trait of interest (e.g., productivity, disease resistance, abiotic stress tolerance, and quality).
(4) Wheat rust Wheat rust is a destructive disease of wheat caused by fungus genus Puccinia, especially a destructive stem rust characterized by reddish blisters that turn black at the end of the growing season. Feuillet et al., 1995;Dedryver et al., 1996;Naik et al., 1998;Prins et al., 2001), SSR (Peng et al., 2000;Raupp et al., 2001;Wang et al., 2002), CAPS (Helguera et al., 2000(Helguera et al., , 2003, AFLP (Hartl et al., 1998), and SCAR (Gold et al., 1999;Liu et al., 1999) have been commonly used for the molecular characterization of plant pathogen and mapping of disease resistance genes in wheat. The development of plant gene transfer systems enable us for the introgression of foreign genes into plant genomes for novel disease control strategies, thus providing a mechanism for broadening the genetic resources available to plant breeders (Zhu et al., 2012).
Fungal Diseases of Wheat
Worldwide, wheat diseases caused by fungal pathogens are more threatening for crop yields and grain quality than those caused by bacteria and viruses. Since, the fungal pathogens are very adaptable and can rapidly evolve into new strains that can infect earlier disease resistant plants. Infection of wheat fungal diseases are influenced by various factors viz., nature of pathogen, susceptibility of host, diversity of virulence, density of inoculums and temperature (Rajaram and Van Ginkel, 1996;McIntosh et al., 1998). The most important fungal diseases in wheat include different types of rust, powdery mildew and Karnal bunt.
Wheat Rust
Wheat rust pathogens belong to genus Puccinia, family Pucciniaceae, order Uredinales and class Basidiomycetes. The rust diseases of wheat such as leaf rust, stem rust, and stripe rust have historically been among the major biotic constraints in the world (Saari and Prescott, 1985;Todorovska et al., 2009). The rusts of wheat is caused by fungal pathogens that can be disseminated thousands of kilometers by wind and are capable of causing considerable economic loss throughout the world (Kolmer, 2005;Goyal and Prasad, 2010). The importance of genetic resistance for the control of rust diseases was demonstrated by Biffen (1905). A prerequisite for developing cultivars with long term rust resistance is the availability of diverse resistance genes.
Leaf Rust
Leaf rust, also known as brown rust, is caused by fungus P. triticina Rob. Ex Desm. f. sp. tritici Eriks (syn. P. recondita). It is a wheat disease of major historical and economic importance. Leaf rust is the most prevalent amongst all the wheat rust diseases occurring around nearly in all wheat grown areas (Kolmer, 2005;Huerta-Espino et al., 2011;Vanzetti et al., 2011). Therefore, it is considered as a widespread and commonly occurring rust disease of wheat. The disease has caused serious epidemics in wheat growing regions of USA (Appel et al., 2009), North Western Mexico (Dubin and Torres, 1981;Singh, 1991;Singh et al., 2004), South America (German et al., 2004), Northern Africa (Abdel-Hak et al., 1980;Deghais et al., 1999), Russia (Volkova et al., 2009), India (Joshi et al., 1975;Nagarajan and Joshi, 1978), Pakistan (Hassan et al., 1973;Hussain et al., 1980), Australia (Watson and Luig, 1961;Keed and White, 1971;Rees and Platz, 1975;Murray and Brennan, 2009), South Africa (Terefe et al., 2009) and other parts of the world. Leaf rust is generally localized on the leaves, but occasionally affects the glumes and awns. Symptoms include circular or oval, orange pustules (urediniospores) on the upper surface of infected leaves. Later on, these pustules become darker due to the formation of black telliospores (Roberson and Luttrell, 1987). The loss in yield depends on several factors such as time of initial infection, crop development stages and relative resistance or susceptibility of the wheat cultivars. Higher yield losses materialized if the initial infection occurs early in the growing season before tillering. However, infection occurred after heading when grain filling is in progress, will cause lesser crop loss (Agrios, 1997). Wheat yield losses are caused due reduction in number of kernels per spike, and kernel weight. Depending on the severity and duration of infection, the losses can vary up to 50% in susceptible wheat cultivars (Knott, 1989;McIntosh et al., 1995).
Cloning of resistance genes is an important approach for providing molecular insights and increasing resistance durability against rust resistance (Ellis et al., 2014;Jonathan et al., 2014). Lawrence et al. (1995) cloned first rust resistance gene L6 from flax (linseed). In case of cereal, Rp1-d was the first rust resistance gene to be cloned by Collins et al. (1999) from corn. More than 30 resistance genes have been cloned in common wheat including Lr10, Lr1, Lr21 for leaf rust (Huang et al., 2003;Cloutier et al., 2007;Loutre et al., 2009;Liu et al., 2012). The resistance genes are ineffective individually to the upcoming pathotypes of rusts in the world, thus pyramiding different resistance genes to breed multiline cultivars may increase the durability of resistance (Wen et al., 2008). Two highly effective genes for leaf rust resistance viz., Lr24, Lr28 and a stripe rust resistance gene Yr15 were selected for pyramiding in the susceptible but high yielding Indian bread wheat variety HD2877 (Revathi et al., 2010). Three highly effective leaf rust resistance genes, Lr 24, Lr 28, and Lr 9 were selected for pyramiding in the bread wheat variety HD 2329 of India (Charpe et al., 2012). Vanzetti et al. (2011) reported that combinations of Lr16, Lr47, Lr19, Lr41, Lr21, Lr25, and Lr29, with Lr34, SV2, Lr46 provide durable and effective resistance to leaf rust. An alternative and efficient strategy to detect quantitative trait loci (QTL) is association mapping (AM) or linkage disequilibrium (LD)-based mapping, in which genotype-phenotype relationships are explored in genetically diverse germplasm (Flint-Garcia et al., 2003;Zhu et al., 2008). AM has proved to be an efficient approach for both tetraploid and hexaploid wheat, by which enhancing previously available QTL information for MAS (Breseghello and Sorrells, 2006;Maccaferri et al., 2011). For leaf rust, QTLs were identified in 164 elite durum wheat accessions from different countries using AM approach (Maccaferri et al., 2010).
Stem Rust
Stem or black rust is a major disease caused by fungus P. graminis f. sp. tritici. Wheat, durum wheat, barley, triticale, barley grasses (Hordeum sp.) and common wheat grass (Agropyron scabrum) are among the most commonly infected crops by stem rust. The Italians Fontana and Tozzetti independently provided the first report on stem rust in wheat in 1767. In large areas of the world, the life cycle of P. graminis consists of continual uredinial generations. The disease either spreads via airborne spores or occasionally from local-wild susceptible barberry (Berberis sp.) plants (Eversmeyer, 2000). Wheat (primary host) and barberry (secondary host) are required to complete the life cycle of fungus (Leonard and Szabo, 2005). Five types of spores (pycniospores, aeciospores, urediniospores, teliospores, and basidiospores) occur in the life cycle of fungus at different developmental stages (Leonard, 2001). Warm temperature (15-30 • C) and dew are the two important factors favoring the crop infection by stem rust. Stem rust usually occurs on the stem, and can also occur on the leaves (both sides), leaf sheaths or in severe infections on the head. Uredia pustules on stem and leaf sheaths are the main symptoms of disease spreading (Leonard, 2001). Reddish brown color and oval or spindle-shaped pustules are seen on the stem and leaf sheath. Pustules would change to black in color at the end of the season when infection is too old (Todorovska et al., 2009) and can cause severe crop loss in a short span of time at the end of the season.
In the early to mid 1950s; stem rust epidemics caused approximately 50% yield losses of wheat in North America (Leonard, 2001). During 1950s, Norman Borlaug and other scientists started developing high-yielding wheat varieties that were resistant to stem rust and other diseases in North America and throughout the world . Resistant plants exhibit no or less number of uredia surrounded by chlorosis or necrosis as compared to susceptible plants.
A new race of stem rust (Ug99) causing a high level of infection on wheat genotypes was found in 1999 in Uganda (Pretorius et al., 2000). Heavy stem rust infections were observed in International Center for Wheat and Maize Improvement (CIMMYT)-derived lines of wheat in Kenya in 2004 (Kolmer, 2005;Todorovska et al., 2009). This race has spread to major wheat growing regions of the world such as Iran, Afghanistan, India, Pakistan, Turkmenistan, Uzbekista, Kazakhstan, USA, and Canada (Todorovska et al., 2009). Therefore it is necessary to develop a resistant germplasm to overcome the spreading of infection in these regions.
Since, breeding program in wheat for developing stem rust resistance is a challenging task for a breeder; therefore, acquisition of genetic resistance is the best alternative for controlling rust epidemics. Currently, about fifty stem rust resistance (Sr) genes have been identified. Moreover, mapping of few genes and their close relatives on different chromosomes of wheat has also been achieved (McIntosh et al., 1998). PCR (STS) and non-hybridization based (RFLP) markers are available for screening the genotypes which are resistant to stem rust disease (William et al., 2008). The molecular markers associated with Sr genes known so far are summarized in (Table 1). RFLP (Sr22-Paull et al., 1995) and STS (Sr2- Hayden et al., 2004;Sr24, Sr26-Mago et al., 2005;SrR-Mago et al., 2002;Sr39-Mas wheat ucdavis), STS/SSR (Sr56- Bansal et al., 2014), SSR/AFLP (Sr45- Periyannan et al., 2014) STS/CAPS (Sr38- Helguera et al., 2003) and SSR (Sr32- Mago et al., 2013;Sr43-Niu et al., 2014;Sr54-Yu et al., 2015) markers have been reported to be associated with different Sr genes in wheat. Sr2 is one of the non-race specific genes which have resulted in successful acquisition of durable rust resistance to slow rusting adult (Singh et al., 2004). It has been widely used by CIMMYT, Mexico in its wheat program for improvement of stem rust resistance and also in USA for hard winter wheat breeding program. Above all, the Sr2 complex when used in combination with other resistance genes has shown remarkable protection against Ug99 (Singh, 1993). CIMMYT and International center for agricultural research in the dry areas (ICARDA) started the global rust initiative (Later in 2008, BGRI-Borlaug global rust initiative) to coordinate efforts to track and study Ug99 and develop resistant varieties of wheat (Stokstad, 2007). Some genes like Sr33 and Sr35 for stem rust resistance were cloned with the objective to increase resistance (Periyannan et al., 2013;Saintenac et al., 2013) Various studies have been conducted to confirm the presence of Sr genes in wheat cultivars. A recombinant inbred line (RIL) population of 83 lines (developed from a cross from Indian wheat cultivars VL404 and WL711) was screened to identify Sr28 gene using SSR markers (Bansal et al., 2012). Haile et al. (2013) screened 58 tetraploid wheat accessions of Ethiopian wheat cultivars for the presence of 30 Sr genes using SSR and STS markers. 88 spring soft wheat of Kazakhstan were studied for presence of Sr genes (Sr2, Sr22, Sr24, Sr36, and Sr46) which are effective against Ug99 (Kokhmetova and Atishova, 2012). Thirty-seven lines of American cultivars with known stem rust resistance genes and five genetic background cultivars were used to further validate the six co-dominant STS markers for Sr25 and Sr26 (Liu et al., 2010). Mago et al. (2011) used DNA markers to check the presence of Sr24, Sr26, SrR, and Sr31 in wheat-rye recombinant T6-1. These Sr genes provide resistance against all strains of stem rust that are prevalent in Australia. However, Sr26 and SrR are effective outside Australia against strain Ug99. 104 F 2:3 population of Gabo 56 with susceptible cultivar Chinese Spring were screened to check the presence of Sr9h using SSR markers. Minor stem rust resistance gene Sr2 was pyramided with two major stem rust resistance genes Sr24 and Sr36 in Indian wheat varieties 'Lok-1' and 'Sonalika' (Nisha et al., 2015). AM study for response to stem rust was conducted on 183 Ethiopian durum wheat accessions and 276 wheat lines from Kenya (Yu et al., 2011;Letta et al., 2013).
Yellow Rust or Stripe Rust
Stripe or yellow rust, caused by P. striiformis f. sp. tritici, mainly infects wheat, but can also cause infection in barley, rye, and triticale. It was first reported in USA (Carleton, 1915) and outbreaks were reported in the Western states in 1960s (Boyd, 2005). Later on, the infections were also reported from other parts of the of world including USA, East Asia (China northwest and southwest), South Asia (India, Pakistan, and Nepal), Oceania (Australia, New Zealand), East Africa (Ethiopia, Kenya), the Arabian Peninsula (Yemen) and Western Europe (Wellings, 2011). Presently, more than 35% of area under wheat cultivation is affected by stripe rust disease (Singh et al., 2004). Cool and wet weather is favorable for the development of yellow rust. Pustules are light yellow and occur on leaves in distinct straight-sided stripes about 1/16 inches wide and of regular length. The spores are yellow to orange in color. Reduced dry matter production, root growth, plant height, size and number of flowering spikes, and the size and number of grains are the parameters affected by infection. These effects were more pronounced with infection beginning at the seedling stage, although infections initiated at anthesis were also associated with reduced root weight and grain yield (Wellings, 2011).
Breeding efforts for stripe rust resistance has been made in the past. Breeding approaches involves developing several crosses with careful phenotypic selection which makes it difficult for a breeder to achieve the desired objective. About 52 permanently named and more than 40 temporarily designated genes or QTL for stripe rust resistance have been reported (Chen, 2005;McIntosh et al., 2011;Ren et al., 2012). Among the permanently named resistance genes, Yr11, Yr12,Yr13,Yr14,Yr16,Yr18,Yr29,Yr30,Yr34,Yr36,Yr39,Yr46,Yr48, and Yr52, confer adult plant or high temperature adult plant (HTAP) resistance genes, whereas the others confer all-stage resistance. The identification and use of the resistant genes is the only way to conquer the impact of disease on wheat production. Till date, 65 (Yr1-Yr65) yellow rust resistance genes have been characterized and designated in wheat (McIntosh et al., 1995;Singh et al., 2004;Boyd, 2005;McIntosh et al., 2008). A wide range of markers are reported to be associated with Yr genes ( Table 1). RFLP (Yr28-Singh et al., 2000), SSR (Yr10- Wang et al., 2002;Yr15, Yr26, YrH52-Peng et al., 2000), STS/CAPS (Y17- Robert et al., 1999;Helguera et al., 2003;YrMoro-Smith et al., 2002), STS (Yr61- Zhou et al., 2014a), DArt (Yr51- Randhawa et al., 2014), RGAP/SSR (Yr59- Zhou et al., 2014c) and SSR (YrSN104- Asad et al., 2012;Yr 50-Liu et al., 2013;Yr64 and Yr65-Cheng et al., 2014) markers have been reported to be associated with different Yr genes in wheat. Most of the identified yellow rust resistant Yr genes have been characterized as the race specific ones and are responsible for acquiring resistance against the isolates of P. striiformis f. sp. tritici only, which carries the corresponding avirulence (avr) gene. Various stripe rust resistant genes have been transferred into hexaploid wheat from different wild species (Kuraparthy et al., 2007a,b;Chhuneja et al., 2008). With the help of molecular marker a study reveals that recent Canadian wheat varieties have the strip rust resistant genes Yr 10, Yr17, Yr18, and Yr 36 (Randhawa et al., 2012). Further, a highly stripe rust resistant gene, namely Yr36 has been used for positional cloning. Yr36 gene, derived from wild emmer wheat, carries broad spectrum resistance for stripe rust races (Fu et al., 2009). A total of 54 wheat genotypes representing breeding lines and current grown cultivars in the western US were tested with race PST-100 and the Yr53-flanking markers, XLRRrev/NLRRrev350, Xgwm441 and the STS marker (STS2F/1R219) developed from RGAP marker, Ptokin2/Xa1NBSF234 (Xu et al., 2013).
Four Gatersleben wheat microsatellite (GWM) markers were used to identify non-specific adult plant disease resistance genes against stripe rust in 160 F 2 plants from the cross of UK/German wheat cultivars Lgst.7/Winzi (Khlestkina et al., 2007). To identify genes for stripe rust in 181 plants from one segregating F 3 line of Xiaoyan/Mingxian cross. SSR primers were used to identify molecular markers flanking Yrxy2, whereas for Yrxy1 RGAP and SSR markers both were used (Zhou et al., 2011). Naz et al. (2012) done QTL analysis by using a genetic map based on 118 SSR markers in 150 back cross lines of German wheat cultivars Zentos and Syn86L. To identify genes for stripe rust resistance in 179 F 2 population of Wuhan 2/Mingxian 169 cross against races CYR30 and CYR31 using RGAP and SSR markers (Zhou et al., 2014b). Yaniv et al. (2015) concluded from their findings that SSR markers from Yr15 region are efficient tools for MAS and for introgression of Yr15 into wheat from T. dicoccoides. In case of stripe rust resistance genes, Yr17, Yr18, and Yr36 were amongst the successfully cloned genes (Helguera et al., 2003;Lagudah et al., 2009;Fu et al., 2009). Stripe rust response for adult plants was evaluated using AM in 192 genotypes including 181 synthetic hexaploid wheat (SHW) and 11 bread wheat cultivars from different countries (Zegeye et al., 2014). Similar studies were performed using 402 wheat varieties and 1000 spring wheat accessions from USA (Naruoka et al., 2015;Maccaferri et al., 2015).
Recent Trends
Recently the new technologies are being used for sequencing of cereal crops, but the storage of data and analysis are difficult due to its vast size. Single nucleotide polymorphism (SNP) genotyping offers a solution to this problem and accelerates the crop improvement by providing insights into their genetic constitution. It has number of advantages over conventional marker system such as rapid processing of large populations, abundance of markers and varieties of genotyping system (Thomson, 2014). In quantitative trait locus (QTL) mapping experiments and genome-wide association studies (GWAS), SNP data is frequently used to detect marker-trait associations (Zhao et al., 2011;Cook et al., 2012). Discovery of SNPs using complete genome is facilitated by recent advances in nextgeneration sequencing (Berkman et al., 2012;Chia et al., 2012;Xu et al., 2012). Genetic studies of number of economically important crops have been successfully done by the application of high-density SNP arrays (Wiedmann et al., 2008;Ganal et al., 2011;Zhao et al., 2011;Sim et al., 2012;Song et al., 2013). 44K SNP genotyping chip was employed for GWAS of diverse rice accessions and identified number of alleles responsible for governing morphological and agronomic traits (Zhao et al., 2011). Similarly, the genetic control of maize kernel composition in a nested AM panel was studied by the use of 50K maize SNP chip (Cook et al., 2012;Hufford et al., 2012). Moreover, the genomic regions targeted by breeding in wheat were detected by 9K SNP wheat (Cavanagh et al., 2013). The most challenging task is to analyze the genotypic data of durum [T. turgidum subsp. durum (Desf.) Husnot] and bread wheat (T. aestivum L.) genome using SNP genotyping platforms (Akhunov et al., 2009). The use of wheat SNP iSelect array has proven to be a promising tool to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat. A combination of eight mapping populations was used to genetically map 46,977 SNPs using wheat 90K array .
Conclusion
Due to global food security and consistent increase in world population, there is an immediate need to increase wheat yield considerably. Fungal diseases continue to cause huge losses and pose a great challenge for wheat production. Novel genetic tools based on molecular marker technologies provide a good alternative for developing improved resistant cultivars. Development of molecular markers such as RFLPs, SSRs, AFLPs, SNPs, and DArT in last more than two decades has revolutionized wheat genomics. Marker assisted breeding and functional genomics tools are effective strategies to develop resistant cultivars against fungal diseases in wheat for achieving estimated production paradigm. In future, functional genomics approaches such as TILLING, RNAi and epigentics etc. are needed to strengthen the development of resistant varieties. Mutagenesisderived broad-spectrum disease resistance may lead to a better understanding of the regulation of defense response networks in wheat. Large-scale genome sequencing and associated bioinformatics are becoming widely accepted research tools for accelerating the analysis of wheat genome structure and function. Currently, functional markers are being increasingly adopted in wheat breeding. These markers are needed for important traits such as disease and stress resistance in order to strengthen the application of molecular markers in breeding programs. The collaborative effort (MASwheat: http://maswheat.ucdavis. edu/index.htm) by United States Department of Agriculture (USDA), National Institute of Food and Agriculture (NIFA) and Borlaug Global Rust Initiative (BGRI) has given the platform for transferring new developments in wheat genomics and biotechnology to increase wheat production. Many traits such as the disease/pest resistance and end-use quality which has increased the competitiveness of wheat breeding programs through MAS were included. Triticeae Coordinated Agricultural Project (T-CAP) focused on studying the effects of climate change on crop yields by identification and incorporation of genetic loci for enhancing tolerance in crops. For improving the barley and wheat germplasm, gene variants for disease resistance, water and nitrogen use efficiency and yield improvement are being identified, along with molecular markers to tag them and accelerate breeding. The International Wheat Genome Sequencing Consortium (IWGSC) will put the foundation to accelerate wheat improvement for wheat growers, scientists, and breeders. The ultimate goal leads to obtain high quality annotation of the genome and thus complete sequencing of the common wheat genome. | v3-fos |
2016-05-12T22:15:10.714Z | {
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} | s2 | Mass and Energy Balances of Dry Thermophilic Anaerobic Digestion Treating Swine Manure Mixed with Rice Straw
To evaluate the feasibility of swine manure treatment by a proposed Dry Thermophilic Anaerobic Digestion (DT-AD) system, we evaluated the methane yield of swine manure treated using a DT-AD method with rice straw under different C/N ratios and solid retention time (SRT) and calculated the mass and energy balances when the DT-AD system is used for swine manure treatment from a model farm with 1000 pigs and the digested residue is used for forage rice production. A traditional swine manure treatment Oxidation Ditch system was used as the study control. The results suggest that methane yield using the proposed DT-AD system increased with a higher C/N ratio and shorter SRT. Correspondently, for the DT-AD system running with SRT of 80 days, the net energy yields for all treatments were negative, due to low biogas production and high heat loss of digestion tank. However, the biogas yield increased when the SRT was shortened to 40 days, and the generated energy was greater than consumed energy when C/N ratio was 20 : 1 and 30 : 1. The results suggest that with the correct optimization of C/N ratio and SRT, the proposed DT-AD system, followed by using digestate for forage rice production, can attain energy self-sufficiency.
Introduction
The number of scaled pig farms in Asia has greatly increased in recent years, while the disposal methods of swine manure are relatively underdeveloped. Particularly, China accounts for approximately 45-50% of the global pig production during the past decade [1,2]. This has resulted in a significant increase in pig farm wastewater discharge, which has become an important source of water body pollution [3,4]. In Japan, industrial treatment of swine waste is also becoming an important pathway for pig farm. During the process of industrial treatment of swine manure, the solids and liquid are first separated [5], followed by further treatment using both liquid and solid processes. This includes treating liquid phase using biological active sludge processes, and composting solid phase [6,7]. However, some of the nutrients contained in swine manure cannot be recovered and are therefore discharged with the wastewater treatment plant effluent. Additionally, organic matter contained in the swine manure cannot be efficiently recovered as an energy source.
Anaerobic digestion is an efficient technology for livestock wastewater treatment, as well as an important technology for recovering biogas as a renewable energy source from organic substrates [8,9]. Digestion of swine manure alone is usually unsuccessful because of its high ammonium concentrations and low C/N ratio [10][11][12]. As such, swine manure is preferably codigested with organic wastes containing high amounts of carbon, to improve the C/N ratio and to further increase biogas production. Codigestion of animal manure with various agroindustrial residues has been previously reported, with particular interest in the codigestion of animal manure with straws. Hills and Roberts [13] reported the benefits of codigesting plant material with low C/N animal manure. Specifically, they found that low C/N manure could provide a sufficient amount of nutrients, while the added plant materials with high carbon content could improve the C/N ratio and therefore decrease the risk of ammonia inhibition in the digestion process. Rice straw is one of the most important energy sources readily available in the rural areas in many countries, particularly in Asia, and it may also 2 Biotechnology Research International be used for biogas production through anaerobic digestion [5,14]. In addition, dry anaerobic digestion is more beneficial than wet anaerobic digestion for compact reactors, because the process has lower water content and higher methane production [15,16]. Furthermore, compared with mesophilic digestion processes, thermophilic digestion achieves higher rates of digestion and greater conversion of organic waste to gas [17,18]. Therefore, a thermophilic digester can be loaded to a higher degree or operated at a lower solid retention time than at mesophilic conditions. But the thermophilic process temperature results in a higher risk for ammonia inhibition. Ammonia toxicity increases with increasing temperature [18].
China is one of the most abundant straw resources in the world, producing more than 620 million tons of straw in 2002, which is the most part of the biomass energy resources [19]. Rice production is also one of the most important agricultural production forms in Japan. In addition, besides common rice production, a series of forage rice varieties (Oryza sativa L.) have been developed for livestock feed in Japan. Some varieties have high levels of nonstructural carbohydrates in their stems and leaves [20], which can improve the digestibility of forage rice straw and enhance the biogas production of anaerobic codigestion of swine manure. Given this, we propose the following innovative system: swine manure produced on a pig farm is treated by the Dry Thermophilic Anaerobic Digestion (DT-AD) process with forage rice straw and generates biogas. Biogas is converted into heat and electricity through a Combined Heat and Power (CHP) system, which is used to run a DT-AD system. In addition, the thermophilic anaerobic digestion process is able to inactivate weed seeds, bacteria, viruses, fungi, and parasites in the feedstock which is of great importance when the digestate is used as fertilizer [21]. The best sanitation effect is obtained at thermophilic temperatures above 50 ∘ C and long retention times. In this study, the digested residue from the DT-AD process is used as fertilizer for forage rice production, and the grain is provided to pig farm as part of feed.
It is, of course, necessary to evaluate whether the proposed DT-AD system with forage rice production is energy self-supporting or not. Energy balance from swine manure discharge through the end-use of digestate and generated heat/power should be considered in the entire chain of the proposed DT-AD system. To evaluate the feasibility of swine manure treated by the proposed system, we engaged with the following study goals: (1) verify the methane yield of swine manure and rice straw treated by DT-AD method under different C/N ratios and solid retention time (SRT) and (2) calculate the mass and energy balances when the DT-AD system is used for swine manure treatment from a farm with 1000 pigs and the digested residue is used for forage rice production.
Methane Production
Assay. The straw of forage rice (Oryza sativa L. Takanari) was chopped into 20 mm pieces and then ground into small particles (Wonder Blender WB-1, Osaka Chemical Ltd. Co., Osaka, Japan), which were further sieved using 10-mesh sieve. Rice straw and swine manure were characterized in terms of their total solid (TS), volatile solid (VS), total nitrogen (TN), and total carbon (TC). As anticipated, rice straw was rich in organic matter and carbohydrates (VS = 82.3%; TC = 35.1%; TN = 0.43%), while swine manure had high nitrogen content (VS = 8.0%; TC = 4.35%; TN = 0.59%; NH 4 + -N = 2567 mg/kg). The inoculum used in this study was taken from a Dry Thermophilic Anaerobic Digestion pilot plant that treats solid garbage including kitchen garbage and office paper, which is run by Tokyo Gas and the Tokyo Environmental Public Service Corporation. To remove the degradable organic matter, the inoculum was incubated before the experiment without any added organic matter.
Samples with different C/N ratios (C/N = 10, 20, 30; named CN10, CN20, CN30 treatments), adjusted with swine manure and rice straw were designed to examine the improvement of anaerobic digestion at different treatment levels. Methane production assays were conducted as semicontinuous experiments in triplicate with 500-mL Duran laboratory bottles under dry thermophilic (55 degree Celsius) conditions. Biogas collection and substrate sampling was done every week. Biogas sample was taken with 50-mL syringes through the sampling tunnel of the stopper and then stored in a vacuumed vial (SVG-30, Nichiden-Rika Glass Co., Ltd., Hyogo, Japan). The volume of biogas produced in the Tetra Pak bag was also measured. The percentage of CH 4 and CO 2 in the biogas was measured using a GC-8A gas chromatograph (Shimadzu, Kyoto, Japan) equipped with a thermal conductivity detector and a 2-m stainless column packed with activated carbon (60/80-mesh sieve). The effects of different C/N ratios on methane yield were measured at SRT of 80 [13] and faster SRT of 40 days.
Mass and Energy Balances Calculation.
For mass and energy balances calculations, a traditional swine manure treatment system was used as a control. This system includes wastewater treated using an Oxidation Ditch (O/D) system and solid waste composting, after the solid-liquid separation of swine manure. The entire system, including the treatment of swine manure using the proposed DT-AD system, followed by using digested residue as fertilizer for forage rice production, was calculated. The harvested grain was used as feed to support pig growth (replaced 10% of the total amount of feed). The mass balance was calculated by wet weight, in which water added by the process was included as an input. Evaporative water losses were not taken into account. The calculation of energy balance includes energy for DT-AD system operation and the energy invested in the DT-AD system plant construction. The calculation boundaries of traditional and proposed systems are shown in Figure 1, respectively.
Traditional System
Mass Balance Calculation Condition. (1) Pig farm: the scale of the pig farm was designed as 1000 pigs; the basic unit of swine manure discharged from pig farm was 5.4 kg/pig/day, in which the biochemical oxygen demand (BOD) was 24352 mg/L, TN was 6759 mg/L, and was 2722 mg/L. (2) Composter: the water content of solid phase was 72%; it was 62% after being adjusted with rice husk. The decomposition rate of the solid phase was 40%; (3) wastewater treatment: the BOD concentration of raw influent was 1200 mg/L and the MLSS of active sludge was 4000 mg/L. Removal efficiencies of BOD and TN were 96% and 80% [22], respectively. The settled sludge concentration was 12000 mg/L and the water content of concentrated sludge was 97%.
Energy Balance Calculation Condition. (1) Pig farm: the fuel, feed, and material used for one pig were converted into an energy unit; (2) composter: the fuel and material used for 1ton raw material was converted into an energy unit; (3) the power and the material used for the wastewater treatment plant were converted into an energy unit.
Proposed
System. There were three parts of the mass energy balance calculation for the suggested system, which include running the pig farm, operating the DT-AD system, and producing the rice. The generated energy was calculated by converting biogas to power and heat using a Combined Heat and Power (CHP) system.
Mass Balance Calculation Condition.
(1) Pig farm: swine manure (feces and urine) was discharged without solid and liquid separation processes; (2) the DT-AD system: the basic unit of biogas yield under different C/N ratios and SRTs are shown in Table 1; (3) the area of forage rice production depended on the nutrient content of digestate. The unit biomass of forage rice was 18.6 t/ha, which included 36% grain and 64% straw.
Energy Balance Calculation Conditions. (1) Pig farm: the grain of harvested forage rice replaced 10% of the total feed, so the energy equated with 10% of the feed was deducted from the total consumption energy; (2) the DT-AD system: biogas produced in the DT-AD system was converted into power and heat by CHP. CHP performances are shown in Table 2. The produced power and heat were provided to the DT-AD system, and the rest was sold for commercial purposes. The energy to run the DT-AD system included power, warming feedstock, and heat loss of the digestion tank and was based on the literature [20]. The energy required to raise the temperature of the feedstock and maintain the temperature of the heated tanks was calculated based on input volumes, tank dimensions, and insulation values; (3) the fuel and material used for forage rice production were converted into consumption energy, including heat, light, power, fertilizer, and farm machine. All energy calculation equations are shown in the appendices. The term "net energy yield" is used for assessing the total system whether it is energy self-supporting or not. The "net energy yield" refers to the gross output energy minus the input energy in the entire chain of the proposed system as shown in Net energy yield = Output energy − Input energy, (1) where "output energy" was the heat and power produced by the DT-AD system; "input energy" for the proposed system was energy consumed in pig farm, DT-AD system, and rice production process, including power, fuel, feed, and material used in pig farm; energy for construction, digestion tank warming, heat loss from tanks, and electrical requirement in the DT-AD system; electrical and material requirement in the rice production process. On the other hand, there was no "output energy" in the traditional system. "Input energy" of traditional system has been described in the "energy balance calculation condition."
Methane Yield under Different C/N Ratios and SRTs.
Each treatment maintained a relatively stable biogas yield. Different levels of biogas were produced at different C/N ratios after 80 days following the start of the experiment, with an SRT of 80 days (Figure 2(a)). The average biogas yield at the CN10 treatment level was 177 ± 80 mL/g VS added between 80 days and 300 days, which was half the yield of the other two CN treatments. Treatments with C/N ratios greater than 20 produced relatively high biogas yields, mostly greater than 400 mL/g VS added . When these higher levels are compared with CN10, the benefit of adding more rice straw to assist in anaerobic digestion of swine manure is clear, with increases up to approximately 2 and 3 times the average biogas production of CN20 (386 ± 139 mL/g VS added ) and CN30 (474 ± 99 mL/g VS added ). Biogas production in CN30 showed a higher and stable level, which is generally in agreement with the literature and indicates an optimal C/N ratio of 25-35 for rice straw [23,24]. Conversely, biogas production of CN10 remained at an "inhibited steady state," which is a condition where the process is stable, but with a low methane yield [10,25], suggesting that the C/N ratio should be well balanced to avoid process failure by ammonia accumulation. A similar trend is observed for the methane yield of each treatment, shown in Figure 2(b). Ammonium concentrations were significantly different among different C/N ratios. Particularly, the ammonium concentration in the CN10 treatment was above 4000 mg-N/kg, whereas, for the CN30 treatment, the ammonium level remained around 1500 mg-N/kg through the entire experimental period. Correspondently, the average methane yield was 91 ± 13 mL-CH 4 /g VS added for CN10. The highest average methane yield was 265 ± 63 mL-CH 4 /g VS added during the 80-to 300-day period with the CN30 treatment, followed by 252 ± 46 mL-CH 4 /g VS added with the CN20 treatment. Methane yields for the CN20 and CN30 treatments, in which 22% and 35% of rice straw (resp.) were added to the feedstock, were similar to the results (213-269 mL-CH 4 /g VS added ) of the codigestion of cow manure with 30% of crop (grass, sugar beet tops, and straw) in the feedstock [26]. The average methane content during the stable period ranged from 52% to 62% in the CN10, CN20, and CN30 treatments, which is similar to the methane content of biogas from typical lignocellulose materials (i.e., grass and maize silage) which range from 54% to 60% [25,27].
The organic loading rate increased significantly when the SRT was reduced from 80 days to 40 days; these increases were from 3.2 kg-VS/m 3 /d to 6 the biogas yield increased significantly with SRT of 40 days under each C/N ratio, even though the trends of biogas productions were similar with those under SRT of 80 days. Finally, the biogas yield per VS was converted to biogas yield per ton of feedstock at different SRTs and C/N ratios for the mass and energy balances calculations shown in Table 1.
Comparison of Mass Balances between Traditional and
Proposed Systems. The daily manure (feces and urine) discharged from 1000 pigs farm was 16.83 tons per day, which is the average amount of waste discharged from pig farm. In the mass balance of the traditional system (Figure 3), after solid and liquid separation, about 1.33 tons of solid phase per day flowed to the composter, while 15.5 tons of liquid phase flowed to the wastewater treatment plant. The BOD and TN concentration contained in the liquid phase was 3336 mg/L and 1497 mg/L, respectively. To treat the liquid phase by using active sludge, 27.6 tons per day of dilution water was added into the flow. Although the removal efficiencies of BOD and TN were relatively high, at 96% and 80%, the BOD and TN concentrations reached 48 and 108 mg/L. In fact, wastewater discharged from most of small scale pig farms cannot achieve these removal efficiencies. The TN concentration of effluent from the pig farm was higher, resulting from the special temporal effluent standard for effluent from livestock operations (700 mg-N/L from 2014) released by Ministry of the Environment, Japan, which is significantly higher than the uniform standard (100 mg-N/L) of industrial effluent. Besides the wastewater discharged from this system, sludge produced in the process of active sludge is another problem, because it must be disposed of and stored for dry treatment. Most of the sludge from active sludge process is dumped after dehydration (approximately 20% solid content) in Japan [15]. In this study, a space with 50 m 2 was used for sludge drying process and produced 0.043 ton per day of dried sludge.
Additionally, 0.68 ton per day of compost was also produced from solid phase after liquid and solid separation. Although the amount of swine manure discharged from 1000 pigs farm was the same, the volume of the digestion tank, biogas yield, digestate output, and paddy field area increased as the C/N ratio increased (Figure 4). To adjust the C/N ratio, different amount of straw and grain was added into swine manure for feedstock. The C/N ratio of 30 in feedstock needed the most amounts of grain and straw, which reached 3.21 tons per day whereas C/N ratio of 20 needed 1.51 tons per day. Correspondingly, the volume of digestion tank increased due to the amount of feedstock increasing. Meanwhile, the biogas production also increased with the loading rate of feedstock increasing. However, the volume of digestion tanks changed according to the different SRT even though the digestion was conducted under the same C/N ratio. Compared to the system with a SRT of 80 days at the same C/N ratio, the volume of digestion tank in the system with a SRT of 40 days was only half the size. The shorter SRT led to the higher organic loading rate. The organic loading rate increased from 3.2 kg-VS/m 3 /d to 6.4 kg-VS/m 3 /d with C/N ratio of 30. The higher organic loading rate resulted in higher biogas production, which could be converted into electricity and heat compared to the traditional system. Because the substrate must be mixed with digestate coming from the dry anaerobic digester before it is fed to the digester, organic loading rate can be allowed up to 10 kg-VS/m 3 /d, which is significantly higher than the loading rate of wet anaerobic digestion process (2-4 kg-VS/m 3 /d) [18]. Furthermore, in the proposed system including the DT-AD system, CHP, and forage rice production, no wastewater and sludge are discharged. Digestate could be used for forage rice production as fertilizer due to containing rich nutrients. Due to previous research, nutrients in livestock waste could be utilized by planting forage rice in paddy field and little nutrient discharged into environment [28,29]. The area of paddy field was calculated basing on the required biomass amount for C/N ratio adjusts. It is obvious that the area was the highest when the biomass was used for C/N ratio of 30 adjusts. Part of harvested grain can be used for replacing the feed of 1000 pigs and all of the rest was used for C/N ratio adjusts.
Comparison of Energy Balances between Traditional and
Proposed Systems. Because the same scale of pig farms was used for the energy balances calculations comparing the traditional and proposed systems, the fuel and power consumed in these farms are both the same with the SRTs of 80 and 40 days ( Figure 5). However, in the proposed system, 10% of the feed is replaced by grain that was fertilized using digestate, so the energy was deduced from the total consumption energy. Among the items contributing to energy consumption, heat loss from digestion tank in the DT-AD process was the largest element. The heat loss increased significantly with C/N ratio of feedstock increased at the same SRT because higher C/N ratio of feedstock made the tank bigger. Similarly, electrical requirement of DT-AD plant also increased with bigger tank. In addition, to achieve the higher C/N ratio, larger area of paddy field was needed for rice production, which resulted in the higher electrical demand for rice production for higher C/N ratio process. Furthermore, compared with the SRT of 80 days, energy consumption for the heat loss decreased significantly due to the smaller tank when the SRT was shortened from 80 days to 40 days. The electrical and heat output increased not only at SRT of 80 days but at SRT of 40 days with C/N ratio increased, caused by the increasing biogas yield. However, although the biogas yield increased with C/N ratio increase, the net energy yield (Table 3) was negative for the proposed DT-AD system running with a SRT of 80 days, due to low biogas production and high heat loss. In contrast, the net energy yield with the SRT of 40 days was positive when the C/N ratios were 20 and Biotechnology Research International 30, indicating that the generated energy was greater than the consumed energy by the entire system. The major reason was the biogas yield increased when the SRT was shortened to 40 days. Furthermore, the electric efficiency for energy balance calculation was 32% (Table 2). According to the literature, electric efficiencies of CHP up to 43% can be achieved, which can improve energy balance [18]. Compared to the proposed DT-AD system, the control scenario (a traditional pig farm with traditional O/D wastewater treatment) generated no energy but rather only consumed it for O/D wastewater treatment and electrical and fuel requirement of compost. Although the net energy yields under SRT of 80 days with C/N ratio as 30 as well as SRT of 40 days with C/N ratio as 10 were higher than that of traditional system, it is difficult to recognize the DT-AD system with these conditions as energy self-supporting systems due to negative net energy yield. However, the net energy yields under SRT of 40 days with C/N ratios as 20 and 30 were positive and significantly higher than that of traditional system, suggesting the DT-AD system with correct optimization can attain energy selfsufficiency.
Conclusion
Compared to the traditional pig farm with traditional wastewater treatment, there is no wastewater discharged from the suggested DT-AD system. Furthermore, it is possible to improve methane yield by adjusting the C/N ratio by adding rice straw into swine manure under dry thermophilic anaerobic conditions. For mass balance, in the proposed DT-AD system, biogas production increased as the C/N ratio increased. However, the area of forage rice vegetation also increased significantly. Because the scale of pig farms and the areas of paddy fields differ across regions, any proposed system must be considered in light of the regional characteristics of pig farms and paddy fields. On the other hand, the tank volume required for the proposed process can be reduced with a shorter SRT, suggesting that the area of the DT-AD plant can also be reduced. With respect to energy balance, the consumption energy associated with the DT-AD system was dominant. The net energy yield was negative, due to low biogas production, when the DT-AD system was running at a C/N of 10 with SRTs of 80 and 40 days. The percentage of heat loss from the digestion tank with an SRT of 80 days was the highest, 8 Biotechnology Research International indicating that the DT-AD system cannot be energy selfsupporting. However, the heat loss from the digestion tank decreased due to the compact nature of the tank when the SRT was reduced from 80 days to 40 days, while biogas production increased due to higher organic loading rate. The generated energy with the SRT of 40 days was greater than the consumed energy when the C/N ratios were 20 and 30, suggesting that, with the correct optimization, the DT-AD system can attain energy self-sufficiency.
A. Output Energy Calculation: Generated Energy
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} | s2 | Relative Bioavailability of Niacin Supplements for Dairy Cows: Effects of Rumen Protection and of Feed Processing
The present study aimed to examine the effective systemic bioavailability of niacin— with particular focus on its galenic form—and feed processing. Experiment 1 was conducted with 35 dairy cows to investigate the effects of various doses of oral supplemented nicotinic acid (NA) either in differing galenic forms (non-rumen protected (nRP) vs. rumen protected form (RP)) on serum niacin concentrations. Experiment 2 was designed as a pharmacokinetic study examining the serum niacin kinetics over 24 h after giving a single oral bolus of 24 g nRP or RP NA admixed in either pelleted or ground concentrate. In both experiments, only the niacin vitamer nicotinamide (NAM) was detected. Results of experiment 1 showed that both galenic forms at a dose of 24 g/cow daily elevated NAM concentrations at the beginning of the experiment. Despite a daily supplementation, NAM concentrations decreased continuously towards the end of the experiment which was more steeply in nRP NA (p = 0.03). On experimental day 21, NAM concentrations were higher when feeding RP NA (p = 0.03) and the highest dose (24 g/day and cow) (p < 0.01). Results of experiment 2 indicated that nRP and RP were characterized by similar pharmacokinetic profiles resulting in similar areas under the curves as a net result of the kinetic counterbalancing alterations. Pelleting seemed not to influence the relative bioavailability.
Introduction
Niacin (vitamin B3) and its vitamers nicotinamide (NAM) and nicotinic acid (NA) are important for the synthesis of the coenzymes NAD and NADP which are involved in a large number of biological pathways [1]. The NRC [2] declared the requirement of niacin for a lactating cow with a body weight of 650 kg and 35 kg milk yield with 289 mg per day and it was shown that ruminants are capable of covering these requirements from different sources. On the one hand, feedstuffs containing niacin and the synthesis from tryptophan and quinolinic acid via salvage and de novo pathway provide one source for covering niacin requirements [1,3]. On the other hand, Santschi, et al. [4] determined a ruminal niacin synthesis of 2213 mg niacin per day in multiparous and fistulated Holstein cows (between 29 and 178 days in milk (DIM); milk production 27.7 ± 1.4 kg/d).
Niacin and its vitamers have recently attracted increased interest as feed additives due to their promising targets for diverse effects on bovine metabolism. It was shown that feeding additional niacin as nicotinic acid (6-12 g niacin/d) influenced the ruminal ecosystem like the stimulation of the microbial protein synthesis [5], the increase of total protozoal counts [6,7] and the increase of butyric acid, valeric acid, propionic acid, and ammonia [5][6][7][8]. It was stated that the supplementation with NA increase the milk yield [9] and induce shifts in the milk composition [10][11][12]. Furthermore, NA as feed additive was suggested to balance catabolic metabolism postpartum, because it was shown that NA is able to stimulate GPR109A receptor resulting in a down-regulation of the lipolysis via the dephosphorylation of the hormone-sensitive lipase in adipose tissue [13].
Santschi, et al. [4] stated that non-rumen protected (nRP) niacin is massively degraded within the rumen. To improve rumen stability of supplemented niacin and therefore increase duodenal bioavailability, new vitamin encapsulation techniques were developed. However, results of studies investigating the effects of rumen protected (RP) NA on bovine metabolism and production were also highly variable [14,15] rising the question whether the rumen protection results in an increased or compromised systemic niacin bioavailability.
Because there are no studies comparing the pharmacokinetics of nRP and RP, the present study was conducted employing a feeding experiment (Experiment 1) and a pharmacokinetic approach (Experiment 2) in order to assess the systemic niacin bioavailability. Moreover, as concentrate feed is often used in a pelleted form for technical reasons, this feed processing step was additionally addressed in Experiment 2.
Experimental Section
In accordance with the German Animal Welfare Act, pertaining to the protection of experimental animals and approved by the Lower Saxony State Office for Consumer Protection and Food Safety (LAVES), Oldenburg, Germany, two experiments were carried out at the experimental station of the Institute of Animal Nutrition, Friedrich-Loeffler-Institute (FLI), Brunswick, Germany.
The basal diet of both experiments consisted of 30% concentrate and 70% roughage mixture on dry matter (DM) basis and was provided as partial mixed ration (PMR). The roughage mixture was composed of 60% maize silage and 40% grass silage and cows were fed at 5:30 a.m. and 3:00 p.m. daily.
The nRP (Niacin feed grade, Lonza Ltd., Basel, Switzerland) and the RP NA (Niashure rumen protected niacin, Balchem Corporation, New Hampton, NY, USA) were included into the pelletized or ground concentrate compromising 12 g NA/kg. For this reason 12.1 g nRP and 18.5 g RP NA were added per kg concentrate.
Animals and Treatments in Experiment 1
Thirty-five late-lactating dairy cows (241 ± 25 DIM) were distributed to one of seven dietary treatment groups. The experiment lasted 21 days and the animals were allocated with regard to lactation number (2.9 ± 0.1), milk yield (27 ± 1 kg/d), and body weight (653 ± 21 kg) resulting in nearly homogeneous groups of five animals each. The cows were kept in a free stall barn with slatted floors and cubicles covered with rubber mats. The factors studied were: (1) the dose of the NA supplement (6, 12, or 24 g NA/d and cow) and (2) the galenic form of the NA supplement (non-rumen protected (nRP) vs. rumen protected (RP)). Treatment groups of the experiment were: no additive (CON); daily supplementation of 6 g nRP NA (6_nRP); 12 g nRP NA (12_nRP); 24 g nRP NA (24_nRP); 6 g RP NA (6_RP); 12 g RP NA (12_RP); 24 g RP NA (24_RP). Therefore, a complete 3 × 2 factorial design with three levels of NA (6, 12, and 24 g/cow and d) and two galenic forms of the NA supplement (nRP, RP) was tested. The additional CON group was tested to record the general performance level without any NA supplement. The PMR was provided in self-feeding stations (TYPE RIC, Insentec, B.V., Marknesse, The Netherlands). The dietary treatment was provided by a computerized concentrate feeding station (Insentec, B.V., Marknese, The Netherlands). The niacin components were included into the pelletized concentrate to provide daily doses of 6, 12, 24 g corresponding to 0.5, 1, or 2 kg. The difference to the total amount of 2 kg was completed with CON concentrate. Thus, cows without NA supplementation received 2 kg of CON.
Animals and Treatments in Experiment 2
The present study was conducted in a 2 × 2 factorial design with four late-lactating cows (241 ± 32 DIM). The cows were fitted with a venous catheter in the Vena jugularis externa and had an average body weight of 544 ± 62 kg. The lactation number ranged from the first to the fifth lactation and the average milk yield was 25 ± 5 kg/d. Cows were kept in a tethered stall with neck straps. Each cow had its own trough, free access to water, and to a salt block containing sodium chloride throughout the experiment. Cows were given two weeks for adaption to housing and feeding regimen which was followed by 16 days of sampling which was divided into five periods. The interval between each period was at least 72 h and maximum 96 h.
The factors studied were: (1) the galenic form of the NA supplement (nRP vs. RP) and (2) the processing form of the dietary concentrate (pellet (P) vs. meal (M)).
Each cow received each dietary treatment once at the beginning of each period (5:30 a.m.). The dietary treatment was provided before the feeding of the PMR to ensure a complete uptake. Cows of the present experiment received 2 kg of nRP_P, nRP_M, RP_P and RP_M to ensure an uptake of 24 g NA. In the following days of each period, cows received a control ration with CON instead of a dietary treatment. Treatments of the experiment were: no additive (CON); bolus of 24 g nRP NA in pelleted concentrate (nRP_P); bolus of 24 g nRP NA in ground concentrate (nRP_M); bolus of 24 g RP NA in pelleted concentrate (RP_P); bolus of 24 g RP NA in ground concentrate (RP_M).
Data Collection and Analysis
The concentrate intake of the animals was recognized individually via an ear transponder, whereas the intake of the PMR was recorded per group in experiment 1. In experiment 2, feed refusals of the individual feed toughs were removed and weighted daily.
Cows of both experiments were milked twice daily at 5:30 a.m. and 3:30 p.m. The body weight was detected automatically after each milking when leaving the milking parlour in experiment 1. In experiment 2, cows were weighed at the beginning and the end of the experiment. Milk samples of experiment 1 were collected twice a week during the morning and afternoon milking and were fixed with Bronopol and stored at 8 °C until analysis. The milk samples were analyzed for fat, protein, and lactose using a milk analyzer based on Fourier transform infrared spectroscopy (Milkoscan FT 6000, Foss Electric, Hillerød, Denmark) and combined with a flow cytometric measurement for somatic cell count analysis (Fossomatic 500, Foss Electric, Hillerød, Denmark).
Samples of roughages were taken two times weekly, whereas samples of concentrates were taken once a week. Samples were pooled over approximately four weeks. Feed samples were dried at 60 °C for 72 h and ground before analysis. Dry matter, crude ash, crude fiber, crude protein, ether extract, neutral detergent fiber, and acid detergent fiber in maize and grass silage and concentrates were analyzed according to the methods of the Association of German Agricultural Analytic and Research Institutes (VDLUFA) [16]. To ensure the intended concentrate to forage ratio, the DM of the forages were determined twice a week in both experiments. Table 1 shows the chemical composition of the experimental feedstuffs. Table 1. Components, chemical composition, and content of nicotinic acid (NA) of concentrates and roughages offered in the present experiments. The galenic forms non-rumen protected (nRP) and rumen protected (RP) NA were admixed either in pelleted (P) or ground (M) concentrate. Blood sampling started at 7:30 a.m. and cows were captured in a self-locking fence in experiment 1. Blood was taken out of the Vena jugularis externa, on experimental day 0, 1, 3, 6, 10, and 21 of the groups 24_nRP and 24_RP, while those of the other groups were only taken on day 21.
Dietary Niacin Content
The content of niacin in the feedstuffs were calculated based on table values [2,18] and on the information of the niacin manufacturers.
Blood Niacin Concentrations
Blood samples of both experiments were centrifuged at 3000× g for 30 min at 15 °C and the serum obtained was stored at −80 °C until analysis. Serum samples were analyzed for the concentrations of NAM and NA using HPLC. At first, samples were thawed at 20 °C and then homogenized which was followed by protein precipitation and fat extraction using ice cold ethanol and n-hexan. After centrifugation at 14,000 rpm, the supernatant was transferred into an amber flask and evaporated in a nitrogen stream at 40 °C and the residue was dissolved in 150 µL of the aqueous mobile phase A. After filtration (syringe filters, 0.45 µm, PVDF, amchro GmbH) 20 µL of the filtrate were injected automatically into a HPLC system (model SCL-10A controller, model LC-10AS pump, model SIL-10AC autosampler, model CTO-10AC oven; Shimadzu, Kyoto, Japan). Samples were run through a C18 column (Insertil ODS, 150 × 3 mm, 5 µm particle size, 150 Å pore size) by using a binary gradient system at a flow rate of 0.4 mL/min. The composition of mobile phase A was 10 mM sodium 1-hexanesulfonate monohydrate in ultrapure water at a pH of 2.3, while mobile phase B was 100% acetonitrile. The gradient profile started with 100% mobile phase A for 10 min, followed by a linear decline to 97% during 10 min and to 60% mobile phase A within the next 2 min. During the following 10 min the system returned to the initial conditions. Quantification of NAM and NA was done simultaneously by a multi wavelength detector at a wavelength of 260 nm. The retention times of NA and NAM were 13.5 min and 18.7 min, respectively. For preparation of standard solutions NA and NAM from Sigma-Aldrich (Steinheim, Germany) was used. Stock solutions (400 µg· mL −1 ) were prepared in bi-distillated water and stored at −20 °C. Mixed standard working solutions in the range of 0.20-2.00 µg· mL −1 were obtained by dilution of stock solutions with mobile phase A directly before use. Quantification was performed comparing peak area with standard curves.
Calculations and Statistics
Fat-corrected milk (FCM) was calculated following Gaines [19]: For analyzing the performance parameters PROC MIXED procedure of the SAS-software package (SAS Enterprise Guide 6.1) was used. Data were analyzed in two steps. First, all experimental groups were considered as separate treatments irrespective of further possible classification traits resulting in a one-factorial design with the treatment group (N = 7) as fixed factor. Secondly, the CON group was excluded from data evaluation to enable the more powerful examination of the pooled effects of NA dose (6, 12 or 24 g) and of the galenic form of the NA supplements (nRP or RP) resulting in a complete 3 by 2 two-factorial design with NA dose, galenic form and their interactions as fixed factors.
For both evaluation strategies, the frequent time-dependent measurements during the experiment for each individual cow were considered as repeated measures where applicable (24_RP; 24_nRP). After testing various structures for the model, the first order autoregressive (ar (1)) showed the lowest Akaike information criterion.
For assessing the serum niacin concentrations of 6_nRP, 12_nRP, and 24_nRP as well as 6_RP, 12_RP, and 24_RP on day 21, the PROC MIXED procedure of the SAS-software package (SAS Enterprise Guide 6.1) was used and the dose (6, 12, or 24 g) and the galenic form of the NA supplement (nRP or RP) and the interaction between those factors were set as fixed effects.
For time-sequence data of 24_nRP and 24_RP, linear regression analysis and subsequent slope comparisons were performed using the PROC MIXED procedure of the SAS-software package (SAS Enterprise Guide 6.1) to investigate the time-depending blood profiles between 24_nRP and 24_RP during the three week feeding period. In particular, the model included the galenic form as fixed factor and the experimental day as a covariate with the galenic form nested in the covariate to enable estimating linear regression coefficients (slopes) for both galenic forms which characterize the blood NAM changes over time. The individual animal was handled as a random factor to consider similarity within individuals. The difference between both regression slopes was tested for significance using the "ESTIMATE" statement.
Experiment 2
For evaluating the data a non-linear regression model of the application STATISTICA (StatSoft, version 10) was used to fit the data of nRP_P, nRP_M, RP_P, and RP_M according to Mercer, et al. [20]: where Rmax is the maximum theoretical NAM concentration, x is the apparent kinetic order, K0.5 is the time for ½ of Rmax and Ks, is the time indicative for the decreasing part of the regression. The estimated parameters were used to calculate the area under the serum concentration time curve (AUC) numerically by applying the trapezoidal method with the formula: with ∆timen = 0. The parameter Imax, the time of occurrence of Rmax, was calculated as follows: = ( s 0.5 ) 0.5 As feeding of the basal (CON) concentrate feed did not reveal a distinct systemic niacin peak the corresponding time-dependent blood concentrations were not fitted to Equation (2) but just subjected to AUC determination according to Equation (3).
The PROC "MIXED" procedure of the SAS was used evaluating the pharmacokinetic parameters of the serum samples. The form of the concentrate (pellet or meal) and the galenic form of the NA supplement (nRP or RP) and the interaction between those factors were considered as fixed effects. The cow which is the subject was considered as a random effect.
Before calculating the relative bioavailability with the following formula, the control feeding related AUC was subtracted from the corresponding AUCs of the other dietary treatments.
Relative bioavailability = 24 dietary treatment 24 reference treatment (nRP − M) with non-rumen protected NA mixed into the concentrate and presented in a meal form (nRP_M) declared as the reference treatment. In all statistical investigations using PROC MIXED procedure of SAS, degrees of freedom of PROC MIXED procedure were calculated using the Kenward-Roger method. For determination of differences between LSMeans, the probability ("PDIFF") option was used applying a Tukey-Kramer test for post-hoc analysis. Differences were considered to be significant when F-test statistics revealed p < 0.05, whereas a tendency was noted if p < 0.10 and p > 0.05.
Results
Only concentrations of NAM were detected in serum samples while the concentrations of NA was always lower than the detection limit.
Experiment 1
The overall performance level of the cows is reflected by the pooled average daily DMI of 20.3 kg at the first experimental day, and 18.9 kg on day 21 of the experiment. The overall data evaluation revealed no significant differences between the treatment groups and the CON group (The mean milk yield and FCM of group CON were 25.7 ± 4.2 kg/d and 28.8 ± 4.8 kg/d. Mean yield of milk fat, milk protein, and milk lactose were 1.2 ± 0.2 kg/d, 0.90 ± 0.11 kg/d, 1.2 ± 0.2 kg/d, whereas mean urea concentration was 203 ± 36.8 ppm.).
Excluding the CON group from data evaluation enabled a more powerful examination of the pooled variance caused by NA dose and galenic form, i.e., by evaluating the data according to a complete 3 (NA doses) by 2 (galenic forms) design (Table 2). However, even under these data evaluation conditions no significant effects of NA dose or galenic form could be identified for the performance parameters. Table 2. Effects of oral supplementation of 6, 12, or 24 g non-rumen protected or rumen protected nicotinic acid on lactation performance of dairy cows (Experiment 1). The NAM concentrations of 24_nRP and 24_RP were investigated on day 1, 3, 6, 10, and 21. As shown in Figure 1, the serum NAM concentration decreased linearly after the first NA uptake in both groups which was more steeply in 24_nRP compared to 24_RP (p = 0.03).
Experiment 2
Due to problems with venous catheter, not each cow received each dietary treatment. Four cows received CON, RP_P and RP_M, whereas three cows received nRP_P and nRP_M. It was ensured that no cow received the same dietary treatment twice. The daily intake of NA was 22.3 g NA and therefore Thirty min before oral dosing, NAM concentrations of nRP_P, nRP_M, RP_P, and RP_M were 0.5 ± 0.2 µg/mL, 0.9 ± 0.2 µg/mL, 0.8 ± 0.2 µg/mL, and 0.8 ± 0.2 µg/mL and did not differ between the dietary treatments. The supplementation of nRP NA resulted in higher Rmax values compared to RP NA (p = 0.03). Feeding nRP NA accelerate the rate of absorption (p = 0.05), because Rmax of nRP NA occurred 1.7 h before the Rmax of RP NA (p = 0.05). Ks was higher when supplementing RP NA compared to nRP NA (p = 0.05). The interaction between the form of concentrate and the galenic form of the supplement influenced Rmax (p = 0.01) and K0.5 (p = 0.02). The use of nRP NA in pelleted form resulted in higher Rmax and K0.5 values compared to the ground form, whereas in the case of RP NA, grounding of the concentrate provoked an increase of Rmax and K0.5 values.
General Remarks on Serum NAM and NA Levels in Bovine Blood
Literary statements regarding circulating blood levels of niacin and the presence of its vitamers are highly variable. As in the present study, Niehoff, et al. [12] (6 g) also detected only the vitamers NAM within the blood serum when using the HPLC-method. However, Campbell, et al. [21] and Morey, et al. [14] also used the HPLC method for the determination of blood niacin concentrations, but they detected both vitamers, NAM and NA. In this respect, it is important to point out that those research groups used bovine plasma as matrix. Therefore, observed differences in plasma and serum vitamer profile might be related to the use of different biological matrices. This might be confirmed by the results of Rungruang, et al. [22] who observed that the niacin concentration varied in different biological matrices with being highest in whole blood followed by red blood cells and leukocytes, milk, and plasma. Beside the explanation of different biological matrices as a cause for the absence of NA in the serum of the present animals, it can further be assumed that this might be due to a rapid conversion of NA to NAM. Ying [1] stated that mainly NAM is used as NAD precursor and therefore the conversion of dietary NA to NAM might be likely.
Effects of NA Supplementation on Serum NAM Concentrations
Present data reveal a dose-effect in experiment 1 with highest NAM concentrations when supplementing 24 g NA and lowest concentrations when supplementing 12 g NA. Present results disagrees with observations of Rungruang, et al. [22] who detected that plasma niacin concentrations increased linearly with increasing rumen protected niacin dose. A numerical and linear increase was obvious when supplementing nRP NA in the present study which was absent when supplementing RP NA. However, it remains fairly unknown why this dose-response relationship was not observed when supplementing RP NA. One explanation might be that these groups suffered from a reduced feed intake which cannot be more specified due to the absence of information of feed intake behavior. In interpreting the blood NAM levels of Experiment 1, it should be considered that just spot blood samples were examined. As Experiment 2 clearly showed that blood NAM levels depend on time relative to intake of NA supplemented feed it can well be that blood samples in Experiment 1 were collected at varying times within the expectable time-dependent systemic NAM fluctuations. However, this hypothesis for explanation of the failure of a clear dose-response relationship cannot further elaborated as standard deviations did not vary amongst all experimental groups.
In the study of Rungruang, et al. [22] plasma niacin concentrations were 1.23, 1.43, 1.50, and 1.65 µg/mL when supplementing 0, 4, 8, or 12 g to thermoneutral, lactating cows [22]. When using the linear regression model stated by Rungruang,et al. [22] the plasma niacin concentrations would increase up to 2.06 µg/mL when supplementing 24 g RP niacin to thermoneutral, lactating cows. Present results might confirm this prediction, as NAM concentrations ranged between 2.2 and 2.5 µg/mL at the beginning of experiment 1. Additionally, peak NAM concentrations were around 2.2 µg/mL in Experiment 2.
In contrast to the present study, where NA could not be detected, Rungruang, et al. [22] stated information about plasma niacin concentrations without differing between NA and NAM or other vitamers. As shown by Morey, et al. [14] NA accounts only for a very small fraction to total blood niacin concentrations which might be confirmed by the present results as NA was under the detection limit. Therefore, plasma niacin concentrations observed by Rungruang, et al. [22] might represent mainly the vitamer NAM making those plasma concentrations comparable to the present results.
Niehoff, et al. [5] and Hannah and Stern [23] suspect that there is a specific concentration of niacin within the rumen which regulates endogenous microbial niacin synthesis. This specific concentration might have regulatory functions like the inhibition of endogenous niacin synthesis in times of additional niacin supply associated with increased microbial degradation of the oversupplied niacin and the increased synthesis of niacin by ruminal microorganisms in the absence of niacin supplementation. Despite the continuous supplementation with 24 g nRP or RP NA, present NAM concentrations decreased towards the end of the experiment which might be a result of exceeding this specific ruminal concentration [5,23]. However, results of Jaster, et al. [24] might weaken the assumption of a specific ruminal concentration, because those researchers observed that serum NA concentrations increased continuously in postpartum dairy cows when supplementing 12 g niacin. On the other hand, the decrease in NAM concentrations might be related to a decreasing DMI, because feedstuffs used in ruminant nutrition are potential sources of niacin [18]. One explanation for the decreased DMI might be that the cows were nearly at the end of gestation which is often associated with a slight decrease in DMI. However, precise information on the DMI of the cows of the present study is lacking, because the consumption of the PMR was recorded group-specific. In addition, present results indicate that NAM concentrations decrease also when using encapsulated NA although this decrease was not as pronounced as in the case of nRP NA. If this decline in RP NA is due to the fact that the ruminal stability of this product is not as high as declared, remains unknown.
Therefore, present results highlight the need for future research aiming to increase the knowledge of relationships between oral niacin supply, feed intake, and ruminal metabolism.
The present results of experiment 2 indicated that maximum theoretical NAM concentrations were higher after nRP NA supplementation. However, as the AUC24 did not differ between nRP and RP NA, a lower bioavailability in RP NA as a consequence of an incomplete release of RP NA can be excluded within the observation period of 24 h. It should be noticed that NAM concentrations detected after 24 h were higher than the baseline level before feeding the supplements. Thus, the relative bioavailability reported herein applies only for the kinetic processes within the first 24 h. For comparative purposes between treatments these limitations have to be considered. However, one has to keep in mind that nRP NA reached maximum theoretical NAM concentrations 1.7 h earlier than RP NA, but that K0.5 values were higher for RP NA. The slower release of niacin from RP NA into the circulation combined with a longer persistence resulted in a similar AUC24 of nRP and RP NA although lower maximum theoretical NAM concentrations when supplementing RP NA. The present observations might confirm the statement mentioned above that both forms are able to affect serum NAM concentrations similarly. However, present results indicate different kinetic parameters which suggest slight differences in the degree of release from the matrix (liberation), absorption, degradation within the rumen, intestinal absorption, and/or elimination.
An important finding of experiment 2 is that serum NAM concentrations of both forms started to increase already 30 min after feeding. Recent studies showed that niacin is not able to accelerate liquid or particulate ruminal fractional turnover rate [6,7]. Mambrini and Peyraud [25] stated that the mean retention time (MRT) for ruminal liquids is 8.7 h and that the MRT increase with increasing particle size. It can be assumed that small amounts of ruminal fluid reach the duodenum within one hour. On the other hand, present results provide evidence that some part of absorption of both galenic forms might occur before the duodenum. However, to our knowledge, no study exists which focuses on ruminal absorption mechanisms of niacin. Nicotinic acid is a monocarboxylic acid and it was shown that NA is transported by a sodium-coupled monocarboxylate transporter (SLC5A8) in a mouse model [26]. By investigating the transcriptome of the rumen epithelium, Baldwin, et al. [27] detected that SCL5A8 is also present in rumen epithelium which provide indications for ruminal absorption mechanisms. Furthermore, there are indications that NA is transported by the monocarboxylate transporter-1 (MCT1) [28]. As MCT1 also exists within the rumen epithelium [29], ruminal absorption of NA seems likely.
Effects on Milk Production
Consistent with our results, Niehoff, et al. [12], Morey, et al. [14] and Aschemann, et al. [30], found no effect of NA on milk yield, FCM as well as milk fat, milk protein, and milk lactose yield. It may be concluded that the experimental time of the present study was too short to induce differences in milk performance, although NAM concentrations were moderately elevated. Another explanation is that present cows were in positive energy balance and as NA is able to balance enhanced lipid mobilization by the downregulation of lipolysis [13], it can be concluded that the absence of effects on milk production parameters is due to absent disturbances in energy metabolism.
Conclusions
In all, both forms are readily available for ruminant's metabolism and are able to substantially affect serum NAM concentrations indicating that the ruminal degradation of nRP is not as massive as assumed formerly [4]. However, both experiments revealed significant protective effects of the encapsulated NA supplement as indicated by significantly higher blood levels under ad libitum conditions (Exp. 1), in a decelerated absorption of NA (significantly prolonged Imax) and a significantly prolonged elimination from the systemic circulation (longer Ks) possibly attributable to the slower release from the NA formulation (Exp. 3). Therefore, results of both experiments support the view that rumen protection of NA increases the systemic NA availability.
However, present results suggest that the absorption of oral supplemented nicotinic acid might have already start within the rumen. Therefore, investigations concerning absorption mechanisms should be followed up to increase the knowledge of niacin within the cow. The nature of the time-dependent decrease in blood niacin concentrations as well as a potential interaction with ruminal microorganisms needs to be elucidated in future studies where the level of total dry matter intake should be especially addressed as a source of variation. | v3-fos |
2016-05-16T09:32:20.826Z | {
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} | s2 | SS1 (NAL1)- and SS2-Mediated Genetic Networks Underlying Source-Sink and Yield Traits in Rice (Oryza sativa L.)
Source leaf/sink capacity (SS) traits are important determinants of grain yield (GY) of rice. To understand the genetic basis of the SS relationship in rice, five SS and GY traits of rice were genetically dissected using two reciprocal introgression populations. Seventy-three QTL affecting the SS and GY traits were identified, most of which were detected in one of the parental genetic backgrounds (GBs). Two major QTL at bins 4.7 (SS1) and 3.12 (SS2) were associated consistently with all measured SS and yield traits in both GBs across two contrasting environments. Strong interactions between SS1/SS2 and the detected QTL led us to the discovery of genetic networks affecting the SS and GY traits. The SS1 acted as a regulator controlling two groups of downstream QTL affecting the source leaf width and grain number per panicle (GNP). SS2 functioned as a regulator positively regulating different groups of downstream QTL affecting the source leaf length, GNP, grain weight, and GY. Map-based cloning of SS1 indicates that SS1 is NAL1 involved in polar auxin/IAA transport. Different alleles at NAL1 were apparently able to qualitatively and/or quantitatively control the IAA transport from the apical meristem to different plant tissues and thus regulate those downstream loci/pathways controlling different SS traits of rice. There was a functional allele and a non-functional mutation in the parents at each of the QTL downstream of SS1 or SS2, which were detectable only in the presence of the functional allele of SS1 or SS2. Our results provided direct evidence that SS and yield traits in rice are controlled by complex signaling pathways and suggest further improvement of rice yield potential with enhanced and balanced SS relationships can be achieved by accurately manipulating allelic combinations at loci in the SS1 and SS2 mediated pathways.
Introduction
Rice (Oryza sativa L) is the staple food of most Asian people. Rice productivity has been more than tripled in China, resulting primarily from the Green Revolution since late 1950s and the hybrid rice technology in late 1970s. However, progress has been slow for more than 2 decades to further improve yield potentials of modern rice cultivars despite tremendous breeding efforts. Plant physiologists believe that high yield potentials of cereal crops are largely determined by enhanced and balanced relationships between the source, sink and flow of assimilates [1,2]. In rice, grain number per panicle (GNP) and grain size are the primary components of the sink capacity for photosynthetic product accumulation. The upper three leaves, especially the flag leaves, are the primary source of assimilate-supply for grain yield [3][4][5]. Besides, efficient transport of assimilates from leaves and stems to developing grains is also important for better grain filling and high yield [6,7]. Therefore, characterizing genes/QTL underlying the sink-source (SS) relationship will greatly enhance our understanding of the genetic basis of yield potential in rice.
Past decades have witnessed tremendous efforts in mapping QTL affecting SS and yield traits in rice. Results from these studies indicate that rice yield and its components are controlled by large numbers of QTL across the rice genome, and influenced by complex epistasis and QTL × environment interactions [8][9][10][11][12][13][14][15][16][17][18][19][20]. An important discovery is that QTL affecting yield traits differ greatly in their phenotypic effects and QTL of large effect tend to be associated with multiple related traits, forming QTL clusters [21,22]. To date, many large-effect QTL affecting yield traits in rice have been cloned [23][24][25][26][27][28][29]. In most cases, the large phenotypic effect (s) at each of the cloned QTL result from the allelic difference between a functional allele and a loss or partial loss of function mutant, though the cloned yield QTL genes have diverse molecular functions [22][23][24][25][26][27][28][29]. Meanwhile, several cases of marker-assisted transfer of large-effect QTL for improving complex traits have been reported with mixed results. Very often, the phenotypic effects of these large-effect QTL tend to vary considerably across genetic backgrounds (GBs) and environments [30][31][32][33][34][35][36]. To date, no successful story for developing new high yielding rice varieties has been reported by marker-assisted selection (MAS) of large-effect QTL. While these large-effect QTL represent only a very small portion of the genes that contribute to genetic variation of complex traits, most reported QTL in rice have moderate effects that vary considerably across different environments and GBs and tend to be involved in complex epistasis [15,[19][20][21]37]. Meanwhile, few efforts have been taken to confirm and characterize 'smalleffect QTL' by cloning or to use them as target QTL for trait improvement in MAS experiments. Further, we found that most QTL affecting grain shape and size traits of rice were detectable only in one of the parental GBs [38]. This raises a serious question on the classic quantitative genetics theory which predicts that all main-effect QTL should be detectable in both parental GBs and QTL main effects and epistatic effects in the model are independent from one another [37,39]. Theoretically, linking phenotypic variation of complex traits to its underlying genes and gene networks have been the greatest challenge because the classical quantitative/population genetics models and relevant statistical methodology have a limited power to detect and characterize high-order epistasis, which is predicted to exist based on the current knowledge of molecular genetics. Recently, we developed the theoretical framework of molecular-quantitative (function-mutation) genetics models that allow detection and characterization of genetic networks underlying complex traits [40]. In other words, genes involved in the same signaling pathways segregating in a mapping population can be detected as "genetic networks" based on the epistatic and predicted regulatory-regulated relationships between QTLs affecting a complex trait either using either the quantitative genetics approach or population genetics approach [20,41,42].
Here, we validated the theory by detecting and characterizing the genetic networks underlying SS and grain yield traits of rice using two reciprocal introgression line (IL) populations, and by map-based cloning one large-effect QTL that acted as a regulator in the upstream of the auxin/IAA mediated signaling pathways controlling SS and yield traits in rice. Our results provide direct evidence for the presence of complex genetic networks controlling complex traits in rice and novel breeding strategies to improve rice yield potential through accurate manipulation of key regulatory loci and their downstream ones in rice.
Detecting the genetic networks underlying SS and yield traits
Materials. Lemont (LT), a commercial semidwarf japonica rice variety from Southern US was used as the female parent to cross with Teqing (TQ), a high-yielding semidwarf indica rice variety from China. The F 1 plants were backcrossed to TQ to develop a BC 1 F 1 population with 100 plants. The BC 1 F 1 plants were used as the male parent to backcross with TQ to produce the BC 2 F 1 population. Consecutive backcrossing was carried out in the same way until BC 3 F 1 and BC 4 F 1 populations followed by several generations of selfing, resulting in a set of 254 TQ-ILs, consisting of 133 BC 2 F 8 , 96 BC 3 F 7 and 25 BC 4 F 6 lines [43]. The procedure for developing 201 LT introgression lines was similar using LT as the recurrent parent. The LT-ILs consisted of 32 BC 2 F 8 , 123 BC 3 F 7 and 46 BC 4 F 6 lines [15].
Phenotyping experiments. The two sets of 455 reciprocal ILs and parents were evaluated for SS and GY traits in Sanya (18.3°N, 109.3°E) in the 2007 winter season and Beijing (40.2°N , 116.2°E) in the 2008 summer season. In both Beijing and Sanya, seeds of each lines were sown on the seedling nursery and 30-day-old seedlings of each line were transplanted into a 2-row plot with 12 plants per row at a spacing of 20 × 17 cm in the field of the experimental farms, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences. A randomized block design was used in each experiment with 3 replications for each line. Two applications of insecticides were applied to control brown planthoppers in the SY experiment. Weeds were controlled by a combination of chemical and manual methods. Measurements for the source leaf traits, flag leaf width (FLW, in mm) and flag leaf length (FLL, in cm), were taken on 3 main stems of each plant in the middle 10 plants of each plot. At the maturity, ten representative plants in each plot were sampled and dried under 72°C for 3 days in an oven. Then, the sampled plants were measured for grain number per panicle (GNP), 1000-grain weight (GW, in g) and grain yield per plant (GY, in g).
Genotyping and linkage map construction. The two sets of ILs were genotyped with the same set of 478 well distributed DNA markers, including 151 simple sequence repeat (SSR) markers, 3 morphological markers and 324 well distributed anchor single nucleotide polymorphic markers (SNPs) (S1 Table) [44]. Two linkage maps were constructed separately from the LT-ILs and TQ-ILs using the MAPMAKER version 3.0. The two resulting linkage maps constructed from the reciprocal IL sets were very similar with 1734.4 cM for the TQ-ILs and 1661.0 cM for the LT-ILs, respectively (S1 Fig). The LT-ILs had an average 83.8±15.5% the LT genome. The TQ-ILs had an average 88.9±8.1% of the TQ genome.
Detecting QTL and QTL networks affecting the SS and GY traits. QTL affecting the SS and GY traits in each of the IL populations were identified by detecting the trait-marker associations using the phenotypic data obtained from each environment and single marker analyses using the SAS PROC GLM [45], in which y k = μ + a i x ik + e, where y k is the phenotypic value of a trait measured on the kth individual; μ is the population mean; a i is the main effect of the one putative QTL; x ik is coefficient of QTL effect derived according to the observed genotypes of the markers; e~N(0,σ e used as the threshold to claim a main-effect QTL in at least one of the population/environment combinations. The putative genetic networks consisting of interacting QTL affecting the SS and GY traits were constructed based on the new function-mutation model of the quantitative genetics theory [20,40]. In this model, two new concepts, functional genetic units (FGUs) and the principle of hierarchy are defined based on two commonest types of functional relationships between genes acting in a signaling pathway affecting complex traits. An FGU represents the mutual functional dependency (FD) among a group of genes functioning at each level of a signaling pathway which affect phenotype(s) in a manner of "house of cards" or complete complementarity. Hierarchy reflects the one-way FD of genes in downstream pathways on their upstream regulator(s). Epistasis is predicted to result from these two types of FD between or among unlinked loci within a signaling pathway. Based on this model, genetic networks underlying the SS and yield traits were detected in 3 steps. First, two-way ANOVA was conducted to detect all significant pairwise epistasis between QTL identified in each of the population/environment combinations with a threshold of P 0.005 in at least one of the population/environment combinations, in which y k = μ + a i x ik + a j x jk + aa ij x ijk + e, where y k is the phenotypic value of a trait measured on the kth individual; μ is the population mean; a i and a j are the main effects of the two putative QTL (Q i and Q j ), respectively; aa ij is the epistatic effect between Q i and Q j ; x ik , x jk , and x ijk are coefficients of QTL effects derived according to the observed genotypes of the markers; e~N(0,σ e 2 ) is the random residual effect. Second, once significant epistasis was detected between two QTL, their relationship and the nature of the parental alleles (a functional one vs a non-functional mutant) were then determined either as one-way FD (one QTL is in the upstream and the other in the downstream) or as the mutual FD (complementarity) by examining if the observed mean trait values of the digenic genotypes fit the expected patterns of the corresponding theoretical models. Third, the pathway effect of each interacting QTL pair was estimated based on the genetic expectations of the multi-locus genotypes and the obtained QTL main and epistatic effects [20,40].
Map-based cloning of SS1
The following experiments were conducted to clone a major QTL, SS1, on rice chromosome 4 that had large and consistent effects on SS traits (FLW and GNP): Development of near isogenic lines (NILs) and fine mapping of SS1. S2 Fig shows the detailed process in fine mapping SS1. Briefly, a BC 2 F 5 TQ-IL (GG253) carrying the homozygous LT introgression in the SS1 region flanked by RM317-RM348 on chromosome 4 and 90.5% of the TQ GB was selected to cross with TQ. The resulting 25 BC 3 F 1 plants were backcrossed to TQ to produce 385 BC 4 F 1 plants. The 4 BC 4 F 1 plants were selfed to generate a 650 BC 4 F 2 population. Six plants with heterozygous genotype at the target region on chromosome 4 and homozygous Lemont genotypes at all other non-target regions were selected in the BC 4 F 2 based on foreground and background selections with 550 SSR markers across the 12 rice chromosomes. In the 2009 winter season, 6,000 BC 4 F 3 Plants were planted in the CAAS experimental farm in Sanya. We developed some insertions and deletions (InDel) and cleaved amplified polymorphic sequences (CAPS) markers in the target region designed from the reference Nipponbare and 93-11 genomic sequences (S2 Table) and determined genotypes of the recombinants with these markers. Fifteenplants heterozygous at the target SS1 region and homozygous TQ genotypes at all non-target regions were selected. The 12,000 BC 4 F 4 segregating individuals were genotyped to identify recombinants in the SS1 region for further fine mapping SS1. The same process was repeated and phenotypic comparisons in FLW and GNP were made between the two parental homozygous recombinants identified inside the target region in the progeny to gradually narrow down the target SS1 region. Finally, a NIL-SS1 containing the LT alleles at SS1 in a small region of 50.3 kb flanked by markers RM3534 and FL98 on chromosome 4 was identified in the TQ BC 4 F 5 population.
Sequence analysis. The parents (TQ and LT) and the NIL-SS1were sequenced for 3 positional candidate genes in the 50.3 kb target region and their promoter regions upstream the transcription starting site. DNA fragments from the materials were amplified with high fidelity using a LA-Taq kit (TakaRa, Dalian, China). The PCR products were cloned into a pGEM-T vector (Promega, USA) according to the manufacturer's specification. The T7 and SP6 universal primers and BigDye Terminator Cycle Sequencing v3.1 (Applied Biosystems, CA, USA) were used for sequencing. Sequence contigs were assembled using the computer program SEQUENCHER 4.1.2. Sequence alignment was conducted using computer program Clustalx 1.83.
Gene expression analysis. Total RNA from young panicles, flag leaves, leaf sheaths, nodes, internode, roots, root and stem junctions of the parents and NIL-SS1 was extracted at the panicle initiation stage using the TRIzol Reagent Kit (Invitrogen, Carlsbad, USA) and treated with DNase I. cDNA was synthesized from 2 μg RNA using SuperScript III Reverse Transcriptase. Quantitative analyses of expression of the candidate genes in different tissues were performed using SYBR Premix Ex TaqTM on an Applied Biosystems 7500 Real-Time PCR System. The relative expression of each transcript was obtained by comparison with the expression of the rice gene ubiquitin. The primers used for the quantitative real-time PCR are listed in S3 Table. Phenotypic characterization. The NIL-SS1 and parents (LT and TQ) were evaluated for their agronomic performances under the normal irrigated field conditions two locations, Hangzhou (30.3°N, 120.2°E), Beijing and Sanya in 3 seasons from 2010-2012. The plants were grown in plots of 13.2 m 2 at a space of 16.5 cm between plants within a row and 25 cm between rows in a randomized complete block design with three replications for each of the NIL-SS1 and parents. The field management followed the standard rice cultivation practices. Eight plants in each plot were sampled and measured for yield and its component traits, including plant height (PH, in cm), productive panicles per plant (PP), FLW, FLL, panicle length (PL, in cm), GNP, filled grains per panicle (FGP), GW, grain length (GL, in mm), grain width (GWH, in mm), GY. Grain yield per plot in kg was measured by harvesting all plants in each plot. Also, the NIL-SS1 and parents were assayed for physiological traits related to yield, including photosynthesis rate (P n ), stomata conductance (g s ), intercellular CO 2 concentration (C i ), transpiration (T r ) and specific leaf weight, at the booting, flowering, grain filling at 7, 14 and 21 days after flowering (DAF) during 9:00-11:00 am on clear days using a portable gas analysis system LI-6400. Accumulation of dry matter in panicles and rate of dry matter translocation in stems and sheaths of the NIL-SS1 and TQ were assayed between at the booting, flowering, grain filling at 7, 14 and 21 DAF.
Identification of the genetic networks underlying the SS and yield traits
Phenotypic variation of the reciprocal ILs. The parents differed significantly for all traits except for GW in both Sanya and Beijing (S4 Table). TQ had longer FLL, more GNP and slender FLW than LT. It had 178.5% and 187.1% higher yield than LT in Sanya and Beijing. Both the LT-ILs and TQ-ILs showed continuous variations with transgressive segregations toward both directions for all traits except for GY. ANOVA indicated that the differences among different genotypes (G) within each set of ILs were highly significant for all measured SS traits and explained an average of 48.7±15.8% of the total phenotypic variation in the IL populations, ranging from 21.0% for GY to 68.0% for GW (S5 Table). The difference between the two locations (E) was also highly significant for all traits except for GW in the LT-ILs and explained an average 16.5±14.3% of the total phenotypic variation in the IL populations, ranging from 0.1% for GW to 37.6% for GY. G x E interaction was also significant for all measured traits but explained an average 15.3±3.0% of the total phenotypic variation in the IL populations.
GB effects of the detected M-QTL and their interactions with the environments. The identified M-QTL showed strong GB effects (S6 and S7 Tables). Of the total 69 detected M-QTL, only 5 M-QTL of large effect at bins 3.12 (qFll3.12, qGnp3.12 and qGw3.12a) and 4.7 (qFlw4.7 and qGnp4.7) were consistently detected in both GBs and environments, though their effects varied considerably in different GBs. The two QTL clusters at bins 4.7 and 3.12 are designated as SS1 and SS2. Four other M-QTL (qFlw6.5, qGw7.5, qFll12.4 and qFlw12.4) had consistent effects in both GBs, but qFlw6.5 was detectable only in Sanya whereas qGw7.5 only in Beijing. Bin 12.2 was associated with FLW in both IL populations, but the LT allele at this region increased FLW in Sanya by 0.8 mm in the TQ-ILs and reduced FLW by 0.7 mm in the LT-ILs in Sanya, suggesting the presence of two different FLW M-QTL (qFlw12.2a and qFlw12.2b) in this region. Similarly, bins 6.7 and 8.4 were associated with GNP in both IL populations with the LT allele at bin 8.4 increased GNP in the LT-ILs but reduced GNP in the TQ-ILs, and the reverse was true for bin 6.7, again suggesting the presence of two different GNP M-QTL in each of the regions.
Of the 41 M-QTL identified in the TQ-ILs, 23 Table). Interestingly, 11 of those M-QTL (the underlined ones) became detectable in both environments when involved in epistasis (S7 Table).
The genetic networks underlying the SS and yield traits. S7 Table shows 87 highly significant interactions between 46 QTL, 34 of which were the identified M-QTL plus 12 additional epistatic QTL. All, except three (qFll3.12 vs qFll11.3, qFll3.12 vs qFll8.4 and qGnp4.7 vs qGnp1.8), of these interactions were detected only in one of the parental GBs, but in both environments.
When the patterns of the observed mean phenotypes of the digenic genotypes at each of the interacting QTL pairs were fitted to the expectations of the function-mutant model [40], two types of FD could be inferred between the interacting QTL, i.e. the one-way FD of a downstream one on its upstream one and the mutual FD between two loci in the same pathway. Furthermore, it could be inferred that the parental alleles at each locus of the interacting QTL pairs consisted of one function allele and a non-functional mutant allele. This information allowed us to construct putative genetic networks underlying the measured SS and yield traits (Fig 1).
The SS1 mediated pathways. Fig 1A shows the SS1 (bin 4.7) mediated genetic network consisting of 11 QTL affecting FLW and GNP with the LT alleles at SS1 predicted to be the regulator(s) controlling 10 QTL of two major groups in the downstream, supported by 21 significant pairwise interactions (S7 Table). Group I-1 included qFlw4.7 as the regulator and 7 FLW QTL in two downstream branches. Branch I -1-1 comprised 6 interacting QTL with qFlw3.5 in the upstream, 4 interacting QTL (qFlw6.3, qFlw6.6, qFlw2.4 and qFlw11.3) in the middle, and qFlw2.2 in the downstream (interactions 1-16 in S7 Table). The LT alleles at all 6 loci of branch I -1-1 were inferred to be functional while the TQ alleles were non-functional mutations at these loci. Branch I -1-2 contained a single QTL qFlw12.2a in the downstream of qFlw4.7 with the functional allele from TQ and estimated a pathway effect of 1.3 (1.8) mm for increased FLW in Beijing (Sanya). Group I-2 had 3 loci in the downstream of qGnp4.7 affecting GNP only. Branch I -2-1 (qGnp2.2) had a pathway effect of 29 (17) for increased GNP in Beijing (Sanya) (interaction 18 in S7 Table). Branch I -2-2 (qGnp8.4b) had a pathway effect of 39 (34) for increased GNP in Beijing (Sanya) (interaction 20 in S7 Table). Branch I -2-3 had qGnp4.1 in the downstream of qGnp4.7 with an estimated pathway effect of 29 (57) for increased GNP in Beijing (Sanya) (interaction 27 in S7 Table). The functional alleles for all GNP QTL downstream of SS1 were from TQ. In addition, qGw4.7 at SS1 interacted with qGw2.4 in a complementary manner with the LT/LT genotype having 2.4 (2.5) g of heavier GW than the remaining 3 digenic genotypes in Beijing (Sanya) (interaction 34 in S7 Table), suggesting the LT alleles at both loci were functional.
The SS2 mediated pathways. Fig 1B shows the SS2 mediated genetic network with qFll3.12, qGnp3.12 (qGy3.12) and qGw3.12 as inferred regulator(s) and 20 QTL in three major downstream groups, supported by 60 highly significant pairwise interactions (S7 Table). Group II-1 consisted of qFll3.12 as the regulator controlling 6 FLL QTL in 3 downstream braches (interactions 35-46 in S7 Table). Branch II -1-1 contained 3 interacting loci with qFll1.8 in the upstream and 2 interacting loci (qFll2.6 and qFll8.4) in the downstream with a pathway effect of 3.3 (2.2) cm for increased FLL in Beijing (Sanya). Branch II -1-2 contained qFll6.7 in the downstream of qFll3.12 with a pathway effect of 2.5 (2.4) cm for increased FLL in Beijing (Sanya). Branch II -1-3 consisted of 2 interacting QTL with qFll3.5 in the upstream and qFll11.3 in the downstream and a pathway effect of 3.0 (2.9) cm for increased FLL in Beijing (Sanya). The LT alleles at all 6 downstream loci were inferred to be functional, while the TQ alleles at these loci were non-functional mutants.
Group II-2 was the most important one with qGnp3.12 (qGy3.12) as the regulator controlling 10 downstream loci affecting GNP and GY (Fig 1B), supported by 45 highly significant interactions (S8 Table). Branch II -2-1 had qGnp6.7b (qGy6.7) in the upstream and 8 downstream loci affecting GNP and/or GY in 2 sub-branches. Sub-branch II -2-1-1 involved 4 interacting loci, qGnp4.1 (qGy4.1), qGy6.6, qGnp1.8 (qGy1.8) and qGnp6.3 (qGy6.3) with pathway effects of 32 (44) for increased GNP, and 8.5 g (13.4 g) for increased GY in Beijing (Sanya). Sub-branch II -2-1-2 involved 4 interacting loci affecting GY with qGy4.7 in the upstream and 3 loci (qGy2.2, qGy2.4 and qGy11.3) in the downstream (Fig 1B and S8 Table). II -2-2 (qGnp3.5 The SS2 (qFll3.12, qGnp3.12 and qGw3.12) mediated pathways affecting FLL, GNP, GW and GY. The rectangular and oval shaped boxes represent the interacting QTL detected in the LT-ILs and TQ-ILs, respectively, while the hexagon shaped boxes represent the interacting QTL detected in both IL populations. Single arrowed solid lines each connecting two interacting QTL indicate an inferred one-way functional dependency (FD) between a upstream QTL and a downstream one of the interacting QTL pair, while double-arrowed dot lines each linking two interacting QTL indicate the mutual FD between the interacting QTL in the same pathway, predicted based on the pattern of the mean trait values of the 4 digenic genotypes [40]. The estimated pathway effects on the traits of each downstream QTL are shown in S7 Table. Underlined QTL were also detected as main-effect QTL (S6 Table). c: The graphical genotypes of 9 high yielding LT-ILs at bin 3.12 (SS2) and its 11 downstream loci and their mean phenotypic values for GNP, GY and GW, in which the black boxes are the homozygotes of the introgressed donor (TQ) alleles and the patched one was heterozygous. and qGy3.5) was a single QTL downstream of SS2 with estimated pathway effects of 40 (61) for increased GNP, and 14.7 g (6.9 g) for increased GY in Beijing (Sanya). The TQ alleles at all above loci were predicted to be functional. In particular, Fig 1C suggests that co-introgression of the TQ alleles at SS2 (qGnp3.12/qGy3.12/qGw3.12b) and varied combinations of its 11 downstream loci affecting GNP, GY and GW QTL into 8 LT ILs resulted in an average increased GY by 95.5% (Fig 1C). Branches II -2-3 (qGnp8.4a) and II -2-4 (qGnp5.5) affected GNP only with the estimated pathway effects of 31 (25) and 31 (40) for increased GNP in Beijing (Sanya) with functional alleles at qGnp8.4a and qGnp5.5 from LT.
Group II-3 consisted of 4 pairs of interacting loci affecting GW. Of these, qGw3.12a was interacting with qGw1.8 and qGw4.1 in a complementary manner. The functional alleles at the three loci were all from LT for increased GW. The remaining two interactions occurred between qGw3.12b and qGw5.5 or qGw8.4. The TQ alleles at all three loci were predicted to be functional for increased GW. The functional genotype of the qGw3.12b and qGw8.4 pair was associated with significantly increased GY (S7 Table and Fig 1B).
Molecular cloning of SS1
To verify the genetic networks and validity of the theoretical model, the following experiments were conducted to clone SS1: Fine mapping of SS1. Genotyping of 6,000 BC 4 F 3 individuals derived from six BC 4 F 2 plants heterozygous only at SS1 with 6 markers identified 25 informative recombinants of three genotypes within this region (Fig 2A). Multiple comparisons of the homozygous recombinant BC 4 F 4 lines for FLW and GNP with the non-recombinant controls placed SS1 in a 309.9 kb region between FL25 and WY17 (Fig 2A). Further fine mapping using 12,000 BC 4 F 4 plants using six new markers between FL25 and WY17 identified 28 informative recombinants and five genotypic classes in the target region, narrowing SS1 down to a 50.3-kb region between RM3534 and FL98 in a single bacterial artificial chromosome clone, AL662950 (http://www. gramene.org/Oryza_sativa/, accessed on 2 Dec, 2014) ( Fig 2B). This region contains four predicted genes (LOC_Os04g52440, LOC_Os04g52450, LOC_Os04g52460 and LOC_Os04g52479) (http://rice.plantbiology.msu.edu/cgi-bin/gbrowse, accessed on 2 Dec, 2014). LOC_Os04g52440 and LOC_Os04g52450 each encodes a 4-aminobutanoate-pyruvate aminotransferase protein with 70% homology. LOC_Os04g52460 is a retrotransposon. LOC_Os04g52479 is previously reported as NARROW LEAF1 (NAL1), encoding a plant-specific protein involved in the auxin polar transport and acted in the upstream of the auxin/IAA signaling pathways [46,47]. Three naturally occurred alleles at NAL1 were also cloned as major QTL, SPIKE [48], GPS [49] and LSCHL4 [50] each with pleiotropic effects on FLW, SNP, roots, photosynthesis rate, yield, etc.
DNA sequence and protein structure variants of SS1. S3 Fig shows the complete DNA sequences containing the coding regions and 1440 bp upstream the transcription starting sites of the three SS1 candidate genes in the NIL-SS1, LT and TQ. For LOC_Os04g52440, the NIL-SS1, LT and TQ have the completely identical sequence in the coding region, but the NIL-SS1 (LT) allele has a 17-bp deletion, 2 nucleotide insertions and 14 SNPs upstream the transcription start site when compared with the TQ allele. In LOC_Os04g52450, many sequence variants were detected between the NIL-SS1 (LT) and TQ alleles, including three nucleotide substitutions in the coding region that resulted in amino acid variations, plus a 34-bp deletion, 38 SNPs and 9 small Indels/Deletions in the promoter region of the gene (S4 Fig). For LOC_Os04g52479 (NAL1), only a single SNP at site 160 upstream the start codon and one nucleotide change which results in the substitution of a histidine (CAT) in the trypsin-like serine and cysteine protease domain of the wide leaf group (NIL-SS1 and LT) by an arginine (CGT) in the narrow leaf group (TQ) (Fig 3A and S5 Fig). This single amino acid substitution results in a clear change in the predicted 3-D structure in the trypsin-like serine and cysteine protease domain of the NAL1 protein between the TQ-SS1 and LT-SS1 alleles and a predicted partial loss of function of the NAL1 protein in TQ (Fig 3B). When the allelic diversity at this site in 144 rice accessions from 16 countries was examined (S9 Table), the overall frequencies of histidine and arginine at this site are 0.424 and 0.576, respectively. However, the former is predominant in the 71 japonica accessions with a frequency of 0.662 (0.843 in the 51 modern japonica varieties), while the latter was predominant in the 73 indica accessions with a Genetic Networks Controlling Rice Source-Sink Traits frequency of 0.808 (100% in 19 indica landraces). The difference in FLW between the CAT (histidine) and CGT (arginine) alleles was insignificant, though they differed significantly for FLW in indica (P = 0.022) and japanica varieties (P = 0.026), respectively. The CAT allele (FLW = 1.77cm) had wider FLW than the CGT allele (FLW = 1.51cm) in indica varieties. However, the CAT allele (FLW = 1.37cm) had smaller FLW than the CGT allele (FLW = 1.62cm) in japonaica varieties.
Gene expression. At the panicle initiation stage, LOC_Os04g52440 expressed at a high level in leaf sheaths and panicles of both the NIL-SS1 and TQ, while NIL-SS1 showed a Genetic Networks Controlling Rice Source-Sink Traits significantly higher expression rate than TQ in flag leaves, leaf sheaths and internodes (S6A Fig). LOC_Os04g52450 expressed at a high level in all tissues with significantly higher expression rates in flag leaves, leaf sheaths and internodes in the NIL-SS1 than in TQ (S6B Fig). LOC_Os4g52479 (NAL1) expressed in all tissues but more strongly in nodes and root/stem conjunctions (S6C Fig). However, differences between the NIL-SS1 and TQ in the expression level of NAL1 were insignificant in all tissues, indicating that the SNP in the promoter region between the NIL-SS1 and TQ did not affect the expression of NAL1.
Phenotypic differences between the NIL-SS1 and TQ. The NIL-SS1 and TQ were similar in plant type and grain size (S7A Fig), but the former had significantly wider FLW and more GNP and filled grains per panicle than TQ in Hangzhou, Beijing and Sanya (S10 Table and S8A Fig). The difference in grain yield per plot between the NIL-SS1 and TQ was insignificant, though the SS1-NIL had consistently higher yield than TQ by 0.4 (3.6%) and 0.5 (3.8%) and 0.3 (3.2%) kg per plot in Hangzhou, Beijing and Sanya, respectively. The NIL-SS1 plants were more vigorous than TQ (S7B Fig). Also, the NIL-SS1 showed consistently reduced photosynthesis rates from the booting stage to late grain filling stage (S11 Table and S8B Fig) in Beijing for 2010 and 2011 when compared with TQ, except that it had a significantly higher photosynthesis rate than TQ at grain filling stage in 2010. No differences in photosynthesis related traits were observed between the NIL-SS1 and TQ in 2012 (S11 Table). Compared to TQ, the NIL-
Discussion
Increasing yield has been the most important target in rice breeding worldwide. Both TQ and LT were commercial cultivars, but TQ has much higher yields and wider adaptability than LT. Tremendous efforts have been taken to dissect the genetic basis of yield using different populations derived from the LT/TQ cross, resulting in identification of large numbers of QTL and complex epistasis for the huge yield difference between the parents [9-12, 14, 15, 38]. Our experimental design of using the reciprocal IL populations plus phenotyping in the long-day summer crop season in Beijing and short-day winter nursery in Sanya provided a unique opportunity to verify all identified QTL in both parental GBs. Thus, the discovered genetic networks underlying SS and yield traits and the cloning of SS1 provided direct evidence and new insights into the genetic and molecular basis of SS and yield traits in rice.
The genetic basis of the SS and yield traits in rice
Our results provided overwhelming evidence for the importance of epistasis in determining SS and yield traits in rice. In this study, 85% of the identified M-QTL and 97% of the epistatic interactions were detectable only in one of the parental GBs. Historically, GB effects of QTL have been reported in rice [15,37,[51][52][53][54], tomato [55,56], drosophila [57] and humans [58], and interpreted as evidence for the presence of epistasis. However, it remains unclear how epistasis causes the GB effects of M-QTL as the classical quantitative genetics theory [37,39] predicts that M-QTL should be detectable in both parental GBs. According to the new functionmutation model [40], a gene acting in signaling pathways affecting a complex trait can be detected as M-QTL in both reciprocal ILs only under two scenarios: (1) it is a regulatory gene controlling multiple downstream pathways affecting the same trait and (2) it is the only locus in one of the downstream pathways segregating in the parents. SS1 (qFlw4.7/qGnp4.7) and SS2 (qFll3.12/qGnp3.12/qGw3.12b) presented the former case, while the other four GB "independent" loci (qFlw6.5, qFlw12.4, qFll12.4 and qGw7.5) fell into the latter. The theory also predicts that when n loci (n 2) acting in a downstream pathway affecting a complex trait are segregating between the parents, P 1 and P 2 , with the functional alleles at k (0 k n) loci in P 1 and those at n-k loci in P 2 , then the k loci would be detectable only in the P 2 (mutant) GB, as a result of genetic complementarity. Thus, one would expect that the k loci would be detectable (having main and/or epistatic effect) in the P 2 GB only if they are co-introgressed into P 2 with the functional allele(s) at their regulator(s), and so for the n-k loci in the P 1 GB. Consistent with the theoretical prediction, the five FLW QTL downstream of SS1 were detectable only in the TQ-ILs when they were co-introgressed into the TQ GB with the functional (LT) allele at SS1 (Fig 1A and S8 Table). The same was true for most GNP (GY) QTL downstream of SS2 (qGy3.12 or qGnp3.12) (Fig 1B). However, most FLL QTL and 2 GNP QTL (qGnp5.5 and qGnp8.4a) downstream of SS2 were detected in the LT-ILs by genetic knock-out (introgression of the mutant TQ alleles into the LT GB). This result suggested that those FLW loci downstream of SS1 and those GNP (GY) loci downstream of SS2 were somewhat "redundant" in their functions such that introgression of the mutant alleles at single downstream loci did not necessarily have phenotypic effects. Otherwise, those GY QTL would have been detected as M-QTL in the TQ-ILs. Curiously, one is wondering why TQ has the functional alleles at so many "redundant" loci affecting GY and fitness (GNP) traits and if this contributes to its high yield potential and yield stability, which remains an important question to be addressed in future.
The nature of loci and allelic diversity underlying SS and yield traits in rice
Consistent with the theoretical prediction [40], most loci affecting rice SS and yield traits identified in this study were functioning in the downstream pathways and the presence of a functional allele and a non-functional mutant was predicted as the nature of allelic diversity at 46 loci involved in epistasis (S7 Table). Further, the mutant alleles at 87% of the loci affecting fitness (GNP) and productivity (GY) were from LT, indicating that the LT (japonica) genome has a much higher genetic load than the TQ (indica) genome. This was consistent with our previous mapping results [59]. Interestingly, we noted that the predicted functional alleles at all epistatic loci were associated with increased values of SS and yield traits. This implies that increased SS capacity and productivity in rice are primarily controlled by positively regulated pathways. Then, one would predict that it is much easier to break a functional multi-locus high yielding genotype than to restore it in randomly segregating breeding populations, which is consistent with empirical observations in plant breeding.
The molecular basis and functionality of the SS1-mediated pathways
Our QTL cloning results plus combined evidence from three recent reports indicate that SS1 (qFlw4.7/qGnp4.7) are the same QTL as SPIKE [48], GPS [49] or LSCHL4 [50], representing allelic differences at NAL1, a gene encoding a trypsin-like serine/cysteine protease involved in the auxin transport by regulating many downstream genes in the auxin/IAA signaling pathways [46,47]. However, the phenotypic effects of different alleles at NAL1 in the three QTL cloning studies appear to be 'inconsistent'. At the sequence level, the alleles at NAL1 in the parents of the 4 independent studies can produce five predicted NAL1 protein variants ( Fig 3A). These include two functional japonica (LT-SS1 and YP9-SPIKE or Nipponbare-LSCHL4) alleles, one naturally occurred indica variant (TQ-SS1, IR64-SPIKE, Takanari-GPS and 9311-LSCHL4) from the substitution of a histidine in the japonicas by an arginine in the indicas, a loss of function japonica (Koshihikari-GPS) mutation with the insertion of a retrotransposon in the second exon, and an induced loss of function mutation (nal1) from a 10-aa deletion in the fourth exon of NAL1 in Taichung 65. Interestingly, while the phenotypic effects of the functional Takanari-GPS (indica) allele causing narrower leaves and increased photosynthesis rate were detectable in both the parental GBs, its effect for increased yield was detectable only in the Takanari (indica) GB by 'genetic knockout', but not in the Koshihikari (japonica) GB by 'gain of function' [49]. In contrast, the YP9-SPIKE or Nipponbare-LSCHL4 (japonica) allele was associated with wider leaves and increased yield across several indica GBs, when compared with the SPIKE-IR64 or LSCHL4-9311 (indica) allele [48,50]. In this study, the LT-SS1 (japonica) allele was predicted to be functional and associated with wider leaves and more GNP, which were consistent with the other two reports. However, its effects on increased yield and reduced photosynthesis rate were inconsistent in the NIL-SS1. Taking all the data together, we came up with a clearer picture of the SS1-mediated pathways discovered in this study. First, the SS1-mediated pathways affecting SS and yield traits are inferred to be part of the auxin mediated pathways in which different alleles at NAL1 play important regulatory roles by qualitative (the nal1 mutant) and/or quantitative control of the efficiency and tissue specificity of IAA transport from the apical meristem to other plant tissues (leaves, stems, roots and panicles, etc). Second, the substitution of a histidine in the japonicas by an arginine in the indicas in the trypsin-like serine and cysteine protease domain of the NAL1 protein resulted in the predicted structural change and partial loss of function of this protein in the indicas (Fig 3B). This protein structural change apparently causes its inability to interact or to be recognized by other proteins [46] in the IAA signal transduction and failure to regulate downstream loci which positively control GNP, leaf width and area, and roots of rice. Third, the japonica haplotype (H-V-I) and indica (R-A-V) one at NAL1 involve 3 amino acid substitutions ( Fig 3A) and are inferred to be ancient since the indica-japonica differentiation. The LT-SS1 haplotype was a hybrid apparently resulting from its indica-japonica origin. Further, we note that wider leaves, large panicles (more secondary branches), fewer panicles, and strong/deep roots are typical characteristics of most japonica landraces, and the opposite is true for most indica landraces. This suggests that this allelic differentiation at NAL1 may have contributed to the well-known indica-japonica subspecific differentiation and their respective adaptations to the warmer, more humid and cloudy environments in the tropics by indicas and the colder and drier areas of high latitude or elevation by japonicas. Forth, the phenotypic effects of different NAL1 alleles on rice productivity and other traits are predicted to depend on the presence and number of the functional alleles at its downstream loci, which would vary considerably in different rice GBs, as clearly demonstrated in this study (S6 and S7 Tables). This was not surprising because its main effects actually represented the cumulated phenotypic effects of many different functioning downstream pathways in the GB. Thus, like the well-known story of the Green Revolution gene, sd1 [20], our results provides another piece of direct evidence validating the function-mutation model of the molecular quantitative genetics theory [40] and its power in dissecting complex traits controlled by signaling pathways.
The SS2-mediated pathways
The SS2-mediated pathways resembled very much the SS1-mediated pathways. Like SS1, SS2 was detected as a major M-QTL cluster (qFll3.12/qGnp3.12/qGy3.12/qGw3.12a) and a key regulator with pleiotropic effects on FLL, GNP, GY and GW by regulating multiple downstream loci (Fig 1A and 1B). However, the phenotypic effects of the SS2-mediated pathways on rice productivity were much stronger, primarily through the functional TQ (indica) alleles at many downstream pathways regulated by the functional TQ (indica) alleles at SS2. This was consistent with our expectation that alleles for increased productivity at most loci were from TQ. Genetically, the SS1-and SS2-mediated pathways appeared to be largely independent from each other. The only overlap was the interacting QTL pair, qGnp4.1/qGy4.1−qGy6.6, and their downstream ones, qGnp1.8/qGy1.8−qGnp6.3/qGy6.3 detected in the downstream of both SS1 and SS2. Interestingly, an epistatic GY QTL, qGy4.7 at SS1 was interacting with several loci in the downstream of SS2, at which the TQ SS1 (qGy4.7) allele was associated for increased GY (Fig 1A and 1B). While this appeared to be consistent with the positive effect of the GPS-Takanari allele for increased yield [49], the possibility that qGy4.7 was a different gene tightly linked to SS1 could not be ruled out because sequence diversities at many loci, including LOC_Os04g52440 and LOC_Os04g52450, are known to exist in the SS1 region. Now, we are in the progress to clone SS2, which is expected to provide important evidence on the nature of the SS2 mediated pathways.
Here, we realize that there is a huge knowledge gap to link the allelic diversity at SS1 or SS2 to their phenotypic effects and many important questions remain to be elucidated in future studies. For example, what are those downstream genes and pathways mediated by SS1 and SS2, and how are they regulated? What are those loci and pathways downstream of SS1 and SS2, and how do they determine rice SS traits and productivity, etc? These questions pose a huge challenge to rice scientists since it would be very difficult to clone those downstream QTL by the map-based cloning approach because of their relatively small effects and complex epistasis involved. Fortunately, with the genetic information on these downstream loci, specific genetic stocks (NILs and ILs of different allelic combinations at the downstream loci in different GBs), available sequences of the parental genomes, different omic technologies are now being used to address these questions. We also realize that the SS traits measured in this study included only morphological components, but not biochemical components, though the association of the Takanari-GPS (indica) allele at NAL1 with increased photosynthesis rate already suggests such possibilities. Also, the SS relationship in rice and other cereals is dynamic, which can be better addressed using systems mapping [60] in future.
Implications in rice improvement
Our results have important implications for further improving rice yield potential and stability through strategies of "molecular ideotype breeding" and "molecular population improvement". Currently, three major ideotypes have been proposed and practiced in breeding to break the yield plateaus of semidwarf rice inbred and hybrid cultivars, including the large panicle (LP) type with large SS traits with fewer panicles per unit area [61,62], the numerous panicle (NP) type with small SS traits and more panicles per unit area [62] and the intermediate panicle (IP) type [63]. In practice, the LP type cultivars tend to show high yield potential under high-input (fertilization) conditions, while the NP type varieties tend to perform better under low-input conditions. The IP type varieties tend to show a much broader adaptability and higher yield potential across both high-and low-input conditions. Lines with extreme large panicle or leaf size are not normally high yielding due to disharmony between the SS traits [6,64]. Our results suggest that varieties with different SS trait combinations can be developed by accurately manipulating different downstream loci to achieve enhanced and balanced SS relationships to maximize yield performances under various scenarios of input. Obviously, this can not be achieved by transferring single or a few major QTL because of the pleiotropic effects of single regulatory genes such as SS1 and SS2 are expected to vary considerably depending on the functionality of its downstream pathways in different GBs. Also, one can perceive that the pleiotropic effects of a downstream pathway is physiological, which can not be broken by recombination. Thus, the long-term breeding strategy for further improving the yield potential and stability of these high yielding Chinese indica lines requires systematic exploitation of more and novel functional alleles from exotic germplasm [65] and efficient transfer and pyramiding of these favorable alleles in the elite rice GBs using the molecular recurrent selection strategy [66]. [10,14,15,38]. The detailed information for the 478 SSR and SNP markers is shown in S1 Table. (PPTX) Table. Phenotypic differences between Teqing (TQ) and its SS1 near isogenic line (NIL-SS1) and Lemont (donor, LT) for SS and yield traits in Hangzhou, Beijing and Sanya. (DOC) S11 Table. Flag leaf net photosynthetic rate (P n , μmol CO 2 m -2 s -1 ), stomatal conductance (g s , mol H 2 Om -2 s -1 ), intercellular CO 2 concentration (C i , μmol CO -2 mol -1 ), transpiration rate (T r , mmol H 2 Om -2 s -1 ), and specific leaf weight (SLW, mg cm -2 ) of leaf area of the two parents (Teqing and Lemont) and NIL-SS1 evaluated under the irrigated condition in Beijing. | v3-fos |
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} | s2 | Anti-inflammatory, antioxidant and antitumor activities of ingredients of Curcuma phaeocaulis Val
Curcuma phaeocaulis Val. is used in Chinese Pharmacopoeia as health food and folk medicine for removing blood stasis, alleviating pain and tumor therapy. This research was aimed to explore and compare three main bioactivities including anti-oxidant, antitumor and anti-inflammatory activities between the ethanol extract of C. Phaeocaulis and its fractions using different in vitro models. Firstly, 70 % ethanol was used to extract C. Phaeocaulis, and then the crude extract was re-extracted, resulting in petroleum ether (EZ-PE), ethyl acetate (EZ-EA), and water fractions (EZ-W), respectively, and then a series of index was detected. Results showed that all the extracts had medium DPPH radical scavenging activity when the concentration was 200 μg/ml and their DPPH radical scavenging activity was in a concentration-dependent manner. The extracts except ethanol extract of C. Phaeocaulis had almost no cytotoxicity to the survival of RAW264.7 cell when the concentration reached 80 μg/ml, and all of them had medium inhibitory effect on nitrite release. Extracts of C. Phaeocaulis had medium intensity antitumor activity, EZ-PE and EZ-EA fractions significantly inhibited the proliferation of four tumor cells (SMMC-7721 cell lines, HepG-2 cell lines, A549 cell lines and Hela cell lines). C. Phaeocaulis had antioxidant and anti-inflammatory activities, which did not carry out centralized phenomenon when re-extracted. EZ-PE and EZ-EA were active antitumor sites of C. Phaeocaulis.
INTRODUCTION
Curcuma phaeocaulis Val. belongs to the family Zingiberaceae. It is an important herbal drug prescribed in the Chinese Pharmacopoeia (Wang and Wang, 2001). It is mainly distributed in the provinces of Guangxi and Sichuan in China (Sasikumar, 2005). Its dried rhizomes have been used as health food and folk medicine with functions of removing blood stasis and alleviating pain (Wang and Wang, 2001). In clinical practice, Rhizoma Curcumae is commonly prescribed for cardiovascular and tumor therapy alone or in combination with other herbs.
Surveys in India showed that Rhizoma Curcuma was one of the most commonly and popularly used medicinal plant for management of dermatological healthcare problems (Kumar et al., 2013). The main bioactive constituents of Rhizoma Curcumae are essential oils, which possess anti-tumor (Wang et al., 2009), anti-inflammatory (Makabe et al., 2006), and neuroprotective properties (Dohare et al., 2008). Different extracts have different constituents showing different biological activities. The water extracts of C. phaeocaulis showed relaxation effects while its polysaccharides induced contraction (Sasaki et al., 2003). Water extract also displayed promoting learning, memory and anti-aging activity of mice (Mao et al., 2000). The methanol extract of C. phaeocaulis was reported to have significant anti-inflammatory activity, which was manifested in its inhibitions on paw swelling, serum haptoglobin concentration, and cyclooxygenase-2 activity in adjuvant arthritis mice (Tohda et al., 2006). The ethanol extract of C. phaeocaulis showed anti-tumor potential, which significantly inhibited MCF-7 cells proliferation by inducing apoptosis mediated by increasing ROS formation, decreasing Delta psi m, regulating BcI-2 family proteins expression, and activating caspases (Chen et al., 2011).
Previous studies mainly focus on a single active extract, the investigation of horizontal bioactivity comparison between the ethanol extract of C. Phaeocaulis and its fractions was little involved. Therefore, it is of great interest to test the antioxidant activity and other activities so that to develop novel promising and natural sources for antioxidants and functional foods. In the present research, we managed to figure out the antioxidant, anti-inflammatory, and anti-tumor activities of the ethanol extract of C. Phaeocaulis and its fractions (petroleum ether, ethyl acetate and water fractions), and then a comparative study between them was carried out.
Plant material
The dried rhizome of C. phaeocaulis, derived from Sichuan province, was purchased from Qingping medicinal material market (Guangzhou, China). A voucher specimen was deposited in the department of Natural Products Studies, School of Light Chemistry and Food Science, South China University of Technology.
Preparation of C. phaeocaulis extract
The dried material was grounded in a cutting mill, then pass through an 100-mesh sieve to obtain a fine powder. All other reagents used in the experiment were of analytical grade. The powder (3.0 kg) of C. phaeocaulis was extracted with 95 % ethanol under reflux (3 × 7 L, each 2.5 h). The leach liquor was combined and concentrated under reduced pressure at 45 °C and the residue was reserved (EZ-Z, 77.8 g), which was suspended in water (1 L) and then partitioned with petroleum ether (3 × 1 L) and ethyl acetate (3 × 1 L) successively to give petroleum ether fraction (EZ-PE, 36.5 g), ethyl acetate fraction (EZ-EA, 28.7 g) and water remains (EZ-W, 9.4 g), respectively.
DPPH radical scavenging assay
The DPPH radical scavenging effects of EZ-Z and its three fractions were detected according to the method of Roy et al. (2010) with a bit modification. The DPPH solution was freshly prepared in methanol at a concentration of 1.75 × 10 −4 mol/L. About 2.0 ml DPPH solution was added to 2.0 ml sample solution, and the mixture was vibrated for 20 s at room temperature. The absorbance of the mixture was recorded at 517 nm after reacting for 0.5 h in the dark. A control, in which the sample was replaced by methanol, was measured by the same way. DPPH radical-scavenging effect was calculated as follows: where A contl is the absorbance value of the control group, and A samp is the absorbance of the sample.
Anti-inflammatory activity
The anti-inflammatory activity assay was performed as described previously. (Mitkus et al., 2013) The mouse macrophage cell line RAW264.7 cells were cultured in Dulbecco's modified Eagle medium (DMEM) supplemented with 10 % heat-inactivated fetal bovine serum (FBS), 1 % penicillin-strepto-mycin and maintained in an atmosphere of 5 % CO 2 at 37 °C. RAW264.7 cells (5 × 10 5 cells/ml) were seeded in 96-well culture plates (100 μl/well) and then incubated with or without lipopolysaccharide (LPS, final concentration 1 μg/ml) in absence or presence of samples with various concentrations (6.25, 12.5, 25.0, 50.0, 100.0 μg/ml) for 24 h. The nitrite accumulated in culture medium was measured as an indication based on the Griess reaction. 100 μl of culture medium was mixed with 100 μl Griess reagent [equal volumes of 1 % (w/v) sulphanilamide in 2.5 % (v/v) phosphoric acid and 0.1 % (w/v) N-1-naphthylenediamine dihydrochloride]. The absorbance of mixture at 540 nm was measured 10 min later and calibrated using a standard curve of sodium nitrate prepared in culture media (Mathew and Sharma 2000;Meli et al., 2000).
Evaluation of anti-tumor effects
The anti-tumor activity of EZ-Z and its three fractions (EZ-PE, EZ-EA and EZ-W) were tested by MTT [3-(4,5-dimethylthiazol-2yl)-2,5-diphenyltertrazoliumbromide] assay with HepG-2, A549, SMMC-7721 and Hela cell lines (Smith et al., 1998;Liu et al., 2012). Cells were all obtained from Sun Yat-Sen University, Guangzhou, China, and were cultured in DMEM medium supplemented with 10 % heat-inactivated FBS, penicillin (100 U/ml) and streptomycin (100 μg/ml) under an atmosphere of 5 % CO 2 at 37 °C. 100 μl exponentially growing cells (5 × 10 4 cells/ml) were seeded in 96-well plates and cultured for 12 h. Then 100 μl sample solution with different concentrations were added to each well for 24 h at 37 °C. Positive controls were treated with the same amount of 5-Fluorouracil (5-F). Blank controls were treated with DMEM medium without any sample. Optical density (OD) at 570 nm was used as a measure of cell viability. Cell survival rate (%) was calculated by the following formula: where OD contl , OD samp and OD blank were the optical density at 570 nm of the 5-F, sample and blank group, respectively.
Statistic analysis
Each experiment was performed in triplicate, and the data were expressed as mean ± SD. The significance of differences between groups was assessed by one-way analyses of variance (ANOVA). P < 0.05 indicated the presence of a statistically significant difference and P < 0.01 was considered highly significant.
Antioxidant activity
Radical-scavenging activity (RSA) assay has been widely used to evaluate the antioxidant effects of natural drugs (Ghazanfari et al., 2006;Hwang et al., 2013;Vulic et al., 2013;Hatamnia et al., 2014), Seeing that the laboratory-generated free radical such as hydroxyl radical and superoxide anion could be easily affected by some side reactions, such as metal-ion chelation and enzyme inhibition brought about by various additives, while DPPH has no these shortages, here we use DPPH radical scavenging assay to evaluate the antioxidant effects of the ethanol extract of C. Phaeocaulis and its fractions (petroleum ether, ethyl acetate and water fractions).
Newly prepared DPPPH solution exhibits a deep purple color and it has maximum absorption at 517 nm, when antioxidant was added, the color generally fades or disappears, and the absorption would change. The reason of the change in color and absorption was mainly because antioxidant molecules can quench DPPH free radicals (i.e. by providing hydrogen atoms or by electron donation, conceivably via a free-radical attack on the DPPH molecule) and convert them to a colorless/bleached product (i.e. 2, 2-diphenyl-1-hydrazine, or a substituted analogous hydrazine) (Yamaguchi et al., 1998). Therefore, when a substance make the absorbance of DPPH solution decrease, it can be thought to possess the antioxidant activity, and the faster the absorbance decreases, the stronger antioxidant activity the extract have.
The DPPH scavenging effect of the crude ethanol extract and its four fractions were tested and compared with each other. Figure 1 reflects the dose-response relationship of extracts; the results were expressed as a percentage of the ratio of the decrease in absorbance at 517 nm to the absorbance of DPPH solution without samples at 517 nm (Yoshida et al., 1989). When the concentration was 200 μg/ml, the EZ-EA afforded greatest RSA on the stable DPPH free radical, measuring 47.04 %, followed by EZ-Z, EZ-PE, EZ-W at 44.66, 42.84 and 30.58 %, respectively.
All extracts exhibited DPPH radical scavenging activity in a concentration-dependent manner that radical scavenging ratio was rising with the increase of sample concentration. Petroleum ether fraction and ethyl acetate exhibited similar radical scavenging ability with ethanol extract of C. Phaeocaulis, indicating that antioxidant activity did not carry out centralized phenomenon when ethanol extract of C. Phaeocaulis had been re-extracted.
Anti-inflammatory activity
Current studies have demonstrated the participation of reactive oxygen species in models of inflammation. C. Phaeocaulis was investigated as potential inhibitors of nitrite production in inflammatory reactions. Stimulation of RAW264.7 macrophages by LPSinduced lead to overproduction of nitrite, which could be detected and quantified. Results presented in Figure 2A showed that all extract and fractions significantly inhibited nitrite release and the release of nitrite decreased in the order of EZ-W (5.44 mmol/ ml), EZ-PE (4.96 mmol/ml), EZ-EA (4.86 mmol/ml) and EZ-Z (4.57 mmol/ml) at the concentration of 80 μg/ml. It was noted that EZ-Z exhibited the most active antiinflammatory effect among all extract and fractions. Many previous literatures showed that methanol/ethanol extracts or fractions had good anti-inflammatory activity. Yang et (2013) reported that ethyl acetate fraction of the seeds of Brucea Javanica showed significant decrease on nitrite production in LPS-induced RAW264.7 macrophages. In this study, EZ-Z and EZ-EA both showed a better anti-inflammatory ability than other fractions. Results presented in Figure 2B showed that the ethanol extract of C. phaeocaulis exhibited a certain cytotoxicity, and the survival rate of RAW 264.7 cells decreased from 94.85 to 74.3 % with the concentration increased from 10 to 80 μg/ml. EZ-PE and EZ-EA exhibited similar intensity cytotoxicity with EZ-Z. EZ-W did not exhibited obvious cytotoxicity, as its cells survival was greater than 87 % even at the highest concentration (80 μg/ml).
Altogether, these results suggest that the ethanol extract of C. phaeocaulis had some anti-inflammatory activity at certain concentration. Since active chemical did not carry out centralized phenomenon when ethanol extract of C. Phaeocaulis had been reextracted, its three sub-fractions exhibited only a certain anti-inflammatory.
Anti-tumor
The antitumor activity of above samples was also determined by MTT assay. Figure 3 shows the cell proliferation inhibition rate of each sample. We can see from the figure that the ethanol extract of C. Phaeocaulis exhibited medium intensity proliferation inhibition effect on four tumor cells, and the effect was in a concentration-depend manner. For Hela cell lines, EZ-PE and EZ-EA both exhibited medium cytotoxicity, and their inhibition rate were higher than EZ-Z and EZ-W. For HepG-2 cell lines, the proliferation inhibition effect of EZ-PE and EZ-EA was significantly higher than EZ-Z and EZ-W at the concentration ≥ 200 μg/ml, while this effect was lower than EZ-Z and EZ-W at the concentration < 200 μg/ml. For SMMC-7721 cell lines, the antitumor activity of three polar extracts of C. phaeocaulis was significantly lower than its ethanol extract, indicating that the active components were scatter- Results are mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, statistically significant in comparison with the control (5-fluorouracil) ed after extraction. For A549 cell lines, when the concentration ≥ 50 μg/ml, the antitumor activity order of four fractions was ethyl acetate fraction ≥ petroleum ether fraction > ethanol extract > water fraction. IC 50 value usually used as a measure of drug effectiveness, which was calculated by regression (curve fitting) of a series cell viability data, it is a value of the drug concentration at which 50 % of the cell population in a designated period was destroyed (Muthu et al., 2011). The IC 50 of all fractions were shown in Figure 4. Considering that the water fraction had little effect of antitumor, the IC 50 value of water fraction was not calculated. For Hela cell lines, the IC 50 of EZ-EA fraction was the lowest, 255.2688 μg/ml, For HepG-2 cell lines, the IC 50 of EZ-PE fraction was the lowest, 132.6822 μg/ml, For SMMC-7721 cell lines, the IC 50 of EZ-EA fraction was the lowest, For A549 cell lines, the IC50 of EZ-Z fraction was the lowest, 111.0659 μg/ml.
These data suggests that extracts of C. phaeocaulis had medium intensity antitumor activity and petroleum ether fraction and ethyl acetate fraction had antitumor activity for some tumor cell lines after re-extracted, indicating that petroleum ether fraction and ethyl acetate fraction were active site of C. phaeocaulis, which is in accordance with Radical-scavenging activity result. All these facts illustrated that radical scavengers may protect cell tissues from free radicals, thereby preventing diseases such as cancer (Young-Joon, 2002).
In conclusion, petroleum ether and ethyl acetate fraction exhibited similar radical scavenging ability with ethanol extract of C. phaeocaulis, as determined by scavenging effect on the DPPH free radical. The ethanol extract of C. phaeocaulis had some antiinflammatory activity at certain concentration, and its three sub-fractions also exhibited similar anti-inflammatory, indicating that antioxidant and anti-inflammatory active chemicals were distributed in four parts when re-extracted. The ethanol extracts of C. phaeocaulis had medium intensity antitumor Results are mean ± SD. *P < 0.05, **P < 0.01, ***P < 0.001, statistically significant in comparison with the control (5fluorouracil) activity and petroleum ether fraction and ethyl acetate fraction had stronger antitumor activity for some tumor cell lines after extracted, indicating that petroleum ether fraction and ethyl acetate fraction were active site of C. phaeocaulis. These data can provide some scientific basis for the further study on the antitumor activity of C. phaeocaulis. In future, animal experiments in vivo should be performed to further conform the antitumor activity of the fractions and to elucidate their related underlying mechanism. | v3-fos |
2019-04-01T13:15:57.023Z | {
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} | s2 | Pre-Scaling Up of Solar Tent Fish Drier in Northern and North Western Part of Lake Tana, Ethiopia
Solar tent fish drier (STFD) reduce post-harvest losses, thereby ensuring continuous availability of cheap animal protein. This study aimed to: (1) minimize post harvest losses by improving the shelf life dried fish; (2) enhance technology multiplication and dissemination system; (3) create clear insight about the technology implementation. This study was carried out in the northern and northwestern part of Lake Tana from June, 2014 to June, 2015. Purposive sampling methods were used to select Dembiya, Alefa and Gondar zuriya districts with their respective locality. Transact walk, interview, focus group discussion, and stakeholder consultation were used to collect qualitative data. Quantitative data were collected from 38 sample households by preparing structured questionnaire. Likert scale scoring, descriptive statistics such as percentage, mean, and standard deviations were used for analysis. The age structure of the sample households shows an average of 33.97 years and 44.7% of the respondents were female. Sample households average family size is 4.6 and the distance from the home to the main road takes 63.89 minutes of walk. The solar tent fish drier was prepared from readily available materials such as; wood, white and black plastic, nail, rope and mesh wire with a size of 2meter height and 1.7 meter length. For this activity, six tents were prepared for three districts and fish species selected for the activity was labeobarbus intermedius. The salt amount used was 60gram iodine salt per liter in brine form. The weight of dried fish becomes stable and dried well in the third day; with total moisture losses of 60%. Drying fish by solar tent fish dryer enables to produce hygienic, high quality, organoleptically good dried fish with low cost. By drying quickly it is possible to reduce post harvest losses thereby ensuring continuous availability of cheap animal protein. Absence of better price for fish dried by solar tent is the main challenge for further adoption. Promotion and market linkage for the quality dried fish; continuous support and follow up are very important to sustain the technology.
dried fish the fishers couldn't obtain the expected benefit. The post harvest losses in the study area are the main challenge due to nonexistence of appropriate preservative methods and expensiveness of other drying technologies. In Gondar zuriya, Dembiya and Alefa woredas/districts the main fish preservative methods are sun drying and salting.
Sun drying and salting still has many limitations, such as long period of drying during cloudy climate. In areas of high humidity, it is often difficult to dry the fish to low moisture content [5]. Sun drying of fish often results in low quality as a result of slow drying, insect infestation and contamination from air borne dust etc [3,5]. For getting better quality-dried fish, it is very essential to use improved methods of fish drying. Moreover, it is also important to maintain required hygiene during the different phases of fish drying by using solar tent fish drier [5,6]. In view of this, the present study aimed to: (1) minimize post harvest losses by improving the shelf life dried fish; (2) enhance technology multiplication and dissemination system; (3) create clear insight about the technology implementation.
Introduction
Fish provide the main source of animal protein to about one billion people globally. Fisheries are an important part of food security, particularly for many poor people in developing countries. In low income food deficient countries, they make up 22% of animal protein consumption overall [1]. Fish may also be the sole accessible and/or affordable source of animal protein for poor households in urban or peri-urban areas. Fish is, however, highly susceptible to deterioration without any preservative or processing measures [2].
Fish is an important food item that has significant socioeconomic contribution as a source of income, employment and cheap protein for marginal people in developing countries including Ethiopia. Lake Tana is one of the major fisheries in Ethiopia [3]. Small fish are especially important for poor consumers, as they can be purchased in small quantities at low cost. Even though the estimated production from Ethiopia commercial fishery is about 51,481tones per year, the actual catch were 15,389tones per year in 2001. FAO estimates fish post harvest losses is among the highest for all commodities; where Ethiopia losses one third of the annual production, which is about 5130tones per year [4,6].
In Lake Tana fisheries there are ten districts that have a potential for fishing, among these districts Gondar zuriya, Dembiya and Alefa districts have taken the main share. The amount of fish caught is high in these areas but due to market distance and discouraging price for budget and time we execute the activities in a cluster approach. The sites were selected based on their representativeness of other districts.
The study areas were selected in purposive sampling methods: at the first stage Dembya, Alefa, and Gondar zuriya woredas were selected purposively. At the second stage two kebeles at each woredas (Mangie and Gurandie from Dembya woreda; Esey-Debir and Dengel-ber from Alefa wored; Enfranze and Firkha-Dangurie from Gondar zuriya woreda) were selected and finally fishers that have drying experience were selected for scaling up the technology.
The activity was conducted in participatory approach. Fishers' teams were established (6 groups) on village based clustering and 6 drying tents were provided to the groups. Practical and theoretical trainings were provided to all groups to make them aware of for preparing the tent from readily available materials. To facilitate the pre scale up activities, focal persons were assigned from each of the groups.
Fishing and drying
Samples of the fish species labeobarbus intermedius were filleted using knife, weighed, and soaked in salt solution 60 gram salt dissolved in one liter of water as recommended by Assefa T. et al. (2008). Weight after drying has been taken to obtain the calculated weight losses.
Method of data collection
Data were collected using data sheet for socioeconomic and social data. Socio-economic researchers collect social data using PRA tools such as focus group discussion and individual interview. Structured and open ended questionnaires were prepared and filled. Information collected were: availability of inputs, ease of management and operation of the tents; group interaction and skill exchange during utilization of the tents, labor utilization, marketability of the product, benefit gained; personal opinions and observation on their feelings, observations, suggestions, and other's views on the tents; perception and attitude towards the technology.
Methods of data analysis
Descriptive statistics such as percentage, mean, standard deviations were also used. Social analysis such as perception and attitude of farmers and stakeholders towards the technologies were analyzed by using likert scale scoring. To know stakeholders' level of agreement on different aspects of the technology score were given: strongly agree = 5; agree = 4; indifferent = 3; disagree = 2; strongly disagree = 1. Sum score were calculated by using a formula = frq. strongly agree*5 + frq. agree*4 + frq. indifferent*3 + frq. disagree*2 + frq. strongly disagree*1; where frq is frequency. Finally the average score were derived by dividing sum score to total sample size.
Responsibilities sharing and exit strategy
The main stakeholders in the activity and training were: local fishers, woreda and kebele fish experts, woreda agriculture experts and development agent, kebele administrators, environmental protection experts, trade and transport (market linkage and promotion) expert, and small enterprise developments (business development service) expert.
To secure the technologies sustainability responsibilities were shared among stakeholder. In addition all trained fisher groups are promised to prepare solar tent fish dryer at their home by teaching and helping untrained neighbours. There were sharing of tasks among stakeholders to further disseminate technology in the future by continuous follow up, support and consultation.
Demographic characteristics of sample households
This study was based on the information collected from a total of 38 sample households and all of these are participate in fishery sector in a full time, seasonal and part time basis. The age structure of the sample households shows an average of 33.97 years. This implies that most of the respondents have had adequate experience on fishing activity. Sample households average family size is 4.6 and the average distance from the home to the main road is 63.89 minutes of walk. This shows fisher travels for an average of one hour to sale their catch to the nearest market.
Inaccessibility of road to sale catches exacerbates the spoilage rate and increase post-harvest loses. Post harvest processing is operated by both men and women; during the study 55.3% of the respondents were men.
The education status of the respondents involved in fishing activities can be described as illiterate except the 47.7% of literate respondents. This indicates that the fishing activity is open not only for poor and illiterate communities but also for educated peoples.
The main means of livelihood in the study area is agriculture (cropping) activity. Of the total households, 36.8% of them participate mainly in fishing activities. This infers that fishing is the best means of income generating mechanism besides cropping and livestock rearing ( Table 3).
Most of the respondents participate seasonally and full time which accounts 36.8% of each. Farmers in the study area participate in fishing seasonally, besides livestock rearing and crop productions. During peak seasons (June to November) farmers mainly focus on agricultural activities like crop production and livestock. However, it doesn't mean that seasonal participants don't go to fishing during pick seasons; because during holyday and religious day (ploughing is not allowed) they go to fishing for their consumption. On the other hand, farmers who have a certain amount of farm land are part time participants as supplementary for income generation.
Training and characteristics of dried fish
The training was held in Dembiya and Gondar Zuriya woreda with a total of 107 participants. With these participants 35.5% of them were female participants. The study areas are known in their production potential but market problems and non-existence of appropriate fish preservative methods exacerbate fish post harvest loses. The training was composed of practical and theoretical components to enhance the stakeholder's knowledge about the technology Figure 1.
The trainings were mainly focused on: advantages of using solar tent fish drier and way of construction in practical; fish preservative type and technique; pre and post harvest handling methods; methods of changing fish left over to animal and human consumption. The main participants in the training were: local fishers, district and kebele fish experts, district agriculture experts and development agents, kebele administrators, environmental protection experts, trade and transport (market linkage and promotion) experts, and small enterprise developments (business development service) expert.
The solar tent fish drier was prepared from readily available materials such as; wood, white and black plastic, nail, rope and mesh wire. For the scaling up six tents were prepared with a size of 2meter height and 1.7 meter length to dry Labeobarbus intermedius fish species. The driers provide hygienic conditions for fish drying and they could be constructed from reasonably priced and readily available materials.
To know the total weight losses, initial weight before drying and final weight after dried have registered. The initial weight of gutted fish before dried was 2kilogram in each tent and the salt amount used was 60gram per liter of water in brine form. After the gutted fish have been immersed in the salt solution for five minutes, drying has started by stowing on the prepared rack. In the first day, the weight losses have increased at an increasing rate. At the second day the weight loss of dried fish continues to increase but it was at decreasing rate. The weight of dried fish becomes stable and dried well in the third day and the final weight data were registered at this time. Studies in agreement with our findings investigates solar tent drier required less time to dry which is about 58 hours [7]. Reason behind this was circulation of hot air within solar tent drier, which increased internal drier temperature and reduced drying time. Fish dried by solar tent require 3 days to reach to the lowest moisture content level [5]. Based on our study, the final weight of dried fish was 0.8 kilogram. When the final weight of dried fish compared with the initial weight there is 0.6kilogram weight loss per kilogram when fish dried in the tent. Weight loss= ((W i -W f )/W I )*100 = (1k.g-0.4k.g)/1k.g)* 100= 60%.
Benefits gained from solar tent fish drier
In the study area fisher's start drying when production becomes high because of the currently emerging dried fish market to Sudan encourages fisher to practice fish drying. However, sun drying still has numerous limitations; such as drying process is not quick during Fishes dried quickly 170 4.5 The taste, texture, odder and color is good 180 4.7 Shelf life of the dried fish is longer 186 4.9 Post harvest lose reduced 177 4.7 More marketable than the traditional 133 3.5 High price for fish dried by solar tent than the local 106 2.8 I will adopt the technology for future 182 4.8 Table 9: Challenges for preparing and using solar tent fish drier. STFD enables the fish to dry quickly and uniformly since the temperature in the tent is above room temperature. A uniformly and quickly dried fish is attractive to see and suitable to eat. Therefore, solar tent fish dryer increases the shelf-life, maintains the quality of the fish in terms of its nutrient, flavor, texture, and appearance, provides ease of handling, and reduces post catch losses thereby ensuring continuous availability of cheap animal protein to the people all year round.
Perception of the fishers and stakeholders
The perception and attitude data collected were mainly focus on input availability, cost of construction, and quality of the product, marketability and future fate of the technology. The respondents and stakeholder's attitude towards the technology were good in most aspects.
The respondents were asked their level of agreement or disagreement on the availability of construct materials, 34.2% of them agree and 15.8% were disagreed on the availability of constructing materials specially the durable white and black polyethylene is difficult to get and purchase.
Even though STFD can be constructed from locally available materials, it requires some materials to be purchased such as; nail, white and black polyethylene and mesh wire. Regarding the cost of construction, 27% of the respondents agree as it is costly but 48.6% are neither agree nor disagree which means there is a frustration about cost for purchasing inputs. The ease of management (maintaining and operating) and implementing construction is easy. But one issue raised by the respondents was fish holding capacity of the tent is not different from the traditional methods of drying.
The tent speeds up the drying process by raising the temperature above room temperature especially when the weather is not ideal. In addition STFD is water proof; the fish doesn't therefore need to be moved when it rains. The hygiene of dried fish with in the tent is remarkable since fishes inside the tent are protected from dust, dirt, and insect attack. The hygiene, rate of drying and organoleptic situation were good. Out of the total respondents 86.8% of them strongly agrees that fish dried by STFD are hygienically good compared the traditional method of drying.
Stakeholders and fishers strongly agree that, rate of dry, organoleptic taste, and shelf life after dried was good. Based on this we can conclude that, good hygiene and earliness of drying reduces spoilage rate of caught. This results in increased shelf life of the fish which have a significant contribution to reduce post harvest losses.
Based on the likert score respondents agree that, STFD is easy to implement and manage. The hygiene, taste, texture, odder, color and prolonged shelf life make the technology smart. Furthermore; STFD reduces post harvest lose by drying quickly during surplus of production with no additional labour cost. These attribute of the technology aspires the fishers to further adoption in the future.
On the other hand; available inputs, cost of constructing, fish holding capacity of the tent, and marketability of fish dried by STFD hesitates fisher for extensive adoption. Fisher strongly asserts absence of differed price for fish dried by solar tent may hinder adoption level in the future if market problem couldn't get solution.
Major challenges for using the technology
Using STFD has certain problems as raised by sample households. Among challenges: input scarcity such as; white and black polythene; market problem especially price for fish dried by the technology is not encouraging; weak extension linkage the fishery sector; knowledge gap for using the technology, and inaccessibility of road. The main challenges in using STFD are the market and price for fish dried by STFD is not different from the traditional. This couldn't motivate the fishers to use and invest on STFD.
Conclusions and Recommends
Local way of drying (sun drying) has many limitations, such as long period of drying during cloudy climate. In areas of high humidity, it is often difficult to dry the fish to low moisture content. Fish dried by sun often results in low quality as a result of slow drying, insect infestation and contamination from air borne dust etc. However, drying fish by solar tent fish dryer enables to produce hygienic, high quality, organoleptically good dried fish with low cost. By drying quickly it is possible to reduce post harvest losses thereby ensuring continuous availability of cheap animal protein.
Market price for fish dried by STD is not different from the traditional. This could future threat for fishers to use and invest on STFD. If the technology is expected to play its role, the following issue requires due attention: promotion and market linkage for the quality dried fish; support fishers by delivering scarce inputs such as; white and black polythene; strengthen extension linkage in the fishery sector; drying a spoiled fish must be banned; fill knowledge gaps about the technology by continuous follow up and support is very important; further scaling out of the technology. | v3-fos |
2018-04-28T04:14:28.318Z | {
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} | 0 | [] | 2015-03-01T00:00:00.000Z | 13808186 | {
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} | s2 | Impact of Multiple Antimicrobial Interventions on Ground Beef Quality
Multiple antimicrobial intervention strategies are employed in beef manufacturing, and some may impact quality and palatability of ground beef patties. Combinations of antimicrobial treatments – hot water (at least 82 °C), lactic acid (4.0 to 5.0%), acidified sodium chlorite (pH of 2.7 to 2.8) and Beefxide (lactic/citric acid mixture; up to 2.5%) – were applied to hot or chilled carcasses and trimmings before manufacturing ground beef patties, which were designated for color evaluation, consumer panel, or trained panel evaluation. Few significant changes were seen in color space values for each treatment combination. Consumer scores for overall liking, flavor liking, and beefy flavor liking were impacted (P < 0.05) by combined antimicrobial treatment effects. Trained panelists detected 18 out of 33 attributes with only scores for fat-like (P = 0.0391) and cardboardy (P < 0.0001) being impacted by treatments. No clear trends were related to any single or combined antimicrobial treatment, and findings support that these food safety interventions have minimal negative impacts on beef patty quality.
the implementation of HACCP on meat and poultry slaughter and dressing operations (Commission of the European Communities, 2001), stating that hygienic performance shall be evaluated by enumeration of indicator microorganisms (aerobic count and Enterobacteriaceae counts) on the carcass at the end of the process (Capita et al., 2004). The standards used to assess the hygienic performance should be completely based on the results acquired, in this case, from destructive sampling methods (Capita et al., 2004) such as excision techniques. In contrast, the USDA Food Safety and Inspection Service (FSIS) published its final rule in 1996 for pathogen reduction; HACCP Systems (FSIS, 1996). The final rule requires the implementation of HACCP plans as a part of a company's control process and is mandatory in all inspected meat and poultry facilities in the United States (FSIS, 1996). However, unlike the European Union standard, it requires a nondestructive method, a swab sample in this case, to be taken from carcass surfaces for the enumeration of microbial counts.
Many sampling methods can be used to evaluate wholesomeness. These methods can be categorized into 2 groups: destructive and nondestructive (Lee and Fung, 1986), with each method having its own set of pros and cons. Excision, being destructive, provides more reliable results due to the efficient recovery of strongly attached bacteria. However, only a limited area can be sampled, processing is time-consuming, and skilled workers are required to properly collect the sample (Capita et al., 2004). In contrast, nondestructive sampling methods, such as swabbing, causes minor or no damage to the surface being tested, allows for larger areas to be sampled, and bacteria with uneven distribution and low colony-forming units can be recovered. The disadvantage of the latter method is that the results vary because only loosely attached bacteria are recovered (Capita et al., 2004).
Previous studies have been conducted to evaluate the efficiency of different sampling methods and enumeration of microorganisms. For instance, Anderson et al (1987) evaluated the effectiveness of swabbing and excision sampling method for the recovery of aerobic bacteria, Enterobactericaceae, and E. coli. The study indicated that there was a higher recovery via excision than swabbing, where swabbing recovered an average of 6 to 16% of aerobic counts compared to the amounts recovered by excision. Similarly, the recovery of Generic Escherichia coli ranged from 5 to 12% of the amount recovered by excision. In agreement with Anderson et al. (1987), additional studies have reported that excision to be a more effective and accurate method compared to swabbing in the recovery of indicator bacteria (Fliss et al., 1991;Martínez et al., 2010;Gallina et al., 2015). However, the altreration of swab materials can enhance its recovery. Gill and Jones (2000) reported the total aerobic bacteria recovered from carcass sides of pork and beef in packing plants were similar whether recovered by excision or swabbing with sponge or gauze. In addition, they reported the more abrasive the swab, the more bacteria would be recovered (Gill and Jones, 2000). While there have been studies to determine differences in sampling methods on carcasses, little information exists to determine the efficacy of various methods in sampling beef trimmings.
The objective of this study was, therefore, to evaluate the recovery of indicator (aerobic bacteria, coliforms, and Escherichia coli biotype I) microorganisms on beef trimmings using 3 different methods: 1) swabbing, 2) rinsing, and 3) grinding.
Sample collection
Meat manufacturing trimmings with varying surface fat contents (5 to 30%) were acquired from a commercial facility and transported to the Texas Tech University Gordon W. Davis Meat Laboratory. Over 3 independent replications, 5 samples of beef trimmings were collected using the N60 technique, with individual pieces measuring approximately 3 in long by 1 in wide and 1/8 inch thick following the USDA-FSIS methodology (FSIS 2014(FSIS , 2015(FSIS , 2016. For each replication, each of the 5 N60 samples obtained for the microbial analysis represented originally a single lot (2000 lb combo) at the commercial facility. The samples collected by the N60 method were then transferred to the food safety laboratory located in the Experimental Sciences building at Texas Tech University under refrigerated conditions and processed no later than 24 h after collection as required by the FSIS protocol.
Swab sampling
Each package of the beef trimmings obtained by the N60 sampling was aseptically opened using a sterile scissor, which was sanitized using 95% ethanol and flaming technique. The samples were placed on trays that were covered with labeled aluminum foil. A 100 cm 2 t emplate was placed on top of each sample. Sterile EZ Reach sponges pre-hydrated with 25 mL Buffered peptone water (BPW) were used for swabbing. The sponge was squeezed inside its bag before swabbing the area to remove the excess liquid. The delimited area was swabbed in horizontal and vertical motion from left to right and from top to bottom. The sponge was then put back in its respective bag, with the swabs being then stomached at 230 rpm for 30 s (Stomacher 400 circulator). Serial 10fold dilutions were performed in BPW 9 mL tubes for each swab. Appropriate dilutions were plated on 3M Petrifilm Aerobic Plate Count Plates (APC) and 3M Petrifilm E. coli/Coliform Count Plates (E. coli/Coliform Petrifilm) and incubated at 36°C ± 1°C. The APC petrifilms were counted at 48 h, whereas E. coli/coliform petrifilms were counted twice at 24 and 48 h procedure was repeated three times in the same manner.
Rinse sampling
In a separate location from the 100 cm 2 area that had been swabbed, 25 g from each of the N60 sample were acquired using sanitized forceps and scissors, and placed in a 55oz Whirl pack bags (Nasco, Fort Atkinson, WI). A volume of 225 mL of BPW was added to each sample. The samples were stomached at 230 rpm for 2 min, and serial 10-fold dilutions in BPW 9 mL tubes were performed. Then, the enrichments were drained out of Whirl pack bags, and the meat pieces were transferred aseptically using forceps to another set of Whirl pack bags, and again 225 mL of BPW was added to each sample. The samples then underwent stomaching at 230 rpm for 2 min, and serial dilutions were performed. This procedure was repeated for a total of three times. Appropriate dilutions were plated onto APC and E. coli/coliform petrifilms and incubated at 36°C ± 1°C. APC petrifilms were counted at 48 h, whereas E. coli/coliform petrifilms were counted twice at 24 and 48 h.
Grind sampling
For each N60 sample, 100 g of the trimmings were collected aseptically separate from the 100 cm 2 that had been previously swabbed, using sanitized forceps into Cabela's Deluxe meat grinder (Cabela's, model 541091, China) to be ground. Between each grinding, the grinder was disassembled, cleaned, and sanitized with bleach to avoid cross contamination. Then, parts were rinsed with potable water to eliminate sanitizer residue. A total of 25 g from each of the ground samples were placed into a Whirl pack bags. The samples then were diluted with 225ml BPW, stomached at 230 rpm for 2 min, and serial 10-fold dilutions were performed. Then, the enrichments were drained out of Whirl pack bags, and the ground meat was transferred aseptically using a spatula to another set of Whirl pack bags, and again 225 mL of BPW was added to each sample. Subsequently, samples were stomached at 230 rpm for 2 min, and serial dilutions were performed. This procedure was repeated for a total of three times. Appropriate dilutions were plated onto APC Petrifilm and E. coli/coliform and incubated at 36°C ± 1°C. APC petrifilms were counted after 48 h, whereas E. coli/coliform petrifilms were counted two times after 24 and 48 h.
Scanning electron microscopy
Scanning electron microscope (SEM) was used to evaluate and show bacterial retention on the sponge after multiple dilutions and stomaching. To achieve this, a sample was taken by swabbing the shoulder portion of a beef carcass with a sponge in 25 mL of BPW (pre-hydrated EZ Reach sterile sponges). The swab was stomached for 30 s at 230 rpm. Excess liquid was squeezed off the sponge before cutting. On both sides of the swab, a 1cm × 1cm piece was cut using a sterile surgical blade and forceps. Each piece was cut horizontally in 2 to obtain subsamples from the exterior and interior of the swab. Subsamples were placed in 6-well plate, one in each well. The swab was transferred to a sterile stomacher bag and weighed. The BPW was added into the bag to obtain 1:10 dilution and stomached. Liquid was squeezed off the swab and 1cm × 1cm subsamples from the exterior and interior ("first rinse") were obtained. The same procedures were performed to get subsamples after the second rinse.
Four mL of 2% glutaraldehyde (Sigma, USA) in phosphate buffered saline, PBS (Sigma-Aldrich, Saint Louis, MO) was added into the wells containing the subsamples. The latter were incubated for 24 h at 4°C. After fixation, the solution was removed from each well using a disposable transfer pipette. The subsamples were washed with PBS twice, followed by dehydration in ascending concentrations of ethanol (25, 70, 95, and 100%), for 10 min at each concentration. Each dehydration was done once except the 95% and 100% which were done 2 times and 4 times, respectively. Critical point drying was performed using the manufacturer's protocol (BAL-TEC, Balzers, Liechtenstein), where the critical temperature of CO 2 was 31.1 C° and the critical pressure of CO 2 was 73.8 bar (1073 psi). The subsamples were mounted on aluminum stubs, sputter-coated with a thin layer of gold, and examined under a Hitachi S-4300SE/N SEM. American Meat Science Association. www.meatandmusclebiology.com
Statistical analysis
Experiments were performed in triplicate. For each of the samples analyzed, duplicate plates were obtained for each dilution and averaged prior to analysis. For each of the tested methodologies, microbial counts were collected and transformed to either log10 counts per 100 cm 2 (swabbing) or log10 counts per g (rinsing and grinding) prior to analysis to allow control and stabilization of statistical variance and fulfillment of the requirements for normality prior to the analysis. Log counts were considered a dependent variable of interest. Analysis of variance was performed using RStudio (version 1.0.44). Each sampling method was analyzed individually from the others, but within each methodology, comparisons of means were obtained between the first, second, and third consecutive collection. Pearson product-moment correlation coefficients were calculated to identify the relationship between the sampling techniques implemented using RStudio (version 1.0.44). In addition, simple linear regressions were computed and graphed using Microsoft Excel (2016). In all tests, the significance level was set at ɑ ≤ 0.05.
Results
The first enumerations obtained from the beef trimmings using swabbing, rinsing, and grinding are presented in (Table 1). There was no significant difference (P > 0.05) in the numbers of aerobic bacteria recovered when comparing the rinsing to grinding methods. However, aerobic bacteria recovered by swabbing was significantly lower (P < 0.05) than both rinsing of the whole sample or grinding followe by rinsing.
The decline in the bacterial numbers recovered as a result of subjecting each sample to multiple sequential samplings is presented in ( Table 2). The sequential sampling using rinsing and grinding techniques resulted in a significant decline (P < 0.05) in the number of bacteria recovered. However, the bacterial recovery when using the swabbing technique was not significantly different (P > 0.05) for each of the 3 sequential samplings. Therefore, the decrease in bacterial number was not significant (P > 0.05) indicating much bacteria remained on the surface of the sample.
By adding all bacterial counts together from all 3 sequential samplings obtained by each of the methods (swabbing, rinsing, and grinding) a comprehensive enumeration of total aerobic bacteria and coliforms present in the beef trimmings was obtained (Table 3). When observing the aerobic bacteria counts, there was no significant difference (P > 0.05) between rinsing of the whole piece and grinding followed by rinsing. Nevertheless, counts obtained by swabbing were significantly lower (P < 0.05) than rinsing and grinding as it was observed when a,b Different superscripts within the column denote statistical differences (P < 0.05).
comparing just the initial samples. For total coliform counts, rinsing was not significantly different (P > 0.05) from either swabbing or grinding, yet swabbing yielded significantly lower counts (P < 0.05) than grinding. The correlation coefficient was calculated to measure the strength and the direction of a linear relationship among the 3 methods. The correlations were 0.90, 0.82, and 0.83 for swab vs. grind, swab vs. rinse, and rinse vs. grind, respectively (Fig. 1, 2, and 3). Simple linear regression was performed to examine the relationship between the first recovery of all possible pairs of the 3 sampling methods, the results of which are illustrated in (Table 4). First, a linear model was computed to examine the relationship between swabbing and grinding and resulted in an r 2 of 0.81. The samples subjected to grinding and then rinsing had approximately 1.47 log more bacteria than the samples that were swabbed. The predicted recovery of grinding was 1.47 + 0.8X where X is the bacterial recovery obtained by swabbing (Fig. 1). Second, a linear model was performed to evaluate the relationship between swabbing and rinsing and resulted in r 2 of 0.67 indicating the percentage of variation of the response variable (Rinsing Log CFU/g) explained by our model. Rinsing of the whole piece had approximately 1.16 log more bacteria than swabbing of the whole piece. The predicted recovery of rinsing was 1.16 + 0.93X where X is the number of aerobic bacteria obtained by swabbing (Fig. 2). Finally, the linear model between rinsing and grinding recovery resulted in an r2 of 0.70, indicating that 70% of the response variation is explained by the linear model. The predicted recovery or grinding was 1.07+ 0.66X where X is the number of bacteria recovered by rinsing (Fig. 3).
Scanning electron microscopy (SEM) pictures of swabs were obtained to examine its bacterial retention, as it was hypothesized that grinding the sample would yield higher bacterial counts because a larger surface area would be exposed in comparison with rinsing and swabbing. It was thought that subjecting the trimmings to multiple samplings would result in a decline in the number of bacteria until it becomes undetectable. The SEM pictures should hypothetically show bacteria attached to the swab on the interior and exterior surfaces since the sponge might retain part of the bacteria recovered from the sample. Results obtained from the SEM pictures revealed that some bacterial cells remained on the interior and exterior layers of the sponge. There was not a specific pattern in how bacteria appeared on the sponge, as they could be seen as a single cell or clusters and were distributed over the entire area.
Discussion
This study indicated that there is noteworthy variation among sampling methods to recover indicator bacteria from beef trimmings. Swabbing is the least effective means to recover bacteria from trim samples, and if the surface is swabbed consecutive times in the same area, there is a possibility that the same amount of bacteria will be recovered the second and third time. Rinsing of either the whole piece of the sample or grinding and then rinsing the grind resulted in improved bacterial recovery with no differences between the 2 methods. The effectiveness of recovering aerobic bacteria and coliforms was highest when using the grinding method, followed by rinsing and least by swabbing. Swabbing yielded lower bacterial counts than any type of method used in this study, likely because swabbing recovers only part of the surface micro-flora (Anderson et al., 1987). Reid et al. (2002) stated that the nature of the swabbing technique supports the 2-way transfer of bacteria from hide to swab and from swab to hide which can occur simultaneously during swabbing. This also could have occurred during the swabbing of the beef trimmings in this study. Furthermore, the SEM pictures confirmed what was stated by Reid et al. (2002), and showed that the swabs retained bacteria as can be seen in Fig. 4 and 5. Additionally, the fat present in beef trim may fill the pores of the swab as the sample is collected, which then could result in lowering the bacterial recovery (Seager et al., 2010). Many studies that compared swabbing with other sampling techniques such as rinsing and excision found swabbing to be the least effective method (Anderson et al., 1987;Dorsa et al., 1996;Gill and Jones, 2000). Grinding of beef trimmings increases the surface area exposed to the diluent, which could have been the reason this sampling method showed superior bacterial recovery in beef trimmings. However, rinsing resulted in counts that were not significantly different than grinding, probably because most of the bacteria are located on the exterior surface of the trimmings especially when it is still intact, like the beef trims.
As expected, the first sampling recovered the highest number of bacteria in all three sampling methods used in this study. This could be because most of the bacteria that are found on the external surface of the trimmings are not necessarily firmly attached. Then, after sampling is performed multiple times, the recovery decreases either because bacteria have already been removed, bacterial attachment is stronger, or there is difficulty reaching deep areas of the meat as in the case of swabbing.
Despite the variation of the effectiveness in each sampling method, the ability to implement any of these meth-ods commercially would be a crucial factor to determine which one should be used. In this study, swabbing was less time-consuming and easier to perform, however, our results indicated that swabbing recovered around one-tenth of what rinsing or grinding followed by rinsing recovered. In addition, grinding the sample, as the results show, did not add much to the recovery of indicators. The time needed for the grinder to be cleaned and sanitized for each sample to be processed was also far greater, making this method more intricate and time consuming. Rinsing the whole pieces of beef trimmings would be the ideal method among those studied when assessing the microbiological condition of beef trims as it recovers more bacteria than swabbing and requires less time to perform in comparison to grinding, yielding basically the same results.
While swabbing recovered fewer bacterial cells, it still plays an important role in process control because it is a nondestructive and non-invasive method. For any given agency or industry conducting microbial data collection, sampling consistency is the key for proper interpretation of results. It is very important that the samples collected and reviewed over time are compared to results from samples collected in the same manner to make informed decisions about process control. It is also critical that each laboratory has written guidelines for sample collection that are followed to achieve consistency from day to day, which allows for a proper verification of the microbial loads present on beef trimmings. | v3-fos |
2016-05-04T20:20:58.661Z | {
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} | s2 | High-quality permanent draft genome sequence of Rhizobium leguminosarum bv. viciae strain GB30; an effective microsymbiont of Pisum sativum growing in Poland
Rhizobium leguminosarum bv. viciae GB30 is an aerobic, motile, Gram-negative, non-spore-forming rod that can exist as a soil saprophyte or as a legume microsymbiont of Pisum sativum. GB30 was isolated in Poland from a nodule recovered from the roots of Pisum sativum growing at Janow. GB30 is also an effective microsymbiont of the annual forage legumes vetch and pea. Here we describe the features of R. leguminosarum bv. viciae strain GB30, together with sequence and annotation. The 7,468,464 bp high-quality permanent draft genome is arranged in 78 scaffolds of 78 contigs containing 7,227 protein-coding genes and 75 RNA-only encoding genes, and is part of the GEBA-RNB project proposal. Electronic supplementary material The online version of this article (doi:10.1186/s40793-015-0029-6) contains supplementary material, which is available to authorized users.
Introduction
The most efficient biological nitrogen fixation occurs when bacterial microsymbionts (rhizobia) form an effective symbiotic association with legume host plants. Legumes can develop these interactions with many different species of rhizobia belonging mainly to the Alphaproteobacteria, including Azorhizobium, Allorhizobium, Bradyrhizobium, Ensifer, Mesorhizobium and Rhizobium [1,2]. The genus Rhizobium contains at the time of writing 71 species, and within a species there may be distinct symbiovars [3].
Within the species Rhizobium leguminosarum, there are three distinct symbiovars [4,5] including bv. phaseoli that forms nodules with Phaseolus vulgaris, bv. trifolii that forms nodules with clover (Trifolium) and bv. viciae that forms nodules on vetch, pea and lentil (Vicia, Lathyrus, Pisum and Lens). In R. leguminosarum the nod genes that define these distinct host specificities are mostly located on the symbiotic plasmid, which has generically been designated pSym. The genomes of R. leguminosarum strains are usually large and complex containing, in addition to pSym, a chromosomal replicon and extra-chromosomal low-copy-number replicons characterized by the presence of repABC replication systems [6][7][8]. Recent studies have revealed that substantial divergence can occur in this genome organization and in the metabolic versatility of R. leguminosarum isolates [5,[9][10][11][12]. Kumar et al. [5] demonstrated that the diversity of R. leguminosarum within a local population of nodule isolates was 10 times higher than that found for Ensifer medicae. It was noted that the abundance of a particular genotype within the population can vary significantly and adaptation to the edaphic environment is a sought after trait particularly for the development of inoculants [13,14].
R. leguminosarum bv. viciae GB30 was isolated as the most abundant nodule inhabitant (>42 %) of Pisum sativum cv. Ramrod plants cultivated at a field site in Janow, Poland [10]. In contrast to other abundant isolates, GB30 formed nodules and fixed nitrogen with both P. sativum and Vicia villosa (cv. Wista). Preliminary investigation into the genome architecture using Eckhardt analysis has revealed that GB30 contained a multipartite genome consisting of six replicons with one chromosome and five plasmids [10]. The genome of this strain could therefore provide important insights into the mechanisms required by effective R. leguminosarum microsymbionts to adapt to a particular edaphic environment. Here, we present a set of general features for Rhizobium leguminosarum bv. viciae GB30 together with the description of the complete genome sequence and annotation.
Organism information
Classification and features R. leguminosarum bv. viciae strain GB30 is a motile, Gram-negative rod in the order Rhizobiales of the class Alphaproteobacteria. The rod-shaped form varies in size with dimensions of 0.8-1 μm in width and 2.3-2.5 μm in length ( Fig. 1 Left and Center). It is fast growing, forming colonies within 3-4 days when grown on half strength Lupin Agar (½LA) [15] at 28°C. Colonies on ½LA are white-opaque, slightly domed and moderately mucoid with smooth margins (Fig. 1 Right). Figure 2 shows the phylogenetic relationship of Rhizobium leguminosarum bv. viciae GB30 in a 16S rRNA gene sequence based tree. This strain is phylogenetically most related to Rhizobium laguerreae FB206 T and Rhizobium gallicum R602sp T based on the 16S rRNA gene alignment with sequence identities of 100 %, as determined using the EzTaxon-e server [16]. Rhizobium laguerreae FB206 T was isolated from effective Vicia faba root nodules in Tunisia [17], whereas Rhizobium gallicum R602sp T was isolated from effective Phaseolus vulgaris root nodules in France [18]. Sequence similarity was also investigated with strains from the GEBA-RNB project [12] and GB30 was found to be closely related to R. leguminosarum bv. trifolii WSM1689 with 100 % 16S rRNA gene sequence identity. R. leguminosarum bv. trifolii WSM1689 is a highly effective microsymbiont of the perennial clover Trifolium uniflorum and has been shown to have a remarkable narrow host range [19]. Minimum Information about the Genome Sequence (MIGS) is provided in Table 1 and Additional file 1: Table S1.
Symbiotaxonomy
R. leguminosarum bv. viciae strain GB30 was obtained from pea nodules (P. sativum cv. Ramrod) growing in sandy loam (N:P:K 0.157:0.014:0.013 %) in Janow near Lublin (Poland). The soil contained a relatively high number of R. leguminosarum bv. viciae, bv. trifolii and bv. phaseoli cells i.e., 9.2 × 10 3 , 4.2 ÷ 10 3 and 1.5 × 10 3 bacteria/g of soil, respectively, as determined by the most probable number (MPN) method [10]. Plants were grown on 1 m 2 plot for six weeks between May and June, 2008. Five randomly chosen pea plants growing in each other's vicinity were harvested; the nodules were collected, surface-sterilized and the microsymbionts isolated [10]. One of the most abundant isolates, GB30, formed nodules (Nod + ) and fixed N 2 (Fix + ) with P. sativum and Vicia villosa (cv. Wista) increasing the wet mass weight by 54 and 38 %, respectively. Plants inoculated with GB30 also showed a 2.6 fold increase in nodule number and a 2.2 fold increase in seed pod number.
Genome project history
This organism was selected for sequencing on the basis of its environmental and agricultural relevance to issues in global carbon cycling, alternative energy production, and biogeochemical importance, and is part of the Genomic Encyclopedia of Bacteria and Archaea, The Root Nodulating Bacteria chapter (GEBA-RNB) project at the U.S. Department of Energy, Joint Genome Institute [12]. The genome project is deposited in the Genomes OnLine Database [20] and the high-quality permanent draft genome sequence in IMG [21]. Sequencing, finishing and annotation were performed by the JGI using state of the art sequencing technology [22]. A summary of the project information is shown in Table 2.
Growth conditions and genomic DNA preparation R. leguminosarum bv. viciae strain GB30 was grown to mid logarithmic phase in TY rich media [23] on a gyratory shaker at 28°C. DNA was isolated from 60 mL of cells viciae GB30 (shown in blue print) relative to other type and non-type strains in the Rhizobium genus using a 901 bp internal region of the 16S rRNA gene. Bradyrhizobium elkanii ATCC 49852 T was used as outgroup. All sites were informative and there were no gap-containing sites. Phylogenetic analyses were performed using MEGA, version 5.05 [36]. The tree was built using the maximum likelihood method with the General Time Reversible model. Bootstrap analysis with 500 replicates was performed to assess the support of the clusters. Type strains are indicated with a superscript T. Strains with a genome sequencing project registered in GOLD [20] are shown in bold and have the GOLD ID mentioned after the strain number, otherwise the NCBI accession number has been provided. Finished genomes are designated with an asterisk using a CTAB (Cetyl trimethyl ammonium bromide) bacterial genomic DNA isolation method [24].
Genome sequencing and assembly
The draft genome of Rhizobium leguminosarum bv. viciae GB30 was generated at the DOE Joint Genome Institute [22]. An Illumina Std shotgun library was constructed and sequenced using the Illumina HiSeq 2000 platform which generated 25,943,396 reads totaling 3,891.5 Mbp. All general aspects of library construction and sequencing performed at the JGI can be found at the JGI web site [25]. All raw Illumina sequence data was passed through DUK, a filtering program developed at JGI, which removes known Illumina sequencing and library preparation artefacts (Mingkun L, Copeland A, Han J. unpublished). Following steps were then performed for assembly: (1) filtered Illumina reads were assembled using Velvet version 1.1.04 [26] (2) 1-3 Kbp simulated paired end reads were created
Genome annotation
Genes were identified using Prodigal [29], as part of the DOE-JGI genome annotation pipeline [30,31]. The predicted CDSs were translated and used to search the National Centre for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGRFam, Pfam, KEGG, COG, and InterPro databases. The tRNAScanSE tool [32] was used to find tRNA genes, whereas ribosomal RNA genes were found by searches against models of the ribosomal RNA genes built from SILVA [33]. Other non-coding RNAs such as the RNA components of the protein secretion complex and the RNase P were identified by searching the genome for the corresponding Rfam profiles using INFERNAL [34]. Additional gene prediction analysis and manual functional annotation was performed within the Integrated Microbial Genomes-Expert Review (IMG-ER) system [35] developed by the Joint Genome Institute, Walnut Creek, CA, USA.
Genome Properties
The genome is 7,468,464 nucleotides with 60.81 % GC content ( Table 3) and comprised of 78 scaffolds of 78 contigs. From a total of 7,302 genes, 7,227 were protein encoding and 75 RNA only encoding genes. The majority of genes (79.57 %) were assigned a putative function whilst the remaining genes were annotated as hypothetical. The distribution of genes into COGs functional categories is presented in Table 4.
Conclusion
Rhizobium leguminosarum bv. viciae GB30 belongs to a group of Alpha-rhizobia strains isolated from Pisum sativum in Poland. Strain GB30 is part of the GEBA-RNB project that sequenced 24 R. leguminosarum strains The total is based on the total number of protein coding genes in the genome. and 12 R. leguminosarum bv. viciae strains [12]. Phylogenetic analysis revealed that GB30 is most closely related to Rhizobium leguminosarum bv. trifolii CB782 and WSM1689, both part of the GEBA-RNB project [12]. Full genome comparison of GB30 and WSM1689 [19] revealed that GB30 has the largest genome (7.4 Mbp), with the highest COG count (5,182), the lowest Pfam % (82.51) and the lowest TIGRfam % (22.13 %). The genome attributes of R. leguminosarum bv. viciae GB30, in conjunction with the other R. leguminosarum genomes, will be important for on-going comparative and functional analyses of the plant microbe interactions required for the successful establishment of agricultural crops.
Additional file
Additional file 1: Table S1. Associated MIGS record. | v3-fos |
2019-04-27T13:09:11.319Z | {
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} | s2 | Bioaccumulation and decontamination mechanisms of persistent organic pollutants (PCB, DDT) in bodies of Bactrian camels
The present study aimed to determine the mechanisms of bioaccumulation and decontamination of Polychlorinated biphenyls (PCBs) and Dichlorodiphenyltrichloroethane (DDT) in the body of two-humped camels Camelus bactrianus . The experiment has been carried out in Suzak region of South Kazakhstan. Four lactating two humped camels received 0.8 mg of indicator PCBs (1.3 μg/kg body weight) and DDT 0.12 (DDT 0.2 µg/Kg body weight) mg per camel/day during two months and followed by a 4-month decontamination period. Milk and hump fat of experimental camels have been sampled. Milk samples were analyzed using a liquid-liquid and hump fat using solid extraction by gas chromatography and mass spectrometry method. Concentrations of PCBs and DDT in milk and hump reached a plateau at the end of the 2 months exposure period. Transfer rates into milk ranged between 2% for PCB 101 and 71 % for PCB 180 of the daily dose, which was generally lower than rates observed in ruminants. In the same time, the most important part of the contaminants has been stored in the humps. At the end of experimentation, the total quantity of PCBs excreted in milk was estimated to 28.6 µg and the total quantity accumulated during the contamination period in humps was 5530 µg. Despite a huge variability between the different congeners of iPCBs, the intermediate storage of lipophilic compounds in the humps reduced the concentrations excreted in milk but on the other hand would extent the duration of the decontamination period in comparison with ruminants.
Introduction
Persistent organic pollutants (POPs) are organic compounds that are resistant to environmental degradation and capable of causing negative effects on human health and the environment [1]. Due to these properties, in 18 May of 2001, 110 countries signed the Stockholm Convention on Conference of United Nation Organization, where the countries agree: to prohibit and put out of production, use, and release of POPs. Initially, twelve POPs have been recognized as causing adverse effects on humans and the ecosystem and within are PCBs as industrial chemicals and DDT among pesticides [2]. There are 209 congeners of PCBs with different physical, chemical and biological properties. PCBs have been used in power and chemical plants; they have been included in transformer and capacitor oils as additives to paints, plastics, rubber, as well as in lubricants and insulating materials. DDT is one of the pesticides, which included to the list of POPs. It is an effective insecticide widely used in agriculture over years during the last century to control the insect vectors of typhus, malaria and dengue fever. Also, it was made available to farmers as an agricultural insecticide [3]. The lactating ruminant may be exposed to DDT and PCB when they are eating contaminated feed or soil during grazing [4] as these compounds are accumulated in the body. According to the previous published data regarding impact of PCBs congeners 54, 80, 155 and one derivative of DDT 4,4 DDE in ruminant (sheep) previously contaminated by intramuscular injection under experimental conditions, the toxic equivalent of pollutants (on a fat basis) was approximately 2.5 https://doi.org/10.26577/2218-7979-2015-8-1-4-8 times higher in milk than in blood [5]. Moreover, studies of the transfer of PCB to milk in goats exposed to a long-term intake of contaminated hay under experimental conditions also shown that the contaminants had rapidly high concentrations of PCBs in milk after one-week exposure [6]. These studies of kinetics of contamination and decontamination of the animals in order to precise the transfer of pollutants in lactation goats and sheep were carried out in European countries. But researches on the transfer of pollutants and the mechanism of distribution of contaminants in camel organs (hump-fat, milk) have never been carried out and the concentration of this pollutant has not been studied in comestible parts of animals. Camels have a special characteristic as a biological model among all farm animals, and in general all mammals. Camels have the ability to survive and adapt to hard environmental conditions. Metabolic studies of PCBs and DDT in the body of Camelus bactrianus allow to understand the adaptive ability to survive in polluted environments. In the comparative studies of the effect of organic and inorganic selenium supplementation on selenium status in camel, metabolism of selenium in camel organism is observed to be less than in cattle [7]. Physiological characteristics of laboratory animals are considered from the standpoint of comparison with human physiology. Impact of these pollutants helped get a general idea, how they can affect the humans. Studies on the sheep and goats were conducted to control the meat of these animals as the object of the food chain. On the one hand, these studies supplement scientific data as a potential contamination object in the food chain. On the other hand, studies on such special biological models as Camelus bactrianus allow to better understand the biological intake of pollutants such as PCBs and DDT. In addition, it is necessary to take into account the fact that in the desert regions camels are sometimes the only type of livestock; as a result they are the only source of milk, meat and wool for humans. That's why this work devoted to study the entry and distribution of DDT and PCBs in the body of camels, as well as ways of removing these contaminants.
Material and methods
The main three steps of this experiment were: (1) contamination of the animals to reach a steady state situation, (2) determination of the POPs concentration in the different compartments (blood. fat and milk), and (3) monitoring of the decontamination process. Regarding the first step, it was necessary to assess the importance of the different compartments: (1.1) weight of the animal, (1.2) weight of the hump as main site of fat storage, (1.3) milk production (especially its fat content). Regarding the second and the third steps, the changes of the POPs concentrations during contamination and decontamination stage are assessed in the different compartments.
For experiment four lactating Camelus Bactrianus, 7-16 years old were used. The weight of animals ranged from 400 to 520 kg. Before experiment, data about age, calving date, and parity were reported as well as sex of calves. All camels have been identified with ear tags. The animals were in healthy conditions all along the study.
Experimental camels were exposed to DDT (Pestanal, analytical standard -31041, Fluka) and PCBs mixture (Aroclor 1254 -analytical standard-48586, Sigma-Aldrich), which were introduced in gelatin capsules (length -2 cm. diameter -9 mm) by hexane solvent. The capsules were filled with icing sugar fixing the introduced chemicals and allowing the evaporation of the solvent.. The contaminants for one camel were quantified for PCBs 1.3 µg/kg and DDT 0.2 µg/ kg body weight by day. In one capsule the concentration of PCBs was 0.8 mg and DDT 0.12 mg per camel/day. As each camel received one capsule during 56 days, the total exposure doses of one camel was 44 mg of PCBs and 6.7 mg of DDT. The daily supply of capsules was realized inside of bread. In order to reach the concentration plateau (steady state) more rapidly, a primary dose of 9.13 mg for PCBs and 1.41 mg DDT was given by intravenous injection on the first day of exposure. This dose with PCBs and DDT solution was prepared in oil solvent (Cremophor ELreference 95921 SUPELCO). The primary dose was 12 times higher than dose in capsules. During the experiment the milk, serum of blood and hump fat were sampled. Also, the body, hump measurements were made and milk yield was estimated, the milk composition (fat content. dry matter and density) was determined at each sampling date.
Analytical works have been done in CPHMA (The Center of Physico-Chemical methods of analysis), Laboratory of Ecology of the Biosphere, in GH-Agilent, with mass spectrometric and flame ionization detection Agilent 6890N / 5973N, equipped with a system of pre-concentration of liquid and solid samples Agilent-Velocity XPT.
Milk and blood serum were analyzed using a liquid-liquid and fat using solid extraction followed by cleanup on a multi-layer silica gel column, evaporative concentration to 20 µL and analysis on 7890A/5975C TAD TVL GC-MS (Agilent, USA) International Journal of Biology and Chemistry 8, №1, 10 (2015) equipped with Combi-PAL autosampler (CTC Analytics AG, Switzerland). Two µL of sample was injected to split/splitless inlet heated to 250 0 C in splitless mode. Separation was done on a DB-5MS 60 m x 0.25 mm. 0.25 µm film column (Agilent, USA) at a constant flow of helium (purity 99.995%, Orenburg-Tehgas, Russia) equal to 1 mL/min. Detection was done in selected ion monitoring mode (SIM) using 6-group program for detection of target ions. PCB209 was used as internal standard spiked to samples in amount of 300 pg.
The results have been expressed by the mean of four camels within three periods ± standard error of the mean (SEM): period 1 -contamination period; period 2 -first two months of decontamination period with fat mobilization; period -3 -second two months of decontamination period with fat storage. The statistical differences between the 3 periods were assessed by variance analysis (ANOVA) using XLstat software (Addinsoft ©). Only the difference between periods was tested.
Results and their discussion
The metabolism of POPs includes the intake, the transport of biological fluid in blood and lymph, their storage in adipose tissue and the excretion through feaces, urine and milk. In the frame of our experiment the concentration in hump fat and excretion in milk has been assessed in order to determine the bioaccumulation and decontamination mechanisms of pollutants in these different compartments. In the gastrointestinal tract, after ingestion of the capsule with contaminants, pollutants enter into forestomach of the camel, and then entered in the bloodstream. The blood transferred the pollutants to other compartments, especially in adipose tissue, the hump representing the main part. A part of the contaminants is excreted with milk in lactating ruminants and probably also through the feaces. For a better understanding, the results were expressed according to the 3 main periods of the experiment: (1) the mean values during the two months of contamination (contamination period), (2) the mean values during the first 2 months of decontamination, and (3), the mean values during the last two months of decontamination. However, the kinetics was presented by taking into account the mean of the 4 camels and the sum of PCBs on the one hand and of DDT/DDE on the other hand.
At the beginning of the contamination period, the lipophilic properties of pollutants lead to a rapid in-creasing of their concentrations in hump, and because the animals are in phase of fat storage, in total quantity. At the same time, the concentrations in milk did not increase in a notable manner. When the plateau was reached after two months of contamination, the concentrations in blood and milk increased, showing the elimination of pollutants (Fig. 1, 2).
It seems that the main storage of organic pollutants in the hump would first slow the transfer into milk but also extend the time necessary for decontamination in comparison to other ruminants.
By considering the cumulative excretion in milk all along the experiment and the quantity of pollutants in hump at the beginning of the experiment, the global kinetics of bioaccumulation and excretion process could be summarized for both PCB and DDT (Fig. 1,2).
This phenomenon is accentuated because of the hump weight decreased after starting decontamination (during summer time) due to the fat mobilization. The concentration and the quantity of pollutants stored in hump decreased regularly all along the decontamination period. The elimination in milk appeared low in quantity because the transfer to milk is in low percentage (between 2 and 9% depending to congeners) contrary to other species as cow and goat. A similar trend occurred for PCBs and DDT.
At the end of experimentation, the total quantity of PCB and DDT excreted in milk were estimated to 28.6 and 0.95 µg respectively and the total quantity accumulated during the contamination period in hump was 5530.4 and 54.3 µg respectively. In consequence, the percentage of excreted pollutants in milk was low: only 0.52% for PCB and 1.74% for DDT on average. The percentage of pollutants accumulated in hump was less than 15% of the total intake with a higher proportion for PCB than for DDT. After 4 months of decontamination, the total quantity of PCB and DDT was disappearing respectively 47.4% and 35.5% of the maximum concentration at the contamination period.
Conclusion
Besides the assessment of the live weight, hump volume and milk yield in field conditions, the main conclusions of our work regarding the transfer of POPs in Bactrian camel model are as follows: The role of the camel hump (from 5.3 to 21.5 kg) as a pivotal organ (due to its importance in the cycle lipid storage/lipid mobilization) in the metabolism of pollutants having lipophilic properties is verified.
At reverse, in spite of the importance of this route of excretion and thanks to its fat content, only small concentrations of pollutants are observed in milk. On average, after 6 months of experiment, the percentage excreted in milk was 0.52% (PCBs) and 1.74% (DDT) of the cumulative POPs in the hump, but there is a high variability between congeners.
Based on the maximum quantity of pollutants in hump during the contamination period and the quantity available at the end of experiment, the percentage of loss of PCB was 47.4% and for DDT, it was 35.5% that means the camel could be completely decontaminated within less than one year.
Moreover, based on literature data, the concentrations of pollutants in milk were low compared to milk from other contaminated dairy animals as goats and cows. The carry-over rate (COR) was 8.9% for PCB52 in our study vs according to the literature 25% in goats, and 7.7% for PCB180 in our study vs 55% in goats and 65% in cows. As the carry over rate for camels seems to be very low, in comparison to other ruminants. we could conclude that: a. The camels would transfer pollutants in milk slowlier than other ruminants; b. The application of transfer rates stated in other ruminants may overestimate the exposure of dairy camels.
c. Complete decontamination of camels would certainly take more time than in other ruminants The present work has been achieved in a private farm. The lack of experimental camel farms in Research structures of Kazakhstan is an important constraint for the future research activities regarding this specie. Regarding the important place of Camel products in Food habits in Kazakhstan, this lack should be considered in future development of research facilities. In the international scientific community interested by the camel (International Society for Camelid Research and Development -ISOCARD), the studies regarding the behavior of camel faced to pollution are very few. The present study appears original and innovative for camel scientists over the world and confirms the interest of this species as a biological model in such research regarding the impact of environmental pollution on animal products. The special focus on Bactrian Camels poorly studied in the scientific literature allowed to enlarge existing knowledge about this specie emblematic of Central Asia. | v3-fos |
2018-04-03T02:37:29.256Z | {
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} | s2 | Seasonal Changes in the Caste Distribution of Foraging Populations of Formosan Subterranean Termite in New Orleans, Louisiana
This study examined the relationship between temperature, precipitation, soil composition, levels of feeding damage, and the caste distribution (workers, soldiers, nymphs) of the Formosan subterranean termite, Coptotermes formosanus Shiraki, collected in underground monitoring stations over a 12 mo period. Because nymphs are the caste that develops into alates, the seasonal abundance of nymphs was examined over a 5 yr period. Numbers of workers, soldiers, and soldier/worker ratio were significantly affected by month. Recruitment and retention of foraging termites in stations was significantly affected by the level of feeding damage. The number of nymphs collected in monitoring stations was highly variable. In the 12 mo test, there was a significant correlation between numbers of nymphs and level of feeding damage, temperature, precipitation, and soil composition. Over a 5 yr period, significantly more nymphs were collected in 2011 than in 2007 and 2008. Peak nymph collections varied from year to year. Overall, peak nymph collections were more likely to occur in Mar., Sept., and Oct. Increasing our knowledge of the environmental factors that influence recruitment and retention of foraging termites in monitoring stations could influence termite bait placement and improve baiting strategies for termite control. Identifying the key factors that cause aggregations of nymphs in underground stations could increase our ability to predict the intensity and location of alate swarms.
Formosan subterranean termite, Coptotermes formosanus Shiraki, is an invasive species and the most destructive structural pest in the southern United States (Lax and Osbrink 2003). Because Formosan subterranean termite colonies have extensive underground gallery systems (King and Spink 1969), it is difficult to eliminate entire C. formosanus colonies using soil insecticides (Su 2005;Osbrink et al. 2005;Osbrink et al. 2014). Baiting programs have been used successfully to eliminate subterranean termite colonies (Su et al. 1995;Eger et al. 2012). Environmental factors such as temperature, humidity, soil type, and soil moisture affect termite activity at bait stations Santos et al. 2010;Cornelius and Osbrink 2011;Ruan et al. 2015). Seasonal variations in caste distribution of foraging populations of C. formosanus could also influence feeding and foraging behavior of termites on baits. For instance, soldier proportions affect wood consumption rates. In the Formosan subterranean termite, wood consumption decreased as soldier proportion increased from 30 to 40% (Su and La Fage 1987). There was a significant interaction of temperature and soldier proportion on survival of C. formosanus. Termite survival declined significantly when soldier proportions exceeded 20% at 20 and 25 C, but not at 30 or 33 C (Fei and Henderson 2002). There was seasonal variation in caste distribution of foraging populations of the subterranean termite, Reticulitermes flavipes (Kollar). Workers were most abundant in the spring and summer months and soldiers were most abundant immediately preceding alate flights (Howard and Haverty 1981). Two studies have examined seasonal changes in soldier proportions of C. formosanus restricted to cypress trees submerged in the Calcasieu River, Lake Charles, Louisiana. Significantly more soldiers were produced at higher temperatures (Waller and La Fage 1988;Delaplane et al. 1991). Microsatellite markers determined that mean annual temperatures and soil moisture was correlated with the level of inbreeding in colonies of R. flavipes and R. grassei (Clément) ). Increasing our understanding of how environmental factors and changes in caste distribution affect termite foraging activity at bait stations will improve termite control strategies.
Nymphs are the caste that develops into alates (winged reproductives). Changes in the numbers of nymphs collected in monitoring stations could serve as an early indicator of the intensity of alate swarms. Also, increased numbers of nymphs in specific monitoring stations could be used to predict the flight dispersal location. In addition, it may take 4-6 yr for an incipient colony of C. formosanus to reach maturity and produce alates (Chouvenc and Su 2014). Thus, the presence of nymphs in a foraging population indicates that the colony has reached reproductive maturity.
Studies of alate production and dispersal of C. formosanus are important for predicting the spread of this invasive species. Formosan subterranean termites are slowly expanding their range throughout the southern United States (Jenkins et al. 2002;Hu and Oi 2004;Brown et al. 2007). Although human transport of termite infested material is the primary method of expansion to new regions, natural dispersal of C. formosanus occurs slowly through the annual nuptial flights of alates. A stochastic model simulating the spread of the invasive termite, Nasutitermes corniger (Motschulsky), determined that number of alates released from the nest, alate survival, maximum pheromone attraction distance between pairs, and mean flight distance were the key factors in predicting the spread of this invasive pest (Tonini et al. 2013). Alates of C. formosanus generally swarm from April through June to give rise to new colonies (Henderson and Delaplane 1994;Henderson colony. Therefore, alate dispersal plays an important role in the spread of C. formosanus in areas where it has become established and in the reinvasion of areas where colonies have been eliminated through termite treatments. There is significant variability in the numbers of C. formosanus alates swarming at the same locations from year to year Puckett et al. 2014). For example, the number of alates captured at the same location in New Orleans, LA was more than three times higher in 2001and 2003than in 2000. In Galveston, TX, significantly more alates were captured in 2009 than in 2010 and 2011 (Puckett et al. 2014). Increasing our understanding of the environmental factors that affect swarming behavior will improve strategies to control infestations and predict the spread of this invasive species.
There is little information about the seasonal abundance of nymphs in C. formosanus colonies. The presence of nymphs in foraging populations of R. flavipes accounted for 3.0-8.4% of the population (Howard and Haverty 1981). Nymphs found in a survey of five entire colonies of C. formosanus restricted to cypress trees accounted for a much lower proportion of the population, ranging from 0 to 0.004% of the colony (Su and La Fage 1999). Reports on the abundance of nymphs in monitoring stations are limited. Numbers of C. formosanus nymphs were recorded from foraging populations in collections of three underground stations sampled at three different times of the year (Su and Scheffrahn 1986). Seasonal abundance of nymphs was also described from four monitoring stations over a period of 12 mo (Raina et al. 2004). Studies of the seasonal abundance of nymphs in mature colonies over long periods of time could increase our knowledge of the environmental factors that influence swarming behavior of alates.
Because of the cryptic nature of subterranean termites, it is difficult to study changes in the caste distribution of field populations. Underground monitoring stations offer a window into the feeding behavior and caste distribution of foraging populations of subterranean termites. The objective of this study was to examine the relationship between temperature, precipitation, soil composition, levels of feeding damage, and the caste distribution (workers, soldiers, nymphs) of C. formosanus collected in underground monitoring stations over a 12 mo period. This study also described the seasonal abundance of nymphs from 20 monitoring stations over a 5 yr period from 2007 to 2011 and examined the relationship between temperature and precipitation and nymph abundance.
Materials and Methods
Two experiments were conducted in a 5.26 km 2 urban park, City Park, New Orleans, Louisiana and in two different areas immediately adjacent to the park. One area was located adjacent to the Orleans canal which borders the west side of City Park > 200 m outside of the park itself. The other area was located adjacent to Bayou St John which borders the east side of City Park > 500 m outside of the park. Both areas were > 2 km from the other monitoring stations located within City Park. For both experiments, populations of C. formosanus were monitored monthly using underground monitoring stations filled with blocks (7.5 by 3.8 by 0.8 cm) of spruce, Picea sp. Colonies located within 200 m of each other were delineated using mark-release-recapture techniques with the dye markers Nile Blue A and neutral red (Sigma-Aldrich, Milwaukee, WI) to determine which stations were part of a single, interconnected tunneling system (Su et al. 1993;Ruan et al. 2015). Average monthly temperature and precipitation was obtained for the NOAA station at the Lakefront airport located about 10 km from City Park (www.noaa.gov).
Seasonal ndspro.com). The monitoring stations were buried in the ground so that the lids were level with the surface of the soil and filled with 10-15 bundles of wood. Each bundle contained seven or eight individual blocks of spruce (7.5 by 3.8 by 0.8 cm) tied together with plastic ties. The stations were placed at the base of trees infested with C. formosanus.
A field test was conducted from June 2011 to May 2012. Termites were collected every month from 30 monitoring stations and 12 C. formosanus colonies, except data were missing from three stations in April and two stations in May due to construction projects. Nine colonies were located in four different areas within City Park that were > 200 m apart, one colony was located along the Orleans canal and two colonies were located along Bayou St John. Every month, all wood was collected from each station and immediately replaced with new wood. Collected wood was brought back to the laboratory. Individual blocks were separated from bundles, termites were removed from wood, carefully separated from soil and debris, and weighed. Individual worker and soldier weights were calculated by weighing four groups of ten workers and ten soldiers for each station. Numbers of workers and soldiers were estimated by dividing the total worker or soldier weight for each collection by the average worker or soldier weights for each station. The number of nymphs in each collection was counted. Out of a total of 355 collections, only a single alate was found. The feeding damage level in each station every month was recorded as none, low, medium, and high. Figure 1A shows a bundle of wood with no termite feeding damage. Feeding damage was recorded as low when termites had constructed shallow grooves on the surface of the wood blocks ( Fig. 1B). Feeding damage was recorded as medium when the grooves were deeper and termites had constructed a gallery system within the wood blocks (Fig. 1C). Feeding damage was recorded as high when termites had consumed most or all of the wood blocks (Fig. 1D).
Soil composition was determined by taking a soil core sample of 20 cm depth within 0.5 m of each station. The composition of 15 g samples of soil was determined using a soil macronutrients kit (LaMotte Company, www.lamotte.com).
Seasonal Abundance of Nymphs in Monitoring Stations from 2007 to 2011. A field test was conducted from January 2007 to November 2011 in an area of City Park > 1 km from the areas studied in the preceding field experiment. Monitoring stations consisted of plastic buckets with the bottom removed to allow underground access by termites (Su and Scheffrahn 1986). The buckets were buried in the ground so that the lid was level with the surface of the soil. Termites were collected monthly from 20 stations and 8 C. formosanus colonies. Termites were removed from wood, separated from debris, and the number of nymphs in each collection was counted. However, termites were not collected from every station during the winter months due to low termite activity levels.
Statistical Analysis. The effect of the level of feeding damage on the numbers of workers, soldiers, nymphs, and the soldier/worker ratio was determined using a Kruskal-Wallis ANOVA and means were separated using Dunn's methods on ranks. The number of workers, soldiers, nymphs, and the soldier/worker ratio collected in stations each month was compared a Kruskal-Wallis ANOVA. Because of missing data from three stations in April and two in May, means were separated using Dunn's method of multiple comparisons on ranks for unequal sample sizes. Linear regression was used to examine the relationship between monthly average temperature and precipitation and monthly average of workers, soldiers, and nymphs. Also, the number of grams of sand, silt, and clay in 15 g samples of soil for each station was compared with the total number of workers, soldiers, and nymphs collected from those stations using linear regression. Data on nymphs were transformed by Log þ 1 for linear regression analysis.
The number of nymphs per month and per year for data collected from 2007 to 2011 was compared using a Kruskal-Wallis ANOVA. Because data were not collected from every station every month, means were separated using Dunn's method on ranks for unequal samples sizes. Linear regression was used to determine the relationship between the average monthly temperature and precipitation over 5 yr and the average numbers of nymphs. Data on nymphs were transformed by Log þ 1 for linear regression analysis. All analyses were conducted using SigmaPlot 11.0 (Systat Software 2008).
Results and Discussion
Seasonal Changes in Caste Distribution of C. formosanus in Monitoring Stations from June 2011 Through May 2012. Recruitment and retention of foraging termites in monitoring stations changed as the level of feeding damage increased. There was a significant effect of feeding damage level on numbers of workers (H ¼ 134.9; P < 0.001), soldiers (H ¼ 134.4; P < 0.001), nymphs (H ¼ 43.2; P < 0.001) and soldier/worker ratio (H ¼ 96.8; P < 0.001). Numbers of workers, soldiers, and nymphs were significantly greater in stations with medium damage levels than stations with no or low damage levels and numbers of workers and soldiers were significantly greater in stations with medium damage than stations with high damage (Dunn's Method on ranks) ( Fig. 2A-C). The soldier/worker ratio was significantly greater in stations with high levels of feeding damage than in station with low levels of feeding damage (Fig. 2D) and retention of both workers and soldiers in monitoring stations increased as feeding damage increased from no damage to medium levels of damage. The number of both workers and soldiers peaked in stations once workers had constructed galleries within the wood blocks and foragers were able to move into tunneling systems within the blocks. When stations contained blocks with high levels of damage, foragers abandoned monitoring stations. However, soldier proportions peaked after wood blocks had been almost completely consumed. Once termites had completely consumed the gallery system within the block, monitoring stations contained mostly soldiers. These results demonstrate that termites are likely to completely consume bait matrices and abandon bait stations within a month when feeding activity is high.
There were seasonal fluctuations in the feeding activity of termites in monitoring stations. There were no stations with high levels of feeding damage from Nov. to Feb. and the majority of stations had low levels of feeding damage. The majority of stations had either medium or high levels of feeding damage from Mar. to Oct. The highest proportion of stations with high levels of feeding damage occurred in April (Fig. 3). When wood was replaced in monitoring stations every month, levels of feeding damage fluctuated as foraging termites gradually colonized the new wood in stations. From Mar. to Oct., there were stations where termites were collected after most of the wood had been consumed. Therefore, feeding rates increased as temperatures increased, resulting in a higher number of stations where foraging termites were depleting their food source and abandoning the monitoring stations before monthly collections. Wood consumption is a more reliable indicator of termite foraging activity in monitoring stations. A previous study measuring wood consumption found a significant correlation of feeding rates with air temperature, soil temperature, and soil moisture . also found that feeding rates of C. formosanus fluctuated seasonally. Fluctuations in recruitment and retention of foragers in monitoring stations due to changes in food availability act as a confounding factor in the evaluation of seasonal changes in caste distribution and foraging activity.
The number of workers was significantly lower in Dec. than in Feb., Mar., April and May, and the number of soldiers was significantly lower in Dec. than in July, Sept., and Mar. (Table 1). The number of workers collected in stations peaked in Mar. Numbers of nymphs per month were not significantly different. Although there was a large peak in nymph numbers in July, the variability in numbers per station was very high. In July, over 300 individuals were collected from two stations, whereas 16 stations had none. Soldier/worker ratios were significantly greater in Aug. than in April and May (Table 1). Average soldier/worker ratios per month in monitoring stations ranged from 6 to 59%. Soldier/worker ratios are generally higher in monitoring stations than ratios in the entire colony. Soldier/worker ratios for entire colonies of C. formosanus ranged from 12 to 28% (Su and La Fage 1999), whereas soldier/worker ratios in traps ranged from 20 to 60% (Haverty 1977). Soldier/worker ratios were higher in Aug. compared with April and May. In Louisiana, Formosan subterranean termites generally swarm from April through June, with peak swarming in May (Henderson and Delaplane 1994;Henderson 1996;Guillot et al. 2010;Mullins et al. 2015). Previous studies of C. formosanus populations located in submerged cypress trees found that soldier/worker ratios were greater in the spring compared with the summer and fall (Waller and La Fage 1988;Delaplane et al. 1991). Soldiers congregate at swarming sites (Stuart 1969). Only a single alate was collected in the 30 monitoring stations throughout 2011-2012. Therefore, the low soldier proportion in stations in April and May was probably due to the movement of soldiers out of stations to congregate at swarming sites in the trees during April and May.
The number of workers in stations was not correlated with temperature, precipitation, or soil composition. There was a significant correlation between precipitation and the numbers of soldiers and nymphs in monitoring stations (Table 2). There was a negative correlation between numbers of nymphs and average temperatures. Although there were very low numbers of nymphs from Dec. to Feb., the average number of nymphs was higher in the fall and spring than in June and Aug. when average temperatures reached 29 C in June and peaked at 30.7 C in Aug.
Average number of nymphs collected in stations was extremely low. The highest number of nymphs collected occurred in July. The peak nymph number in a single collection of 545 nymphs accounted for 0.03% of termites in the collection and the average number of nymphs per month in July accounted for 0.006% of the average number of termites collected. In contrast, a study examining underground monitors on the campus of University of New Orleans found peak nymph numbers from one station in May that accounted for 21% of the collection (Raina et al. 2004). Also, the presence of nymphs in foraging populations of R. flavipes is much higher, accounting for 3.0-8.4% of the population (Howard and Haverty 1981).
The percent sand in soils at each station ranged from 36.6 to 93.3%. Most of the stations were located in soils containing >50% sand (Fig. 4). Soil composition had no effect on numbers of workers and soldiers in stations. However, the number of nymphs in stations was positively correlated with the amount of silt and negatively correlated with the amount of sand (Table 2).
Seasonal Abundance of Nymphs in Monitoring Stations from 2007 to 2011. There were significantly more nymphs collected in monitoring stations in 2011 than in 2007 and 2008 (H ¼ 20.08, P ¼ <0.001) (Fig. 5). In a comparison of the total number of nymphs collected in stations each month over the 5 yr period, significantly more nymphs were collected in Mar., Sept., and Oct. than in Jan. (H ¼ 56.66; P ¼ <0.001; comparison test on ranks could not distinguish between monthly nymph collections (Dunn's Method; Fig. 7A-C).
In 2010, the number of nymphs collected in April was significantly greater than the number collected in Jan. (Fig. 7D). In 2011, the number of nymphs collected in Oct. was greater than in Jan., and the number collected in Mar. was greater than the number collected in Jan., Feb., April, May, Aug., and Nov. (Fig. 7E). Overall, there was no correlation between number of nymphs collected in stations with either average monthly temperature (R 2 ¼ 0.02; P ¼ 0.65) or precipitation (R 2 ¼ 0.12; P ¼ 0.27). However, there was a significant negative correlation between precipitation and number of nymphs in 2009 (R 2 ¼ 0.58; P ¼ 0.004) and a marginally positive correlation between precipitation and number of nymphs in 2011 (R 2 ¼ 0.36; P ¼ 0.53) ( Table 3). It is likely that numbers of nymphs in monitoring stations are related to nymph production by the colony. Environmental factors, such as precipitation, may influence nymph production weeks or months before changes occur in the number of nymphs in foraging populations.
The number of nymphs collected from stations was highly variable. Peak nymph collections varied from year to year. When Su and La Fage (1999) examined caste distributions from five entire colonies restricted to cypress trees, two colonies contained no nymphs, two colonies contained < four nymphs and one colony contained 322 nymphs. Collections of nymphs from foraging populations of Coptotermes gestroi (Wasmann) found a wide variation in the number of nymphs collected from different colonies and in different seasons (Albino and Costa-Leonardo 2011). In a study examining four stations on the University of New Orleans campus over a 12 mo period, numbers of nymphs were comparatively high, ranging from 4 to 21% in one station, Bars followed by the same letters were not significantly different (P > 0.05) (Dunn's test on ranks). Error bars 6 SEM. Lines represent average monthly temperatures (black circle) and total monthly precipitation (white square). 0 to 4.3% in one station, and 0% to <1% in the other two stations (Raina et al. 2004).
Overall, collections of nymphs from 2007 to 2011 fluctuated significantly from year to year and were more likely to peak in Mar. and have a secondary peak in Sept.-Oct. However, peak numbers of nymphs in stations varied by location and season. Raina et al. (2004) found that the timing of peak numbers of nymphs varied between four stations, with one station peaking in May, one station peaking in Oct., one station having a peak in Oct.-Nov. and a second peak in May, and one station having peak numbers of nymphs collected between June through Aug. Nymph numbers in most collections consisted of 0-2 nymphs, with rare collections of over 50 nymphs (nine collections over 5 yr). Because of the extremely low numbers and high variability of nymphs collected in monitoring stations, it is difficult to determine how seasonal and environmental factors affect their abundance in foraging populations of C. formosanus.
Conclusions
It is difficult to monitor 14 populations of subterranean termites in the field. Underground monitoring stations provide a method for sampling the foraging activity and caste distributions of subterranean termites. Recruitment and retention of termites to bait stations is a crucial component of baiting strategies for termite control. This study demonstrates that C. formosanus can rapidly deplete the bait matrix during the months with the highest levels of foraging activity. Depletion of the bait matrix and subsequent abandonment by termites increases the time needed to eliminate C. formosanus colonies. These results indicate that it is necessary to improve bait technology to maximize consumption of bait toxins by foraging populations of C. formosanus. Advances in the development of durable and fluid baits may provide better control of C. formosanus infestations than standard bait stations where rapid depletion of bait is a problem (Eger et al. 2014;Su 2015).
Because nymphs are a reproductive caste, it is important to identify the environmental factors that affect nymph production in order to improve strategies for termite control. However, there was no consistent correlation between either temperature or precipitation and numbers of nymphs collected in monitoring stations. Peak numbers of nymphs in monitoring stations varied by year and location. In contrast, alate swarms in New Orleans consistently peak in May (Henderson 1996;Mullins et al. 2015). Further studies are needed to better understand factors causing nymphs to aggregate in certain stations at specific times and how these aggregations correlate with alate production and swarming behavior. Increasing our knowledge of the environmental factors that affect termite foraging behavior and caste distribution in monitoring stations could result in the development of novel methods for termite control. | v3-fos |
2016-05-04T20:20:58.661Z | {
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} | s2 | Callus cell proliferation from broccoli leaf slice using IBA and BAP in vitro culture: Its biochemical and antioxidant properties
Plant tissue or cell culture keeps a significant role in micro-propagation in the plant production industry. Combination of 6-Benzylaminopurine (BAP) and other plant growth regulators like 1-Naphthaleneacetic acid (NAA) or Indole-3-acetic acid (IAA) or indole-3-butyric acid (IBA) was used in the most of the research in tissue culture. The study was carried out to investigate the optimization of the concentration of IBA and BAP combination (0, 0.25, 0.50, 1.0, 1.50, 2.0, 2.5, 3.0 and 3.5 mg/l) for the root, callus and leaf proliferation from the leaf cutting slice. The highest number (6.75) of root proliferation was observed in the concentration of 2.0 mg/l IBA+0.25 mg/l BAP combination. The callus initiation was found in the concentration of IBA 1.0–3.5 mg/l+BAP 1.0–2.0 mg/l. However, the highest callus weight was observed at the concentration of IBA 1.5 mg/l+BAP 1.0 mg/l combination than other combination of concentrations. Positively leaf initiation and formation was better in the concentration of IBA 1–3.5 mg/l+BAP 1.0–2.0 mg/l combination. In addition, the 2,2-diphenyl-2-picrylhydarzyl (DPPH) free radical scavenging potential was higher (70.1%) in leaves extract than in callus extracts (46.3%) at the concentration of 10 mg/ml though both extracts had lower DPPH free radical scavenging activity compared to the positive control, vitamin C and BHT. Theresults conclude that the optimum concentration was IBA 1.5 mg/l+BAP 1.0 mg/l combination to produce callus cell proliferation and concentration of 2.0 mg/l IBA+0.25 mg/l BAP combination was the optimum for root proliferation of broccoli in vitro.
a b s t r a c t
Plant tissue or cell culture keeps a significant role in micropropagation in the plant production industry. Combination of 6-Benzylaminopurine (BAP) and other plant growth regulators like 1-Naphthaleneacetic acid (NAA) or Indole-3-acetic acid (IAA) or indole-3-butyric acid (IBA) was used in the most of the research in tissue culture. The study was carried out to investigate the optimization of the concentration of IBA and BAP combination (0, 0.25, 0.50, 1.0, 1.50, 2.0, 2.5, 3.0 and 3.5 mg/l) for the root, callus and leaf proliferation from the leaf cutting slice. The highest number (6.75) of root proliferation was observed in the concentration of 2.0 mg/l IBAþ 0.25 mg/l BAP combination. The callus initiation was found in the concentration of IBA 1.0-3.5 mg/l þ BAP 1.0-2.0 mg/l. However, the highest callus weight was observed at the concentration of IBA 1.5 mg/l þBAP 1.0 mg/l combination than other combination of concentrations. Positively leaf initiation and formation was better in the concentration of IBA 1-3.5 mg/l þBAP 1.0-2.0 mg/l combination. In addition, the 2,2-diphenyl-2-picrylhydarzyl (DPPH) free radical scavenging potential was higher (70.1%) in leaves extract than in callus extracts (46.3%) at the concentration of 10 mg/ml though both extracts had lower DPPH free radical scavenging activity compared to the positive control, vitamin C and BHT. Theresults conclude that the optimum concentration was IBA 1.5 mg/l þBAP 1.0 mg/l combination to produce callus cell Value of the data 1. The data provides the information of the effect of different concentrations of IBA (auxin) and BAP (cytokinin) on the leaf, root and callus proliferation from broccoli leaves slice in vitro culture. 2. This data would be valuable for further studies of physiological, biochemical and antioxidant activity in broccoli explants in vitro culture.
Data
In the data, the effects of IBA and BAP on the callus, roots and leaf formation have been shown (Table 1.2). In Table 1.3, effects of different combinations of hormones on the fresh weight of callus produced have been mentioned. Furthermore, measurement of the OD reading of control, positive control (vitamin C and BHT) and other samples have been taken at 515 nm using spectrometer
Preparation of Murashige and Skoog (MS) basal media
The MS basal media [1] were used as control and seed germination was prepared following the standard procedures for MS powder form preparation (Table 1.1). MS powder form was added in a beaker with 800 ml distilled water followed by 30 g of sucrose and 2.8 phyta gels and adjusted the pH to 5.8 so that the final volume of the medium was 1000 ml.
Media in the autoclave
MS basal media with auxin was prepared by adjusting the pH to 5.8 by using 1 N HCl and 1 M NaOH. Then, the media was fractional in 30 ml and was added into jam jars (7 Â 4.5 cm 2 ) and autoclaved at 15 psi and 121°C for 20 min. After that, the sterilized media were cooled and kept in culture room under dark condition. Preparation of media was completed a week before use to reduce water condensation in jam jars and the media was sterilized completely.
Seed sterilization and germination in the MS media
Seeds of broccoli were obtained from the nursery. A total of 100 seeds were used on MS [1] basal medium. The 20 jam jars were used to culture the seeds and five seeds were germinated on every jam jars. The seeds were washed in 70% ethanol for about 5 min, and then rinsed in 15% chlorox for 15 min. The seeds were brought into the laminar flow hood and further rinsed with sterile DH20 for a few seconds. Then, the sterilized seeds were germinated on MS basal media for 7 days. This process was carried out under aseptic condition in the laminar flow. The seeds were exposed to light from cool white fluorescent tubes for a photoperiod of 16 h in the incubation room at 25-28°C.
MS basal media with IAA and IBA and BAP (2nd time media preparation)
The MS media with IBA and BAP were used as rooting media, MS powder form was added in a beaker filled with 800 ml distilled water and 30 g of sucrose was added. Then, the hormones with specific concentration were added. The pH was similarly adjusted and 2.8 g phyta gel was added, so that 1000 ml of medium was prepared. The media with hormones were prepared for 10 replicates of each hormone concentration. The BAP (as cytokinin) and IBA (as auxin) concentrations were 0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3 and 3.5 mg/l.
Leaf cutting slice culture on MS supplemented with IBA and BAP
After one week of germination, 7 days seedlings were selected as a source of explants. The explants leaves were cut and transferred into the media with different concentrations of IBA and BAP 0, 0.25, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5 mg/l. Each treatment was consisted as five replications. Broccoli leaves were sliced in the clean bench. After that, in vitro culture on MS basal was performed. The leaf slice cultures were put in the growth chamber in the incubation room at 25-28°C. Randomized complete block designed (RCBD) was used during sampling setting.
Antioxidant activity of broccoli
The antioxidant was evaluated based on the scavenging activity on the stable 2,2-diphenyl-2-picrylhydarzyl (DPPH) free radical measured by spectrophotometer [2]. DPPH was useful reagent for investigating the free radical activities of compounds. A freshly prepared DPPH solution was exhibited a deep purple color with maximum absorption at 515 nm. The DPPH observation was a non-enzymatic method currently used to provide basic information on the ability of extracts to scavenge free radical. The OD reading of control, positive control (vitamin C and BHT [3]) and all samples were taken at 515 nm using spectrometer. The use of the percentage of free radical scavenging activity was calculated by the following formula for vitamin C. Vitamin C¼ [(A controlÀ A sample)/A control]x100 [3].
Data collection
Root and callus formation and leaf proliferation were observed and data were collected after one month of treatment setting. The 2,2-diphenyl-2-picrylhydarzyl (DPPH) free radical was measured.
Design and statistical analysis
Randomized block design was used during sampling setting. Standard deviation and then standard error was made to compare the replicates. Least Significant Difference (LSD) test was used for data analysis. | v3-fos |
2019-05-28T13:13:23.460Z | {
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} | s2 | Sustainability of Sheep and Goat Production Systems
Sustainability of sheep and goat production systems has been investigated in this chapter in terms of environmental, social, and economic sustainability. Strategies to reduce waste from animal husbandry activities and the negative impact of animal husbandry on environment have been described. Social sustainability has been analyzed in relation to animal welfare and human–animal relationship. Economic sustainability of sheep and goat production systems in the Mediterranean countries has been addressed in terms of animal management plans to improve animal health, quality of products, and increase profitability of animal production systems. In particular, strategies to change the basic standard for sheep and goat productions into high standard of nutritional, hygienic, and technological quality have been analyzed.
Introduction
Sustainable development aims to meet human needs by preserving the natural environment so that these needs can be met both in the present and in the future (Peacock and Sherman 2010). The field of sustainable development can be divided into three concepts: environmental, social, and economic sustainability.
Environmental sustainability is linked to energy use, biodiversity and genetic conservation, and environmental management; when applied to farm animals, environmental sustainability is associated to the negative impact of husbandry on air, soil, and water pollution. Waste from animal husbandry comprises fecal and urinary output, and production of fermentation and respiration gases, such as carbon dioxide (CO 2 ) and methane (CH 4 ). In the waste usually high amounts of water, nitrogen (N), and other inorganic molecules are found.
The link between animal production and natural environment is acquiring more importance for the sustainability of the farm system (de Rancourt et al. 2006).
Consumer concerns about the quality and sustainability, including ethical aspects, of the production cycle of animal food products is increasing. Social sustainability concerns politics, social institution, culture, tradition, and civil society. In this chapter social sustainability is discussed as animal welfare and human-animal relationship. In particular, the concerns about life quality of farm animal in relation to human-animal relationship to optimize animal production are presented.
In the Mediterranean area small ruminant farming systems represent one of the most important agricultural activity connected to the utilization of marginal lands, with prevalence of pastoral system, low level of mechanization, and production of typical products, mainly cheeses. Although small ruminant farming systems are largely diffused in all the Mediterranean countries, the level of animal management is far from an acceptable level of animal health, quality of products, and profitability.
Environmental Sustainability of Sheep and Goat Production System
Ruminant livestock produce about 80 million tons of methane (CH 4 ) accounting for about 28 % of anthropomorphic emissions each year (Beauchemin et al. 2008). CH 4 is physiologically produced as a by-product of digestion; at farm level CH 4 is emitted both from direct ruminant fermentation and from manure. Methane production by ruminants is influenced by animal size, dry matter intake, carbohydrates, and other components of the diet (Wilkerson et al. 1994). The increasing level of concentrate in the diet of ruminants causes changes in the fermented substrate from fiber to starch and a decline in ruminant pH with a reduction of the proportion of dietary energy converted to CH 4 . However, the increased level of concentrate in ruminant diet should be limited at 50 % of the diet to avoid negative effects on milk quality. A number of nutritional management strategies to reduce enteric CH 4 production have been reported, among which are increasing the level of grain and lipids, and supplementation with ionophores in the diet. Furthermore, a number of feeding strategies to reduce CH 4 emissions in animal production systems have been proposed, such as feeding maize and cereal silages instead of grass silage, improved pasture management, inclusion of legumes, yeast and enzyme, feed additives, or plants characterized by secondary compounds with potential CH 4 suppressing properties (Beauchemin et al. 2008). Nitrogen losses originate mainly from the imbalance and the asynchrony between the rate at which carbohydrates and proteins are degraded at rumen level (Tamminga 1996). The imbalance between the simultaneous availability of net energy and amino acids in the rumen is the main cause for NH 3 ruminal losses; ammonia, after its conversion into urea in the liver, is found in blood and milk, and is excreted in urine. Apart from the contradictory results on the relationship between CP level of diet and milk yield and composition, the concentration of urea in the milk is always regarded as a good indicator of efficient use of dietary protein by the animals, and it is currently used to evaluate and to adjust the diet (Cannas 2002). The efficiency of dietary N utilization for milk protein synthesis is rather low in dairy sheep and goat (15-35 %) (NRC 1988), and the use of high protein level diets for sustaining milk production in lactating animals is widely studied. High protein level diet can result in a number of deleterious events: reducing environmental sustainability of sheep and goat farming, causing an increase of N output to the environment, and high levels of ammonia pollution in animal houses, which originates from animals' urine and feces and can be injurious to both livestock and stock persons' health. An increased N excretion in urine and feces, as a consequence of poor dietary N absorption, can result also in high growth of microorganisms. Sevi et al. (1999Sevi et al. ( , 2006 suggest that the efficiency of utilization of dietary N in the lactating ewe increases with decreasing protein levels in the diet from 16 to 13 %, especially when limiting amino acids (lysine and methionine) in the ration are encapsulated to prevent bacterial deamination in the rumen. Sheep fed with a moderate protein level excrete more N than sheep fed with low protein level of the diet. On the contrary, the low protein level of the diet results in lower amount of feces, in less wet feces, and in higher NH 3 release in the urine. The choice of a proper ventilation regimen in small ruminant housing is critical for the control of environment and for removing aerial pollutants, which originate from animals and their excreta. In particular, low ventilation rates can fail in removing efficiently the moisture and gases, which originate from the respiratory activity of animals and the decomposition and fermentation of manure, resulting in increased relative humidity and higher air concentrations of ammonia and carbon dioxide. Very high ventilation rates, instead, can result in higher air dust concentrations, probably due to reduced humidity levels and to turbulent air currents maintaining dust particles suspended in the air for a longer time. Ventilation rate is based on the length of ventilation cycles and on air speed. During summer, dairy sheep need an average ventilation rate of about 65 m 3 /h/head achieved by giving most ventilation cycles during the hottest hours of the day (Sevi et al. 2002(Sevi et al. , 2003b. However, also overnight air exchange for removing gases, mostly ammonia, originated from excreta decomposition and fermentation are of great importance. Furthermore, combining a moderate protein level of the diet (16 %) with low ventilation rates result in excretion of 40-64 % of higher volumes of urine and 40-79 % greater amounts of total water.
Litter management by using paraformaldehyde and bentonite is an effective strategy for reducing emissions from manure. Paraformaldehyde is a polyoxymethylene containing 90 to 98 % formaldehyde, which has a recognized bacteriostatic effect on the microorganisms naturally present in droppings. Litter treatment with paraformaldehyde was shown to influence milk hygienic quality reducing somatic cell count and microbial cell load of 10 and 15 %, respectively. The use of paraformaldehyde for litter disinfection markedly increased protein (10 %) and fat (20 %) content in sheep milk with a consequent improvement of milk coagulation performance. Addition of paraformaldehyde to the bedding is a procedure that may be applied at intervals suitably far apart to be not economically prohibitive. Its use, however, would remain limited to circumstances in which there are difficulties in processing or marketing milk of low hygienic quality which could not be easily resolved using other cheaper methods (Sevi et al. 2000). In a subsequent study (Sevi et al. 2003a), the effects of litter renewal intervals on the yield and quality of ewe milk were evaluated as an alternative strategy to litter treatment with antimicrobial products. Bentonite has been used to reduce the levels of airborne particulates in livestock housing and improve the hygienic quality of ewe milk. Bentonite is mainly composed of clay minerals and has a high waterabsorbing capacity. It is relatively inexpensive and there are no reports of it having adverse effects on the health of either ewes or people. Litter renewal of litter at 4 weeks intervals can sustain health status of the mammary gland and improve ewe performance at the same levels as litter treatment with bentonite.
Livestock Sustainability: Human-Animal Relationship and Sheep and Goat Welfare
During the second half of the 20th Century, in the industrialized nations, production of meat increased; the increase regarded mainly poultry and pig production systems fed on grain and concentrated diets. The increase was less pronounced in sheep and goat production. In the developing countries production of bovine meat and sheep and goat meat increased more than threefold from 1961 to 2001 (Fraser 2008). The increased production was characterized by an increase in the number of animals and in a reduced number of farms rather than in an increase in the number of farms. In the industrialized countries, these events coincided with a cultural change in the way of looking at farm animal particularly on confinement production system. Such concern was addressed to preserve animal welfare by a scientific approach to the matter. In intensive production systems of sheep and goats, a number of researches have been conducted to define technical parameters in animal housing to control their impact on animal welfare and production ). Stocking density is a critical factor in sheep and goat housing because space allocation is known to affect both the performance and welfare of livestock. Space allowance reduction from 2 to 1 m 2 /head showed interesting effects on feeding behavior in goats. In horned goats, a reduction of feeding activity and of resting time is found; a slighter reduction of the same parameters in goats without horns is observed (Loretz et al. 2004). In ewes confined in a space allowance of 1.5 m 2 /head, a reduced humoral immune response is observed compared with ewes housed at a space allowance of 3 m 2 /head. Furthermore, ewes that have free access to an outdoor area display an increased cell mediated immune response compared with ewes enclosed indoor (Caroprese et al. 2009). Among structural housing parameters in sheep and goat buildings, inadequate airspace may be a limitation to high efficiency of production and good health in farmed livestock. This could be of practical interest when sheep are raised in warm climates and do not benefit from efficient ventilation system. Ventilation regimen, indeed, has a main role in sustaining the welfare by affecting thermal exchanges between the animal's body surface. With a pending high heat load situation, a moderate ventilation rate (65 m 3 /h per ewe) improves the well-being of the lactating ewe compared to a low ventilation rate (35 m 3 /h per ewe), as suggested by behavioral, endocrine, and immune indicators. Under such conditions, a fan ventilation system, programmed to operate over upper critical air temperature (30 C) and relative humidity (70 %), has been proved to be economically unattractive, because it involves about a threefold greater energy cost and does not lead to remarkable improvements of ewe welfare and productivity compared to a moderate ventilation regimen (65 m 3 /h per ewe) (Sevi et al. 2002). Under heat stress, feed intake decreases especially when sheep are fed on low quality feed due to both the effort of reducing heat production and the slower feed transit through the digestive tract (Costa et al. 1992). Feed administration in late afternoon is beneficial in minimizing the impact of thermal stress on ewes' immune function and udder health (Sevi et al. 2001a).
One of the main factors in influencing the welfare of an animal is the quality of the human-animal relationship. A poor human-animal relationship can lead to chronic fear of humans and to handling difficulties, injury, and stress and, as a consequence to impaired growth, reproductive performance, and product quality (Hemsworth and Coleman 1998;Jones 1997). The nature and frequency of the relationship are different in sheep and goat farming system according to the management system, i.e., shepherding, intensive system, extensive systems. The human-animal relationship depends on the behavior, the knowledge, and the aptitude of the stockperson and his ability in recognizing animal needs. Frequent interaction between the animal and the stockman with repeated animal manipulation is a potential stress factor for sheep and goats. It is considered that sheep and goats are rustic animals; as a consequence, usually stockman handle them roughly, especially those with less experience or aptitude. On the contrary, it is well known that small ruminants have ancestral predatory fear, a gregarious nature, and a difficulty of adaptation to unfamiliar environments and integration with unknown groups. As a result, sheep and goat suffer if handling is excessive or inappropriate when rearing practices change suddenly or when regrouping and relocation occur suddenly or frequently (Sevi et al. 2001b). In lactating ewes, member exchange among groups increases aggression and altered immune response; also relocation results in a reduced immune response. An useful tool to minimize the stress related to artificial rearing is gentling, a friendly approach of the stockman towards the newborn animal. Several studies have highlighted that gentling strongly encourages the lamb and the kid reared without their mothers to positively interact with the stockman, whereas gentling has no beneficial effects on dam-reared animals. In artificially reared lambs, gentling improves their immune reactivity, making it comparable to that of dam-suckled lambs and reduced their plasma cortisol responses to handling ). The genetic predisposition may play an important role in building positive human-animal relationship, and lamb gentling results in an improvement in the quality of human-animal relationship particularly in more reactive breeds. In particular, breeds that are more sensitive to disturbance by human handling more promptly build a positive relationship with humans possible because a higher disturbance generates a need to be reassured through social support (Caroprese et al. 2012).
The results obtained from these and other studies were used to regulate, manly in the European Union, a number of laws regarding production systems, transport, and slaughter of sheep and goat reinforced by EU directives. More recent evolution focused on voluntary certification of animal welfare to achieve standard of production recognized by retails and suppliers.
Economic Perspectives of Sustainable Sheep and Goat Farming
In the last 30 years, a progressive decline of the traditional pastoral system based on transhumance has been observed (Manrique et al. 1996). As a consequence of the decrease in rural populations and in traditional farming systems, sheep and goat livestock systems need to be changed to improve animal welfare, and to increase the animal productive efficiency, and food quality with particular regard to food safety (Gibon et al. 1999;Ronchi and Nardone 2003). The reduction of veterinary costs linked to the enhanced animal health status and the increase of biological efficiency in terms of quantity and quality of milk and meat production can be considered as the strategies to improve the economic profits of a sustainable sheep and goat production. Veterinary and particularly parasitic diseases are one of the most important issues affecting health management in extensive small ruminant breeding being responsible of productivity losses. Infections can be considered deleterious for sheep and goat welfare and productivity, increasing mortality, management costs, and requirements for the use of anthelmintics. A sanitary program aiming to reduction of drugs requires high standard of welfare of animals and adequate management practices to improve farmers' income.
The need for increasing flock profits conforming to the quality standards is dependent on husbandry systems aiming to improve small ruminant welfare and health animal status. Extensive farming has proved to be beneficial to the welfare needs of lactating ewes but exposure to climatic extremes and seasonal fluctuations of pasture can threaten the welfare of extensively managed flocks. The gradual diffusion of semi-intensive husbandry systems led to the increase in highly productive dairy breeds. In this perspective, the maintenance of high standard of welfare of animals can markedly improve their biological efficiency. Under more intensive farming conditions, sheep and goats' welfare is influenced by the microenvironment control, the choice of proper housing, and building conditions to avoid crowding, aggressive behavior, increased ambient pollution, and poor animal health.
Farm management and health status of sheep and goat are mainly responsible for the quality of animal-based food products. Sheep and goat husbandry is strictly associated with rural societies contributing to the manufacture of local typical products which are expression of the regional cultural tradition.
Although products from small ruminants are intended to be free of chemical contaminants, the basic standard for sheep and goat productions lack high standard of nutritional, hygienic, and technological quality. Milk must have a desirable chemical composition and must be of satisfactory hygienic quality. This is essential in relation to public health, the suitability of milk for processing, and the quality of milk products. The health of the udder can have a profound effect on the quality and processing characteristics of milk. The most widely used indicator of udder health is somatic cell count (SCC), a measure of the number of white blood cells, known as leucocytes in milk. An elevated SCC usually indicates the presence of mastitis. Mastitis is caused by pathogenic bacteria entering the mammary gland via the teat canal and multiplying within the udder sinuses or epithelia or in the teat duct. Mammary inflammation during mastitis causes a range of physical, microbiological, and chemical changes in milk. The microorganisms found in raw milk may come from several sources: organisms from the udder, the environment (e.g., water, soil), milking equipment, bulk milk storage tank, tank in processing plant (Fajardo-Lira and Nielsen 1998).
In the Mediterranean area, due to the reproductive seasonality of sheep, ewes are usually in their later stage of lactation in late spring and summer. Lactation is thus often shortened given that dairy factories stop collecting milk from farms since it is produced in smaller amounts and its coagulating behavior is deteriorated. Indeed, a number of events can occur in summer, which have a deleterious effect on coagulating properties of sheep milk and, namely, (1) the use of fat and nitrogen reserves to supply energy through gluconeogenesis at the expense of the mammary gland (Amaral-Phillips et al. 1993), (2) a plasma mineral imbalance, especially due to a reduction in sodium, potassium, calcium, and phosphorus and to an increase in chloride concentrations (Kume et al. 1987), (3) an increased milk pH, due to high amounts of CO 2 dissipated via the panting (Habeeb et al. 1992), (4) an increased plasmin (PL) activity, the main endogenous proteinase in milk (Bianchi et al. 2004), (5) an increased bacterial load in milk, due to enhanced multiplication and growth of microorganisms in the litter (Sevi et al. 2001a). A worsening in milk coagulating behavior in ewes reared in pens without shading areas and receiving feed during the warmest part of the day has been observed (Sevi et al. 2001a). Under moderate heat stress, also a low ventilation rate has deleterious effects on milk yield and on clotting properties of milk (Sevi et al. 2003c). When collected for cheese making, the bulk milk from ewes in less ventilated houses has higher microbial load and somatic cell count compared to milk from ewes in more ventilated houses. As a result, a weaker caseous matrix of the curd releasing higher concentration of fat and protein in the whey was observed (Albenzio et al. 2005).
Profitability of dairy farms largely depends on milk casein content and milk hygienic quality in terms of pathogen, spoilage bacteria, and somatic cell count, giving that sheep and goat milk is almost totally destined for cheese making as raw milk. Milk yield and casein content increased to around 10 %, as well as the coagulation properties of milk (+8 %) when ewes are housed with a space allocation of 2 m 2 per animal (Sevi et al. 1999). A stocking density of 1 m 2 per ewe has deleterious effects on the hygienic quality of milk. Higher levels of airborne microorganisms also affected the mammary system of the animals with higher microbial cell loads and somatic cell counts being recorded in milk from ewes housed under high stocking density conditions. Milk produced by high densely stocked ewes, which are housed on a straw litter treated with bentonite, displayed lower concentrations of bacteria in their milk together with lower airborne microorganism loads. An increase of milk yield (3 %), of milk fat (10 %) and casein content (5 %), and of milk clotting time (8 %) was recorded. When no litter treatment is used, higher SCC (+40 %) was found in milk due to greater bacterial colonization of the udder. Adequate airspace allocation of 7 m 3 /animal leads to increase in milk yield (20 %) and milk casein content (10 %) and improves renneting ability and hygienic quality of milk mainly in terms of somatic cell count (À10 %) (Sevi et al. 2001c).
Protein supplementation in grazing dairy ewes is a popular strategy for upgrading sheep nutrition in order to reduce the variability and improve ewe milk yield and composition. Feeding strategies together with several other management practices may improve the overall quality of milk for cheese making. Bulk milk produced by the ewes receiving a low crude protein diet (13 %) displayed higher casein (10 %) and low urea contents (À20 %). Therefore, the choice of a proper dietary crude protein level plays a main role in sustaining protein synthesis in the mammary gland . The use of appropriate supplements in the diet of small ruminants can succeed in improving the nutritional features of animal-based food. This goal besides adding functional properties to animal-based food can meet the recently growing consumer demand both for quality food products and more ethical food production. Adequate supplementations in the diet of sheep and goat have been proved to sustain their welfare during stressful conditions such as thermal stress, the transition period. The use of flaxseed in the diet of lactating ewes under heat stress succeeds in increasing milk yield and ameliorating nutritional milk composition particularly in terms of milk fatty acid profile .
Lamb meat is valuable from a nutritional point of view for its high CLA content which can exert positive effects on human health (Schmid et al. 2006). The proportion of saturated and unsaturated fatty acid in meat from lambs subjected to different regimes highlights a better fatty acid profile in meat from artificially reared lambs from a nutritional and health promoting point of view. In particular, unsaturated fatty acids are considered hypolipidemic by reducing both plasma cholesterol and triglycerides, and a low intake of saturated fat as well as an increased polyunsaturated to saturated fatty acid ratio are associated with a lower risk of human coronary heart disease (Oriani et al. 2005). The addition of probiotics to milk replacer play a role in modulating the health status of lambs. Meat from artificially reared lamb fed milk replacer containing probiotic showed an improved fatty acid profile for human diet, in terms of higher CLA and lower SFA content .
Human induced climate changes, and subsequent global warming, are involving also European countries located within the temperate zone. As a result, the importance of sheep and goat farming is expected to increase gradually in comparison with cattle farming in both rural and industrialized countries. In fact, sheep and goats are more tolerant to climate extremes, in terms of production, reproduction, and resistance to diseases, and less competitive with humans for crops and grains than cattle. So that the role that sheep and goat farming are about to play is achieved in a fully sustainable way; the effort of research and the production world is invoked. It must aim to find feeding strategies and management practices for reducing emissions from sheep and goat farming, to identify dimensional and physical parameters, and management practices for sustaining flock welfare, and to raise the profitability of sheep and goat farming by reducing the impact of veterinary costs and increasing the commercial value of sheep and goat products. | v3-fos |
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} | s2 | Assessment of Knowledge, Attitude and Practice Towards Whole Grains Among Children Aged 10 and 11 Years In Kuala Lumpur, Malaysia
The United State Food and Drug Administration (FDA) define a whole grain as consisting of the intact grain, cracked, flaked kernel or ground, which includes the endosperm, bran and germ. This definition has been adapted from the American Association of Cereal Chemists (AACC). Whole grains are a good source of B vitamins, mineral, fiber, basic amino acids and phytochemicals [1]. Several studies have focused on the role of whole grains in body weight regulation [2]. It has been demonstrated that whole grains consumption as part of an overall healthy lifestyle may be beneficial for children to achieve and maintain a healthy weight, as the outcome of the study showed that whole grains intake was inversely associated with body mass index (BMI) z-score [3]. Whole grains which are enriched with fiber and low energy density may help with weight maintenance by inducing the satiety [4].
Introduction
The United State Food and Drug Administration (FDA) define a whole grain as consisting of the intact grain, cracked, flaked kernel or ground, which includes the endosperm, bran and germ. This definition has been adapted from the American Association of Cereal Chemists (AACC). Whole grains are a good source of B vitamins, mineral, fiber, basic amino acids and phytochemicals [1]. Several studies have focused on the role of whole grains in body weight regulation [2]. It has been demonstrated that whole grains consumption as part of an overall healthy lifestyle may be beneficial for children to achieve and maintain a healthy weight, as the outcome of the study showed that whole grains intake was inversely associated with body mass index (BMI) z-score [3]. Whole grains which are enriched with fiber and low energy density may help with weight maintenance by inducing the satiety [4].
The Dietary Guideline for American (2010) [5] and Malaysian Dietary Guideline (2010) [6] recommend that at least half of all grains should be consumed as whole grains and that whole grains consumption should be increased by replacing refined grains with whole grains. The federal evidence-based dietary recommendation to increase whole grains consumption in childhood has implication for overall health and quality of life extending into adulthood. In spite of positive health benefits and dietary recommendations, national dietary intake data from United State demonstrated that whole grains consumption by children were less than one serving per day [7]. Several potential barriers exist that may be contributing to the low consumption of whole grains among children including appearance, cost, taste, texture, lack of knowledge towards whole grains benefits and ability to http://scidoc.org/ijfs.php identify whole grains foods [8]. It is necessary to develop and implement effective nutrition education particularly on whole grains, strengthen whole grains education through multiple channels, enhance the whole grains knowledge of children, focus on whole grains intervention measures and urge the children to form a good whole grains intake practice.
To plan such interventions, nutrition professionals need to understand the various factors that contribute to whole grains consumption behaviors. Enhancements in knowledge, attitude, practice, outcome expectations, perceptions, skills and self-efficacy are deemed to be the potential mediating and enabling factors for the attainment of appropriate dietary preferences and practices [9]. It would be helpful to have detail information about the KAP towards whole grains which may facilitate efforts to improve child health and whole grains consumption among this population group. To our knowledge, there are no published studies on KAP focused primarily on whole grains in Malaysia. Hence, this study was carried out to investigate KAP towards whole grains among aged 10 and 11 years children in Kuala Lumpur, Malaysia. The information will be used to develop continuing education intervention regarding promotion of whole grains to children.
Study Design and Sampling
Kuala Lumpur is classified into three zones, namely Keramat, BangsarPudu and Sentul. Two primary schools from each zone were randomly selected to participate in this study from a list of entire primary schools in Kuala Lumpur were obtained from the Kuala Lumpur Federal Territory Education Department. In this cross sectional study, a total of 384 school children aged 10 and 11 years were derived from six primary schools through two-stage random cluster sampling method. Kuala Lumpur is situated midway along the west coast of Peninsular Malaysia, possessing a population of over one and a half million people drawn from Malaysia's entire multiethnic group. The study protocol was reviewed and approved by the ethics committee of Universiti Kebangsaan Malaysia. Permission to carry out data collection was granted by Ministry of Education, Malaysia and Kuala Lumpur Federal Territory Education Department. Parental consent was obtained for all children prior to participation. Verbal consent was obtained from the children too before the study began in order to enable us to administer the questionnaires and acquire anthropometric measurements.
The sample size was calculated using a formulation by Krejcie& Morgan (1970) [10] as follows: where n is the required sample size, χ 2 is the table value of chi square, N is the population size in Kuala Lumpur, P is the population proportion and d is the degree of accuracy expressed as a proportion. At a total 42183 school children aged 10 and 11 years in Kuala Lumpur, confidence level of 95%, a relative precision of 5% and a predicted prevalence of 50% since there are no similar studies conducted in Kuala Lumpur, the sample size required for the study was 381. Taking into account a non-response rate of 10%, the required sample size was increased to 419. A total of 420 children within the inclusion criteria were invited to participate in this study. Respondents comprised both sexes and from all the main ethnic groups in Malaysia, namely Malays, Chinese and Indians as well as Sabah and Sarawak natives. In this present study, no differentiation was made between the ethnic groups. Inclusion criteria were apparently healthy Malaysian school children aged 10 to11 years, were able to read, write and understand Malay. School children with mental disabilities and who were unable to read were excluded from the study. However, only 384 children successfully completed the study, resulting in a response rate of 91.4%. Drop-outs were mainly due to absent from school or parents refusing to give consent.
Data was collected in two stages: first stage involved the answering of guided self-administered KAP towards whole grains questionnaire by children. The investigator was present in the classroom to assist children so that the questions were fully understood and well-completed. While in the second stage, anthropometric measurements of the children were taken. The whole process was conducted by one investigator throughout to avoid the problem of inter-interview variations.
Study Questionnaire
A validated guided self-administered questionnaire, which comprised of 24 demographic factors, 15 knowledge items, 15 attitude items and 10 practice items was used for data collection. The language used was Bahasa Malaysia which is the mother tongue of Malaysian. Questionnaire was pre-tested for clarity and ease of comprehension prior to being applied in the study [11]. The overall questionnaire consisted of four main sections namely demographic factors, knowledge domain, attitude domain and practice domain. Demographic factors were intended to discover the demographic and whole grains consumption pattern. Whereas, knowledge domain reflects general nutrition and whole grains information including food pyramid, source of carbohydrate, definition of whole grains, source of whole grains, nutritional content of whole grains and the benefits of whole grains consumption. Attitudedomain defined as school children's opinions and belief towards whole grains consumption, awareness and socio-cultural perspective. Whereas, practice domain corresponded to school children's practice towards whole grains consumption such as the frequency of intake of whole grains ready-to-eat cereal, whole grains bread, corn, whole grains biscuit, oat, barley and brown rice.
Knowledge domain consisted of 15 multiple choice items. Each item had two answer options and "Not Sure" option. Only one of the options was the correct answer. Correct answer received one point, incorrect and "Not Sure" answers received zero points. Attitude domain comprised of 15 liker scale items. School children could indicate their degree of agreement towards the statement given. Liker scale of five points will be used to represent the scores, as such "Strongly Agree", "Agree", "Not Sure", "Disagree" and "Strongly Disagree". Numerical scores 5, 4, 3, 2 and 1 will be given to category "Strongly agree", "Agree", "Not Sure", "Disagree" and "Strongly Disagree" respectively. For those items which were negatively phrased, scores will be re-coded as 5, 4, 3, 2, and 1 for category "Strongly Disagree", "Disagree", "Not Sure", "Agree" and "Strongly Agree". Meanwhile, practice domain comprised of ten items assessed by "Everyday", "Always" (1-7 days in a weeks), "Sometimes" (14 days in a month), "Seldom" (not in the category of "Always" and "Sometimes") and "Never" category, scored as 5, 4, 3, 2 and 1. The detail of the development and validation of the questionnaire will be published somewhere else. http://scidoc.org/ijfs.php
Anthropometric Measurements
The body weight of each child was measure twice using a calibrated TANITA digital scale Model 300GS (TANITA, Cranlea& Co. Birmingham, England) and recorded to the nearest 0.1kg. The children were weighed with their uniforms on, without belts, barefooted with emptied pockets. Respondents were asked to stand still with the body weight equally distributed on both feet. The angles of head of the respondents have to be in the Frankfurt plane [12]. The height of the child was measured twice using a portable stadiometer (Leicester, UK) attached to a smooth wall and recorded to the nearest 0.1cm. The respondents were asked to stand erect, barefooted, with heels, buttocks, head and shoulder blades in a vertical line against the wall. Height was measured in the upright position against a vertical scale and with the head positioned so that the top of the external auditory meatus was in the level with the inferior margin of the bone orbit [12]. The reported body weight and height were the average values from both readings. Z scores for BMI-for-age were determined using the software WHO Anthro version 1.0.3 (WHO, Geneva, Switzerland).
Statistical Analysis
Statistical analysis was done using the SPSS version 22.0 (IBM SPSS Statistics, 2014). Data was entered, cleaned and checked before data analysis. Each variable was examined for normality distribution using Kolmogorov Smirnov test. Distribution of the data was assessed by descriptive analysis, and presented as means with standard deviation for normally distributed or median with interquartile range fornon-normally distributed. The scores for KAP were transformed into percentage scores by dividing the scores obtained by the respondents with the possible maximum scores and multiplied by 100. The sum score of each outcome was assessed based on Bloom's cut off point [13]. Based on the sum scores, level of knowledge was classified into low level knowledge (less than 60%; 0-8 scores), moderate level knowledge (60-80%; 9-11 scores) and high level knowledge (80-100%; 12-15 scores). Meanwhile, the scores were classified into positive attitude (80-100%; 60-75 scores), neutral attitude (60%-80%; 45-59 scores) and negative attitude (less than 60%; 15-44 scores). Subsequently, level of practice was classified into poor level (less than 60%; 10-29 scores), fair level (60-80%; 30-40 scores) and good level (80-100%; 41-50 scores). The Spearman's rank correlation test was applied to determine the associations among knowledge, attitude and practice. Meanwhile, the Pearson correlation coefficient was applied to investigate the relationships between BMI z-score with knowledge, attitude and practice. A two sided p value of < 0.05 was considered statistically significant.
Results
The demographic information and anthropometric measurements of the children is summarized in Table 1. A total of 384 children aged 10 and 11 years or studying in Grade 4 and Grade 5 consented to the study. 51.0% were boys and 49.0% were girls with 1:1.04 female and male sex ratio. Majority of the school children were Malays (80.5%). It was found that out of a total of 384school children, 74.5% of them had tried whole grains foods before. However, only 9.1% of them consumed the whole grain products on a regular basis (daily). If given a choice, majority of the children chose whole grains ready-to-eat cereals as their preferred whole grains breakfast (60.4%), followed by whole grains bread (20.6%), oat (12.8%), whole grains biscuit (3.3%) and corn (2.9%). The overall mean ± SD of BMI z-score was 0.42 ± 1.49.
Children answered a total of 15 close-ended questions about food pyramid, source of carbohydrate, definition of whole grains, source of whole grains, nutritional content of whole grains and the benefits of whole grains consumption. The median score for knowledge was 7.00 (IqR 4.00). Majority (70.3%) of the children had low knowledge on whole grains. Meanwhile, 24.8%had moderate knowledgeand 4.9% had high level of knowledge on whole grains. The knowledge items with percentage of correct answer are displayed in Table 2. A large majority of the children (83.3%) were aware of the food pyramid's shape. However, less than half wereable to identify the detail of food pyramid and the function of carbohydrate. In response to items assessing knowledge about whole grains, only 48.7% of the children were able to correctly identify the definition of whole grains, while the majority of the children correctly answered the question regarding whole grains foods and nutrients. However, more than half of the children were unable to identify the benefits of whole grains consumption.
Concerning attitudes towards whole grains consumption, the children obtained a median score of 51.00 (IqR 8.00) out of 75. The attitude towards whole grains was generally neutral as majority (72.6%) of the children scored 45-59. Meanwhile, 8.6% were in positive attitude and 18.8% were in negative attitude towards whole grain consumption. The attitude items with percentage for positive attitude are presented in Table 3. Only 26.8% of them showed some concern regarding whole grains foods choices despite they were still young and healthy. Susceptibility perception was high as majority of them chose to put effort towards increasing whole grains consumption, such as studied hard to determine the functions of whole grains, spent more time on internet to search the advantages of eating whole grain foods and spent more time on book reading to search the food which contains whole grains. The median score for practice was 23.00 (IqR 8.00).
The practice towards whole grains was generally poor as majority (83.9%) of the children showed unsatisfactory score. Meanwhile, only 2.3% and 13.8% of the children were in goodandfair practice level, respectively. The practice items with percentage for good practice are presented in Table 4. The analysis for each item on consumption practices showed that the whole grains intake was relatively poor. Table 5 presents the correlation coefficient between whole grains knowledge, attitude, practice and BMI zscore. It was found that only practice domain was inversely associated with BMI z-score (r=-0.117, p=0.022). With regard to the KAP towards whole grains, it was found that the children who had higher knowledge level would have a better attitude and greater practice towards whole grains consumption. Significant positive correlations were found between knowledge with attitude (r=0.335, p<0.001), attitude with practice (r=0.171, p=0.001), as well as knowledge with practice (r=0.162, p=0.001).
Weight 34.33± 9.93 a Height 134.64 ± 11.08 a BMI z-score 0.42 ± 1.49 a a Mean ± standard deviation; BMI: body mass index A4 I don't like to eat whole grains ready-to-eat cereal with low fat milk because it is tasteless.
224(58.3)
Effort towards increasing whole grain intake A5 I study hard to determine the function of whole grains. 253(65.9) A6 I try to spend more times on internet to search the advantages of eating whole grains foods.
201(52.3)
A7 I try to spend more times on book reading to search the food which contains whole grains.
235(61.2)
A8 I will buy whole grains ready-to-eat cereal as breakfast if it is sold at school canteen.
222(57.8)
Action towards achieving whole grain recommendation A9 I will finish all the whole grains foods despite I don't like it. 161(41.9) A10 I am not worried about the whole grains food choices because I am still healthy. 103(26.8)
A11
I will choose whole grains ready-to-eat cereals as my breakfast if there is a choice between whole grains ready-to-eat cereal and coconut milk rice.
254(66.1) A12 I will seek for the advice from teacher and parents if encounter any problem regarding whole grains.
163(42.5)
Health and whole grain intake A13 I am interested to take whole grain foods if I am informed about the benefit of it.
A14
In my opinion, whole grains ready-to-eat cereals have more nutrients and healthier compared to non-whole grains food such as white bread, coconut milk rice and roti canai.
215(56.0) A15 I will choose white bread if there is a choice between whole grains bread and white bread at home.
57(14.9)
a Percentage of children who answered "strongly agree" or "agree" for attitude that they should have and "strongly disagree" or "disagree" for attitude that they should not have http://scidoc.org/ijfs.php
Discussion
The present study assessed knowledge, attitudes and practice towards whole grains among children aged 10 and 11 years in Kuala Lumpur, Malaysia. Bloom's cut off point was used to determine the level of KAP because the conceptual framework of the present study was based on taxonomy of educational objectives developed by Bloom (1956). According to Bloom's taxonomy (1956), human behaviours are derived from the integration of the cognitive, affective and psychomotor domains. Knowledge, attitudes and practices could be representative of the cognitive, affective and psychomotor domains, respectively. Knowledge refers to the factual, conceptual, procedural and met cognitive thought [13]. Attitude is an internal or covert feeling and emotion or selective nature of intended behaviour which represents the affective domain [13]. Meanwhile, practice represents the psychomotor domain. It refers to the physical movement, coordination and use of motor or neuromuscular activities [13].
The outcomes of the present study showed that children had low level knowledge and practice towards whole grains. Data from USDA's 1994-1996 Continuing Survey of Food Intakes by Individuals (CSFII) indicated that only 9% of children aged 2 to 19 consumed three or more servings of whole grains daily [7]. The obstacles for the consumption of whole grains foods that are most frequently cited are limited availability, confusion about the identification of whole grains, low consumer awareness and aversion to the colour, texture and taste of whole grains foods [8]. These issues present challenges to school foodservice as well as their parents, to provide whole grains foods that children will consume and to educate children about the health benefits of whole grains inclusion in their meal.
The finding also demonstrated that knowledge, attitude and practice were correlated with each another. The KAP model suggested that behaviour was a result of knowledge and practice, it is in accordance with a KAP model [14]. There is a need for nutrition and food professionals to collaborate on a variety of fronts to encourage the increase consumption of whole grains. Education programs are more likely to be more successful if they include examples of whole grains foods and activities that reflect the target children's lifestyle, preferences and culture. Behavioural change is Percentage of children who answered "always" or "often" Table 5. Correlation coefficient between whole grains knowledge, attitude, practice and body mass index z-score (n=384).
http://scidoc.org/ijfs.php difficult to achieve, but is more likely to occur if food and nutrition professionals can speak with one voice about the benefits of whole grains consumption as an integral part of an overall healthy diet. Besides, respective organisations and government sector may offer whole grain foods which provide the opportunity for children to experience and accept a healthy new repertoire of whole grain alternatives in their diet at young ages. Previous interventions have been made through recipe modification and social marketing techniques, to successfully modify the intake of low fat milk [15], fruits and vegetables [16], as well as fat intake [17]. The program demonstrated that change in food preparation practices markedly increased vegetable, fruit and low fat milk intakes, while modified fat content of foods, resulted in significant changes in nutrient intake of children. Such modifications were well received by the children, as the program provided them with palatable food options.
A nutritionally adequate diet is essential for optimal growth and development. For the school-aged children, a healthy diet containing all the food groups in required amounts is important for optimum BMI and reduces the risk of diet-related chronic diseases. The study revealed that practice domain was inversely associated with BMI z-score and it is indicated that children with higher whole grains consumption have lower BMI z-score. It is in line with a previous study [3]. Reduced BMI z-score with higher whole grains consumption may be mediated in part by enhanced insulin sensitivity and increased satiety [4]. Proper nutrition education particularly on whole grains in childhood may reinforce lifelong healthy eating habits that contribute to improve long-term health and the development of healthier eating habits that are carried into adulthood.
It is possible that the children might not tell the truth especially questions on attitude and practice which may introduce to social desirability bias. It was minimized by assuring children of their anonymity and confidentiality of individual reports. The present study provides preliminary information to increase our understanding of the factors that may influence the whole grains consumption of the children. Further a comprehensive study is needed in all geographical locations of the country to know the actual KAP towards whole grains in whole Malaysia.
Conclusion
The outcomes of the present study indicated that children supplied with knowledge may eventually develop positive attitude and good practice towards whole grains, which may be useful in managing childhood obesity by lowering BMI z-score. However, a wide gap was observed between the recommended and actual practices, and their overall whole grains-related knowledge was insufficient. This study reveals the importance of KAP towards whole grains among children that assist with identification of specific preventive childhood obesity actions. Therefore, we suggest that further action is required to develop whole grains-related education programs for the children. | v3-fos |
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} | s2 | Modeling the synergistic antibacterial effects of honey characteristics of different botanical origins from the Sahara Desert of Algeria
Background: Honey has multiple therapeutic properties due to its composition with diverse components. Objectives: This study aims to investigate the antimicrobial efficacy of Saharan honeys against bacterial pathogens, the variation of honey floral origins, and its physicochemical characteristics. Materials and Methods: The antimicrobial activity of 32 samples of honey collected from the Algerian Sahara Desert was tested on four bacteria; Bacillus subtilis, Clostridium perfringens, Escherichia coli, and Staphylococcus aureus. The botanical origin of honeys and their physicochemical properties were determined and their combined antibacterial effects were modeled using a generalized linear mixed model (GLMM). Results: Out of the 32 study samples, 14 were monofloral and 18 were multifloral. The pollen density was on average 7.86 × 106 grains/10 g of honey, water content was 14.6%, electrical conductivity (EC) was 0.5 μS/cm, pH was 4.38 ± 0 50, hydroxymethylfurfural (HMF) content was 82 mg/kg of honey, total sugars = 83%, reducing sugars = 71%, and the concentration of proline = 525.5 ± 550.2 mg/kg of honey. GLMM revealed that the antibacterial effect of honey varied significantly between bacteria and floral origins. This effect increased with increasing of water content and reducing sugars in honey, but it significantly decreased with increase of honey EC. E. coli was the most sensitive species with an inhibition zone of 10.1 ± 4.7 mm, while C. perfringens was the less sensitive. Honeys dominated by pollen of Fabaceae sp. were most effective with an overall antimicrobial activity equals to 13.5 ± 4.7 mm. Conclusion: Saharan honeys, of certain botanical origins, have physicochemical and pollinic characteristics with relevant potential for antibacterial purposes. This encourages a more comprehensive characterization of honeys with in vivo and in vitro investigations.
INTRODUCTION
In recent years, pathogenic microorganisms have developed multiple drug resistance due to the abundant and wide spared use of antimicrobial drugs that were commonly used in human medicine (Al-Waili et al., 2011;Noori et al., 2013). Even with the broad spectrum of some antibacterial agents, the choice of most suitable remains relatively limited due to the development of bacterial resistance, breakthrough infections, and ever-increasing therapeutic problem (Shahid et al., 2008). Alternative antimicrobial strategies are therefore urgently needed using various natural, traditional, and nonconventional sources (Al-Waili et al., 2011;Lucera et al., 2012). Antimicrobial substances originated from natural resources have been widely exploited for this purpose, with a specific focus of studies on a specific product "Honey" due to a long tradition of use within various medical and food systems (Lusby et al., 2005;Al-Waili et al., 2011). Honey is used to treat certain topical infections and even for accelerating wound healing and epithelization (Simon et al., 2006;Mandal and Mandal, 2011).
Honey is used for centuries and still widely used as an antiseptic where its main characterized role is the prevention and limitation of bacterial infection derived largely from biochemical properties related to peroxide generation via glucose oxidase activity (Brudzynski, 2006), nonperoxide effect such as, osmolarity, acidity, aromatic acids, phenolic, and other phytochemical compounds such as methylglyoxal (Mundo et al., 2004;Lusby et al., 2005;Lee et al., 2008;Mavric et al., 2008). Moreover, honey serves as a natural antioxidant and a rich source of minerals, carbohydrates, proteins, and vitamins with nutraceutical and probiotic properties (Bertoncelj et al., 2007;Begum et al., 2015).
In addition, the antibiotic and antiseptic effects of honey have been scientifically proven in several studies (Shamala et al., 2002;Werner and Laccourreye, 2011). These effects are mainly due to the bio-chemical composition of honey that contains high sugar and low water concentrations with low pH. These properties generate the high osmolarity that produces the antimicrobial action (Wahdan, 1998). Honey also contains molecules inhibiting bacterial growth, such as hydrogen peroxide produced by glucose oxidase; and also the non-peroxide inhibins also known as phytochemicals composed (Cushnie and Lamb, 2005;Adeleke et al., 2006;Bell, 2007;Montenegro and Mejías, 2013).
It is noteworthy to mention that different analysis techniques of honey components may be implemented. The analysis of some of these substances requires special and sophisticated methods such as those performed using spectrophotometric assays, particularly gas chromatography-mass spectrometer (GC-MS), liquid chromatography-mass spectrometer (LC-MS), and nuclear magnetic resonance (NMR). These techniques are used to assess contents of molecules and elucidate the structure of active molecules (Bertoncelj et al., 2007;Tiwari et al., 2014Tiwari et al., , 2015. The antimicrobial activities of honey have been extensively investigated against a large category of bacterial and fungal pathogens including Staphylococcus aureus, S. pyogenes, S. mutans, Bacillus cereus, Listeria monocytogens, Escherichia coli, Klesiella pneumonia, Pseudomonas aeruginosa, and Candida albicans (Mundo et al., 2004;Basualdo et al., 2007;Lee et al., 2008;Sherlock et al., 2010;Estevinho et al., 2011). The differences reported in antimicrobial effects of honey are dependent on its geographical origin thus the botanical source as well as time and processing harvesting, storage conditions, and the nature of pathogens tested (Sherlock et al., 2010;Al-Waili et al., 2011).
Since the antibacterial activity of honey varies depending on the floral origin (Salomon, 2010;Alzahrani et al., 2012), many studies investigated the biochemical composition and pollen contents of honeys of different melliferous plant species to determine levels of natural antibiotic compounds (e.g., Lins et al., 2003;Muñoz et al., 2007). The content of these inhibins in honey pollens depends on the plant species from which they originate in other words according to the floral origin. However, few studies examined the physicochemical composition and antibiotic properties of honey whose floral origin is derived from plant species living under extreme environmental conditions such as the Sahara Desert.
Although the honeybee (Apis mellifera) is known as a polylectic species (Reybroeck et al., 2014), honey harvested from the Saharan regions show great variability in pollen composition and density (Noori et al., 2013). This is mainly due to local ecological and floristic characteristics where the hive was installed. Moreover, under the environmental conditions of desert, diversity and abundance of plants are low (Bradai et al., 2015); so that the bee produces two honey categories (i) monofloral honey (i.e., mainly dominated by the pollen of one plant) in regions very little diversified in melliferous plants, or (ii) a multifloral honey (i.e., containing mixed pollen origin) when melliferous plants are diversified and abundant (Von der Ohe et al., 2004). This difference in the pollen composition in honey may result from the flowering period of plants (Campos et al., 2008). Additionally to this, the elective factor that the bee can exercise among the available melliferous plants should be considered (Reybroeck et al., 2014).
Given these facts, the aim of this study is based on the following question: do the botanical origin and pollen composition of honey affect its antibiotic properties and therefore its antibacterial potency? Moreover, the study seeks to determine if differences in physicochemical composition of honey can induce a different impact on its antimicrobial activity against pathogenic bacteria, with taking into account the botanical origin differences. Hence the interest of a physicochemical and pollen analysis of honeys of the Sahara which proves not only important to characterize these honeys and determine their floral origin, but also to determine the most effective floral origin and the parameters that have more antimicrobial effect against the bacteria tested.
Choice and Collection of Honey Samples
Honey samples of the current study were collected from nine localities in southwestern Algeria, in the region of Naama and Bechar located in the Algerian Sahara (Figure 1), where the FIGURE 1 | Geographic location of the study area including honey harvesting sites (solid circles) in the region of Bechar (1, Benzireg; 2, Beni Ounif; 3, Djedid; 4, Sfissifa) and Naama (5, Ain Safra; 6, El Hamar; 7, Djneine; 8, Tiout; 9, Moghrar) located in the Desert Sahara of Algeria.
prevailing climate is hot arid. People of the Sahara, as well as the Algerian populations in general, frequently use honey as a cure for several diseases due to its multiple healing properties (Boukraâ, 2013), specifically the higher efficacy of the Saharan honey compared to that of North Africa (Boukraa and Niar, 2007). Undoubtedly, the spread of the use of honey in traditional and modern medicine has origins linked to the religious beliefs of Muslim people, where many Koranic and Islamic texts reveal that honey is a proven remedy.
A total of 32 honey samples, 20 from Bechar and 12 from Naama, were recovered from local beekeepers just after honey extraction. Each sample was preserved under low temperature before processing to various analyzes in the laboratory.
Pollinic Analysis
The pollen analysis of honeys consisted of two steps following the method of Crompton and Wojtas (1993). The first is the identification of pollen grains observed, whereas the second step was devoted to their count. All honey samples were analyzed without coloring. This allows showing the pollen grain in its natural color with its true appearance for facilitate the identification. Observations were carried out under an optical microscope at a magnification × 100.
Pollen was identified based on comparisons of the observed grains with those known in references. The latters are microscopic preparations of reference that we set up ourselves from fresh anther of local plants and with the help an Atlas of Microphotography (Reille, 1995).
For each sample of honey, the number of pollen grains in 10 g of honey was first counted and the results of that count were then classified in ascending order from I to V (see details in Yang et al., 2014). In parallel, this counts allowed us to make a classification of botanical taxa identified into frequencies; which determines if the honey in question comes from either (i) multiple plants pollinated by bees, so without a clear predominance of a particular plant (multifloral honey), or (ii) otherwise, honey is classified as monofloral (syn. unifloral) in which pollen grains of one plant species dominate (Von der Ohe et al., 2004).
Physicochemical Analysis of Honeys
For curative purposes and to benefit from this natural remedy, it is recommended to use fresh and natural honey (Bogdanov and Blumer, 2001). Since antiseptic and antibiotic substances tend to disappear-or at least to be less active-in old honeys (Lobreau-Callen et al., 2000), it is therefore required to proceed prior to physicochemical analyzes of quality control to be able to bind honey features with its microbiological activity. This concerns particularly water and sugar contents, pH, hydroxymethylfurfural (HMF), and obviously proline (Helrich, 1990;Bogdanov et al., 2002). Thus, each honey sample had undergone some physicochemical analyzes: • Water content (WC): expressed in %, is determined using a refractometer for measuring the refractive index at 20 • C with reference to the table Chataway according to the method followed by Bogdanov et al. (2002). • pH: was determined by a pH meter on a solution composed of 10 g of honey and 75 mL of distilled water (Bogdanov et al., 2002). • Electrical conductivity (EC): measured (in µS/cm) using a conductimeter device at 20 • C of the test solution that consisted of 20% honey weighed as dry matter dissolved in distilled water and brought to a volume of 1/5 (Bogdanov et al., 2002). • Hydroxymethylfurfural (HMF): was measured using Winkler's method (Bogdanov et al., 1999). HMF content is expressed in mg per 1 kg of honey. The HMF is a product of the degradation of fructose and glucose by intramolecular dehydration (Nombré et al., 2010). This parameter is used to control the freshness and quality of honey; thereby a value greater than 60 mg/kg indicates an old honey or the latter has undergone heat treatment degrading its properties (Oddo et al., 1999). Determining the HMF content is based on the measurement of absorbance by spectrophotometry at a wavelength of 550 nm in the presence of barbituric acid and para-toluidine. • Total sugars: sugars represent the largest part of the dry matter of the bee's honey (Apis mellifera). Their analysis comes forth by refractometer, which is a quick and simple method (Helrich, 1990). • Reducing sugars: The amount of total reducing sugars, expressed in% from total sugars, was determined titrimetrically according to the volumetric method (Helrich, 1990).
• Proline: The proline content (mg/kg honey) was determined using the colorimetric assay with ninhydrin following the method of Ough (1969) defined by Bogdanov et al. (2002). The proline content provides useful information on the maturity of honey and therefore can be used to detect forgeries. It is considered that honey is mature when its proline content is greater than 183 mg/kg. Lower values indicate a lack of maturity or honey falsification (Meda et al., 2005).
Antibacterial Disc Diffusion Assays
The antibacterial activities of honeys were tested using the agar disc diffusion against four pathogens and resistant bacterial strains, namely: E. coli (ATCC25922), S. aureus (ATCC25923), Clostridium perfringens, and Bacillus subtilis. Pure strains of C. perfringens were provided by the microbiological laboratory of the hospital Mustapha Chaabani (Golea, Ghardaia, Algeria). While B. subtilis has been isolated from human feces and identified at the Microbiology Laboratory of Bachir Ben Nacer Hospital in El Oued (Algeria), using conventional phenotypic identification protocols. C. perfringens was cultivated using anaerobic jars (GasPak system), whereas other bacteria were grown and purified on nutrient agar (NA). Bacterial inoculum suspensions containing 10 6 -10 8 CFU/mL were prepared in sterile saline (0.9 g/L) and spread on Mueller-Hinton (MH) agar plates for each strain. Using sterile forceps, Whatman's filter discs (Ø = 5 mm), impregnated with different honeys were placed on the inoculated plates and left at 4 • C for 2 h to allow the diffusion before being incubated at 37 • C for 24 h. The clear inhibition zones around the discs indicated the presence of antibacterial activity of honey (Harley et al., 2010) which was measured as zone diameter in mm excluding the diameter of disc. Experiments were carried out in triplicates.
Standard antibiotic discs of trimethoprim-sulfamethoxazole "SXT" (1.25/23.75 µg per disc) served as a positive control. This combination antimicrobial agent was tested on the Gramnegative bacterium E. coli and the Gram-positive bacterium S. aureus. The sterile H 2 O served as a negative control in order to determine the minimum inhibitory concentration (MIC) of the study honeys. For that, each honey sample was used to prepare solutions of different proportion (w/v): 5, 10, 15, 20, 25, and 75%. However, no antibacterial activity was observed for all these honey dilutions. Consequently, we only analyzed data related to honey at natural state i.e., used without dilution. Despite that, we focused on the objective of characterizing Saharan honeys in relation with their diverse floral origins.
Modeling the Synergistic Antibacterial Effects of Honey Features
As most of studies attributed the antibacterial effects of honey particularly to high sugar content, low water content, low pH and high concentration of flavonoids (Wahdan, 1998). However, these parameters furthermore vary following the botanical origins of honey and the ecological factors that influence both melliferous plants likewise the behavior, physiology and fitness of bees (Reybroeck et al., 2014). Therefore several (biotic and abiotic) parameters are involved in the variation of the honey quality and thus its antimicrobial activities, which makes taking into account all these variables to modeling its antibiotic and antiseptic activities a real challenge to achieve, specifically when it is tested against several pathogens that may react differently.
Accordingly, we used as much as relevant variables of the study honeys in a single statistical model to explain how the antimicrobial activity (diameter of inhibition zone) varies following: floral origins (pollens parameters), physicochemical characteristics of honey, and tested bacteria. We included all the study bacteria in a single model as honey is usually applied to heal diseases caused by the mixture of pathogenic bacteria. Linear mixed-effects models represent the best fit to this kind of data (Pinheiro et al., 2015). In addition, we added to the model other parameters that ensures that the honey is natural with high quality such HMF and proline which provides information about the maturity of honey (Bogdanov et al., 2002). Finally, because samples of honey were collected from different sites (several samples from the same site) in the Sahara Desert, we used generalized linear mixed model (GLMM) to deal with pseudoreplications.
Statistical Analyses and Modeling Procedures
The values of the physicochemical parameters of the studied honeys were summarized for each botanical origin as means ± standard deviations (SD) and the range (min and max) of observations. The variation of each parameter between botanical origins was tested by the analysis of variance (One-way ANOVA) using the software R (R Core Team, 2015). Multiple comparisons of means (Tukey HSD tests) were performed afterward each ANOVA to distinguish homogeneous groups among botanical origins.
Descriptive statistics (mean, SD, and quartiles) of the antimicrobial activity were computed for each floral origin and bacterial strain based on replicates of honey samples containing that floral origin. Computations were performed using the function "numSummary" in R (R Core Team, 2015) and plotted using the package "ggplot2" (Chang, 2013).
The variation in antibacterial activity was modeled using a mixed-effects modeling procedure in R. The library "nlme" was used to test the effects of bacterial strains, floral origins as well as physicochemical parameters of honey on the dependent variable "inhibition zone." The categorical factors (bacterial strains and floral origins) and all continuous explanatory variables (physicochemical parameters) were included in a GLMM as a fixed effect, while "honey samples" from which replications were carried out were considered as a random effect (Pinheiro et al., 2015). The interaction of the two factors of "Bacterial strains × Floral origin" was also encompassed into the model using the function "lme" and the maximum likelihood (ML) method. The effect of each factor as well as their interaction was achieved using the function "anova" with the selection of likelihood ratio (LR) test with "marginal" type because our data were unbalanced with regards to the number of honey samples of each floral origin. The Akaike information criterion (AIC) was used to select the model with the best fit. Finally, the function "Effect" was applied for constructing "effect plots" of every single explanatory variable included in the GLMM.
Physicochemical and Pollen Parameters of Honey
The physicochemical analysis of the study honeys, generally, indicated a water content of 14.6%, with an acidic pH (4.38 ± 0.50), EC = 0.5 µs/cm, a HMF content = 82 mg/kg honey. The total sugars were 83% while the reducing sugars = 71%. On average, pollen density was 7.86 × 10 6 grains/10 g of honey, while the concentration of proline = 525.5 ± 550.2 mg/kg honey ( Table 1).
At the scale of pollinic composition, honeys dominated by Fabaceae sp. pollen contained less water (WC = 12.2%), while those dominated by Astragalus gyzensis were the most moisturized with WC = 15.8 ± 0.5%. The unifloral honey of Prunus persica had the highest EC value (0.57 µS/cm) and pH (5.05). The pH values of other types of honey ranged between 4.3 and 4.5. The unifloral honey of Fabaceae sp. showed the highest values of total sugars (86%) and HMF (184 mg/kg honey), but was the poorest in reducing sugars (63.4%). For the latter parameter, Eucalyptus globulus and Diplotaxis harra were the richest with 77 and 75%, respectively. The physicochemical parameters of multifloral honey were intermediate compared to other honeys except for pollen density where the maximum was recorded with 14.83 × 10 6 grains/10 g of honey. The concentration of proline was higher in honeys of A. gyzensis, Retama retam and the multifloral, which represent the same homogenous group according to Tukey's test. Whereas the honey dominated by Fabaceae sp. pollen was the least rich in proline with only 14 mg/kg of honey. All ANOVAs revealed very significant differences (P < 0.001) between floral origins for all honey parameters, where homogeneous groups of Tukey's test differ between honeys from one parameter to another ( Table 1).
Antibacterial Activity of Honey according to Floral Origins
Overall, the antibacterial action of Saharan honeys differed from one bacterium to another. E. coli was the most sensitive species Values of each parameter are given in means ± SD [range in square brackets], with the same superscript letters indicating no differences between means according to Tukey's post hoc tests, which followed One-way ANOVAs (F, F-value with df numerator and df denominator, P, P-value).
The use of trimethoprim-sulfamethoxazole as positive control against the strains of reference revealed inhibition activities of 24 mm for E. coli and 24.3 mm for S. aureus.
At the level of bacteria, all floral origins of honey showed an antimicrobial activity against S. aureus but with rather similar reactions (9-10.5 mm), except with P. persica-based honey, whose activity was only 6 mm. The bacteria E. coli experienced a greater inhibition effect when treated with honey of Fabaceae sp. (15.0 mm), Z. lotus (12.3 mm), and multifloral honey (11.6 mm). Whereas, a large variation in antibacterial activity of honeys was observed with both bacteria B. subtilis and C. perfringens. For B. subtilis, the antibacterial activity was higher with Fabaceae sp. honey (20 mm), but it was zero with those of E. globulus and P. persica. Similarly for C. perfringens, it was resistant toward honeys dominated by pollen of A. gyzensis, D. harra, and R. retam, while its growth was greatly reduced under treatment based on honey of P. persica (Figure 2).
The assessment of antimicrobial activity of different antibiotics were determined against the two reference strains by measuring diameters of the inhibition zones. E. coli and S. aureus were clearly sensitive to all tested antibiotics. The Sulfamides (Trimethoprim-sulfamethoxazole, Clindamycin, and Fusidic acid) and Aminozides antibiotics (Gentamicin) were the most active antibiotics against E. coli.
Influence of Honey Parameters on Antibacterial Activity
Modeling the synergistic antimicrobial effects of honey parameters revealed that the inhibition zone "antimicrobial activity" was negatively associated with the bacteria C. perfringens and E. coli (P < 0.001 and P = 0.002, respectively). Whereas the variation of that activity was not significantly related in B. subtilis and S. aureus. The GLMM indicated that antimicrobial activity was higher (P = 0.003) in honeys dominated with Fabaceae sp. pollen compared to the other floral origins, where the diameter of inhibition zone significantly decreased when bacteria were treated respectively with multifloral honey (P = 0.049), D. harra (P = 0.030), R. retam (P < 0.001), P. persica (P < 0.001), E. globulus (P < 0.001). The inhibition zone was not significantly associated with honey of Z. lotus (P = 0.345) ( Table 2).
Regarding the physicochemical parameters of honey, the statistical model demonstrated that the antimicrobial activity increased with increasing water content (P = 0.040); whereas it significantly decreased with increasing electrical conductivity (EC) (P = 0.007). Moreover, the antimicrobial activity was positively correlated with reducing sugars (P = 0.036). The rest of parameters have no significant effect on the variation of inhibition zone diameter (Figure 3, Table 2).
The interaction of the two factors "Bacterial strains × Floral origin" showed that the antimicrobial effect of Saharan honeys against C. perfringens and E. coli was deemed positively related to honeys originated from E. globulus, P. persica, R. retam, Z. lotus, and multifloral origin. While the inhibition zone in S. aureus was associated negatively with Fabaceae sp. but positively with honeys of E. globulus, R. retam, and P. persica ( Table 2).
The LR test of the GLMM revealed that there was a highly significant effect of the bacterial strains, floral origins and their interaction "Bacterial strains × Floral origins" (P < 0.001) on the variation of antimicrobial activity of Saharan honeys (Table 3). Moreover, water content, EC, and reducing sugars concentration in honey significantly affected the antimicrobial activity. However, the effects of pH, HMF, total sugars, pollen density, and proline content were not significant (P > 0.05).
DISCUSSION
This essay showed that both physicochemical properties and pollen composition of Saharan honey differ depending on their botanical origins. Thus, according to these two characteristics the antibacterial activity of these honeys varies between the tested bacteria. This may be explained by the fact that the antibacterial activity of honey essentially depends on the type of flowers from which bees gather nectar (Allen et al., 1991). But also the sensitivity/resistance of study strains influences that activity (Shahid et al., 2008), as it is the case of E. coli which reacted with high antibacterial activity values for both study honeys and antibiotics.
The significant variation in antimicrobial activity among the bacterial strains is assigned to the specificity of each bacterium, which reacts differently to honey parameters. According to Zaika (1988), Gram-positive bacteria are more resistant to essential oils than Gram-negative bacteria. This statement was however not confirmed by honey-related studies. Nevertheless, our honeys showed a higher antibacterial activity against E. coli, a Gramnegative bacterium, compared to the other three Gram-positive bacteria. Indeed, S. aureus resisted to several antibiotics so the resulted inhibition zones by honeys were slightly lower compared to those of E. coli. Though testing quantitatively a variety of each group species with a good number of isolates provides determine relevantly the activity trend of honeys. Despite that, our results are in agreement with the investigations of Shamala et al. (2002) in which honey showed a significant antibacterial activity against E. coli either in vitro and in vivo conditions. Additionally, the marked sensitivity of study bacteria to certain types of honey (e.g., with the origin of Fabaceae sp.) is probably linked to medicinal properties of the dominant flower from which honey was produced. These effective honeys can be used as an alternative to fight against some resistance strains.
Our results revealed that the overall antimicrobial activity increases with the content of water in honey. These findings are similar to those of honeys from New Zealand, where the antibacterial activity was found to be more effective at low concentrations of honey (Molan and Russell, 1988). This assumes that the antimicrobial activity of our honeys depends on the content of endogenous hydrogen peroxide, which is the main antibacterial agent in honey (Morse, 1986). In fact, the antibacterial potential of hydrogen peroxide results from the action of these highly reactive oxidizing molecules, which play the role of a "cleaning agent" attacking the cell membrane of microorganisms by producing free radicals that induce cell destruction. The latter cause damage to cell membrane lipids, isolating the cell, inhibiting the entry of nutrients, and the removal of waste material; thus triggering gradually slow death of the microorganism (Lu et al., 2005;Brudzynski, 2006;Erejuwa et al., 2012). Since water is essential to the oxidation process, hydrogen peroxide is typically produced in immature honeys in which water content is high. While in a ripe honey in which moisture content is low, glucose oxidase remains inactive so the oxidation process are limited. Thus, the honey contains a small amount of hydrogen peroxide insufficient to prevent bacterial growth unless water content increases (Bogdanov and Blumer, 2001). That perfectly explains the positive correlation between honey moisture content and the antimicrobial action obtained in the statistical model. Furthermore, other molecules grouped under the name of non-peroxide inhibins can be the cause of the antibacterial action of honey; their origin is also the subject of lively discussions (Mavric et al., 2008;Mandal and Mandal, 2011). Some studies state that these molecules are of plant origin, while others declare that are added by bees when developing honey. The role of non-peroxide inhibins, often underestimated, is very important as they are at a large extent: insensitive to heat and light, and remains intact after honey storage for long periods (Bogdanov, 1984;Reybroeck et al., 2014).
The antimicrobial activity of Saharan honeys was more effective against bacteria when the honey has low EC. The latter is linked to the ionizable material content in which the mineral matter represents the essential. EC depends on the nature of the dissolved ions and their concentration (Rejsek, 2002), which in turn is linked to the botanical origin of honey and indirectly linked to various environmental conditions, including edaphic factors upon which melliferous plants substantially depend (Thasyvorlor and Manikis, 1995). This corroborates with our findings where the antimicrobial activity varied significantly between botanical origins, which are behind the significant change in EC.
Furthermore, according to Bonté and Desmoulière (2013), potassium salts represent almost half of honey inorganic materials, but there is also calcium, sodium, magnesium, copper, manganese, chlorine, sulfur, silicon, iron, and more than 30 trace elements. Minerals play an important role in biological systems, but can also cause harmful effects if their inputs exceed the recommended amounts (Tuzen and Soylak, 2005). Our findings imply that the factors that may affect the antibacterial activity of honey can have a redundant activity, or be mutually dependent, or even have antagonistic or synergistic activity against different bacterial species (Thasyvorlor and Manikis, 1995;Wahdan, 1998).
The positive correlation of the antimicrobial activity with reducing sugars is associated to the osmotic effect generated by high sugar concentration in honey. As honey is hypertonic, and due to the action of simple sugars on water contained in bacteria, it causes the lysis of the bacterial membrane, inhibition of the growth and then death of the microorganism (Couquet et al., 2013). For this parameter, our results are similar to those reported in Mandal and Mandal (2011).
Since the antibacterial activity was high with honeys originated from Fabaceae sp. P. persica, Z. lotus and multifloral honey, we speculate that these honeys contain a high content of hydrogen peroxide and even other non-peroxide inhibins such as lysozymes, flavonoids, aromatic acids, and volatile substances (Wahdan, 1998;Brudzynski, 2006;Montenegro and Mejías, 2013). Therefore, the use of sophisticated and complementary techniques enables detecting and quantifying accurately these compounds in different botanical origins of honey (Alzahrani et al., 2012). For example, for the analysis of phenolic acids and flavonoids, which depend on the floral origin of honey, the use of modern conventional techniques such as GC-MS and LC-MS allows to determine the floral origin of honey having the more effective use as an antimicrobial agent (Bertoncelj et al., 2007;Boukraâ, 2013). In addition, NMR allows the analysis of complex mixtures of natural products such as honey and thus the identification and quantification of various families of compounds regardless of their structure (Tiwari et al., 2015).
CONCLUSION
This assay shows that Saharan honeys have multiple floral origins, which are causing differences in their physicochemical and pollinic characteristics. The GLMM revealed that antibacterial effect increases with increasing water content and reducing sugars in honey, while it decreases with increasing EC. These three parameters are the more relevant parameters that were correlated with antibacterial activity that differed significantly from one bacterium to another. E. coli was the most sensitive species while C. perfringens was the least sensitive. Honeys Sum Sq., sum of squares; Df, degrees of freedom; F, F-statistic; P, P-value; Sig, significance codes; ***P < 0.001, **P < 0.01, *P < 0.05, ns, not significant: P > 0.05.
tested against B. subtilis and S. aureus indicated intermediate antibacterial activity.
In light of floral origins, our results suggest that Saharan honeys with the floral origin of Fabaceae sp. have a higher detrimental effect on bacteria compared to other spontaneous Saharan species, known for their common uses in traditional medicine such as Zizyphus lotus or D. harra. Most likely, this returns to the source of nectar collected from these species welladapted to arid conditions. Yet, several factors, particularly the ecological ones, can affect the melliferous plants; thus additional research are required to fill the scientific gaps in this still virgin field of research in drylands.
AUTHOR CONTRIBUTIONS
HL designed the study, collected honey samples, carried out all laboratory experiments (antibiotic tests, honey antibacterial assays, physicochemical, and pollinic analyses), and drafted the manuscript. LB contributed in the pollinic analysis. SB gave technical support and conceptual advice. TM helped in drafting and revision of the manuscript. SH and MM performed physicochemical analyses on honey samples. RH conducted the experiment of honey antibacterial tests. HC conceived the paper, analyzed and modeled statistically data, wrote and revised the article. | v3-fos |
2019-03-19T13:08:19.608Z | {
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} | s2 | Genotypic Variation in Osmotic Stress Tolerance Among Rice Cultivars and Its Association with L-Type Lateral Root Development
Abstract The differences in osmotic stress tolerance and morphological characteristics of the root system of stress-tolerant and stress-sensitive rice cultivars were clarified by examining genetic variation. Fifty-four Rice Diversity Research Set cultivars, and Azucena, IRAT109, Dular (droughttolerant), IR64 (drought-sensitive), and IR28 (salt-sensitive) were used. Rice seedlings were cultivated for 14 days by water culture (control). Polyethylene glycol 6000 was dissolved in the culture medium as osmotic stress treatment on day 7 to adjust the water potential to –0.42 MPa (stress treatment). The stress treatment to control ratio (S/C ratio) was calculated to evaluate the degree of stress tolerance. The dry-weight S/C ratio in the shoot showed a significant varietal difference from 0.874 to 0.376 and that in the root from 0.931 to 0.342, and root, respectively, and these values were significantly correlated. Five osmotic stress-tolerant and 5 stress-sensitive cultivars were selected, and their root-system morphology was investigated in detail. The number of the L-type lateral roots, which were longer and thicker, increased 1.5 – 3.6 times that of the control with osmotic stress treatment in the tolerant cultivar group. It slightly decreased 0.8 – 0.9 times that of the control with osmotic stress in the sensitive cultivar group. The number of crown roots and S-type lateral roots, which were finer and shorter, decreased with stress in both cultivar groups; however, this decrease was significantly lower in the tolerant cultivar group. Thus it is suggested that the maintenance of root-system development, especially L-type lateral roots under osmotic stress, involves genetic variation in the genes responsible for the dry matter production.
The green revolution, which began in the last century, achieved a breakthrough in productivity by improving shoot traits and promoting high input of fertilizer and irrigation. However, the present rice production, after more than half a century from the green revolution, is still threatened by environmental stresses such as drought, salinity, low fertility of soil, and high and /or low temperature. Among these stresses, water deficit commonly occurs in rain-fed rice production areas; which occupy about half of the total rice production area in the world (Maclean et al., 2002). Rice productivity under a rain-fed ecosystem is lower than that under irrigated cultivation because of the high sensitivity of rice to water shortage (Bouman et al., 2007). Therefore, further genetic improvement, in addition to novel production technologies, is highly required for sustainable rice production.
Recently, many scientists have started to evaluate root function to seek novel strategies for genetic improvement of rice productivity, believing that "roots are the key to a second green revolution" (Gewin, 2010). Obviously, roots play an important role in growth and grain production throughout rice growing stages; however, little attention has been paid to root traits in rice breeding because of the time-and labor-consuming sample collection and /or huge effort required to analyze the data. Previous studies on rice drought tolerance found some root traits that were responsible for superior drought resistance and /or resilience. For example, deep rooting and root thickness are important morphological traits that allow plants to take up water from a deeper soil layer (Araki and Iijima, 1998;Kato et al., 2007).
The plasticity of root development has been emphasized as an important trait for adaptation to soil moisture changes (Yamauchi et al., 1996;Suralta et al., 2008;Kano et al., 2011). The lateral root constitutes approximately 90% of the total length in a plant root system (Yamauchi et al., 1987a(Yamauchi et al., , 1987b. Therefore, the lateral root is considered to play a major role in nutrition and water absorption. It is important to extend lateral roots under a drought stress condition effectively in the soil to obtain the limited soil resources. There are two types of lateral roots in rice: thick and long lateral roots with higher order branching and thin and short lateral roots without higher order branching (Kawata and Shibayama, 1965;Kono et al., 1972).These two types of lateral roots are also found in other cereals. Anatomical studies revealed that thick and long lateral roots (L-type) have an inner structure similar to that of seminal roots and nodal roots. whereas short lateral roots (S-type) have a simpler vascular bundle (Yamauchi et al., 1987b). The different types of lateral roots vary in anatomy, developmental characteristics, carbon and nitrogen dynamics, developmental responses to various soil environments (Yamauchi et al., 1996), and genetic regulation of their development (Wang et al., 2006). L-type lateral roots tend to show sharper developmental responses to various soil moisture conditions (Bañoc et al., 2000a;Suralta et al., 2010).
Root distribution has also been quantitatively characterized by using several morphological traits, and wide genotypic differences have been detected (Nemoto et al., 1998;Kato et al., 2007;Uga et al., 2009). Although previous studies revealed genotypic differences in root development, information about the genotypic diversity of root traits and their response to osmotic stresses is limited because the employed cultivars do not fully cover a wide range of genetically diverse cultivars. The Rice Diversity Research Set of germplasm (RDRS), which was developed by the National Institute of Agrobiological Science (NIAS), has made possible a wide and comprehensive evaluation of genotypic diversity of rice (Kojima et al., 2005). Many studies have been conducted on the genetic variation in the shoot using RDRS Matsunami et al., 2012;Iseki et al., 2013;Matsunami et al., 2013 ). Alternatively, the studies on genetic variations with the root system using RDRS are limited. Uga et al. (2009) analyzed anatomical and morphological traits under rainfed upland conditions using RDRS, and found differences in root characteristics between japonica and indica accessions. Determining the responsible traits by using material with a wide genetic background may give essential information for further breeding strategies or genetic analysis. Matsunami et al. (2012) reported the genotypic variation in biomass production in shoot and root under soil moisture deficit by using the RDRS.
In this study, therefore, we aimed to evaluate the genotypic variation in the biomass production and root morphological development in response to osmotic stress to identify key root traits that contribute to osmotic stress tolerance by using the RDRS which has a wide range of genetically diverse cultivars.
Seeds were germinated in the dark at 28ºC in petri dishes for 3 days. During this period, the seminal roots of the germinating seedlings elongated approximately 1 cm. There was no varietal variation in the degree of elongation and germination of the seminal root. These seedlings were transplanted onto plastic nets (2.5 × 2.5 mm mesh) that floated on a solution of nutrients. The solution contained 1.5 × 10 −3 M KNO 3 , 1.0 × 10 −3 M Ca(NO 3 ) 2 , 2.5 × 10 −4 M NH 4 H 2 PO 4 , 5.0 × 10 −4 M MgSO 4 , 1.3 × 10 −5 M Fe-EDTA, 2.3 × 10 −6 M MnCl 2 , 1.2 × 10 −5 M H 3 BO 3 , 1.9 × 10 −7 M ZnSO4, 7.9 × 10 −8 M CuSO 4 , and 7.5 × 10 −9 M (NH 4 ) 6 Mo 7 O 24 . Sixteen seedlings were placed on each net and cultivated in a beaker that contained 1,000 mL of this solution. Twenty plants per beaker were cultivated. Ten plants were used for the measurement of shoot and root dry weights and 10 plants were used for the measurement of root traits. Distilled water was added every day, and the water level was maintained after transplanting, constantly. The solution was aerated by continuous bubbling with air (1,000 mL air /min) provided by an aerator (HPα 10000; NISSO, Japan). The bubbles did not travel as far as the root axis, and the growth of root systems was not inhibited by this procedure (Ogawa et al., 2009). The walls of the beakers were covered with heavy paper to exclude light and stimulate the growth of root systems. The plants were illuminated with white light with a 12-h photoperiod in a growth chamber that was maintained at 28 ± 0.2ºC with a relative humidity of approximately 70% (MLR-350H; SANYO, Japan). The photon flux density of photosynthetically active radiation (PAR; 400 -700 nm) at the top of each plant was 320 μmol・m −2 ・s −1 .
Stress treatment
Seven days after transplanting, 200 g polyethylene glycol (PEG) 6000 per liter of nutrient solution was dissolved to induce osmotic stress. The water potential of the nutrient solutions was determined using a vapor pressure osmometer (model 5520, Wescor). The resulting water potential values were -0.42 MPa (stress treatment) and -0.08 MPa (control). High-molecular weight PEG was used as an osmoticum because it is virtually excluded from entering the root apoplast (Carpita et al., 1979) and thus removes water from the cell and cell wall space. PEG has no apparent toxic effects under well-aerated conditions (Verslues et al., 1998;Raymond and Smirnoff, 2002;Ober and Sharp, 2003).
Measurement of growth
After 7 days of stress treatment (14 days after transplanting), plants were sampled, and shoots and roots were desiccated at 80ºC for more than 3 days. The dry weight of these samples was measured.
Sampled roots were immediately fixed and stained in 0.1% (w /v) Coomassie Brilliant Blue G250 in FAA (5% formaldehyde, 50% ethanol, 5% acetic acid [v /v]), and kept for more than 3 days. Images of the root systems were captured by an image scanner (Epson Perfection V700 Photo scanner, EPSON, USA) at 1200 dpi, and the total length, the total number of root tips, and average root diameter were measured by WinRHIZO (Regent Instruments Inc. Quebec, Canada). The number of L-type lateral roots and crown roots were counted by visual observation. The number of S-type lateral roots was calculated by subtracting the number of crown roots and L-type lateral roots from the total number of root tips.
Data analysis
One cultivation examination was performed for each cultivar and each treatment. The data in each control and stress treatment are the averages of 10 replications (10 seedlings). Analysis of variance and principal component analysis (PCA) were performed using the statistical software Ekuseru-Toukei 2010 (Social Survey Research Information, Japan). Seven data sets (the root dry weight, the total root length, the root surface area, the average root diameter, the number of crown roots, the number of S-type lateral roots, and the number of L-type lateral roots), each including 5 stress-tolerant cultivars and 5 stress-sensitive cultivars, were used for the PCA.
Results and Discussion
Osmotic stress treatment inhibited the shoot and root growth in all cultivars, and there were genetic variations in plant growth under osmotic stress conditions. The value of the stress to control ratio (S /C ratio) was defined as the index of the osmotic stress tolerance. The shoot dry weight had a maximum S /C ratio of 0.874 in IR58, and the minimum value was 0.376 in Basilanon (Table 1). The root dry weight had a maximum S /C ratio of 0.931 in IR58, and the minimum value was 0.342 in Basilanon. The total root number had a maximum S/C ratio of 0.908 in Milyang 23, and the minimum value was 0.231 in Basilanon ( Fig. 1-A). The total root length had a maximum S/C ratio of 0.744 in Jarjan, and the minimum value was 0.230 in Basilanon ( Fig. 1-B). The average root diameter increased after the stress treatment in all but 3 cultivars: Jarjan, Nepal was inhibited. IR28 and IR58 show osmotic stress tolerance but are sensitive to sodium stress, suggesting that different resistance mechanisms are involved in osmotic stress and salt stress. IRAT109 (Nemoto et al., 1998;Bañoc et al., 2000a;Luo, 2010), Azucena (Dwivedi et al., 2010), and Dular (De Datta et al., 1975;Kobata et al., 1996;Bañoc et al., 2000a) were reported to be drought-resistant cultivars in previous studies. Among the 59 cultivars used in this study, the S/C ratio of the dry weight of shoots and roots were ranked 35th and 19th in IRAT109, 24th and 33rd in Azucena, and 42nd and 33rd in Dular, respectively. Some cultivars demonstrated osmotic stress tolerance more than drought tolerance, although this is an early result of this study. RDRS is a group of cultivars that cover the genetic diversity of rice around the world (Kojima et al., 2005). These results suggest the presence of cultivars among the global rice resources that are tolerant to osmotic stress.
The differences in the morphological characteristics between cultivars that are tolerant and those sensitive to osmotic stress are shown in Table 2. In tolerant cultivars, osmotic stress treatment increased the number of L-type lateral roots 1.5 to 3.6 times that of the control. On the other hand, in sensitive cultivars, the number of L-type lateral roots was 0.8 to 0.9 times that of the control. The numbers of crown roots and S-type lateral roots decreased with the osmotic stress treatment. The degree of the decrease in the tolerant cultivars was smaller than that in the sensitive cultivars. Additionally, to elucidate the factor 555, and Rexmont ( Fig. 1-C). The maximum value of the S/C ratio of average diameter was 1.288 in Vary Futsi, and the minimum value was 0.884 in Jarjan. The surface area of root had a maximum S /C ratio of 0.712 in IR58, and the minimum value was 0.230 in Basilanon (Fig. 1-D). Kato et al. (2006) reported that specific root length of deep roots decreases and a root is enlarged under a drought stress condition in several rice cultivars. Water deficiency, often coinciding with nutrient deficiency, can result in increased root tissue density in some species (Trubat et al., 2006). Mechanical impedance on soils increases with drying, and in some species, root diameter may increase (Manes et al., 2006), stay constant or decrease (Bartsch, 1987). Stimulated ethylene production may play a key role in mediating an increased root diameter under mechanical stress (Clark et al., 2003). On the other hand, root diameter has been reported to decrease by drought stress (Uga et al., 2008;Henry et al., 2012).
There was a significant correlation between the S /C ratio of the shoot dry weight and the S/C ratio of the root dry weight (Fig. 2). From these results, we selected 5 cultivars as osmotic stress-tolerant cultivars (IR58, Calotoc, IR28, Deejiaohualuo, and Jinguoyin), and we also selected 5 cultivars as the osmotic stress-sensitive cultivars (Basilanon, Tupa729, Deng Pao Zhai, Khau Tan Chiem, and Nepal 555). In comparison with the results of the study by Matsunami et al. (2012), which determined the genotypic difference in biomass production under soil moisture deficit among the RDRS, some stress-tolerant cultivars in this study also exhibited superior growth under soil moisture deficit; ex. Calotoc was ranked 14th under -0.10 MPa soil water potential (SWP) regime, and 16th under -0.52 MPa SWP regime. Deejiaohualuo was ranked 8th under -0.10 MPa SWP regime, which were identified as stress-tolerant cultivars in this study. In contrast, Deng Pao Zhai and Nepal 555, which were identified as stresssensitive cultivars in this study, exhibited greater growth under -0.52 MPa SWP regime among the RDRS. There was a discrepancy concerning the tolerant and sensitive cultivars between the two experiments. This inconsistency may be caused by the difference in the strength, duration and kind of stresses and plant growth stage. Kano et al. (2011) also reported that a result obtained on drought stress using the soil does not agree with the result obtained on osmotic stress using the PEG treatment.
Salt stress is a combined stress comprising osmotic stress and sodium stress (Munns, 2002;Chaves et al., 2009). In previous studies, IR28 and IR58, which were selected as cultivars that were tolerant to the osmotic stress in this study, were reported as being sensitive to salt stress (Igarashi et al., 1997;Dionisio-Sese and Tobita, 1998;Lee et al., 2003;Hossain et al., 2011). Under salt stress conditions, IR58 (Lee et al., 2003) and IR28 (Dionisio-Sese and Tobita, 1998) accumulated sodium ions, and growth 0.5 1 S/C ratio in root dry weight S/C ratio in root dry weight S/C ratio in root dry weight y g responsible for the osmotic stress tolerance in roots, 7 root traits in the 5 stress-tolerant cultivars and the 5 stresssensitive cultivars were evaluated by PCA under stress and control conditions. The first and second principal components (PC1 and PC2) accounted for 68.5% and 19.3% of the total variance, respectively. A scatter plot of all the accessions based on PC1 and PC2 scores of cultivars and treatments was constructed (Fig. 3). PC1 scores were higher in the control conditions than in stress treatment in all cultivars. PC2 scores in tolerant cultivars were higher than those in sensitive cultivars under stress treatment. The absolute value of the factor loading of the number of L-type lateral roots in PC2 was the highest of the 7 root traits (Table 3). Because L-type lateral roots are long and have higher-order branches, these roots account for an important portion of total root length and surface area (Yamauchi et al., 1987b). Previous studies showed that the development of the L-type lateral root is an important root trait for drought tolerance. Bañoc et al. (2000a) reported that changes in the soil water content affected the root morphology and that the growth of L-type lateral roots was stimulated under water deficit. The emergence and elongation of L-type lateral roots contributed to the extension of the root zone and the maintenance of water and nutrient absorption under conditions of water deficit (Suralta et al., 2010). In this study, the importance of the Significance 1) ** * *** ns 1) ***, **, ***, and n.s. indicate significant diffserences in S / C ratio between stress-tolerant and stress-sensitive cultivars at p < 0.05, p < 0.01, p < 0.001, and not significant by the Student's t -test, respectively. L-type lateral root was demonstrated under osmotic stress conditions using rice cultivar groups with genetic variations. In this study, genotypic variations were shown to affect the osmotic stress tolerance among 59 cultivars of rice seedlings. From this result, cultivars that were tolerant and sensitive to osmotic stress were selected, and their root morphology was examined. The number of L-type lateral roots increased especially in the tolerant cultivars under osmotic stress. Further studies will be required to obtain more information to determine the mechanisms of osmotic stress tolerance from the aspect of plant physiology and molecular biology by comparing the stresstolerant and stress-sensitive cultivars selected in this study. | v3-fos |
2018-04-03T06:04:43.074Z | {
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"year": 2015
} | s2 | Identification of Associated SSR Markers for Yield Component and Fiber Quality Traits Based on Frame Map and Upland Cotton Collections
Detecting QTLs (quantitative trait loci) that enhance cotton yield and fiber quality traits and accelerate breeding has been the focus of many cotton breeders. In the present study, 359 SSR (simple sequence repeat) markers were used for the association mapping of 241 Upland cotton collections. A total of 333 markers, representing 733 polymorphic loci, were detected. The average linkage disequilibrium (LD) decay distances were 8.58 cM (r2 > 0.1) and 5.76 cM (r2 > 0.2). 241 collections were arranged into two subgroups using STRUCTURE software. Mixed linear modeling (MLM) methods (with population structure (Q) and relative kinship matrix (K)) were applied to analyze four phenotypic datasets obtained from four environments (two different locations and two years). Forty-six markers associated with the number of bolls per plant (NB), boll weight (BW), lint percentage (LP), fiber length (FL), fiber strength (FS) and fiber micornaire value (FM) were repeatedly detected in at least two environments. Of 46 associated markers, 32 were identified as new association markers, and 14 had been previously reported in the literature. Nine association markers were near QTLs (at a distance of less than 1–2 LD decay on the reference map) that had been previously described. These results provide new useful markers for marker-assisted selection in breeding programs and new insights for understanding the genetic basis of Upland cotton yields and fiber quality traits at the whole-genome level.
Introduction
Cotton is an important industrial crop in China. Many cotton breeders have focused on detecting and using marker-associated quantitative trait loci (QTLs) for marker-assisted selection (MAS) in breeding programs. Linkage analysis is a classic strategy for detecting QTLs in segregated populations derived from two inbred lines. Since Shappley [1] first reported QTLs associated with the agronomic and fiber traits of Upland cotton, thousands of QTLs have been identified through segregation analyses in cotton [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Two population types have been used in these QTL mapping studies: populations derived from interspecies crosses between Gossypium hirsutum and Gossypium barbadense and populations derived from intraspecies crosses within G. hirsutum. Most QTLs and linkage markers detected based on these interspecies populations are difficult to directly utilize for MAS because the Upland cotton varieties or lines are major material resources in breeding programs. However, when QTL and linkage markers were detected in intraspecies populations, only a few genomic areas can be scanned because of the low number of polymorphisms between Upland cotton varieties, and these results are only suitable for breeding populations derived from QTL-detected populations. For better understand the genetic basis of interesting traits in different breeding materials, such as the QTL distributions, configurations, and the percentage contribution to phenotypic variation, cotton breeders need to employ new analysis method.
In recent years, association mapping based on disequilibrium analysis has been introduced into plant QTL mapping. The new mapping strategy provided a powerful method for QTL mapping of germplasm populations. Compared with QTL mapping based on linkage analysis, association mapping has many advantages, including a higher resolution, increased genome coverage, lower time and money consumption, and reduced risk. Abdurakhmonov et al. [16] first conducted association mapping in which association between SSR (simple sequence repeat) markers and fiber quality traits was detected based on a germplasm resource population comprising 208 landrace stocks and 77 photoperiodic variety accessions, and a core set of 95 microsatellite markers. Abdurakhmonov et al. [17] also conducted genome-wide linkage disequilibrium (LD) scanning and association mapping based on a panel consisting of 334 G. hirsutum variety accessions from Uzbek, Latin American, and Australian ecotypes. In two environments, an average of 20 SSR markers were found to be associated with the main fiber quality traits using a unified mixed liner model (MLM) incorporating population structure and kinship, and 12-22 SSR markers were associated with fiber length, fiber strength, fiber fineness and six other fiber quality traits. Approximately 25% to 54% of these markers had previously been detected in studies based on linkage analysis. Zeng et al. [18] identified associations between SSR markers and fiber traits using an exotic germplasm population derived from species polycrosses (SPs) among tetraploid Gossypium species. A total of 202 fragments were analyzed, and fifty-nine markers showed a significant association with six fiber quality traits. These studies confirmed the feasibility of applying association analysis to explore complex traits in Upland cotton collections.
Following system and cross selection, the Upland cotton varieties found in China were demonstrated to show distinct characteristics. Generally, Chinese Upland cotton varieties are typically classified into three ecotypes: the Yellow River valley type, the Yangtze River valley type and the interior land type, according to the areas in which cotton was planted and cultivated. The Yellow River valley type is characterized by high disease resistance and high yields, while the Yangtze River valley type exhibits a high lint percentage or large bolls. Additionally, the interior land type shows adaptation to long days and short growing seasons in high-latitude areas. Furthermore, a large number of germplasm resources, including high lint percent and fiber quality lines, have been developed through cotton breeding. These varieties and germplasm resource lines have provided important materials for improving the yields and fiber quality of Upland cotton varieties in China. Zhang et al. [19] performed general linear model (GLM) association mapping of 12 agronomic and fiber quality traits based on 121 SSR markers and 81 G. hirsutum L. collections, and detected 180 loci that were significantly associated with 12 traits in more than one environment. Mei et al. [20] conducted association mapping of yields and yield component traits using 356 representative Upland cotton cultivars and 145 polymorphism markers. Cai et al. [21] performed association mapping of fiber quality traits in 99 G. hirsutum L. collections with 97 polymorphic microsatellite marker primer pairs. Zhao et al. [22] carried out association mapping based on Verticillium Wilt Resistance using a collection of 329 cotton (G. hirsutum L.) accessions obtained from a Chinese cotton germplasm collection. The results of these studies indicated the feasibility of applying association analysis to explore complex traits in Upland cotton collections in China. To better understand the genetic foundation of the yield and fiber quality traits at the population level and identify associated SSR markers, we performed whole-genome association analyses using 359 SSR polymorphism markers well distributed in reference maps [23,24] and a panel of 241 varieties and germplasm resource lines in the present study.
Selection of accessions and determination of phenotypic data
A total of 241 Upland cotton accessions were selected for genotype screening and evaluation of yield components and fiber quality traits to identify loci associated with yield components and fiber quality QTLs. All of the collections were derived from four sources: ① elite varieties popularly cultivated in China; ② germplasm resource lines with outstanding yield components or fiber qualities; ③ parental lines that are typically used in breeding programs; and ④ historical varieties and germplasm resources lines from abroad, including 20 collections from the US, 6 from the Uzbek, 6 from the Sudan, one from Australia and one from Cuba (S1 Table). , and lint percentage (LP). Ten plants growing near to each other were selected to count the total number of bolls. The average number for ten plants was scored as NB. Twentyfive bolls from each plot were weighed to determine the BW and then ginned by roller gin to evaluate the LP. Fifteen grams of lint was sent to the Supervision and Testing Center of cotton quality, the Ministry of Agriculture to measure the fiber quality. The following fiber quality traits were evaluated using the High-Volume Index (HVI) spectrum: 2.5% fiber span length (FL, mm), fiber strength (FS, cN/tex), and the micronaire reading (FM).
SSR markers and genotyping
In 2010, the young, not yet fully expanded leaves were collected from five plants of each line. DNA was extracted from the leaves as previously described [25]. A total of 359 polymorphic SSRs were used to genotype the 241 Upland cotton collections. The 359 SSRs included three resources: ① 302 SSRs separated by a distance of approximately 10.0 cM on all 26 chromosomes (A1-A13, D1-D13), and covered 94.6% (3241.3 cM/3425.8 cM) of the reference map [23,24]; ② 27 markers separated by approximately 1-3 cM distance on the 50.0-80.0 cM area of A1 and D1 chromosomes; and ③ 30 markers linked to the QTLs of three yield components traits (NB, BW, and LP) and three fiber quality traits (FL, FS, and FM). The SSR primer sequences used in these analyses were obtained from the Cotton Microsatellite Database (CMD, http:// www.cottonmarker.org/). The marker nomenclature consisted of a letter that specified the origin of the marker followed by the primer number. As previously described [26], the SSR analysis was conducted by polymerase chain reaction (PCR) and 6% non-denaturing polyacrylamide gel electrophoresis (PAGE). PCR runs were performed for 30 cycles of 45 s at 94°C at the annealing temperature for 45 s and 72°C for 60 s, and a final extension step at 72°C for 5 min. For each SSR primer, the polymorphic bands were identified according to the fragment size. The presence of polymorphic DNA fragments was scored as 1, and the absence of fragments was scored as zero. Multiple polymorphic DNA fragments presented or absented together in panel were identified as same marker locus. For the STRUCTURE software, "1" indicates fragments present, "0" indicates absent, and "-1" indicates missing data. For the Tassel software, "2/2" indicates fragments present, "1/1" indicates absent, and "0/0" indicates missing data.
Data analysis
LD values (r 2 and p value) between marker fragments were calculated using TASSEL 3.0 software [27]. The genetic distances between marker pairs were calculated based on the position of these markers on the genetic map [23,24]. Minor loci with a frequency < 0.05 were filtered out to reduce problematic and biased LD estimations between pairs of loci [28,29]. The r 2 values for pairs of SSR loci were plotted as a function of map distances, and LD decay (r 2 < 0.1) was estimated using the average distances of marker pairs showing LD values lower than 0.1 [30].
Analysis of variance (ANOVA) for the phenotypic data was conducted using the Statistical Analysis System (SAS8.1, Cary, NC). The broad-sense heredity of the six traits was calculated using the following equation: where σ 2 e is the residual variance component, and σ 2 G is the genotypic variance component. The population structure was analyzed using STURCTURE 2.2 software [31,32,33], with a running time of 100,000 and 50,000 replications after burn-in. Models for admixture and correlated allele frequencies were employed in the population structure analysis. The pairwise kinship of all 241 collections was calculated using TASSEL 3.0 software [27]. The MLM association analysis of the yield components and fiber quality traits was performed with TAS-SEL 3.0 software, incorporating filtered marker data and the K and Q matrices. We also performed GLM association analyses using the same four datasets, incorporating pairwise kinship information as a covariate and 1,000 permutations for the correction of multiple testing. To make up for the deficiency of using p-values in association, significant MLM associations (p < 0.05) across more than two environments were ranked, and the significance of these markers (p < 0.05) in the permutation test was compared using GLM association tests. The p-values derived from the MLM and GLM analyses were also separately tested using the positive false discovery rate (pFDR) test [34] for multiple testing corrections. The minimum Bayes factor (BFmin) was calculated using following formula: BFmin = -e à p à ln(p) [17,35,36].
Amplification fragment polymorphisms of the SSR markers
A total of 359 SSR markers were used to genotype 241 collections, among which 26 (7.2%) of the markers presented homomorphisms, and 333 markers covering 86.6% reference map (2968 cM/3425.8 cM) produced 733 polymorphic loci, averaging 2.2 loci per marker. The observed locus frequencies ranged from 50.19% to 99.62%, averaging 78.17%. The average genetic diversity was 0.358 (ranging from 0.008 to 0.802). The average polymorphism information content (PIC) was 0.300 (ranging from 0.008 to 0.773).
Population structure and LD of the marker pairs
The population structure was determined using STRUCTURE software, with K values ranging from 1-10. The LnP(D) value increased continuously with no obvious inflexion point before the panel was divided into 9 subgroups. However, the Δk value decreased rapidly at K = 2 and K = 3, and the locus frequency divergence among the subpopulations (Net nucleotide distance) was significant at k = 2, but not at k = 3. Fig. 1 shows that Δk presented a second peak for K = 9, indicating that this panel could be continuously further divided until into 9 subgroups. Pritchard et al. [31] suggested focusing on values of K that capture most of the structure in the data and that seem biologically sensible when the model choice criterion continues to increase with increasing K. To avoid an overcorrected population structure that would lead to the disappearance of the association loci in the association analysis [37], we adopted K = 2, not 9. The first subgroup contained 120 collections, comprising the majority of the elite varieties and parental lines that are typically used in breeding programs from the Yangzi river valley. The second subgroup included 121 collections consisting of germplasm resources lines, historical varieties from abroad, and the majority of the elite varieties and parental lines from the Yellow river valley (S1 Table). Cluster analysis of 241 Upland cotton collections showed majority of subgroup 1, as well as majority of subgroup 2, was clustered together (S1 Fig.).
Approximately 9.36% of the marker pairs showed significant LD, with p values lower than 0.05 (S2 Table). Approximately 18.90% of the collinear marker pairs showed significant LD, and 40.50% of the obtained LD values (r 2 ) were greater than 0.1. Approximately 8.87% of the non-collinear marker pairs showed significant LD, and 3.45% of the LD values (r 2 ) were greater than 0.1. Most of the significant LD values were higher than 0.2 were obtained from collinear marker pairs (S2 Fig., S2 Table). The LD value (r 2 ) decreased rapidly at genetic distances of less than 10 cM. The longest genetic distance between markers was 108 cM. The average genetic distance between markers was 8.58 cM and 5.76 cM for r 2 > 0.1 and r 2 > 0.2 (Fig. 2).
Performance of phenotype and Broad-sense heritability
For all yield and fiber quality traits, the 241 collections presented a wide-range of phenotypic variation in the four different environments (S3 Table). For example, in environment 1 (E1), the NB, BW and LP ranged from 6. 49 (Table 1).
Among the six evaluated traits, LP showed the highest broad-sense heritability, ranging from 0.67 to 0.81. FS and FL exhibited heritabilities higher than 0.5 in three environments and lower than 0.5 in one environment. The broad-sense heritability of the FM was lower than 0.5 in three environments and higher than 0.5 in one environment. The NB and BW showed lower heritabilities compared with the other traits across the four environments, ranging from 0.33-0.42 (Table 2, S4 Table).
Association mapping
For all six traits, including the three yield component traits (NB, BW and LP) and the three fiber quality traits (FL, FS and FM), we applied an MLM (+ kinship + Q-matrix) model to analyze the four datasets derived from the 241 collections at two locations over two years. Only markers showing significance in more than one environment were used to further test Twenty markers tolerated the FDR test in one or more environments, including 12 for yield traits and 8 for fiber quality traits. Fifty one marker loci (25 for yield traits and 26 for fiber quality traits) presented moderate-to-strong or strong-to-very strong evidence for association in different environments. Sixteen markers for yield traits and nine for fiber quality traits passed the permutation test at the 0.05 level in the GLM analysis. In total, forty-six markers associated with different traits were accepted in our analysis (Table 3 and Table 4).
We compared the associated markers identified in the present study with SSR markers previously identified through linkage QTL and association mapping analyses [39][40][41][42][43]. Among 46 markers, 14 were found to be associated or linked with the same traits (LP, FL, FS and FM) identified in previous studies (Table 5). Of the 14 markers, five were associated with LP, four were associated with FL and FS respectively, and one was associated with FM. Because the different markers were used in different studies, only a few markers could be directly compared. Therefore, we also employed the reference map as a bridge to compare the results obtained in the present study with the results from previous studies [39][40][41][42][43]. Nine markers were found to be near the QTLs controlling the same traits with a distance of less than 1-2 LD decay on the reference map (Table 6).
Discussion
Genetic diversity and population structure To maintain relatively high levels of polymorphism and to take advantage of association mapping, different ecotypes from China, including lines from cotton germplasm resources, historical varieties from abroad (the Uzbek, the US, Australia, Cuba and Sudan), mutants lines derived from radiation breeding programs, and some progenies of intra-and interspecies [20], respectively. A low genetic diversity was not only found in Chinese Upland cotton collections but also in American Upland cotton collections [38] and other country's collections [44]. Population structure is an important factor that typically leads to spurious associations. Although the genetic background of Upland cotton is narrow, recent studies have revealed the population structure in association panels for Upland cotton [20-22, 38, 44]. Of 241 collections, 127 came from the Yangzi River valley, and 76 came from the Yellow River valley. In the present study, 73.2% (93/127) of the germplasm resources, varieties and breeding lines from the Yangtze River valley were classified into the P1 sub-group. A total of 75.0% (57/76) of the Table 3 doi:10.1371/journal.pone.0118073.t004 germplasm resources, varieties and breeding lines from the Yellow River valley were classified into the P2 sub-group. The results revealed that the major differences in this panel came from the different ecotypes. However, 25.0% (19/76) of the collections from the Yellow River valley and 26.8% (34/127) of the collections from the Yangzi River valley were not arranged into corresponding subgroups. The fact indicates that there is still frequent gene exchange between different ecotype collections in China (S1 Table). These results were consistent with the results of previous studies [45] and recent reports [20][21][22]. Evanno et al. [46] conducted population structure analyses using three classic models: the island model, the hierarchical island model and the contact zone model, and K = 2 corresponds to the uppermost structural level in the contact zone model. In this study, population structure was similar with that of the contact zone model. The result was consistent with the fact that China is not a native cotton growing area. Most cotton varieties planted in China are derived from only a few germplasm resources (e.g., DPL, Stoneville, King, Uganda, Foster, and Trice) introduced from abroad [47]. [20], the ratio of LD was low and similar to the findings of Zhao [22]. Among the collinear marker pairs, 29.2% showed LD values (r 2 ) greater than 0.2. For the non-collinear marker pairs, this ratio was 0.5% (S2 Table). Further examination of the LD data revealed that approximately 80.5% of moderate LD (0.2 < r 2 < 0.4) and 91.5% of strong LD (r 2 > 0.4) was caused by linkage. Our results also showed that approximately 43.6% of moderate LD (r 2 > 0.1) was caused by other factors in this panel. LD resulting from noncollinear marker pairs has been previously described [16,20,22,44]. Abdurakhmonov [16] provided several possible explanations for LD between non-collinear markers, including selection, co-selection of loci, population stratification, and relatedness, genetic drift or bottlenecks. These elements might also generate LD values leading to spurious marker-trait associations [48][49][50], indicating the necessity of seriously considering population structure (Q) and relatedness (K) when conducting population-based association mapping in cotton germplasm resources [16].
In the present study, the observed LD value (r 2 ) rapidly decreased when the genetic distance was less than 10 cM. The speed of population LD decay was 8.58 or 5.76 cM for r 2 > 0.1 or 0.2, respectively. The LD decay block was similar to that described in recent association analysis studies [20][21][22] but faster than that described in studies using landrace [16,17] and SP panels [18]. We selected markers that were spaced approximately 10 cM apart from the frame linkage map [23,24]. Because of the shortage of polymorphism markers, there were some gaps of more than 15 to 46.8 cM along the 26 chromosomes. Although more markers are needed to conduct genome-wide association analyses (GWAS) of complex traits, the size of the LD blocks would guarantee that the identified SSR markers would be sufficient for MAS in Upland cotton breeding programs because increasing the number of markers per chromosome does not necessarily result in a stronger response to selection, particularly at a shorter distance between markers, such as 10 cM for an F 2 population of 500 individuals [51].
QTLs obtained through association mapping
To avoid spurious associations, different methods have been developed to control population structure, such as structured association (SA) [48], genomic control (GC) [52], EIGENSTRAT [53], stepwise regression (SWR) [54] and mixed linear models (MLM) [55]. To generate more accurate correlations with less-inflated type I errors [55], the MLM (+K+Q) method was employed in the present study. Considering the history of Upland cotton cultivation and the relatively simple population structure in this panel, GLM (+K) was also employed in the present study, and the results derived from the GLM and MLM were compared. For all six traits, the GLM (p < 0.05) detected 216 associated markers, and 155 markers were detected in more than one environment. The MLM (p < 0.05) identified 195 associated markers, and 84 markers were detected in more than one environment. After the correction of population structure using Q-matrix information, approximately 50% of the markers were not repeatedly detected in the MLM compared with the GLM, suggesting that the population structure should be seriously considered in stratified populations [17]. However, comparing the results obtained from the GLM and MLM provides more information. In the present study, all of the associated markers detected through the MLM were associated with the same traits in the GLM analysis across two to four environments. Notably, for the same traits, we compared the map positions of the associated markers derived from the GLM and MLM analyses, and we found more than one associated markers from the GLM were close to (within one or two LD blocks) associated markers detected using the MLM. This observation provided more support for the validity of the MLM results [17].
Interestingly, out of the 46 associated markers detected, some nearby markers (map distance within 1 LD block) were associated with the same traits. For example, both of NAU3736 and CIR307 on D1 were associated with FS and NB, JESPR101 and NAU3700 on D3 were associated with FM (S3 Fig.). These nearby markers might associate with the same QTL allele with a high probability.
Comparing the results derived from different populations or using different analytical approaches for cotton QTL detection provides more information for interpreting the results of the present study. Among all 46 markers associated with yield and fiber quality traits, 14 markers associated with the same traits were identified in previous studies (Table 5). Thirteen markers were detected through linkage analysis, and three markers were detected via association analysis. When we employed the reference map as a bridge to compare the results of the present study with those from previous studies, the 9 associated markers identified were near the QTL-linked/associated markers controlling the same traits identified in other reports, at distances of less than 1-2 LD decay on the reference map (Table 6). Considering the different markers used in the prior studies and the precision of QTL detection, these nearby marker pairs should be linked to the same QTLs reported.
MLM analysis generates more accurate correlations with less-inflated type I errors. However, significant MLM-derived associations are subjected to multiple testing corrections. The results of correction for multiple testing could be misleading due to the unknown influence of pvalue adjustment methods applied under the MLM approach [17]. Perhaps a modified statistical approach should be applied to adjust MLM p-values, though answering this question will require further studies [17]. In the present study, to maintain low false positive results, we employed four environmental datasets and four different significance tests (p-value, BFmin, FDR and permutation testing). Although most of the associated markers did not tolerate multiple testing for the FDR, the results of the present study obtained using the MLM method were supported by the BFmin, FDR and permutation testing from the GLM analysis as well as the findings of previous studies. These results exhibited a relatively high confidence level and can be considered for use in MAS programs.
To date, few SSR markers have been efficiently employed in MAS programs in cotton because the majority of available marker information was derived from populations resulting from bi-parental crosses with limited genetic backgrounds, covering only a few meiotic events since experimental hybridization [17]. Recent association mapping of Upland cotton collections confirmed the feasibility of applying association analysis to explore complex traits in Upland cotton collections and provided useful markers for marker-assisted breeding programs [18][19][20][21][22]. Similar to linkage mapping, association mapping using different materials harboring different genes and different markers can provide more information for marker-assisted breeding programs as well as insight into the genetic basis of interesting traits in Upland cotton. The results of the present study provided new useful markers for marker-assisted selection in cotton breeding programs and clues for the fine mapping of yield and fiber quality traits. These results will also enhance our current understanding of the genetic basis of Upland cotton yield and fiber quality traits at the whole-genome level. | v3-fos |
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} | s2 | Production of bio-ethanol from molasses by Schizosaccharomyces species.
Aims: The aims of this study were isolation of Schizosaccharomyces species and production of bio-ethanol from local sugarcane molasses. Study Design: The study was designated as an experimental study. Place and Duration of Study: This study was conducted at the Department of Microbiology and Molecular Biology, Faculty of Science and Technology, Al-Neelain University, Khartoum – Sudan “1 st February to 30 th May 2014”. Methodology: Schizosaccharomyces species were isolated from three different sources (Lentils, Banana and Sorghum Fermented dough) using poured plate technique consisting Yeast Extract Agar (YEA) medium. Physical and microbiological analyses were carried out for molasses samples. Raw Molasses (RM) in range of 100-500 ml and Sucrose-determined molasses in range of 10-50% sucrose were fermented using three isolates for each concentration separately. The bio-ethanol was determined and evaluated. Original Research Article Bakhiet and Mahmoud; ARRB, 7(1): 45-53, 2015; Article no.ARRB.2015.104 46 Results: The moisture content of molasses was found to be 65%. The ash was 6.50%. The pH value was decreased by one unit during the fermentation processes due to the molasses degradation with acid production. Bio-ethanol was produced from two types of molasses preparations (raw molasses and sucrose determined concentration samples). Schizosaccharomyces spp. fermented molasses samples at all concentrations except 100% because the solution was hypertonic and the microorganisms did not tolerate that concentration. The highest volume of ethanol obtained at concentration of 3:300 ml of molasses/row. While the lowest one obtained at concentration of 4:10% of sucrose / row. The final bio-ethanol was appeared to be colourless, clear, bright, and free from turbidity indicating its high specification quality. Conclusion: The best conditions to obtain a highest volume of bio-ethanol are appropriate concentrations of molasses and suitable pH. The highest volume of bio-ethanol was 23.51 ml which obtained at 85.5 g/solids (molasses) and pH 6. While highest volume of bio-ethanol is sucrosedetermined concentration sample was 16.03 ml at 71.25 g/solids and pH 6. We recommended the utilization of Schizosaccharomyces species in large scale production of ethanol to manage the industrial wastes.
INTRODUCTION
Sugarcane molasses is a viscous, dark and sugar-rich by-product of sugar extraction from the sugarcane (Saccharum officinarum L.) [1]. It contains about 62% of carbohydrates in the form of 30% un-crystallized sucrose and about 32% of invert sugar which is a mixture of glucose and fructose [2].
The sugar, which is converted into molasses, is adjusted to 14-16%, which permits an alcohol content of 8 -10 volume percentage in the fermented worts [2].
The term 'molasses' is applied to the final effluent obtained in the preparation of sugar by repeated crystallization. The amount of molasses obtained and its quality (composition) provide information about the nature of the beets (local conditions of growth and effects of the weather) and the processing in the sugar factory, such as the efficiency of the juice clarification, the method of crystallization during boiling, and the separation of the sugar crystals from the lowgrade massecuite [3].
In white sugar factories the yield of molasses is in the neighbourhood of 4% on beets, corresponding to up to 25% on sugar. With average sugar content in the beets of 16-18% only 13 to 14% of the sugar will be recovered as a commercial product. As an average, 2.2-2.6% sugar on beets will go into the molasses when raw sugar is produced. The yield of molasses is affected by various factors and differs from batch to batch [3].
Sugarcane molasses has several important roles in livestock feeding, due to the nutritive, appetizing and physical properties of its sugar content. Molasses is rather difficult to handle because of its viscosity: it is rarely fed directly in its liquid form but instead mixed to other ingredients [1].
Sugarcane molasses are also used for alcohol (rhum or fuel ethanol) production and the distillery process yields vinasses that can also be used in animal feeding [4].
Ethanol known as ethyl alcohol or grain alcohol is a flammable, colourless, mildly toxic chemical compound with a distinctive perfume-like odour and the ethanol is found in alcoholic beverages. In common usage, it is often referred to simply as alcohol [5].
Traditionally ethanol is produced from cane molasses by fermentation with yeasts. Due to product inhibition ethanol concentration is usually limited to 8-9% by volume [2].
Ethanol fermentation is a continuous process, the molasses flow in and fermented wash flows out of the fermentor. The concentration of yeast cell cycle can be segregated in different fermentors for the yeast cell growth and carbon dioxide evolved. The process is continued and yeast cells remain in suspension. Finally the yeast cells are removed and clear wash is taken for distillation. The yeast strains normally employed in industrial process show a limited tolerance to ethanol, temperature and high osmotic pressure of the medium [6].
Fermentation of sugar-based raw materials is referred to as "first generation" use of lignocelluloses raw materials is commonly called "second generation" bio-ethanol. The "third generation" of algal bio-ethanol is at an early stage of investigation [7].
Microorganisms play an important role in biotransformation of waste products into human, animal and plant consumables. Yeast cells are used in household fermentation, food production, industrial fermentation and biotransformation process. Fermentation of sugars by yeast is the oldest and largest application of this technology, it process involves conversion of sugars to alcohol and carbon dioxide by the yeasts Schizosaccharomyces and Saccharomyces [8].
Schizosaccharomyces pombe, also called "Fission Yeast", is a species of yeast. It is used as a model organism in molecular and cells biology. It is a unicellular eukaryote, whose cells are rod-shaped. Cells typically measure 3 to 4 micrometers in diameter and 7 to 14 micrometers in length [6].
Schizosaccharomyces pombe is usually found in sugar-containing fermentations of alcohol from the subtropical regions [9].
Even though its origin dates back to quite a long time ago, it was not widely known before the 1890's. It was discovered in 1893 when a group working in a Brewery Association Laboratory in Germany was looking at sediment found in millet beer imported from East Africa that gave it an unsavory acidic taste [9]. P. Lindner was the first to describe Schizosaccharomyces pombe. He chose as its epithet the Swahili word for beer, pombe. It was identified as yeast, and it became known as the fission yeast because it reproduces by means of fission unlike its relative Saccharomyces cerevisiae. The name Schizosaccharomyces was assigned to it because Schizo-means "different," which had been previously used to describe other fission species [9].
The sequencing of its genome was significant since S. pombe is a single-celled living archiascomycete fungus that shares many features with cells of more complicated eukaryotes [10]. Researchers have identified fifty genes of S. pombe associated with human diseases including cystic fibrosis, hereditary deafness, and diabetes [10]. Researchers state that the largest groups of human disease-related genes are those implicated in cancer. There are 23 such genes, and they are involved in DNA damage and repair, checkpoint controls, and the cell cycle. All these processes are involved with maintaining genomic stability [10]. These discoveries are important because it will allow researchers to find out more about the evolution of one-celled and multi-celled eukaryotic organisms compared to others such as bacteria, which do not have nucleated cells. Further analyses and comparisons should reveal which genes define eukaryotic cells and the transition from one-celled to multi-celled organisms [10].
Schizosaccharomyces
pombe is a chemoorganotroph, so it uses organic compounds as a source of energy and does not require light to grow. These fission yeasts can grow under both aerobic and anaerobic conditions. Fission yeasts are facultatively fermentative and exhibits aerobic fermentation in the presence of excess sugar [11]. Alcohol dehydrogenase (ADH) catalyzes the reduction of acetaldehyde to ethanol in the last step of alcohol fermentation. This reduction is coupled with the oxidation of NADH and provides the NAD+ essential for the glyceraldehyde-3phosphate oxidation in glycolysis. Therefore, ethanol production is important to maintain the redox balance in the cytoplasm [11]. For a while, it has been widely assumed that S. pombe does not contain a mitochondrial ADH isoenzyme, and therefore does not have ethanol-dependent respiratory activity in the mitochondria [12]. Ethanol-dependent respiratory activity is generally attributed to the presence of mitochondrial ADH isoenzymes. However, it was shown recently using genetic knockout strains that S. pombe does exhibit mitochondrial ADH activity, but the physiological function of yeast mitochondrial ADH enzymes is unclear [12].
Schizosaccharomyces pombe has evolved as a natural inositol auxotroph. Inositol is essential for the growth of all eukaryotic cells because it is a precursor of a major membrane phospholipid, sphingolipids, and glycosylphosphatidyl-inositol. These phosphorylated metabolites of inositol play an important role in the signal transduction pathways [9]. It was discovered that S. pombe might have evolved as a natural inositol auxotroph because the natural environment of S. pombe contains a significant amount of phytic acid, which can be utilized as a source of inositol under very specific conditions. However, more research needs to be done in this area [9].
Isolates of S. pombe, T. delbrueckki, and Z. bailii exhibit tolerance up to 60% glucose concentration and are commonly associated with alcoholic fermentation for wine and champagne production. As the fermentation progressed, species with low acid tolerance decreased in population [13]. Species such as S. pombe, with moderate tolerance to acidic conditions, die off after day 10. In general, Kombucha fermentation is initiated by osmo-tolerant species of yeast, which are capable of growing in the presence of high concentrations of sugar. The process is then succeeded and ultimately dominated by acidtolerant species [13].
The fission yeast Schizosaccaromyces pombe is a harmless, rapidly growing eukaryote. Therefore, there are no pathologies associated with this particular organism [9].
The main objective of the current study is to produce bio-ethanol from molasses using the fission yeast (Schizosaccharomyces) and detect and determine the bio-ethanol.
Collection of Samples
Forty litres of sugarcane molasses sample were obtained from the Distillery Unit of Kennan Sugars (D.U.K.S) Company-White Province -Sudan. The sugarcane molasses were collected in clean, durable plastic container and stored at room temperature for further uses.
The banana, lentils and sorghum fermented dough which used to isolate yeast were collected form Sudanese local markets for formers and home for later. These sources were very cheap in Sudan, spoiled mainly by yeast and known as the main habitat of Schizosaccharomyces.
Isolation of Schizosaccharomyces
The samples were labelled alphabetically (A= Lentils, B= Banana, and C=Sorghum Fermented Dough). The lentils and banana samples were swabbed using sterile cotton swab, while a loop full of fermented dough was taken. All the samples were inoculated onto three sterile plates containing Yeast Extract Agar (yeast extract 6.5 g/l, glucose 20 g/l, peptone 10 g/l, agar 15 g/l supplemented by 0.3 g Chloramphenicol Sodium Succinate (BP)) for each one labelled digitally and alphabetically (A 1 , A 2 , A 3 , B 1 , B 2 , B 3 , C 1 , C 2 , and C 3 ) then incubated at 36ºC for 48 hours [14].
Subsequently plates were examined for yeast growth. The culture characteristics were observed and Gram stain method. The microorganisms were examined microscopically using (Olympus CX21FS1, binocular compound microscope) to verify the results [15].
Physical characteristics of the molasses sample
The physical characteristics of sugar cane molasses such as moisture content, ash measurement and pH were analyzed following standard methods [16].
Moisture content and ash measurement
The moisture content and ash measurement of molasses was performed by taken 10 grams of molasses sample and oven dried in a crucible at 104ºC for 30 minutes [3]. Then the results were calculated using the following equations:
Ash (unit) = Weight of molasses before burning (A) -Weight of molasses after burning (X) (2)
Were A is the weight of molasses before burning. While X is the weight of molasses after.
The pH value
The pH value was measured before and after inoculation of molasses samples using pH meter device (pH 213 Microprocessor-based Bench pH/mV/C Meters. HANNAINSTRUMENTS).
Identification of the Microorganisms Originally Present in Molasses
Serial dilutions were obtained by taking one ml of molasses into sterile test tube and diluted by adding 9 ml of previously sterilized distilled water. This step was repeated 10 times to obtain one 10 th of the previous dilution every time. From these serial dilutions the 4 th dilution containing 1/1000 parts of molasses was used for culturing fungi on Sabouraud's Dextrose Agar and incubated at 28ºC for 5 days. Bacteria was cultured from the 6 th dilution containing 1/100000 parts of molasses on Nutrient Agar and incubated at 37ºC for 24 hours. All microorganisms were identified microscopically by Gram stain for bacterial cell and Lactophenol cotton blue stain for fungal cells [3,15].
Inoculation of Molasses by Isolated Yeast
The molasses samples were prepared as raw material and sucrose determined samples were autoclaved at 121ºC for 10 minutes. The raw samples were placed into 15 flasks each three flasks contain equal volume of molasses supplemented with 0.5 g urea as nitrogen source (1:500 ml of molasses/row, 2:400 ml of molasses /row, 3: 300 ml of molasses /row, 4:200 ml of molasses /row and 5:100 ml of molasses / row). Also the sucrose determined samples were placed into 15 flasks (1:50% of sucrose / row, 2:35% of sucrose / row, 3: 25% of sucrose / row, and 4:10% of sucrose / row). All flasks' volume was completed to 500 ml using sterile distilled water. Each flask was inoculated with 10 ml (10 7 -10 8 CFU/ml) of 24 hours microbial suspension and incubated at 33ºC for 5 days [17].
Distillation and Detection of Ethanol
After incubation period, the flasks were distilled using sample distillation method at 78ºC for 3 hours [18]. The distilled volume was detected chemically using K 2 Cr 2 O 7 H + , KMnO 4 H + and iodine with NaOH. Two millilitres of distilled molasses were taken into two test tubes labelled T 1 and T 2 and 1 ml of K 2 Cr 2 O 7 H + and KMnO 4 H + , was added to each tube respectively. While 1ml of distilled molasses was taken in other test tube labelled T 3 , 3 ml of iodine were added followed by 3 drops of NaOH. The tube was heated and then cooled using tap water and the white precipitate was observed [19].
Isolation of Schizosaccharomyces Species
The culture characteristics of Schizosaccharomyces species was appeared as white coloured, semi mucoid, round shaped colonies.
While microscopically, the microorganism was appeared as Gram positive, rod-shaped, thick cell wall, purple colour colonies, some appeared as long rod, thin, purple colour contained true mycelium (Hyphae) Figs. 1 and 2. These findings were in agreement with the literature data reported by Mandeep and Kocher [6].
Physical Characteristics of the Molasses Sample
The physical characteristics of sugarcane molasses were determined and calculated. The present study exhibits that the percentage moisture content was 65%. The ash was calculated as 6.50%. While the pH shown 7, 0±0.2. These findings were in disagreement with the findings of Gasmalla et al. [20] who reported that the pH value of obtained molasses was 5.8±0.35. The ash was 12.69% on wet weight basis. Also these findings were in disagreement with the findings of Osunkoya and Okwudinka [21] who reported that the pH value of obtained molasses was 5.1. The ash was 8.24%.
Microorganisms Originally Present in Molasses
As can be seen in Table 1, the total bacterial and fungal counts were estimated. These findings were in disagreement with the findings of Gasmalla et al. [20] who reported that the total viable count in dilution of 10 1 was 3 X 10 2 and the yeasts and moulds count was 2 X 10 2 .
Production of Ethanol from Raw Molasses
As can be seen in Table 2, all isolated Schizosaccharomyces species (A, B, and C) not produced ethanol at concentrated molasses (100%) in the first row (500 ml molasses). The production of ethanol started at 80% in the second row (400 ml molasses + 100 ml distilled water) resulting in 13.68 ml of ethanol for the samples A and C, while sample B resulted in 12.54 ml of ethanol. At the concentration of 60%in the third row (300 ml molasses + 200 ml distilled water) the three isolates produced almost resemble volume of the ethanol; sample A produced 23.34 ml of ethanol while samples B and C produced 23.51 ml. These findings were highest than that reported by Choi et al. [18]. After distillation, the volume of ethanol produced was 23.51 ml per 85.5 g of molasses. These results were in disagreement with the findings ofGasmalla et al. [20] who reported that after distillation, the volume of ethanol produced was 20 ml per 100 g of molasses. These conditions were considered suitable for yeast activity and high yield of alcohol.
At 40% in the fourth row (200 ml molasses + 300 ml distilled water) all isolates produced similar volumes of ethanol (19.09 ml). The highest production of ethanol was observed at the concentration of 20% in the last row (100 ml molasses + 400 ml distilled water) and the isolates exhibited varies volume as 15.33 ml for isolate A, 11.40 ml for isolate B, and 10.68 ml for isolate C. These findings were higher than that found by Hafiz et al. [22] who reported that in 400 ml molasses mash supplemented with 0.15, 0.25 and 0.50% urea found that ethanol yields were 3.8, 4.3 and 4.2 using Saccharomyces and Schizosaccharomyses. Also the present study in disagreement with the literature data reported by Choi et al. [18] using of ethanol-producing yeast strain CHFY0201 isolated from soil in South Korea using an enrichment technique in a yeast peptone dextrose medium at 30ºC during shaking flask cultivation was 0.59±0.01 g/l/h. S. pombe CHFY0201 yielded a final ethanol concentration of 72.1 +/-0.27 g/l and a theoretical yield of 82.7 +/-1.52% at a maximum ethanol productivity of 1.16 +/-0.07 g/l/h. Also the present study in agreement with findings of Choi et al. [18] who reported that S. pombe CHFY0201 is a potential producer for industrial bio-ethanol production.
The pH of molasses was decreased through the fermentation period by 1 unit due to the accumulation of acids. These results were in disagreement with literature data [19].
Production of Ethanol from Molasses with Different Concentrations of Sucrose
The concentration of sucrose in molasses was measured using refractometer device.
As can be seen in Table 3, the isolated Schizosaccharomyces species (A, B, and C) started the production of ethanol at 50% of molassesin the first row resulting in 16.03 ml of ethanol for the samples A and C, while sample B resulted 15.68 ml of ethanol. At the concentration of 35% in the second row the three isolates shown variable manner of ethanol production. Sample A produced 11.22 ml of ethanol while sample B produced 9.89 ml and sample C produced 12.47 ml. These results were lower than that produced at the first row (50%). At the concentration of 25% in the third row all isolates produced similar volumes of ethanol (10.69 ml). The lowest production of ethanol was observed at the concentration of 10% in the last row and the isolates exhibited varies volume as 5.34 ml for isolate A, 4.99 ml for isolate B, and 3.92ml for isolate C. The present results were in disagreement with the findings of Gasmalla et al. [20] who reported that the ethanol yield in 10% and 25% sugar concentration were 5.5 and 10.3 respectively. While the yield was 11.04 in 20% sugar concentration which is almost similar to the present study at the concentration of 35%.
Hemamalini et al. [2] reported that the yeasts Saccharomyces cervisiae Schizosaccharomyces pombe were used as free cells in continuous ethanol fermentation ethanol yield was noted as 5.25% and 7.20% respectively.
These findings were in disagreement with the present study.
The pH of molasses was decreased through the fermentation period by 1 unit. These results were in disagreement with the findings study achieved by Mandeep and Kocher in an agreement with the findings of previous study accomplished by James [17]. [2] reported that the Saccharomyces cervisiae and were used as free cells in continuous ethanol fermentation and the ethanol yield was noted as 5.25% and 7.20% respectively.
These findings were in disagreement with the present study.
The pH of molasses was decreased through the fermentation period by 1 unit. These results were in disagreement with the findings of previous Mandeep and Kocher [6] and in an agreement with the findings of previous before addition of sample (a), to colourless after addition of sample (b)
Detection of Ethanol
The presence of ethanol was indicated by change in sample's colour when subjected to different chemical reagents. In the first test using KMnO 4 H + purple colour of KMnO reduced to colourless solution figure 3 second test and after addition of K yellow colour of K 2 Cr 2 O 7 H + changed to green colour Fig. 4. In the third confirmatory test, by using heated iodine followed by cooling and adding of NaOH the yellow colour precipitate called iodo-form was observed results were in agreement with Caldwell [1] and Rachel [8]. The presence of ethanol was indicated by change in sample's colour when subjected to different chemical reagents. In the first test when purple colour of KMnO 4 H + reduced to colourless solution figure 3. In the and after addition of K 2 Cr 2 O 7 H + the changed to green In the third confirmatory test, by using heated iodine followed by cooling and llow colour precipitate
CONCLUSION
Experimental results of producing ethanol from molasses showed that high yield of alcohol (23.51 ml) was obtained especially when the raw molasses of 85.5 g/solids and the pH were 6-5and 33ºC, ethanol in fermented mash; also it could be deducted that Schizosaccharomyces species can be used as alternative to Saccharomyces cereveisiae to produce high quality ethanol from high sugar concentration. To obtain ethanol in large-scale production, it is highly recommended to control the fermentation and distillation processes using yeast strains of Schizosaccharomyces species which have high ability to tolerate high sugar concentration and ethanol concentration too. | v3-fos |
2016-05-12T22:15:10.714Z | {
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} | s2 | Biological Activity and Phytochemical Study of Scutellaria platystegia.
This study aimed to determine biological activity and phytochemical study of Scutellaria platystegia (family Labiatae). Methanolic (MeOH) extract of aerial parts of S. platystegia and SPE fractions of methanolic extract (specially 20% and 40% methanolic fractions), growing in East-Azarbaijan province of Iran were found to have radical scavenging activity by DPPH (2, 2-diphenyl -1- pycryl hydrazyl) assay. Dichloromethane (DCM) extract of this plant exhibited animalarial activity by cell free method providing IC50 at 1.1876 mg/mL. Crude extracts did not exhibit any toxicity assessed by brine shrimp lethality assay. Phytochemical study of methanolic extract by using reverse phase HPLC method and NMR instrument for isolation and identification of pure compounds respectively, yielded 2-(4- hydroxy phenyl) ethyl-O-β-D- glucopyranoside from 10% and apigenin 7-O-glucoside, verbascoside and martynoside from 40% SPE fraction. Occurance of verbascoside and martynoside as biochemical markers appeared to be widespread in this genus. Antioxidant and antimalarial activity of MeOH and DCM extracts, respectively, as well as no general toxicity of them could provide a basis for further in-vitro and in-vivo studies and clinical trials to develop new therapeutical alternatives.
Introduction
Scutellaria which belongs to Labiatae family, spread throughout the world, with approximately 350 currently recognized species (1)(2). Plants of this genus have been traditionally used in China, Korea, and Japan as an agent for activating blood circulation, inducing diuresis and reducing oedema. Some other applications of these plants in folk medicine are due to their anti-inflammatory, antiviral, sedative and antioxidant effects (3). Modern pharmacologic researches on crude extracts and isolated compounds of the plants of this genus, confirmed multiple biological activities, including anticonvulsant (2, 4), prolyl oligopeptidase inhibitory, hepatoprotective (3, 5), memory improvement (6-7) effects. In some in-vitro methods, phytochemicals of some species of Scutellaria, exhibited potent cytotoxic effects on some of the human tumour cell lines (8-10). Flavonoids (3,(11)(12) and neoclerodan diterpenoids (1,(13)(14) as well as iridoids (3,15), phenyl alcohol glycosides and alkaloids (3, 16) have been isolated from several species of Scutellaria. Due to Remarkable and diverse biological activities of other species of scutellaria genus, this study aimed to evaluate biological activity and identify chemical composition of this plant. To our knowledge there have been no reports on biological activities and chemical composition of S. platystegia.
Antimalaria assay
The antimalaria potential of extracts was determined using cell free method which was described by Fitch et al. (19) with some modifications (20). Different concentrations of the n-hexan, DCM and methanolic extracts ranging from 0-2 mg/mL in 10% DMSO, were incubated in 300 µL of haematin which was freshly dissolved in 0.1 M NaOH, 10 mM oleic acid and 10 µM HCl. Afterwards 500 mM sodium acetate buffer, pH 5, was added to test tubes for adjusting reaction volume to 1000 µL. Positive control was chloroquine diphosphate in this test. The samples were incubated overnight at 37 ºC with regular shaking. After incubation, samples were centrifuged at 14,000 × g, for 10 min, at 21 °C and the hemozoin pellet repeatedly washed with sonication (30 min, at 21 °C; FS100 bath sonicator; Decon Ultrasonics Ltd.) in 2.5% (w/v) SDS in phosphate buffered saline followed by a final wash in 0.1 M sodium bicarbonate, pH 9.0, until the supernatant became clear which usually happens after 3-5 washes. After the final wash, the supernatant was removed and the pellets were re-suspended in 1 mL of 0.1 M NaOH before determining the hemozoin content by measuring the absorbance at 400 nm (Beckmann DU640 spectrophotometer). Results were recorded as IC%, which is inhibition of heme crystallization compared to chloroquine as positive control, using the following formula: IC% = [(AB-AA)/AB] × 100, where AB and AA are absorbance of blank and test samples respectively. Final results which mean inhibition of hemezoin polymerization have been shown as IC50.
Brine shrimp lethality assay
This test is proposed as a preliminary and simple assay to study general toxicity of plant extracts. The eggs of Artemia salina purchased from Water Life, Middlesex, UK, were hatched in a flask containing 300 mL of artificial sea water aerated by the aid of an air pump. The flasks were kept in a 29-30 ºC water bath and a bright light was left on. Afterwards, nauplii were hatched after 48 h. 1 mg/mL of n-hexan, DCM, MeOH were prepared by dissolving them in 5% DMSO. These solutions were serially diluted to obtain 7 concentrations, by the aid of aerated sea
Plant material
Aerial parts of Scutellaria platystegia (family Labiatae) were gathered from Yam region of East Azarbaijan province of Iran in June 2009. A voucher specimen (Tbz-Fph-724) for this collection has been deposited in the Herbarium of pharmacy faculty, Tabriz University of Medical Sciences, Tabriz, Iran. 100 g of the air dried and grounded sample was extracted by the aid of Soxhlet apparatus using hexane, dichloromethane (DCM) and methanol (MeOH) respectively (1 L for each solvent). Obtained extracts were individually concentrated under vacuum in a rotary evaporator (Heidolph, Germany), yielding 1.67 g, 1.50 g and 24.50 g respectively.
DPPH assay Antioxidant activity of extracts and different SPE fractions was performed using DPPH assay. The basis of this experiment was Bleaching of purple coloured methanolic solution of 2, 2-diphenyl -1-pycryl hydrazyl (DPPH) (sigma). In order to obtain antioxidant activity, different sample solution series were prepared. 5 mL of each concentration of methanolic extract and SPE fractions were added to 5 mL of 0.004% methanolic solution of DPPH. After 30 min incubation of solutions at room temperature and bleaching of DPPH, absorption of samples was monitored at 517 nm against a blank. Inhibition of DPPH was calculated as RC 50 that was extrapolated from dose-response curve. Tests were carried out in duplicate (17-18).
water this experiment was carried out for twice. About ten nauplii were transferred in to each test tube. The number of alive nauplii were counted after 24 h. The control test tubes contained 5% DMSO, saline and podophyllotoxin (21-23).
Isolation of compounds
Preparative reversed phase HPLC with photodiode array detector was used for isolation of phytochemicals from 20 and 40% SPE fractions. Each fraction was analysed repeatedly by preparative reverse phase HPLC (Knauer, preparative pump 1800), equipped with a Reprosil 100 C18 (250 mm length, 20 mm i.d, particle size 10 µm, Dr. Maisch, Germany) column. The mobile phase consisted of (A) methanol and (B) water. The following mobile phase program was used over 60 min to isolate glycosylated phenylethanoid (Figure 1) from the 10% SPE fraction: A initially changed to 10% in 15 min. then it changed to 20% in 50 min, maintained there for 10 min. A program over a run time of 50 min was applied for separation of 7-glucoapigenin (Figure 2), verbascoside ( Figure 3) and martynoside (Figure 4) from the 40% SPE fraction: 17% A initially changed to 28% in 40 min. Then, it stayed there for 10 min. Photodiode Array Detector (PDA) was used to monitor the chromatogram, and the HPLC separation was carried out at room temperature. The flow rate was 8 mL/min and the injection volume was 1 mL. Structures of compounds were determined by H and C NMR (Brukerspectrospin at 200MHz) as well as comparison with the literature data of respective compounds.
DPPH assay was performed to determine
Radical scavenging activity of extracts and SPE fractions of this plant. As it can be seen in Table 1, methanolic extract showed better antioxidant activity than other crude extracts. Table 2 demonstrated that among SPE fractions, 20% and 40% hydroalcoholic fractions were more potent antioxidants. Results of antimalarial activity of this plant, which was determined by cell free method, exhibited in Table 3. DCM crude extract, providing IC50 at 1.1876 mg/mL showed potential of antimalarial activity.
Observation of radical scavenging activity from methanolic extract and SPE fractions encouraged us to study this plant phytochemically. Reverse-phase prep-HPLC analysis of SPE fractions of methanolic extract of aerial parts of S. platystegia (Labiatae) yielded 2-(4-hydroxy phenyl) ethyl-O-β-D-glucopyranoside from 10% ,one flavonoid (Apigenin 7-O-glucoside) and 2 phenyl ethanoid glycosides (verbascoside and martynoside) from 40% SPE fractions. In fact compounds 1-4 have been identified previously from other species of this genus (26-34), whereas this is the first report of these phytochemicals from S. platystegia. Distribution of compounds 1-4 has been demonstrated in Table 4.
Discussion
Recently, phytochemicals as bioactive components of plant extracts has received considerable attention. Antioxidants, the agents against oxidative stress-mediated disorders, with free radical scavenging activity, can prevent damages caused by various disorders (35-38). Antioxidant capacity of phenolic compounds isolated from plants (39-42) and Correlation of phenol content and antioxidant activity has been shown in different studies as well (43-44). According to some evidences, flavonoids and phenylethanoids as plant derived polyphenolic compounds act as free radical acceptors, and potent antioxidants (45-49). Plants of Scutellaria genus, used in traditional medicine for thousands years, with variety of confirmed pharmacological effects in modern researches, has been shown free radical scavenging and antioxidant activities due to existence of different phenolic compounds such as flavonoids and phenylethanoids (50-57). Results of this study demonstrated that verbascoside, martynoside and apigenin as antioxidant compounds (45,(58)(59)(60)(61)(62), which existed in methanolic extract and isolated from 40% fraction were responsible for good radical scavenging activity of this methanolic fraction (0.0342 mg/mL). Further investigations will reveal other phytochemicals responsible for radical scavenging activity of 20% and 60% fractions. Identification of apigenin, martynoside and verbascoside as anti-inflammatory and antioxidant constituents from methanolic extract, is in agreement with traditional usage of this plant as an antiinflammatory agent (63-66) and confirm its use in folk medicine.
Malaria, a malignancy with worldwide spread, results in loss of lives each year. Resistance of deadly forms of malaria parasites to anti-malarial drugs highlights needs for new antimalarial drugs (67). Anti-fever herbal plants used in traditional medicine might contain some antimalarial phytochemicals which could lead to development of new drugs for treatment of this mortal malignancy (68). Diverse nature of Iran possesses medicinal plants which could be alternative choice for treatment of malaria. In previous works, traditionally used febrifuge plants to treat fever as a symptom of malaria, have been selected for antimalarial studies (69-71). Since several species of Scutellaria have been used as febrifuge in folk medicine, extracts of S. platystegia were subjected to in-vitro antimalarial test (57, 72-73) and interestingly DCM extract of this plant demonstrated antimalarial activity. Further investigations are needed to identify and purify compounds responsible for antimalarial activity of this plant.
Brine shrimp lethality assay, a suitable, simple, rapid procedure with low cost (74-75), was chosen to determine general toxicity of plant extracts. None of the plant extracts exhibited any toxicity at highest test concentrations (1 mg/mL).
Biological activity of methanolic extract conducted us to phytochemical study of this plant. 2-(4-hydroxy phenyl) ethyl-O-β-Dglucopyranoside (from 10% SPE fraction), Apigenin-7-O-glucoside, verbascoside and martynoside (from 40% SPE fraction) were isolated and identified by UV and NMR analysis. All spectroscopic data were in agreement with respective published data. Identified components have been reported from other species of Scutellaria genus, while distribution of verbascoside and martynoside appears to be widespread (Table 4). So, it is concluded that these two phytochemicals could be determined as chemical biomarkers in this genus. To our knowledge, this is the first report on the antioxidant and antimalarial activity as well as occurrence of compounds 1-4 within this species.
Conclusion
It can be concluded that antioxidant and antimalarial activity of MeOH and DCM extracts, respectively, as well as no general toxicity of them, could provide a basis for further in-vitro and in-vivo studies and clinical trials to develop new therapeutical alternatives. More over the results of present study show that it is worth to do further phytochemical studies on Iranian Scutellaria species and to isolate compounds responsible for antioxidant and antimalarial activities. | v3-fos |
2019-04-25T13:05:26.964Z | {
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} | s2 | The Influence of Geomorphology on the Sensorial Quality of Red Wines from the Șarba wine region, Odobești Vineyard
. This study aims at making a sensorial analysis of red wines from the Șarba wine region, Odobești Vineyard. In order to determine wines from a sensory point of view, we first studied the influence of geomorphology on the sensory character. In the analysis of red wines sensorial quality we used several wines from 2012 (i.e. Pinot noir, Cabernet Sauvignon, Black Fetească and Merlot), as 2012 was a beneficial year from the point of view of red grapes ripening, and the oenoclimatic index was favourable to obtaining savoury and flavoured wines. The vegetal flavour does not affect the wines’ harmony too much.
INTRODUCTION
The Șarba wine region in the Odobeşti Vineyard is situated on the foothills of the Curvature Sub Carpathian region, that reach altitudes of 220 m. Due to the conditions of pedoclimate and soil, which is highly acidic, the wines obtained are appreciated as fresh and fruity. The lithological substratum is made of sands and alluvial-proluvial gravels, covered by loess deposits. The alternance of these strata form a detritus Pleistocene complex, comprising marine pliocenic marls, clays and sands (Chiriac, 2009). The soil is represented by leached chernozems (cambic and clay-illuviated), dominant in the Eastern and Central part of the wine region, and brown soils to the West. Through their medium and light texture, these soils ensure permeability (Chiriac, 2009). The area's geomorphologic and hydrographic ensemble allows for the existence of a great variety of grapevine varieties in the plantation (Gâștescu, 2010). Global solar radiation reaches annual averages over 125 Kcal/cm², varying between 110 Northern exposures and 140 on Southern exposures ( Figure 1). Average annual temperature is about 9-10ºC, thus a medium thermal amplitude; the most important values were calculated in 2012 (www.meteorologia.ro). The average annual duration of solar irradiance is about 2100 hours (Fig. 4). These high values also justify the annual amount of temperature that are lower than or equal to 0º C, around 3800º, which ensures for optimal ripening conditions and the concentration of sugars ad aromatic substances in grapes ( Figure 3).
The oenoclimatic aptitude index is the sum of the active heat balance and the total real hours of sunshine, from which we subtract the excess precipitations during the active life of vines. The resulting values are higher than 4150, reaching 4214 in 2012, a value that is specific to the area ( Figure 4).
MATERIALS AND METHODS
The materials used in the present study consisted of four red wines from 2012 which, compared to the other two years, was beneficial to red grape ripening and to obtaining harmonious wines. The taste of fruit is stronger in the case of Black Fetească and Merlot wines, being marked between 7.9 (Pinot noir and Cabernet Sauvignon) and 8.9 (Fetească neagră and Merlot). Black Fetească wines are very buttery, being marked between 7.9 (Merlot) and 9 (Fetească neagră). Cabernet sauvignon and Pinot noir wines recorded intermediary values; the average marks were 8.1 and 8.4 respectively. Cabernet Sauvignon wines are the most savoury; wines were marked between 5.8 (Fetească neagră) and 7.8 (Cabernet sauvignon). Pinot noir and Merlot wines recorded intermediary values; the average mark was 6.8. It is noted that Cabernet Sauvignon wines are the most harmonious; wines were marked between 5.9 (Pinot noir and Black Fetească) and 7.9 (Cabernet sauvignon and Merlot).
ILNS Volume 49
It is noted that the taste of caramel is more pronounced in the case of Fetească neagră wines; wines were marked between 1.4 (Pinot noir) and 4.4 (Black Fetească
CONCLUSIONS
Red wines of 2012 show intense olfactory notes, a full body and a bouquet specific to the variety. The most beneficial year for red grape ripening was 2012, as the oenoclimatic index was most beneficial to these varieties in order to obtain buttery wines, having berry, savoury and fruity flavors. Pedoclimatic indicators in the area resulted in harmonious wines, with notes of caramel and faint leathery notes. A faint vegetal flavour consistent with the geomorphological and hydrographic ensemble of the area is always present, but it does not affect the harmonious character of wines. | v3-fos |
2018-04-03T01:58:08.320Z | {
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} | s2 | Establishment of Hairy Root Cultures of Rhaponticum carthamoides (Willd.) Iljin for the Production of Biomass and Caffeic Acid Derivatives
The aim of the study was to obtain transformed roots of Rhaponticum carthamoides and evaluate their phytochemical profile. Hairy roots were induced from leaf explants by the transformation of Agrobacterium rhizogenes strains A4 and ATCC 15834. The best response (43%) was achieved by infection with A4 strain. The effects of different liquid media (WPM, B5, SH) with full and half-strength concentrations of macro- and micronutrients on biomass accumulation of the best grown hairy root line (RC3) at two different lighting conditions (light or dark) were investigated. The highest biomass (93 g L−1 of the fresh weight after 35 days) was obtained in WPM medium under periodic light. UPLC-PDA-ESI-MS3 and HPLC-PDA analyses of 80% aqueous methanol extracts from the obtained hairy roots revealed the presence of eleven caffeoylquinic acids and their derivatives and five flavonoid glycosides. The production of caffeoylquinic acids and their derivatives was elevated in hairy roots grown in the light. Only light-grown hairy roots demonstrated the capability for the biosynthesis of such flavonoid glycosides as quercetagetin, quercetin, luteolin, and patuletin hexosides. Chlorogenic acid, 3,5-di-O-caffeoylquinic acid and a tentatively identified tricaffeoylquinic acid derivative were detected as the major compounds present in the transformed roots.
Introduction
Rhaponticum carthamoides (Willd.) Iljin, a member of the Asteraceae family, is a perennial, herbaceous species naturally growing in the mountains of South Siberia, Middle Asia, and Mongolia. It is commonly known as "maral root" or Russian leuzea and has been used for centuries in traditional Siberian medicine as a stimulant, mostly in the case of overstrain and weakness after illness [1]. The root and rhizome extracts of R. carthamoides possess a wide range of biological activities, including adaptogenic, antioxidant, cardioprotective, immunomodulatory, antihyperlipidemic, antihyperglycemic, and antimicrobial effects [1]. These pharmacological properties are attributed to the presence of a variety of secondary metabolites including triterpenoids, polyacetylenes, sesquiterpene lactones, phenolic acids, flavonoids, and ecdysteroids with 20-hydroxyecdysone as the principal component [1].
The medicinal importance and endangered status of R. carthamoides, have resulted in its cultivation worldwide, including Central and Eastern Europe. However, 3-4 years are required to obtain plant roots with a satisfactory content of the pharmacologically active compounds by field cultivation. In addition, it is inefficient to harvest the roots from fieldgrown plants as these results in the loss of the mother plant. It would be desirable to develop an effective biotechnological method for the production of suitable plant material in a shorter time period, regardless of seasonal and climatic conditions. One approach could be the use of hairy root cultures transformed by Agrobacterium rhizogenes. This type of in vitro culture has gained considerable attention because of their fast growth in media without growth regulators, their genetic and biochemical stability and their ability to biosynthesise selected secondary metabolites at levels comparable to, or even higher than, those found in roots of intact plants [2,3]. A previous work [4] reports that transformed root cultures of R. carthamoides were found to be ineffective for ecdysone production, but no information is available regarding polyphenol accumulation and no optimization data is given for biomass production by the culture. The aim of this study was the establishment of hairy roots of R. carthamoides and the phytochemical profiling of their polyphenolic constituents. Two A. rhizogenes strains (A4 and ATCC 15834) and leaf explants were used for hairy root induction. The effect of different liquid nutrient media (WPM, B5, SH and 1/2 WPM, 1/2 B5, 1/2 SH) and culture conditions (light or dark) on hairy root growth, in terms of fresh and dry biomass accumulation, were also investigated. The incorporation of T-DNA genes into the plant genome was demonstrated by PCR analysis.
Furthermore, the hairy root cultures exhibiting the highest biomass productivity and roots of the soil-cultivated plants of R. carthamoides were characterized to their main phytochemical markers, including caffeoylquinic acids, flavonoid glycosides, and 20-hydroxyecdysone. The comprehensive qualitative and quantitative phytochemical profiling of the plant samples was performed by UPLC-PDA-ESI-MS 3 and HPLC-PDA methods. Two agropine-type strains of Agrobacterium rhizogenes (A4 and ATCC 15834) were used for hairy root induction. The bacteria were grown for 48 h on YEB solid (1.5%) medium [6], at 26 ∘ C in the dark.
Induction and Establishment of Hairy Root
Culture. The leaf explants were wounded with a sterile needle immersed in the bacterial culture. Inoculation was carried out in the middle part of the petiole or at the basal part of the leaf lamina. Control explants were wounded identically with sterile needle without bacteria. Infected and control explants were placed on hormone-free MS agar (0.7%) medium with or without acetosyringone (AcS) (200 M) and incubated in the dark for 5 weeks. The experiment was repeated three times; 25-35 explants were used for each treatment: type of bacterial strain/site of infection/medium with or without AcS.
Five weeks after initial inoculation, the transformation frequency (the percentage of explants forming roots after infection with A. rhizogenes with respect to total number of infected explants), the number of roots per responding explant, and the root length were determined (Table 1).
Liquid Culture of Hairy Roots.
Adventitious roots (1-2 cm long) (Figure 1(a)) were excised from explants and transferred individually into 100 mL Erlenmeyer flasks containing 20 mL half-strength Gamborg (1/2 B5) liquid medium [7] without growth regulators and supplemented with 500 mg L −1 ampicillin for the elimination of the bacteria. The cultures were maintained in the dark, on a rotary shaker at 80 rpm. After several subcultures of 7 days each, the concentration of ampicillin was reduced to 300 mg L −1 . After four successive subcultures, the antibiotic was eliminated from the medium and eight axenic root lines were obtained (RC1-RC8). Among them, line RC3, showed the fastest growth and produced more lateral roots than the other seven lines. Therefore, this line was chosen for further experiments.
Culture of R. carthamoides Hairy Roots in Different Media.
Six different liquid media were tested for their effect on root biomass production: Schenk and Hildebrandt (SH) [8], Woody Plant (WPM) [9], and Gamborg (B5) with full and half-strength macro-and microsalt concentration ( HPLC grade solvents, acetonitrile, orthophosphoric acid, and redistilled water were obtained from POCH (Poland) and Merck (Germany).
Extraction
Procedure. An accurately weighed sample of lyophilized and powdered plant material was first extracted with n-hexane. The samples were 600 mg for the 35-dayold hairy roots cultured in WPM medium in the light (HR-L) or in the dark (HR-D) and 300 mg for the roots of soilgrown 3-year-old plants (SR). After filtration, the n-hexane extract was discarded. The defatted sample was sonicated for 15 min with 80% (v/v) aqueous methanol (25 mL) at 35 ∘ C using an ultrasonic bath and then twice with 10 mL of the same solvent for 15 min. The combined extracts were diluted with methanol to 50 mL, filtered through a PTFE syringe filter (25 mm, 0.2 m, AlChem, Czech Republic) and the filtrate was directly injected into the HPLC or UPLC system. 3 Analysis. The UPLC-PDA-ESI-MS 3 analysis was performed using an UPLC-3000 RS system (Dionex, Germany) equipped with a dual lowpressure gradient pump, an autosampler, a column compartment, a diode array detector, and an AmaZon SL ion trap mass spectrometer with an ESI interface (Bruker Daltonik, Germany). The samples were separated on a Kinetex XB-C18 column (1.7 m, 150 × 2.1 mm i.d., Phenomenex, USA). The mobile phase consisted of solvent A (0.1% aqueous solution of formic acid, v/v) and solvent B (acetonitrile with 0.1% formic acid, v/v) with an elution profile as follows: 0−45 min 6−26% B (v/v), 45-55 min 26-95% B, 55-63 min 95% B, and 63-70 min 95-6% B. The flow rate was 0.3 mL min −1 , the column temperature was maintained at 25 ∘ C. The UV-Vis spectra were recorded over the range 200−600 nm, and chromatograms were acquired at 245, 325, and 350 nm. The LC eluate was introduced directly into the ESI interface without splitting. The nebulizer pressure was 40 psi; dry gas flow 9 L min −1 ; dry temperature 300 ∘ C; and capillary voltage 4.5 kV. The analysis was carried out using a scan from m/z 200 to 2200. The compounds were analyzed in a negative ion mode. with an elution profile as follows: 0-1 min 5% B (v/v), 1-16 min 5-30% B, 16-17 min 30-50%, 17-19 min 50% B, 19-20 min 50-5% B, and 20-25 min 5% B (equilibration). The flow rate was 1.4 mL min −1 and the column temperature was maintained at 30 ∘ C. The phenolic compounds were identified and classified into three groups based on their UV-Vis spectra, retention times, and the qualitative results obtained from UPLC-PDA-ESI-MS 3 (the accurate mass and the MS fragmentation patterns). The detection wavelength was set at 245 nm for 20-hydroxyecdysone, 325 nm for caffeic acid derivatives including caffeoylquinic acids, and 350 nm for the flavonoid glycosides. Four external standards were used for calibration including chlorogenic acid (CHA), cynarin (CA), 20-hydroxyecdysone (EC), and isoquercitrin (IQ). The calibration equations were constructed using seven concentration levels of each analyte within the range of approximately 2.4-240 g mL −1 for CHA, 1.0-100 g mL −1 for CA, 1.0-107 g mL −1 for EC, and 1.0-103 g mL −1 for IQ. The tentatively identified peaks were quantified as equivalents of the following standards: chlorogenic acid isomers as CHA, dicaffeoylquinic acid isomers, tricaffeoylquinic acid and its derivative as CA, 20-hydroxyecdysone as EC, and the flavonoid monoglycosides as IQ.
Statistical Analysis.
The statistics (calculation of RSD and SE, one-way analysis of variance, significance tests, and linearity studies) were performed using the software Statistica 10.0PL for Windows (StatSoft Inc., Poland).
Induction of Hairy
Roots. The first adventitious roots were visible 2-3 weeks after inoculation. No roots were observed in noninfected control explants. The highest frequency of hairy root induction was achieved on explants infected with strain A4 and cultured on MS medium supplemented with AcS. It was 43.3% when leaf explants were wounded at the lamina base and 37.3% after infection at the middle part of the petiole. The differences were not statistically significant ( ≥ 0.05) ( Table 1). It has been well documented that bacterial strains differ in their virulence and the choice of the appropriate strain is an important factor for successful transformation [10,11]. After infection with strain ATCC 15834, 18.3% of lamina and 22.7% of petiole explants responded by producing roots after 5 weeks of culture on MS medium containing AcS (200 M) ( Table 1). The site of infection also did not have any significant effect on frequency of hairy root induction.
Acetosyringone (AcS) has been reported to induce the expression of vir genes and thus affect Agrobacteriummediated transformation [12]. Therefore, it was added to R. carthamoides root induction medium at the concentration of 200 M, a concentration which was found to have a positive effect on the transformation frequency of Picrorhiza kurroa [13]. the number of explants producing roots, although the effect was not statistically significant at = 0.05 (Table 1). The relatively low differences in root formation between treatments given with and without AcS suggest that this compound is not a key factor in the transformation of R. carthamoides, which may be due to the high level of phenolic compounds present in the leaf explants.
Growth of Hairy Roots in Different Liquid
Media. The hairy roots (RC3 line) grown in full strength media possessed greater biomass than roots cultured in half-strength media (Figures 2(a) and 2(b)). This was similar to hairy root cultures of Levisticum officinale grown in B5 medium, which showed a greater increase in biomass (350 g L −1 FW and 10 g L −1 DW) than roots grown in 1/2 B5 medium (200 g L −1 FW and 7 g L −1 DW) [14]. In the present study, the highest accumulation of hairy root biomass was achieved in WPM medium with a full concentration of nutrients. After 35 days, the fresh weight of hairy roots was 93 g L −1 grown in photoperiod and 82.8 g L −1 for roots cultured in the dark (Figure 2(a)). The values for dry weights were 12.0 g L −1 and 7.5 g L −1 , respectively (Figure 2(b)). The roots were thin with an average root diameter of 0.5 mm and had long and numerous branches (Figure 1(b)). The WPM medium was also the best for the growth of transformed roots of other plant species like as Trigonella foenum-graecum [15] or Dracocephalum moldavica [16]. Of the tested media, SH, B5, and WPM with half-strength macro-and microsalt concentration were found to induce the lowest level of R. carthamoides root biomass in terms of both fresh and dry weights (Figures 2(a) and 2(b)). The transformed roots maintained in SH and B5 media with full and half-strength content of macro-and micronutrients were thick with an average root diameter of 0.9-1.5 mm and had short and small branches. Generally, exposure to light increased the growth of hairy roots of R. carthamoides, except for the roots cultured in SH and 1/2 SH media. In these media fresh weights of the roots grown under photoperiod were lower than those achieved under darkness. However, the differences were not statistically significant at = 0.05. The hairy roots were found to be stable in terms of increase in root biomass and their morphology. The physical culture conditions affected also the morphology of R. carthamoides hairy roots; that is, roots cultured in the photoperiod were green (Figure 1(b)). Greening was absent in the dark-grown roots which were beige. The previous report results showed that exposure of hairy root cultures to light can induce greening due to enhanced chlorophyll biosynthesis [17,18].
PCR Analysis.
The genetic transformation of the R. carthamoides hairy roots was confirmed by PCR. Using specific PCR primers four amplified bands of expected size 107 bp, 386 bp, 582 bp, and 500 bp corresponding to the rolA, rolB, rolC, and aux1 genes, respectively, appeared in the hairy root line RC3 ( Figure 3, lanes 8, 9, 10, and 13, resp.) but not in the nontransformed shoots used as a negative control. PCR analysis was carried out using primers specific to virG to confirm that hairy roots were not contaminated with A. rhizogenes (Figure 3, lane 12).
The results of the PCR analysis revealed the insertion of both T L -DNA (the presence of A, B, C rol gene fragments) and T R -DNA (the presence of the aux1 gene fragment) into the genome of R. carthamoides hairy roots. 3 . The UPLC-PDA-ESI-MS 3 studies of 80% aqueous Table 3). The detected compounds were identified by comparing their retention times, UV-Vis spectra, and fragmentation patterns in MS spectra with those of the reference compounds and the literature data [19][20][21][22]. The UPLC-PDA study showed that the caffeoylquinic acids and their derivatives constitute the major phenolic class occurring in both the hairy roots and the roots of soil-grown plants. These compounds (peaks 1-4 and 11-15 Their preliminary identification was facilitated by analysis of structure-diagnostic hierarchical keys proposed by Clifford et al. [19]. Compounds 1 and 2, exhibiting the MS 2 base ions at m/z 191 and the secondary ions at m/z 179 of the intensity of 43% and 4%, respectively, were identified as NCHA (neochlorogenic acid, 3-O-caffeoylquinic acid) and CHA (chlorogenic acid, 5-O-caffeoylquinic acid), respectively. The third isomer (compound 3), due to its MS 2 base ion observed at m/z 173, was assigned as CCHA (cryptochlorogenic acid, 4-O-caffeoylquinic acid). Finally, the unequivocal identification of compounds 1-3 was confirmed by comparison of their retention time and MS data with the commercially available standard of CHA as well as with the qualitative standards of NCHA and CCHA prepared in our laboratory according to Clifford et al. [23].
Identification of Polyphenols and 20-Hydroxyecdysone in Hairy Roots and Roots of Soil-Grown Plants by UPLC-PDA-ESI-MS
The further five compounds (4 and 11-14) ( Table 3), eluting after chlorogenic acid, were classified as dicaffeoylquinic acids, all of which exhibited the UV-Vis absorption maxima at 325 or 328 nm and whose deprotonated molecular ions were found at m/z 515. In the MS 2 spectra, these compounds gave base peaks at m/z 353 ([M-H-caffeoyl] − ) and the secondary ions at m/z 335 or 191 with varying intensities (10-30% of the base peak). Additionally, at the MS 3 level, the base peak at m/z 173 was characteristic of the isomers with a caffeoyl moiety substituted at position C-4 of quinic acid, whereas other substitutions gave base peaks at m/z 191. A comparison of the elution order and the fragmentation patterns of the product ions described above to those reported in the literature for dicaffeoylquinic acids [21,24] suggests that the detected isomers 4 and 11-14 were 1,3-; 3,4-; 3,5-; 1,5-; and 4,5-Odicaffeoylquinic acids, respectively. Finally, compound 4 was compared with the commercial standard of cynarin (1,3-di-O-caffeoylquinic acid).
A search for tricaffeoylquinic acids with the deprotonated molecular ion at m/z 677 and typical UV-Vis absorption maxima at 325 nm resulted in the identification of one chromatographic peak. On the basis of its MS 2 base peak at m/z 497 and the secondary ion at m/z 515 (20% of base peak intensity), which yielded an MS 3 base peak at m/z 353, the compound 15 was identified as 1,4,5-tri-O-caffeoylquinic acid, according to the literature data [20,21].
As shown in Table 3, there are two further compounds with UV-Vis spectra typical of caffeic acid derivatives with absorption maxima at 327-329 nm. These compounds, elut- tricaffeoylquinic acid substituted with an unidentified group. Due to the lack of suitable reference standards and literature data, the complete identification of these compounds needs isolation and full spectral characterization. The analyzed extract of soil-grown roots only gave one peak with a UV-Vis spectrum demonstrating absorption maxima at 247 nm, which is typical of ecdysones. The MS spectrum revealed its molecular mass to be 480 amu based on [M+HCOO] − ion at m/z 525 and [M−H] − at m/z 479. A comparison of these spectral data with those obtained from the authentic standard allowed to confirm the identification of 20-hydroxyecdysone (compound 8) ( Table 3).
The other group of compounds exhibits the UV-Vis spectra characteristic of flavonoids with two absorption maxima, first at 250-260 nm and second at 350-370 nm. All compounds 5-7 and 9-10 were identified as flavonoid hexosides due to neutral losses of 162 mass units in their MS 2 spectra. Flavonoid 5 was assigned as a quercetagetin hexoside, since the MS study of its deprotonated molecular ion (m/z 479) provided a characteristic product ion at m/z 317 in the negative mode MS of quercetagetin aglycone [22]. Likewise, compound 10 was tentatively identified as patuletin hexoside by comparing its UV-Vis spectrum and fragmentation pattern of the aglycone moiety in MS 3 spectrum with the literature [22]. Compounds 6 and 7 had identical MS profiles: fragmentation of deprotonated ion [M−H] − at m/z 463 yielded the base ion at m/z 301 in MS 2 which corresponded to either of the two characteristic aglycones of R. carthamoides, quercetin, or 6-hydroxykaempferol [25][26][27]. According to the literature data, the MS spectra of quercetin and 6hydroxykaempferol reveal the presence of characteristic fragment ions at m/z 151 and m/z 167, respectively [22]. Thus, according to the observed MS 3 fragmentation (Table 3), the aglycones of compounds 6 and 7 were assigned as quercetin. The MS 2 spectrum of compound 9 revealed an ion of aglycone moiety at m/z 285, which could suggest the presence of luteolin or kaempferol. The comparison of the UV-Vis spectrum of 9 and the fragmentation pattern of its aglycone in MS 3 spectrum with the literature [22,28,29] indicated the presence of luteolin.
Quantitative HPLC-PDA Analysis.
The contents of mono-, di-, and tricaffeoylquinic acids and their derivatives and flavonoid glycosides in HR-L an HR-D hairy roots selected from optimum medium (WPM) were determined by HPLC-PDA analysis and compared with the roots of 3year-old nontransformed plants of R. carthamoides grown in the soil (Table 4 and Figure 4). The growing interest of caffeoylquinic acids and their derivatives is based on their diverse biological activities which include anti-inflammatory, analgesic, antipyretic, and anticarcinogenic effects [30,31]. Caffeoylquinic acids are free radical and metal scavengers and have been shown to modulate the gene expression of antioxidant enzymes [32]. Also, they have neuroprotective, neurotrophic [33], and hepatoprotective activity [34]. Table 4.
The results indicate that the total concentration of caffeoylquinic acids and their derivatives (calculated as the sum of compounds 1-4 and 11-17) ( Table 4) was about 2times higher in hairy roots cultured in photoperiod (HR-L) (19.08 mg g −1 DW) than that found in dark-grown hairy roots (HR-D) (11.45 mg g −1 DW) ( Table 4). The mean individual caffeic acid derivative content followed a similar pattern. It suggests a regulation response to light of the phenylpropanoid biosynthetic pathway. The positive effect of light on the biosynthesis of caffeic acid derivatives has been observed in transformed roots of some other plant species, such as Echinacea purpurea [35] and Cichorium intybus [36].
5-O-caffeoylquinic acid (chlorogenic acid, compound 2) (Table 4, Figure 4) was the main constituent of the monocaffeoylquinic acid derivatives detected in the transformed roots of R. carthamoides. Its content ranged from 1.96 mg g −1 DW to 5.12 mg g −1 DW and was higher in HR-L root culture ( Table 4). The amounts were much higher than chlorogenic acid level in transformed roots of Echinacea purpurea [35,37], Fagopyrum tataricum [38], or Polygonum multiflorum [39]. In transformed roots of R. carthamoides the chlorogenic acid was further esterified with caffeic acid to produce the 3,5-di-O-caffeoylquinic acid (compound 12) ( Table 4). The amount of the compound was 3.08 mg g −1 DW in HR-L and 1.92 mg g −1 DW in HR-D (Table 4). Additionally, in extracts of HR-L and HR-D four other dicaffeoylquinic acids were found but at considerably lower amounts compared with 3,5-O-dicaffeoylquinic acid (Table 4). In both types of R. carthamoides hairy root culture, the predominant fraction was tricaffeoylquinic acid derivatives (8.01 mg g −1 DW and 5.89 mg g −1 DW in HR-L and HR-D hairy roots, resp.) with compound 16 (substituted tricaffeoylquinic acid) being the most abundant component. This compound represented up to 75% of the sum of the tricaffeoylquinic acids detected in transformed roots ( Table 4). The tricaffeoylquinic acids and their derivatives are less common in plants than mono-, and dicaffeoyl ones [34]. This type of compounds was earlier identified in other species of family Asteraceae, such as Arnica montana [21] and Erigeron breviscapus [20]. To date there have been no reports on tricaffeoylquinic acid production in R. carthamoides.
Considerable differences in qualitative and quantitative profiles of phytochemicals between transformed roots and normal roots of soil-grown plants of R. carthamoides (SR) were observed. The production of caffeoylquinic acids and their derivatives was 2-3-times higher in SR roots than in transformed roots. The most prominent component of SR roots was chlorogenic acid (18.26 mg g −1 DW) ( Table 4). The SR roots accumulated 17-23 times less of compound 16 (tricaffeoylqunic acid derivative) than transformed roots, which was dominant component in the latter. Moreover, 1,4,5-tri-O-caffeoylquinic acid (compound 15) ( Table 4) was identified only in the hairy root cultures. The differences between transformed roots and nontransformed roots of R. carthamoides were also observed in respect to other groups of secondary metabolites. Only hairy roots were able to produce the flavonoid glycosides (quercetagetin, quercetin, luteolin, and patuletin hexosides) when they were cultured in the light conditions. The total flavonoid content in this sample was 2.93 mg g −1 DW (Table 4). A comparative study of the ecdysteroids of transformed and normal roots of R. carthamoides showed that 20-hydroxyecdysone (compound 8) was only produced in the latter, reaching a level of 5.6 mg g −1 DW (Table 4).
The results of the present study showed that the transformation by A. rhizogenes strain A4 led to important modification of the metabolic pathways. Differences in the chemical profiles of transformed and normal roots have been also reported in other plant species [40,41] which indicate that the insertion of Ri T-DNA interferes with the biosynthesis of the secondary metabolites. However, the differences observed between transformed and normal roots of R. carthamoides with regard to the qualitative and quantitative spectra of secondary metabolites could be also caused by differences in the developmental stage of roots or by environmental conditions (in vitro or in vivo).
Conclusions
The present study demonstrates that hairy roots of R. carthamoides are easily grown in liquid WPM medium. They produce a substantial biomass of approximately 90 g L −1 of fresh weight in 80 mL medium after a short cultivation period of 35 days. The establishment of hairy root culture with highly increased levels of tricaffeoylquinic acids and their derivatives observed in the present study indicates that the hairy roots can be used as potential sources of these secondary metabolites instead of the normal roots of soil-grown plants. This is especially important because tricaffeoylquinic acids have been shown to possess antimutagenic, antihyperglycemic, strong antioxidant, and radical scavenging effects. However, it has been found that the tricaffeoylquinic acids have more biological activity than mono-and dicaffeoylquinic acid derivatives [42][43][44]. The antioxidant activity of hairy roots is currently under investigation. | v3-fos |
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} | s2 | Assessment of drought tolerance of 49 switchgrass (Panicum virgatum) genotypes using physiological and morphological parameters
Background Switchgrass (Panicum virgatum L.) is a warm-season C4 grass that is a target lignocellulosic biofuel species. In many regions, drought stress is one of the major limiting factors for switchgrass growth. The objective of this study was to evaluate the drought tolerance of 49 switchgrass genotypes. The relative drought stress tolerance was determined based on a set of parameters including plant height, leaf length, leaf width, leaf sheath length, leaf relative water content (RWC), electrolyte leakage (EL), photosynthetic rate (Pn), stomatal conductance (gs), transpiration rate (Tr), intercellular CO2 concentration (Ci), and water use efficiency (WUE). Results SRAP marker analysis determined that the selected 49 switchgrass genotypes represent a diverse genetic pool of switchgrass germplasm. Principal component analysis (PCA) and drought stress indexes (DSI) of each physiological parameter showed significant differences in the drought stress tolerance among the 49 genotypes. Heatmap and PCA data revealed that physiological parameters are more sensitive than morphological parameters in distinguishing the control and drought treatments. Metabolite profiling data found that under drought stress, the five best drought-tolerant genotypes tended to have higher levels of abscisic acid (ABA), spermine, trehalose, and fructose in comparison to the five most drought-sensitive genotypes. Conclusion Based on PCA ranking value, the genotypes TEM-SEC, TEM-LoDorm, BN-13645-64, Alamo, BN-10860-61, BN-12323-69, TEM-SLC, T-2086, T-2100, T-2101, Caddo, and Blackwell-1 had relatively higher ranking values, indicating that they are more tolerant to drought. In contrast, the genotypes Grif Nebraska 28, Grenville-2, Central Iowa Germplasm, Cave-in-Rock, Dacotah, and Nebraska 28 were found to be relatively sensitive to drought stress. By analyzing physiological response parameters and different metabolic profiles, the methods utilized in this study identified drought-tolerant and drought-sensitive switchgrass genotypes. These results provide a foundation for future research directed at understanding the molecular mechanisms underlying switchgrass tolerance to drought. Electronic supplementary material The online version of this article (doi:10.1186/s13068-015-0342-8) contains supplementary material, which is available to authorized users.
Background
Switchgrass (Panicum virgatum L.) has been designated as a model bioenergy crop in the United States [1]. As a warm-season perennial grass native to North America, switchgrass produces substantial aboveground biomass and has adapted to grow over an extensive range of habitats [2,3]. To avoid competition with food crops for arable land, switchgrass will primarily be grown on marginal land, of which millions of hectares are affected by drought [4]. Drought stress will be one of the major abiotic stresses encountered when growing switchgrass for use as a biofuel. Indeed, a recent study suggests that drought stress could be one major economic risk factor that limits biofuel production [5]. Therefore, a major goal of switchgrass breeding programs is to identify and select for genotypes with improved tolerance to drought stress [6].
Two distinct switchgrass ecotypes, lowland and upland, have been recognized and are generally defined based on their morphological characteristics and habitat preferences. Lowland ecotypes are mostly tetraploid (2n = 4× =36), whereas upland ecotypes tend to be octaploid (2n = 8× =72) with a few tetraploid exceptions [7]. In addition, lowland ecotypes are usually tall, coarse in leaf texture, and are adapted to grow in the flood plain region of North America. Alternatively, upland ecotypes are shorter, have finer leaves, and are predominantly found in the cooler climates of the northern United States [8,9]. Previous studies have evaluated a number of switchgrass germplasm cultivars in response to drought stress [4,10,11]. Jiang et al. [4] found that drought stress in the upland switchgrass cultivar Cave-in-Rock reduced tissue water content and leaf dry weight while simultaneously increasing total carotenoid concentration and electrolyte leakage. Interestingly, the values of these parameters returned to those similar to the control (wellwatered) plants after re-watering [4]. Under greenhouse conditions, Barney et al. [10] estimated that drought treatments (−4.0 and −11.0 MPa) could decrease the height and number of tillers, as well as decrease the overall leaf area, of drought-stressed switchgrass plants. They also found that drought treatments reduced biomass yields by up to 80 % [10]. In a field trial using the switchgrass cultivar Sunburst, drought stress reduced yields to approximately 26 % of those obtained in a year with above-average precipitation [12]. Although upland switchgrass genotypes have generally been considered to be more drought tolerant than lowland genotypes [13,14], lowland switchgrass cultivars have been reported to outperform upland cultivars under various adverse environmental conditions, including drought stress [10]. Thus, a more systematic evaluation of drought tolerance, one that examines a greater number of diverse lowland and upland switchgrass cultivars in a controlled manner, is required.
It is difficult to assess drought stress tolerance of a large collection of switchgrass germplasm based solely on the data collected from a drought treatment experiment, because there is significant genetic and phenotypic variation among switchgrass germplasms under non-stressed (control) conditions. The Drought Stress Index (DSI) is a method to evaluate the effect of drought stress on individual germplasm based on the difference between drought treatment and the control plants. DSI is calculated as DSI = (value of trait under stress condition)/ (value of trait under controlled condition) × 100. This equation removes the effect of germplasm variation from the drought stress evaluation and can therefore be used to assess a large collection of germplasm simultaneously [15].
Drought stress has a wide range of effects on the morphological, physiological, and biochemical processes in plants, and it can negatively affect the productivity of both dry land and irrigated crops [16][17][18]. Droughttolerant plants usually possess a combination of distinct morphological and physiological characteristics such as reduced leaf area, an extensive root system, the ability to sustain high leaf tissue water potential, and maintenance of a higher chlorophyll content and photosynthetic efficiency under drought conditions [19,20]. Physiological measurements such as leaf relative water content (RWC), electrolyte leakage (EL), photosynthetic rate (Pn), stomatal conductance (g s ), transpiration rate (Tr), and water use efficiency (WUE) have been widely used as markers for evaluating drought stress tolerance in various plant species [21,22]. Plant hormones such as abscisic acid (ABA) and jasmonic acid (JA) play an important role in plant response to drought stress [23]. An increase in JA is required for ABA levels to increase under drought conditions [24]. A recent study has shown that exogenous spraying of JA activates the plant antioxidant defense system and improves drought tolerance in some Brassica species [25]. Therefore, ABA and JA levels are routinely used as indicators of plant drought tolerance. In response to drought treatments, a variety of other metabolites are synthesized, including amino acids (e.g., proline) [26,27], nonstructural carbohydrates (e.g., glucose, fructose, sucrose, raffinose, and trehalose), inositol and inositol-phosphates, polyamines (PAs) (e.g., putrescine, spermidine, and spermine), and glycine betaine (GB). Increased carbohydrate turnover has also been observed in drought-tolerant plants [27,28]. Proline, sugars, and glycine betaine are osmotically neutral metabolites that play important roles in osmotic adjustment [29][30][31][32]. In guard cells, inositol phosphates can release vacuolar Ca 2+ into the cytosol in response to drought stress [33]. Polyamines (PAs) are ubiquitous, nitrogen-containing polycationic compounds that are found in all eukaryotic cells. In plants, the most abundant PAs are putrescine, spermidine, and spermine, and an increase in PA levels has been closely correlated with drought tolerance [34][35][36]. Therefore, metabolic profiling of drought-stressed plants could help evaluate their tolerance to drought stress.
Various molecular markers have been used to evaluate the genetic diversity within and between switchgrass genotypes [37][38][39]. Among the different types of markers, sequence-related amplified polymorphism (SRAP) markers are useful because of their reproducibility, low cost, ability to amplify without prior knowledge of the target sequence, and ease of use [40]. SRAP markers have been successfully used to evaluate genetic diversity and to construct genetic maps in species ranging from field crops to forage grasses and tree species [40][41][42][43].
Systematically evaluating diverse switchgrass germplasms in response to drought stress will be helpful for identifying genetic resources that can be used to breed elite switchgrass cultivars with improved drought tolerance. Switchgrass germplasms with distinct responses to drought stress will be useful for studying the mechanisms underlying drought tolerance and for identifying genes or molecular markers that can be used for molecular breeding. The objectives of this study were: (1) to determine the morphological, physiological, and metabolic parameters that are important indicators of switchgrass drought tolerance, and (2) to identify drought-tolerant and drought-sensitive switchgrass genotypes from 49 genetically diverse lowland and upland switchgrass genotypes.
UPGMA clustering analysis to evaluate the genetic background of 49 switchgrass genotypes
Switchgrass has a diverse geographic distribution [8]. Presently, a method for efficient systematic evaluation of diverse switchgrass germplasms for drought tolerance has not yet been reported. In this study, we selected 49 switchgrass genotypes from 49 accessions that include both upland and lowland ecotypes for drought stress evaluation (Table 1). To estimate the genetic diversity of the 49 switchgrass genotypes, we performed SRAP analysis (Table 3). However, for each of the morphological parameters (plant height, LL, LW, and SL), the effects of soil moisture regime and the interaction between soil moisture and genotype were not significant (p ≤ 0.05) ( Table 3).
To identify the key parameters for assessing drought tolerance in switchgrass, both physiological and morphological measurements were used to plot a heatmap. As shown in Fig. 2, the morphological and physiological Fig. 2, dot-highlighted); however, these genotypes are scattered under drought stress conditions (group b in Fig. 2, dot-highlighted).
To evaluate the contributions of each parameter in the control and drought-treated switchgrass plants, we performed PCA using both physiological (RWC, EL, Pn, g s , Tr, Ci, and WUE) and morphological (plant height, LL, LW, and SL) parameters collected from plants after 30 days of drought treatment. The physiological parameters contributed more than the morphological parameters to the separation of the control and drought-treated groups (Fig. 3). Among the seven physiological parameters, Pn, g s , Ci, Tr, and RWC were positively associated with the control treatment (well-watered) group (Fig. 3, circled). WUE and EL were positively correlated with drought treatment (Fig. 3, box). The four morphological traits (plant height, LL, LW, and SL) did not contribute to the separation of the genotypes under either condition. A similar result was found after 15 days of drought treatment (Additional file 1: Figure S1).
Hierarchical clustering analysis of the heatmap also indicated that the physiological and morphological measurements could cluster the 49 genotypes into three distinct groups (top of Fig. 2 group I, II, III). The four morphological measurements, which reflect relative long-term response to abiotic stress, were clustered together (top of Fig. 2, group I) and were not consistently different between the control (Fig. 2, group a) and the short-term drought treatment groups (Fig. 2, group b). Thus, morphological traits do not appear to closely correlate with short-term drought tolerance in switchgrass (Additional file 2: Tables S1, S2).
Summary of analysis of variance for the effects of treatments, lines, and the interaction on leaf relative water content (RWC), electrolyte leakage (EL), photosynthetic rate (Pn), stomatal conductance (g s ), transpiration rate (Tr), intercellular CO 2 concentration (Ci), water use efficiency (WUE), leaf length (LL), leaf width (LW) and leaf sheath length (SL) with the data of 30 days
** Significant at P ≤ 0.01, *** significant at P ≤ 0.001, NS nonsignificant at P ≤ 0.05 Fig. 2). In general, all 49 genotypes showed increased WUE and EL under drought treatment. The WUE is a parameter that is derived from the Pn and Tr values. WUE consistently increased under drought treatment in all 49 genotypes, while the EL, a measurement of the damage of cell membrane, consistently increased in all 49 genotypes in response to drought treatment. As shown in Additional file 8: Figure S7, a large variation in WUE was observed. The genotypes Blackwell-3, Forestburg, 70SG0021, Sunburst, and BN-11357-63 tended to have higher DSIs (>187.7 %) for WUE. Alternatively, the genotypes 70SG0017, Grif Nebraska 28, 70SG003, BN-12323-69, and Pathfinder tended to have relatively lower DSIs (<96.5 %) for WUE. Several lowland genotypes, including BN-13645-64, Alamo, and TEM-SLC, had intermediate WUEs and DSIs ranging from 122.7 to 154.5 %. The EL reflects cell membrane damage that occurs during drought stress. In addition, the EL may also affect Tr and Pn (and subsequently affect WUE). Drought stress resulted in an increased EL for all genotypes (Additional
The 49 switchgrass genotypes can be clustered into three groups based on DSI values for seven physiological measurements at 30 days of drought treatment
Heatmap hierarchical clustering and PCA indicated that physiological parameters are important for distinguishing the control and drought treatments in switchgrass. To cluster the switchgrass genotypes that had similar physiological responses to drought, we performed PCA using the DSI of seven physiological measurements collected at 30 days of drought treatment. The results of this PCA analysis identified three major groups (group I, II and III) (Fig. 4). In general, the lowland genotypes clustered mainly into groups I and II; however, upland genotypes such as BN-10860-61, T-2100, T-2101, Caddo, and BN-18758-67 also clustered in groups I and II. This suggests that these upland genotypes have similar tolerance to drought as their lowland counterparts. The seven physiological parameters (Pn, Ci, g s , Tr, RWC, WUE and EL) allow to separate 49 switchgrass genotypes that were either grown under well-watered (circled) or drought treatment (box) conditions. Arrows represent physiological traits with various length based on the impact of each trait on the separation of genotypes. RWC relative water content, EL electrolyte leakage, Pn photosynthetic rate, g s stomatal conductance, Tr transpiration rate, Ci intercellular CO 2 concentration, WUE water use efficiency, LL leaf length, LW leaf width, SL leaf sheath length PCA using the DSI values of seven physiological measurements collected at 30 days also suggests that the first principal component (PC1) explained approximately 57.83 % of the variance in the data and that the second (PC2) and third components (PC3) explained an additional 17.48 and 12.22 % of the variance, respectively. Together, the three components (PC1, PC2, and PC3) could explain 87.53 % of the variance among the 49 genotypes (Additional file 10: Figure S9). Because of the importance of physiological parameters for distinguishing the control and drought treatments in switchgrass, the relationships among the seven physiological parameters were further analyzed. We performed correlation analysis using Pearson's method. Table 4 shows that under drought stress, the correlations of Pn with EL, RWC, Tr, g s, and WUE were significant (p < 0.05) because they had large correlation coefficients (r) of −0.549, 0.555, 0.766, 0.737 and 0.847, respectively. These findings reveal that these physiological indicators, particularly Pn, are important parameters for assessing tolerance to abiotic stresses, including drought. Since the PCA that was based on the DSI of seven physiological parameters ( Fig. 4; Additional file 10: Figure S9) showed that three major components (PC1, PC2, and PC3) could explain 87.53 % of the variance in response to drought treatment (Additional file 10: Figure S9 (Table 5). In contrast, genotypes including Grif Nebraska 28, Grenville-2, Central Iowa Germplasm, Cave-in-Rock, Dacotah, and Nebraska 28 had relatively lower ranking values and thus, were found to be more sensitive to drought stress.
Different metabolic responses of the five best drought-tolerant genotypes and the five most drought-sensitive genotypes
To examine if metabolic responses varied under drought stress, we selected the five most drought-tolerant genotypes (top 10 % genotypes) and the five most droughtsensitive genotypes (bottom 10 % genotypes) for metabolite profiling ( Table 5). The levels of 14 metabolites, including ABA, JA, JA-Ile, betaine, proline, putrescine, spermine, spermidine, fructose, glucose, inositol, sucrose, trehalose, and raffinose were analyzed. Among the 14 metabolites, differences in ABA, spermine, trehalose, and fructose were found between the five best drought-tolerant genotypes and the five most droughtsensitive genotypes (Fig. 5). In general, the five best drought-tolerant genotypes tended to accumulate higher levels of ABA, spermine, trehalose, and fructose under drought stress than the five most drought-sensitive genotypes (Fig. 5).
Evaluation of switchgrass germplasm with different physiological and metabolic parameters
In this study, we screened 49 diverse switchgrass genotypes for their tolerance to drought stress by measuring physiological, morphological, and metabolic traits. Our results indicate that the physiological parameters contributed more than the morphological traits in separating the control and drought-treated groups. This suggests that physiological characteristics may be closely associated with short-term drought tolerance in switchgrass. Previously, the evaluation of plant drought tolerance has been complicated due to inconsistencies in testing environments, the interactions between different developmental stages of plant growth, and the handling of a large number of plant genotypes [45]. Thus, no comprehensive, standardized system for measuring drought resistance has been established [46]. Indices that are based on yield loss under drought conditions, in comparison with normal conditions, have been used in crop breeding programs; however, these indices are labor intensive and time consuming [47,48]. In this study, we measured a set of physiological parameters under drought treatment to effectively classify a relatively large collection of switchgrass germplasm. This process is non-destructive and sensitive to in planta conditions, which makes it favorable for collecting more reliable drought-related data.
Drought stress significantly altered the physiological parameters (Pn, g s , Tr, Ci, and WUE) of all 49 switchgrass genotypes (Additional file 3: Figure S2; Additional file 4: Figure S3; Additional file 5: Figure S4; Additional file 6: Figure S5; Additional file 7: Figure S6; Additional file 8: Figure S7; Additional file 9: Figure S8). During drought conditions, the Pn may be inhibited due to stomatal closure. This could inhibit RuBisco activity and increase respiration rates, ultimately leading to depleted carbohydrate reserves, reduced growth rates, and early plant senescence. In response to water deficit, the stomata may also close to conserve water; however, stomatal closure (lower g s ) may block gas exchange and result in an increase in the O 2 /CO 2 ratio. With an increase in excess O 2 molecules, energy may be directed to them and the production of toxic reactive oxygen species (ROS) becomes a concern [49,50]. In turn, these ROS may destroy important cellular components such as proteins, lipids, and nucleic acids, resulting in cell membrane damage (increased EL). Excess ROS may also damage components of the photosynthesis system, reducing the Pn and leaf RWC (Additional file 7: Figure S6) and increasing EL (Additional file 9: Figure S8) [51]. In order to cope with abiotic stresses, such as drought, plants have evolved the ability to evoke antioxidant defense systems, osmotic adjustments, and hormonal regulations of stomatal functions [17,18]. The DSIs for each physiological parameter (Additional file 3: Figure S2; Additional file 4: Figure S3; Additional file 5: Figure S4; Additional file 6: Figure S5; Additional file 7: Figure S6; Additional file 8: Figure S7; Additional file 9: Figure S8) were used to evaluate the relative drought tolerance of all 49 switchgrass genotypes. Our results showed that the drought-tolerant genotypes had higher RWC, g s , Pn, Tr, and Ci, and a lower EL than the drought-sensitive genotypes. In addition, the five best drought-tolerant genotypes tended to accumulate higher levels of ABA, spermine, fructose, and trehalose under drought stress than the five most drought-sensitive genotypes (Fig. 5). It has been well documented that ABA induces stomatal closure and reduces water loss through transpiration [23]. Our results show that the drought-tolerant genotypes had higher levels of ABA, g s , and Tr, suggesting that these genotypes may achieve a higher tolerance to drought stress by maintaining better gas exchange (high g s and Tr). This high level of gas exchange would reduce ROS toxicity, providing stronger signal-mediated regulations (Fig. 5, higher ABA, spermine, and trehalose) and osmotic adjustments (higher levels of trehalose and fructose). Fructose and trehalose are important osmoprotectants that facilitate osmotic adjustment. A previous study in Arabidopsis also showed that spermine is closely correlated with drought tolerance [52]. No consistent differences in any of the other metabolites between drought-tolerant and drought-sensitive genotypes were found in our study. In addition to regulating gas exchange, plants possess various antioxidant metabolites and enzymes to remove ROS. Stomatal functions and photosynthesis efficiency rates under drought conditions may not only be regulated by hormones, such as ABA. The integrity of these processes could also be maintained by other metabolites that might facilitate such harsh osmotic adjustments, ultimately improving drought tolerance in plants [23,53].
Table 4 The correlation coefficient (r) between physiological measurements in 49 switchgrass genotypes under drought stress
Drought-tolerant genotypes have also been shown to have a higher photosynthetic function (higher Pn) relative to drought-sensitive genotypes. Similar results were also found in switchgrass [4], maize [54], and creeping bentgrass [55] under drought treatment. Mohamed [11] found that water stress affected several switchgrass cultivars (Carthage, Alamo, Kanlow, Southlow, Cavein-Rock, Forestburg, Blackwell, Nebraska 28, Shelter, Shawnee, Dacotah, Sunburst, and WI) physiologically by decreasing photosynthesis. Jiang et al. [4] evaluated the upland switchgrass cultivar Cave-in-Rock and noted that drought stress reduced tissue water content, leaf dry
Methods for analysis of large physiological datasets
It is still challenging to reliably analyze and interpret large physiological datasets collected from plants grown under drought and well-watered conditions. Various methods and statistical models have been proposed for such analyses. Correlation analysis, PCA, and clustering are considered to be good methods for evaluating the relationships between the parameters and their principal components in phenotypic screening for drought tolerance [21,47,48]. In this study, PCA and correlation analysis showed that the differences in drought tolerance among the 49 switchgrass genotypes were largely due to variations in physiological parameters, especially Pn (Table 4; Fig. 4). Our results also found that some lowland genotypes, such as TEM-SEC, TEM-LoDorm, BN-13645-64, Alamo, and TEM-SLC, have relatively good tolerance to drought. These genotypes maintain higher Pn, Tr, g s , Ci, and RWC and lower EL in comparison to the upland genotypes (Additional file 3: Figure S2; Additional file 4: Figure S3; Additional file 5: Figure S4; Additional file 6: Figure S5; Additional file 7: Figure S6; Additional file 9: Figure S8; Table 5). Although the upland genotypes had a comparatively greater WUE than the lowland genotypes, our data showed that WUE was highly variable (Additional file 8: Figure S7). In fact, WUE alone may not be enough of a factor for evaluating drought tolerance [56].
A heatmap is a visual method that can be used to explore complex associations between multiple parameters collected from various treatments. It is often useful to combine heatmap with hierarchical clustering, which is a way of arranging items in a hierarchy based on the distance or similarity between them. Despite its benefits, heatmap analysis (Fig. 2) could not clearly identify the significant differences between the genotypes in this study. PCA biplots (Figs. 3, 4), however, could show the relative contributions of the parameters to the clustered groups. In our study, the PCA based on the DSI of seven physiological parameters yielded three PCs that accounted for 87.53 % of the total variance ( Fig. 4; Additional file 10: Figure S9). For the purpose of evaluating switchgrass tolerance to drought stress, the three PCs were sufficient to represent the seven physiological parameters. To comprehensively evaluate the relative drought tolerance of the 49 switchgrass genotypes, a ranking value was calculated for each of the genotypes analyzed in this study (Table 5)
Conclusion
There is wide variation in the drought tolerance of the 49 switchgrass genotypes examined in this study. Based on DSI values for each physiological parameter, cluster analysis, and PCA ranking, we found that genotypes TEM-SEC, TEM-LoDorm, BN-13645-64, Alamo, BN-10860-61, BN-12323-69, TEM-SLC, T-2086, T-2100, T-2101, Caddo, and Blackwell-1 were more drought tolerant. We also found that genotypes Grif Nebraska 28, Grenville-2, Central Iowa Germplasm, Cave-in-Rock, Dacotah, and Nebraska 28 were relatively sensitive to drought stress. The physiological measurements and metabolic profiles generated in this study offered a sensitive, reliable approach for identifying switchgrass genotypes that are tolerant or sensitive to drought stress. The results of this study provide a foundation for further investigating the molecular mechanisms underlying switchgrass tolerance to drought stress.
Plant materials and culture
This study was performed in a greenhouse at Virginia Tech (Blacksburg, VA, USA). Diverse switchgrass germplasm accessions were originally obtained from the United States Department of Agriculture Germplasm Center and were maintained in the Virginia Tech Kentland Farm Agricultural Station (Blacksburg, VA, USA). One genotype from each of the 49 switchgrass accessions was chosen for this study (Table 1). Each switchgrass genotype was propagated by splitting tillers. On May 12, 2012, a tiller from each genotype was planted in a large pot (40 cm diam., 45 cm deep) filled with 12 kg of a mixture of sandy loam top soil and sand (2:1, v/v, 0.1-1.0 mm diam.). After 2 months of culture, six tillers from each genotype were transplanted into six plastic pots (17 cm diam., 20 cm high, with four holes at the bottom for drainage) and filled with 3.5 kg of a soil and sand mixture (soil:sand = 2:1 v/v, sand: 0.1-1.0 mm diam.). Of the 49 genotypes (Table 1) [8,57], and the rest were upland ecotypes.
Drought stress treatment
After the plants were grown for 2 months (Sep 10, 2012) and had reached the E5 developmental stage [58], they were exposed to one of two soil moisture treatments (well-watered or drought stress) for 30 days.
The plants from each genotype were randomly assigned to either the control group (n = 6), which was kept well watered to maintain the soil moisture content at container capacity, or to the drought treatment group (n = 6), in which the soil moisture was allowed to gradually decline from day 0 to day 30 by reducing the amount of water used for irrigation. Water was added daily to compensate for 30-50 % ET loss during the experiment over the 30-day period. ET was determined by weighing the pots [59]. In addition, the volumetric soil moisture content (VWC) was monitored using a soil moisture meter (model HH2, Delta-T Devices, Cambridge, England).
In a separate experiment, the soil water content (SWC) of the growth media was determined based on differences in soil sample weight before and after drying at 105 °C to a constant weight. This difference was expressed as the percentage of the weight lost relative to the oven-dried weight. Soil samples were taken at different time points and each data point is the average of the measurements.
On average, the volumetric water content (VWC) was reduced from 40.00 to 21.24 % and the SWC was reduced from 26.21 to 17.34 % between days 0 and 15. Between days 15 and 25, the VWC was reduced from 21.24 to 10.94 % and the SWC was reduced from 17.34 to 8.09 %. Finally, the VWC was reduced from 10.94 to 5.79 % and the SWC was reduced from 8.09 to 4.31 % between days 25 and 30. The well-watered pots were irrigated daily to maintain approximately 40.0 % volumetric soil moisture ( Table 6). The amount of water given each day was determined according to ET [59].
Physiological measurements
To measure electrolyte leakage (EL) and relative water content (RWC), leaf samples were collected after 0, 5,10,15,20,25, and 30 days of drought stress. At the same time points, the photosynthetic rate (Pn), stomatal conductance (g s ), intercellular CO 2 concentration (Ci), and transpiration rate (Tr) were determined. At the end of the experiment (30 days), leaf tissue samples for metabolite and genetic diversity analyses were collected and frozen in liquid N 2 .
Leaf electrolyte leakage (EL) was measured according to the method of Marcum [60] with some modifications. The top 2nd or 3rd mature leaf blades were excised and cut into 2-cm segments. After rinsing 3 times with deionized H 2 O, 0.2 g of the leaf tissue was placed in a 50-mL test tube containing 20 mL deionized H 2 O. The test tubes were agitated on a shaker for approximately 24 h, and the solution conductivity (C 1 ) was measured with a conductivity meter (SR60IC, VWR, Radnor, PA, USA). The leaf samples were then autoclaved at 120 °C for 30 min, and when the tubes cooled to room temperature, the conductivity of the solution containing the killed tissue was measured (C 2 ). The relative EL was calculated using the formula: EL (%) = (C 1 /C 2 ) × 100.
Leaf relative water content (RWC) was determined according to the method of Barrs and Weatherley and was based on the following formula: RWC = (FW − DW)/ (TW − DW) × 100, where FW is leaf fresh weight, DW (dry weight) is the weight of the leaves after drying at 85 °C for 3 days, and TW (turgid weight) is the weight of the leaves after soaking them in distilled water for 24 h at 20 °C. The photosynthetic rate (Pn), stomatal conductance (g s ), intercellular CO 2 concentration (C i ) and transpiration rate (Tr) were measured using a portable photosynthesis system (Li-6400XT, LI-COR, Inc., Lincoln, NE, USA) under a controlled atmosphere (385 μmol mol −1 CO 2 , 500 μmol s −1 flow rate, 26 °C) and a LI-COR 6400 LED external light source that provided a photosynthetic photon flux density (PPFD) of 2000 μmol m −2 s −1 . The uppermost fully expanded leaf on the main tiller in each pot was selected for these measurements. Three readings were collected for each sample, and the average was used for statistical analysis.
Plant tissues were frozen in liquid nitrogen, lyophilized overnight and transferred to 2-mL screw-cap tubes (http://www.sarstedt.com) containing three 3.2mm stainless steel beads (http://www.biospec.com). The tissue was ground, and aliquots of approximately 50 mg were automatically transferred to new tubes using the iWall instrument at the GLBRC Cell Wall facility at Michigan State University (https://www.glbrc.org/ research/enabling-technologies). Chemical extraction was performed using a 10 % methanol and 1 % acetic acid solvent containing internal standards of 10 μM dh-JA, 10 μM ribitol, 10 μM [ 2 H 3 ]proline, and 1 μM [ 2 H 6 ]ABA. For extraction, 400 μL of extraction solvent was added to approximately 50 mg of ground plant tissue, and the mixture was incubated at 70 °C for 30 min. The extract was centrifuged for 15 min at 13,000 rpm, and 200 μL of supernatant was transferred to a new 1.5-mL microcentrifuge tube. For each plant, 60 μL of extract was transferred to each of two 96-well PCR tubes for the analysis of two groups of metabolites: (1) ABA, JA, and JA-Ile, and (2) polyamines and proline. For sugar analysis using GC-MS, 10 μL of the extract was transferred to a new 1.5-ml microcentrifuge tube for derivatization. For derivatization, 10 μL of extract was evaporated to complete dryness overnight using a SpeedVac. Ten microliters of 40 mg mL −1 O-methylhydroxylamine hydrochloride in pyridine was added to the dried plant extract and the tubes incubated for 90 min at 30 °C with gentle rocking. Forty-five microliters of N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA) with 1 % trimethylchlorosilane (TMCS) was then added to the mixture, and the tubes incubated at 37 °C for an additional 30 min. For sugar analysis, 50 μL of the derivatized product was transferred to a glass vial containing a glass insert (http://www.restek.com). All materials were barcoded to keep track of each sample throughout the entire extraction and derivatization procedure.
Metabolite determination using GC-MS
To analyze the plants' sugar profiles, GC-MS was performed using a 6890N network GC system with a 5973 mass selective detector (Agilent Technologies, http:// www.agilent.com, Santa Clara, CA, USA).
Metabolite analysis using LC-MS/MS
For the analysis of ABA, JA, and JA-Ile, methods from Chung et al. [63] were used with modifications. Briefly, extracts (10 μL) were injected into an Ascentis Express C18 column (2.7 μM, 2.1 × 50 mm, Supelco Analytical) and attached to an Acquity Ultraperformance Liquid Chromatography System (Waters, http://www. waters.com, Milford, MA, USA) for LC reverse-phase analysis. The column temperature was maintained at 50 °C. A steep gradient was executed between solvents A and B (A-0.15 % formic acid in MilliQ water, Bmethanol) with an analysis time of 3 min/sample and a 0.4 mL min −1 flow rate. The gradient profile was as follows: 30 % B for the initial step; a linear gradient to 70 % B in 1.5 min; 100 % B in 2 min; 100 % B maintained for 2.5 min; and 30 % B from 2.5 min to 3 min. Mass spectra were acquired using electrospray ionization in negative ion mode and multiple reaction monitoring (MRM). A Quattro Premier XE tandem quadrupole mass spectrometer (Waters) was coupled to the LC to identify and detect analytic signals under the following conditions: 3.00 kV capillary voltage; 100 °C source temperature; 300 °C desolvation temperature; 20 L h −1 nebulizer nitrogen flow rate; and 300 L h −1 desolvation nitrogen gas flow rate. The transitions from precursor molecules to characteristic product ions were monitored for JA (m/z 209 > 59), dh-JA (m/z 211 > 59), JA-Ile (m/z 322 > 130), ABA (m/z 263 > 153), and [ 2 H 6 ] ABA (m/z 269 > 159). The collision energies and source cone potentials were optimized for each transition using Waters QuanOptimize software. Because this method does not distinguish JA-Ile from JA-Leu, the values reported for JA-Ile represent the sum of JA-Ile and JA-Leu. In Arabidopsis seedlings, the amount of JA-Leu is reported to be <25 % that of JA-Ile [64].
For the analysis of putrescine and spermine, methods from Gu et al. [65] were used with modifications. Briefly, the extracts (10 μL) were injected into a Symmetry C18 column (2.1 × 100 mm, 3.5 μM particle size, Waters) and attached to a Shimadzu (Columbia, MD, USA) LC-20AD HPLC system for LC reverse-phase analysis. The column temperature was maintained at 30 °C. A steep gradient was executed between solvents A and B (A-1 mM perfluoroheptanoic acid in MilliQ water, B-acetonitrile) with an analysis time of 6 min/sample and a 0.3 mL min −1 flow rate. The gradient profile was as follows: 2 % B for the initial step; a linear gradient to 20 % B in 0.1 min; 80 % B in 2.5 min; 80 % B maintained for 4 min; 20 % B in 4.1 min; and 2 % B in 6 min. Mass spectra were acquired using electrospray ionization in positive ion mode and MRM. A Quattro micro mass spectrometer (Waters) was coupled to the LC to identify and detect analytic signals under the following conditions: electrospray negative ionization mode; 3.17 kV capillary voltage; 110 °C source temperature; 350 °C desolvation temperature; 20 L h −1 nebulizer nitrogen flow rate; and 400 L h −1 desolvation nitrogen gas flow rate. The transitions from precursor molecules to characteristic product ions were monitored for putrescine (m/z 89 > 72), proline (m/z 116 > 70), betaine (m/z 118 > 59), [ 2 H 3 ]proline (m/z 119 > 73), spermidine (m/z 146 > 72), and spermine (203 > 112). The collision energies and source cone potentials were optimized for each transition using Waters QuanOptimize software.
Drought tolerance evaluation
To assess the drought tolerance of different populations, the drought stress index (DSI) was used in this study. DSI was calculated using the formula: DSI = (value of trait under stress condition)/(value of trait under controlled condition) × 100 [15].
DNA extraction and genetic diversity analysis
DNA was extracted from approximately 200 mg of leaf tissue from each of the 49 genotypes using the CTAB method [66]. The quality of the DNA was assessed by electrophoresis on 0.8 % agarose gels, and the quantity of the DNA was measured by comparing the samples to standardized lambda DNA size markers.
For SRAP-PCR amplification, 12 pairs of previously reported SRAP primers were selected for this study ( Table 2) [67]. SRAP analysis was performed as described previously [40]. Briefly, each 20 μL PCR reaction mixture consisted of 40 ng genomic DNA, 0.2 mM dNTPs, 2.5 mM MgCl 2 , 0.5 μM primers, 1× PCR buffer, and 1 unit of Taq polymerase. The amplification was performed in four steps: pre-denaturation at 94 °C for 4 min; 5 cycles of 1 min denaturation at 94 °C, 1 min annealing at 35 °C and 1.5 min extension at 72 °C; 35 cycles of 1 min at 94 °C, 1 min at 50 °C, and 1.5 min at 72 °C; and a final extension step at 72 °C for 7 min. The PCR fragments were separated on a 5 % agarose gel, stained with 0.01 % ethidium bromide, and visualized using a Gel-Document Image System ™ under UV light (Bio-Rad, Hercules, CA, USA).
Experimental design and statistical analysis
A split plot design was used in this experiment, with the soil moisture regimes as the main plots and the switchgrass genotypes as the subplots. Each genotype had six replicates for each soil moisture treatment (well-watered and drought). All data were subjected to analysis of variance (ANOVA, SAS 8.1, SAS Institute Inc., Cary, NC, USA). The treatment means were separated using Fisher's protected least significant difference (LSD) test at a 5 % probability level.
R statistical software (PCA analysis, R2.15.1 by R Development Core Team) was used to determine the correlations between physiological and morphological traits and to perform principal component analysis of the traits.
Each genomic DNA fragment obtained from the SRAP primer combinations was scored as present (1) or absent (0). These data were used to calculate genetic distances and to draw genetic distance dendrograms of the 49 switchgrass genotypes. The dendrograms were drawn using NTSYS-pc version 2.2 and were based on the DICE matrix and UPGMA (Unweighted Pair Group Method) arithmetical averages in the SAHN module. Concordance between the genotypic data and the dendrogram was determined using a Mantel test [68]. In addition, genetic distance dendrograms were drawn using DARwin5 software, which is based on the DICE matrix and UPGMA in the hierarchical clustering module and on unweighted neighbor-joining in the neighbor-joining module. | v3-fos |
2016-05-12T22:15:10.714Z | {
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} | s2 | Influences of Environmental Factors on Leaf Morphology of Chinese Jujubes
Rainfall and temperature are the primary limiting factors for optimum quality and yield of cultivated jujube (Ziziphus jujuba Mill.). Adaptation to arid and cool environments has been and remains an important goal of many jujube improvement programs. This study summarized the survey results of 116 Chinese jujube varieties grown at 33 sites in China. The objective was to identify the environmental factors that influence leaf morphology, and the implications for breeding and introduction of new jujube varieties. Jujube leaf morphological traits were evaluated for their potential relationships with mean annual temperature (MAT) and mean annual precipitation (MAP). The results showed that many leaf morphological traits had a strong linear relationship with local precipitation and temperature. Longer veins per unit area (VLA) and reduced leaf area and leaf perimeter were typical of arid areas. VLA was inversely related to MAT and MAP at the centers of origin of jujube. There was a positive relationship between leaf shape (perimeter2/area) and both MAT and MAP. These results indicated that leaf vein traits of Chinese jujubes might have resulted from their adaptation to environmental factors in the course of long-term evolution. Principal component analysis allocated the 116 jujube varieties to three different groups, differentiated on the basis of morphological and physiological leaf characteristics. Jujube varieties from the Hebei, Shandong, Henan, southern Shanxi and central Shaanxi provinces were closely related, as were varieties from northwest Shanxi and northeast Shaanxi provinces, and varieties from the Gansu and Ningxia provinces. These close relationships were partially attributed to the frequent exchanges of varieties within each group. Leaf venation characteristics might be used as reference indices for jujube variety introduction between different locations.
Introduction
Cultivated jujube (Ziziphus jujuba Mill.), which belongs to the Rhamnaceae family, is an economically important fruit tree in China [1]. Jujube fruits are consumed for their medicinal performance is affected [21]. The influence of environmental factors on plant growth can be either direct, via the impact of physical conditions on primary growth processes, or indirect due to developmental adaptation [25]. Plant growth is affected by numerous environmental factors, including water shortage and excess, temperature, nutrient availability, and light [26,27]. Many plant traits are sensitive to climate [28]. Studies focusing on interspecific patterns between plant traits and climatic factors have identified a correlation between leaf area and mean annual precipitation (MAP) [29]. Variation in the leaf size and shape has been shown to be correlated with climatic factors [30]. In addition, other environmental factors, such as light intensity and nutrient availability, can influence leaf size and shape [31].
The relationships between functional leaf traits and climatic conditions have been emphasized for at least a century [32]. Leaf VLA usually increases with a decrease in average annual precipitation [33,34]. Leaf VLA and rainfall are strongly negatively related in evergreen shrubs and trees [32]. Jujube varieties growing in arid and semi-arid regions tend to have leathery and high-VLA leaves. Leaves with high leaf dry mass per area (LMA) usually have thick leaf blades, and small and thick-walled cells, which can adapt to very dry conditions [23].
Several studies have attempted to explain how plasticity and genotype affect the relationships between jujube tree traits and environmental factors [35][36][37]. Su and Liu [38] studied the photosynthetic characteristics of linze jujube under high temperature and irradiation. Cui et al. [39] investigated the response of vegetative growth, fruit development and water use efficiency of pear-jujubes to regulated water deficit at various growth stages and different levels of water deficit at a single growth stage. Gao et al. [40] studied the antioxidant capacity of different jujube cultivars grown in the Loess Plateau of China. Ma et al. [41] evaluated the effects of water deficit at different growth stages on pear-jujube trees. Cui et al. [42] pointed out that regulated water deficit, controlled by irrigation, could improve fruit quality and water use efficiency of pear-jujube trees. Cui et al. [42] also used the method of stable carbon isotope discrimination to study the water use efficiency of pear-jujube trees under regulated water deficit irrigation.
A clear understanding of vein traits of jujube leaves can help to understand and predict whole plant performance under different climatic conditions, with applications in breeding of improved jujube varieties [18]. An analysis of jujube leaf morphology under different climatic conditions can also improve our understanding of adaptive strategies of jujube in response to drought stress. However, few studies have been conducted on jujube leaf traits and their role in responding to climatic stresses. The sensitivity of leaf morphology of Chinese jujube to climate is generally poorly understood [5,41].
In this study, a survey and analysis has been conducted to investigate the relationship between jujube leaf morphology and climatic factors, across 33 sites in northern China. The objectives were (1) to determine how leaf venation traits of Chinese jujubes vary under different climatic conditions, especially under drought stress, (2) to quantify the relationships between functionally linked leaf traits and climatic factors, including mean annual temperature (MAT) and mean annual precipitation (MAP), and (3) to identify the similarities among jujube varieties grown at 33 sites in China.
Study sites and leaf sampling
Leaf samples were collected mainly in private orchards, with the permission of land owners. We confirmed that the field studies did not involve any endangered or protected species.
Jujube leaf samples were collected in 33 sites in northern China in 2012 (Fig 1). The sampling sites above covered all of the three jujube production area in northern China, alluvial soils in the middle and lower reaches of the Yellow River and Haihe River (ASYH area), hills in the Loess Plateau (HLP area), and arid valleys and hills in Northwest China (AVHN area) [1]. The climates of these cultivation areas are very different, which provided a good opportunity to study the relationship between leaf morphology and environmental factors. The sampling sites covered all three jujube production areas.
The climates at the 33 study sites are generally temperate continental monsoon or temperate continental, with comparably low precipitation, and large diurnal and annual temperature differences. Winter periods are usually cold and dry, while summers periods are warm and wet. Moving closer to the center of continent, the climate becomes drier, with more frequent drought. For each sampling site, long-term climate data collected over 62 years (1951-2012), including MAT(°C) and MAP (mm), were obtained from the China Meteorological Data Sharing Service System (CMDSSS; http://cdc.cma.gov.cn/; Table 1). According to Table 1, Gansu and Ningxia Provinces tend to suffer from drought stresses since the average annual precipitations from the sampling sites in these provinces were all lower than 300 mm, while other provinces had much higher precipitations, usually larger than 500 mm. These two provinces are also prone to low temperature stresses since average annual temperatures were all below 10°C for their sampling sites.
Leaf sample collection
Totally, leaf samples from 116 jujube varieties were collected from 33 the sites in northern China (S1 Table). The samples were collected during August 2012. The jujube varieties, representing the core collection in three cultivation areas, were analyzed for their leaf traits. The diameters at breast height (DBH) were 20-40 cm; the tree ages were over 20 years old. For each jujube variety, three representative trees were randomly selected. Five shedding shoots were sampled from both the exterior ('sun leaves') and interior ('shade leaves') canopies of five randomly selected trees from each jujube variety. Then, five leaves were randomly sampled from each shoot resulting in 25 leave samples per Jujube variety. The leaf samples were stored in a freezer at 4°C before processing.
Measurement of leaf morphologic parameters
Approximately three to five mid-leaves were selected from each shedding shoot to investigate vein visibility through chemical clearing [23]. All leaves were cleared using a protocol published previously [13,17,43]. Each leaf (excluding the petiole) was cut from the stem and gently patted dry before measuring leaf area [44]. Leaves were fixed in 70% formalin-acetic acid-alcohol (48% ethanol, 10% formalin, 5% glacial acetic acid, 37% water) and cleared in 2.5%-5% sodium hydroxide in water or ethanol, bleached with sodium hypochlorite, and stained with safranin and fast green [23]. Leaf area, perimeter, and vein density were measured using the ImageJ image analysis software (public software; http://rsb.info.nih.gov/ij/) [45]. Vein density was calculated as the sum of the lengths of all vein segments (mm) per unit area (mm 2 ). An adaxial section of approximately one square centimeter at the right side of the midrib was excised from a sampled leaf to determine vein density. Leaf perimeter increased in proportion to the square root of leaf area for a given leaf type [46]. Leaf shape was recorded as perimeter 2 /area [47]. Since perimeter 2 / area was independent of leaf size, its mean value was calculated to represent all leaves sampled for each leaf type [48].
Data analysis
One-way analysis of variance (ANOVA) was performed on leaf trait data. A total of 21 representative jujube varieties from seven provinces were analyzed for their differences in leaf area, perimeter, and vein density through ANOVA. Then the differences of these leaf morphological traits were also analyzed for jujube varieties from three different jujube production areas, or ASYH, HLP, and AVHN areas mentioned previously. According to the Kolmogorov-Smirnov normality test (K-S test), VLA, leaf area, and leaf perimeter were normally distributed (p = 0.055, 0.200, and 0.200, respectively). Thus, post-hoc tests of VLA, leaf area, leaf perimeter could be conducted. Linear regression analysis was used to investigate potential relationships between leaf traits (e.g., vein density, leaf shape parameter of perimeter 2 /area) and environmental factors (e.g., mean annual precipitation and temperature). Finally, PCA and hierarchical clustering were performed on the morphological traits (VLA, leaf area, leaf perimeter, loopiness, distance between veins, number of nodes, and areole area) of the jujube leaves. The PCA results were used to describe plant trait and function types among populations via a covariance matrix, with data standardization [49]. For the statistical analyses described above, the SPSS (Statistical Product and Service Solutions) and SigmaPlot 11.0 (Systat Software, Richmond, CA, USA) software packages were used.
Influences of climatic factors on leaf morphology
Across the 33 sampling sites (Fig 1; Table 1), climatic conditions varied greatly, especially for MAT and MAP. The jujube leaves differed in size and shape due to environmental influences. VLA of jujube leaves had a negative linear relationship with MAP (r 2 = 0.678, p = 0.01) and MAT (r 2 = 0.449, p = 0.01), respectively (Fig 2A and 2C). Jujube leaf shape (perimeter 2 /area) significantly increased with MAP (r 2 = 0.158, p = 0.04) and MAT (r 2 = 0.218, p = 0.04; Fig 2B and 2D). MAP in the Gansu and Ningxia provinces was substantially lower than in other provinces, while MAT in the Gansu, Ningxia and Shaanxi provinces was slightly lower than those in other provinces (Table 1). Jujube from the Gansu, Ningxia and Shaanxi provinces had higher VLA values and lower leaf area and perimeter, particularly in Gansu. At the same time, the jujube varieties in the Shandong, Henan, Shanxi and Hebei provinces had relatively lower VLA, and higher leaf area and perimeter (Figs 2 and 3). Thus, it can be generally concluded that jujube grown in regions with lower MAP usually had higher VLA, and lower leaf area and perimeter.
Comparisons of leaf morphologic traits
Most of the morphologic traits, including VLA (Fig 3A), leaf area (Fig 3B), and leaf perimeter ( Fig 3C) varied among the 21 jujube varieties representing the 33 testing sites in northern China. VLA presented significantly higher values in Z. jujuba Mill. cv. Tongxinyuanzao from Ningxia Province and the lowest was for Z. jujuba Mill. cv. Dabailing from the Shandong Province (Fig 3A). Leaf (Fig 3B). Leaf perimeter presented significantly higher values in the variety Z. jujuba Mill. cv. Taiguhupingzao from Shanxi Province and significantly lower values in Z. jujuba Mill. cv. Minqinxiaozao from Gansu Province (Fig 3C). Average annual rainfall in Gansu and Ningxia was markedly lower than rainfall in the other provinces (p<0.05), while average annual temperature in Gansu, Ningxia, and Shaanxi provinces was slightly lower compared to the remaining provinces. Thus, it could be generally concluded that jujube varieties from dry regions usually had lower leaf area and perimeter, and higher, than varieties from humid regions.
Similarities of leaf venation characteristics among different jujube varieties
PCA results for plant leaf traits reflected morphological similarities among the 116 jujube varieties investigated (Fig 4). The first two axes accounted for 84.05% of the variability of leaf morphological traits. Hierarchical clustering divided the jujube varieties into three groups. Group 1 included mainly jujube varieties from Hebei, Shandong, Henan, southern Shanxi and central Shaanxi provinces. Members of Group 2 were mainly from northwest Shanxi and northeast Shaanxi, or along the Yellow River Canyon. Group 3 included mainly the jujube varieties from Gansu and Ningxia provinces, which possessed varying degrees of drought tolerance.
VLA, leaf area and leaf perimeter differed significantly among the growth habits. VLA presented significantly higher values in the jujube variety from the AVHN area and significantly lower values from the ASYH area (df = 35, F = 60.702, P<0.05; Fig 5A). Leaf area presented significantly lower values in the jujube variety from the AVHN area and significantly higher values from the HLP area (df = 35, F = 22.650, P<0.05; Fig 5B). Leaf perimeter presented significantly higher values in the jujube variety from the HLP area (df = 35, F = 8.726, P<0.05; Fig 5C).
Influences of climate on jujube leaf area
Interspecific variation in leaf area was related to climate. All of heat, cold, drought, nutrient and high-radiation stresses contribute to development of jujube trees with relatively small leaves [44]. Water and temperature are among the factors with the greatest impact on jujube leaf size [2]. The variety Z. jujuba Mill. cv. Minqinxiaozao from Ningxia Province had smaller leaf area and perimeter, as it often grew under drought and nutrient stress conditions. The variety Z. jujuba Mill. cv. Tuntunzao from Shanxi Province had larger leaf area and perimeter, as water and nutrients were sufficient in this province. This finding is similar to Li and Bao [50], Influences of Environments on Jujube Leaves who reported that jujube plants growing in drier sites have higher VLA. These leaf morphological traits reflect a general trend in plant adaptation when water is limited [51].
Jujube perimeter 2 /area, which is an index of intrinsic or size-independent shape [52] was positively related to MAT (r 2 = 0.112) and MAP (r 2 = 0.040), respectively (Fig 2B and 2D). Royer et al. [30] reported a significant linear relationship between perimeter/area and MAT within four jujube varieties in the eastern USA. The sizes and shapes of leaves were strongly linearly related to temperature and rainfall. There are biological bases for these relationships [52][53][54][55]. Warmer leaf temperatures promote both photosynthesis and transpiration [56]. VLA, leaf area and leaf perimeter of jujube from the Gansu and Ningxia provinces compared to other provinces (P<0.05; Fig 3). Jujube in the Gansu and Ningxia Provinces (arid valleys and hills), where the climate is dry and cool, tended to have smaller leaves to reduce evaporation, while larger leaves were more common in more humid areas such as the Shandong and Henan provinces. VLA, leaf area and leaf perimeter from the northwest Shanxi and northeast Shaanxi provinces were not remarkably different from the Shandong, Hebei, and Henan provinces (p>0.05; Fig 3). This might be because southern Shanxi and central Shaanxi provinces have alluvial soils in the middle and lower reaches of the Yellow River and Haihe River, while northeast and northwest Shanxi have hills in the Loess Plateau [1].
Since external factors, such as temperature and light regimes, fluctuate strongly, the impact on leaf growth could adversely affect leaf shape [24]. The lamina perimeter 2 /area is an index of leaf shape. All mesophyll regions of leaves with higher perimeter 2 /area will be closer to the veins [57]. Furthermore, leaves with higher perimeter/area tend to have a thinner boundary layer over the bulk of the lamina, which can enhance convective cooling and gas exchange at low wind speeds [48]. This can partially explain the finding that perimeter 2 /area increased with mean annual temperature and precipitation.
Relationship between VLA of Chinese jujube and drought tolerance
VLA was negatively and linearly related to MAP and MAT at the centers of origin of Chinese jujube (Fig 2). The negative relationship between vein density and MAP was also reported in other studies [13,14,58]. Leaf properties, such as vein density, are strongly related to the hydraulic conductivity of leaves [12]. The venation network is a key limiter of the hydraulic proficiency of angiosperm plants [12]. Vein traits are thought to reflect the gas and water exchange characteristics between leaves and the atmosphere, which are greatly influenced by climatic factors on the leaf, tree, stand, and even regional scales [58][59][60].
VLA can be used as an indicator of adaptation of jujube varieties to the local climate and habitat [58]. Since water supply must match transpiration demand of plants, VLA and stomatal pore area per leaf area tend to be positively related [9,47]. A higher VLA can increase leaf xylem hydraulics, as it corresponds to a larger number of xylem flow pathways in parallel and a greater surface area of bundle sheaths and, thus, higher total permeability for water flow out of the veins [14,16]. Higher VLA can improve leaf life span by providing redundant pathways around damaged sites or embolism during drought [32]. Thus, plants in dry regions tend to have higher VLA, which might lead to a longer leaf life span due to both biomechanical and hydraulic effects [18]. The resistance mechanisms of jujube in response to water stress can be explained in part through the leaf and water relationship [2].
The differences in other morphological traits of jujube leaves might also be caused by other regional environmental factors, such as soil fertility, thermal seasonality, and/or phylogenetic differences. Huff et al. [61] and Royer et al. [62] found that morphology of leaves from cold climates was consistent with the ecophysiological principles. A well-known generalization is that fast-growing, resource-acquisitive species tend to have lower LMA, higher light-saturation rates of photosynthesis per mass (A mass ), higher N concentration per mass (N mass ) and respiration rate per mass (R mass ), but shorter leaf lifespan (LL), in contrast to slow-growing, resourceconservative species [20]. Thus, the jujube varieties in the drier Gansu and Ningxia provinces had relatively higher LMA, lower N mass and R mass , but longer LL, in contrast to the jujube varieties in other humid provinces such as Henan, Shanxi and Shandong.
Adaptation of Chinese jujubes to local climatic conditions
Most of the jujube varieties investigated can grow well in their respective areas of origin. For instance, Z. jujuba Mill. cv. Lanzhouyuanzao and Z. jujuba Mill. cv. Tongxinyuanzao grow well and produce high yields in the Gansu and Ningxia provinces, where mean annual precipitation are only 156.5 and 257.8 mm, respectively. In this study, the highest values of VLA were found in the jujube varieties in these areas, which implies that VLA is a result of interactions between plant and environmental factors and can be used to reflect changes in the jujube plant morphology in response to environmental factors [63]. Uhl [58] also pointed out that VLA is a morphological characteristic that can adapt to changing environments. Thus, based on the analysis of VLA values, it can be concluded that jujube varieties in Gansu and Ningxia provinces have gradually adapted to their local climatic conditions of low temperature, high irradiance, and limited rainfall. This conclusion is consistent with some recent findings that leaf traits of Chinese jujubes have adapted to their local environments in the course of long-term evolution, embodying the ecological strategy of Chinese jujubes for drought resistance under the pressure of natural selection [4,38,39].
Introduction of jujube varieties based on vein traits
PCA divided the 116 jujube varieties into three different groups, according to leaf traits (Fig 4). Jujube varieties from Hebei, Shandong, Henan, and central Shaanxi provinces were similar and included in Group 1. Similarly, varieties from northwest Shanxi and northeast Shaanxi were similar and assigned to Group 2. Varieties from Gansu and Ningxia provinces were similar, comprising Group 3. This clustering result was consistent with the division of cultivation areas of Chinese jujubes [1]. In general, there were three jujube areas in China based on local natural conditions, including the area of alluvial soils in the middle and lower reaches of the Yellow River and Haihe River (ASYH area), the area of hills in the Loess Plateau (HLP area), and the area in arid valleys and hills in Northwest China (AVHN area). Interestingly, Hebei, Shandong, Henan, and central Shaanxi provinces all belonged to the ASYH area. Northwest Shanxi and northeast Shaanxi belonged to the HLP area, and Gansu and Ningxia provinces were in the AVHN area. Thus, within the context of leaf vein characters, the division of jujube cultivation areas was appropriate.
In China, introduction of new jujube varieties into some areas should take into consideration several ecological conditions, including temperature, precipitation, latitude, solar radiation, and altitude. The smaller the ecological differences, the easier the introduction of a new variety [1]. In this study, for jujube varieties from Gansu and Ningxia Provinces (Group 3 in Fig 4), there were no significant differences among the leaf morphological traits, as was the case for varieties from the Henan, Hebei, and Shandong provinces. The climatic conditions in Ningxia and Gansu were similar. Actually, for a long period, many jujube varieties from Gansu Province were introduced to Ningxia Province. The results of PCA of leaf venation characteristics partially showed the flow of jujube varieties among the provinces of China. Thus, when introducing proper jujube varieties, leaf venation characteristics should be taken into consideration. The jujube varieties that have leaf VLA, area, and perimeter similar to existing local varieties, might adapt more easily to the new environment.
Conclusions
Jujube is a drought-tolerant tree species stretching across a variety of climatic conditions in China. This study summarized the survey results of 116 varieties of Chinese jujube grown in different environments across 33 sites in China. The results show that some important characteristics of jujube leaf morphology are linearly related to climatic factors such as MAT and MAP. Under drought stress, Chinese jujube tends to have higher VLA, and lower leaf area and leaf perimeter than varieties from humid regions. VLA was one of the key anatomical traits closely related to jujube transpiration and photosynthesis. VLA values varied among the sampling sites and were sensitive to climate. There was a linear relationship between jujube leaf VLA and the climatic factors MAP and MAT. By contrast, the shapes of jujube leaves (represented by leaf outline permeter 2 /area) were largely insensitive to MAT and weakly, linearly related to MAP.
Jujube from the Gansu, Ningxia and Shaanxi provinces had relatively higher VLA values and lower leaf area and perimeter. This was particularly the case for varieties from Gansu Province. Jujube varieties from Shandong, Henan, Shanxi and Hebei provinces had relatively lower VLA and higher leaf area and perimeter. According to the analysis of leaf morphological traits, different jujube varieties have gradually adapted to the local climatic conditions in their areas of origin. The jujube varieties were similar in morphology when grown under similar environmental conditions.
The results of PCA of leaf venation characteristics of 116 jujube varieties confirmed that the division into three main jujube cultivar areas in northern China is reasonable. Leaf morphological traits might be used as reference indices for jujube introduction between different areas. Generally, the jujube varieties with leaf VLA, area, and perimeter similar to existing local varieties might be easier to introduce.
Supporting Information S1 Table. Jujube varieties studied for leaf morphological traits in this study. A total of 116 different jujube varieties were sampled in 33 sites in northern China. (DOC) | v3-fos |
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} | s2 | Genetic analysis reveals diversity and genetic relationship among Trichoderma isolates from potting media, cultivated soil and uncultivated soil
Background Trichoderma is one of the most common fungi in soil. However, little information is available concerning the diversity of Trichoderma in soil with no previous history of cultivation. This study was conducted to investigate the most common species and the level of genetic relatedness of Trichoderma species from uncultivated soil in relation to cultivated soil and potting media. Results A total of 24, 15 and 13 Trichoderma isolates were recovered from 84 potting media samples, 45 cultivated soil samples and 65 uncultivated soil samples, respectively. Analysis based on the internal transcribed spacer region of the ribosomal RNA (rRNA) and the translation elongation factor gene (EF1) indicated the presence of 9 Trichoderma species: T. harzianum (16 isolates), T. asperellum (13), T. citrinoviride (9), T. orientalis (3), T. ghanense (3), T. hamatum (3), T. longibrachiatum (2), T. atroviride (2), and T. viride (1). All species were found to occur in potting media samples, while five Trichoderma species were recovered from the cultivated soils and four from the uncultivated soils. AFLP analysis of the 52 Trichoderma isolates produced 52 genotypes and 993 polymorphic loci. Low to moderate levels of genetic diversity were found within populations of Trichoderma species (H = 0.0780 to 0.2208). Analysis of Molecular Variance indicated the presence of very low levels of genetic differentiation (Fst = 0.0002 to 0.0139) among populations of the same Trichoderma species obtained from the potting media, cultivated soil and uncultivated soil. Conclusion The study provides evidence for occurrence of Trichoderma isolates in soil with no previous history of cultivation. The lack of genetic differentiation among Trichoderma populations from potting media, cultivated soil and uncultivated soil suggests that some factors could have been responsible for moving Trichoderma propagules among the three substrates. The study reports for the first time the presence of 4 Trichoderma species in Oman: T. asperellum, T. ghanense, T. longibrachiatum and T. orientalis.
Background
Trichoderma species are free living fungi that are commonly found in soil and woody materials. They are symbionts on plants and play an important role as antagonistic fungi towards pathogenic fungi [1,2]. Trichoderma species are generally characterized by their rapid growth and ability to survive in variable environmental conditions. They are commonly found in agricultural lands, forests, and deserts. They are important contributors in the decomposition of plant materials. Some species of Trichoderma are economically important because of their ability to produce industrial enzymes and antibiotics [3,4]. Soil-based system is the preferable choice for production of vegetables in the Arabian Peninsula and in different parts of the world. However, due to poor soil characteristics [5][6][7], many growers tend to use potting media and organic fertilizers in the production system of vegetables. In addition, they also replace farm soil with uncultivated soil (fallow soil) in order to reduce populations of soilborn fungal pathogens [7]. Trichoderma species are known to be very common in cultivated soils and potting media [8][9][10][11]. However, no information is available concerning diversity of Trichoderma in uncultivated soil and their relationship to Trichoderma species from cultivated soil and potting media. This makes it difficult for growers to know the impact of soil replacement on lowering Trichoderma diversity in farm soil.
Populations of fungi can vary in their levels of genetic diversity from one species to the other [12], one geographical region to the other [13] and between different cultivation systems [14]. As a result, several molecular markers have been developed and used to characterize the level of genetic diversity within and among fungal populations. These include the use of isozyme variation, Restriction Fragment Length Polymorphism (RFLP), Amplified Fragment Length Polymorphism (AFLP) and Random Amplified Polymorphic DNA (RAPD). AFLP has been found to be powerful in the characterization of genetic diversity among and within populations of different fungi [15,16].
This study was conducted to characterize the genetic diversity of Trichoderma species in uncultivated soils and their genetic relationship with Trichoderma species isolated from cultivated soils and potting media. Results will provide a basis for future studies on Trichoderma in soil and potting media.
The ITS rRNA gene showed higher level of intraspecific variation compared to the EF1 gene, which gave higher resolution in separating Trichoderma species. The bootstrap support for separating species from each other was 99 % for the EF1 gene (Fig. 2). However, the bootstrap support for separating species based on the ITS rRNA gene showed that it ranges from 67 to 100 %, with one species (T. asperellum) not forming a tight cluster (Fig. 1). When the sequences of ITS rDNA and EF1 were used to produce a single tree, the resolution in separating Trichoderma species imporved to 99-100 % bootstrap support (Fig. 3).
No relationship was observed between clustering of the isolates based on ITS rDNA or EF1 sequences and clustering based on the substrates from which the isolates were obtained (Figs. 1, 2; Table 1). For example, T. harzianum isolates grouped into several sub-clusters. However, neither ITS-based sub-clustering, nor EF1-based sub-clustering correlated with the substrates from which the isolates were obtained. All ITS and EF1 sequences were deposited in the European Nucleotide Archive ( Table 1).
Analysis of diversity within populations of Trichoderma species
Analysis of 52 Trichoderma isolates using 3 primer-pair combinations produced 993 polymorphic loci (100 % polymorphism), with the percentage of polymorphic loci ranging from 16 % to 80 % for the different Trichoderma species. The number of polymorphic loci produced by the three primer combinations were 277 (EcoRI-AGA/ MseI-CAT), 389 (EcoRI-AGT/MseI-CAT) and 327 (EcoRI-AGT/MseI-CAA). The three primer pair combinations also resulted in moderate levels of Nei's gene diversity, which were 0.1732, 0.2632 and 0.1810 respectively. AFLP analysis of the 52 Trichoderma isolates produced 52 different AFLP genotypes ( Table 2; Fig. 4). Each isolate representing a genotype differed from the others by at least 155 alleles. Trichoderma isolates showed a moderate level of genetic diversity (H = 0.2110). Trichoderma viride was excluded from population specific analysis of genotypic and genetic diversity because it consisted of one isolate. The seven populations differed in their level of gene diversity. The percent polymorphic loci ranged from 16 to 80 % and Nei's gene diversity estimates ranged from 0.0780 to 0.2208 (Table 2).
Genetic similarity and cluster analysis
The level of genetic similarity among the seven populations was found to vary from 92 to 99 %. T. asperellum, T. harzianum and T. citrinoviride were found to share a high level of genetic similarity (Fig. 4a). Trichoderma atroviride shared the least level of genetic similarity with other Trichoderma species. Cluster analysis showed that T. asperellum, T. harzianum, T. citrinoviride, T. ghanense and T. longibrachiatum clustered together (Fig. 4a). Cluster analysis of the three most common species (T. asperellum, T. harzianum, and T. citrinoviride) showed that there was no relationship between clustering of isolate of the same species and the substrata from which they were isolated (Fig. 4b). In addition, there was no relationship between clustering of Trichoderma isolates and the species they belong to.
Partition of genetic variation
Analysis showed that the percent genetic variation is 1.39 % among populations of T. asperellum obtained from potting media, cultivated soil and uncultivated soil (F = 0.0139; P = 0.3059). The percent genetic variation among populations of T. harzianum obtained from potting media, cultivated soil and uncultivated soil was found to be 0.02 % (F = 0.0002; P = 0.4575). These values indicate that most of the genetic variation is within populations of the same species. They also indicate that the level of gene flow among populations of fungal isolates is high among potting media, cultivated soil and uncultivated soil.
Discussion
Trichoderma is a widespread genus of fungi. Previous studies in Oman provided evidence for occurrence of T. hamatum in the greenhouse soil [5] and T. harzianum, and T. parceramosum in desert crusts [17]. Our current investigation revealed presence of 9 Trichoderma species in potting media samples, 5 species in cultivated soil samples and 4 species in uncultivated soil samples. The higher level of diversity in Trichoderma species in potting media is related to the fact that these material consist of different organic and inorganic ingredients including peat moss, sphagnum, shredded bark, sawdust, vermiculite, perlite, clay and sand [18]. The Trichoderma species could have therefore been naturally occurring in these products or they could have been introduced after composting [18,19].
Identification of Trichoderma to the species level based on reference sequences from the National Center for Biotechnology Information correlated with phylogenic analysis based on sequences of the ITS rRNA and EF1 genes. However, the limited intraspecific variation within Trichoderma species based on sequences of the EF1 gene helped gave better resolution in separating Trichoderma species when compared to sequences of the ITS region. The EF1 gene, especially when combined with ITS rDNA data, can give better resolution and is increasingly used in the identification of several fungal species [16,20]. The frequency of isolation of Trichoderma from cultivated soil (33 %) was higher than that from uncultivated soil (20 %). Since none of the sampled farms add commercial products of Trichoderma to soil, Trichoderma isolates could have been naturally occurring in the cultivated soil. Another possible source of Trichoderma into farms is the use of potting media. Many farmers in Oman use potting media products for germination of vegetable crops or in soil [7,11]. Since findings from this study and from previous studies indicated that potting media act as a source of Trichoderma [10], it is possible that potting media contributed to moving Trichoderma isolates to cultivated soils. Our study showed the occurrence of four Trichoderma species in soils with no previous history of cultivation. Wind driven sand, which is common is Oman, could have contributed to moving some Trichoderma propagules to areas without vegetation [7]. The lack of relationship between AFLP based clustering of Trichoderma isolates and their origin as well as the insignificantly (P > 0.05) very low levels of genetic differentiation among populations of the same species obtained from cultivated and uncultivated soils may explain the hypothesis of movement of Trichoderma isolates between cultivated and uncultivated soils. In addition, some of the Trichoderma isolates were recovered from soil trapped behind dams. During rainy periods in Oman, which are very limited in this part of the world, the flowing water from mountainous areas is usually trapped behind dams. Since it is common to find Acacia spp. and some other plants in the way of the flowing water, it is possible that Trichoderma propagules could have been moved by the flowing water and then deposited in the dam soil. A study is in progress to characterize naturally occurring fungal species in the path of flowing water and from the rhizosphere of wild plants.
Farmers in Oman usually replace farm soils with uncultivated soils imported from soils trapped behind dams or non-cultivated lands. Besides reducing pathogen inoculum in farms [7], this practice could help introduce beneficial Trichoderma isolates, especially T. asperellum and T. harzianum, into farms.
Several species of Trichoderma have been long used as biological control agents to manage diseases of vegetable and other crops [10,21]. Trichoderma harzianum and T. asperellum are the two most common species and were isolated from potting media, cultivated soil and uncultivated soil. T. harzianum is a common species in soil and potting media and it is commercially used as a biological control agent [10,21]. T. asperellum has been used for induction of resistance to different diseases [22,23]. The relatively high level of occurrence of T. asperellum and T. harzianum in Oman soils (82 % of the total isolates) might contribute to improving soil health through disease suppression in different crop systems The overall level of genetic diversity of Trichoderma isolates was found to be moderate (H = 0.2110). The level of genetic diversity for the different species varied from 0.1133 to 0.2208. However, clustering based on AFLP data did not correlate with sources of the isolates, nor with clustering based on the ITS rRNA and the EF1 genes. Variation in the level of genetic diversity and sequences among the different species could be related to several reasons. Multiple introductions of Trichoderma isolates into Oman could have played a major role in augmenting the genetic diversity of Trichoderma populations [15,16,24]. The hypothesis of multiple introductions is supported by the formation of several AFLP genotypes and the lack of relationship between AFLP data and the source of the isolates. It is also supported by the lack of relationship between ITS/EF1 based clustering and the sources of Trichoderma isolates. This may indicate that the isolates were introduced at different times and from different sources. Other factors which could have affected the level of genetic diversity is the differences in the reproduction modes and the level of sexual recombination between the different species [15,16].
Conclusion
This study provided evidence that the diversity in Trichoderma species varies from one substrate to the other. This is the first report showing T. asperellum, T. ghanense, T. longibrachiatum and T. orientalis in Oman. AFLP analysis suggested possible introductions of Trichoderma isolates from potting media into cultivated soil and also movement of Trichoderma between cultivated and uncultivated soils. The relatively high level of diversity in Trichoderma species and isolates may give an indication about the health of soil and its ability to contribute in the suppression of soilborn diseases that affect different crops. In addition, the high diversity may make it possible to find and select Trichoderma isolates with high antagonistic properties. Studies are in progress to characterize the biological properties of some of the Trichoderma isolates obtained in this study. Future studies are required to focus on characterizing Trichoderma isolates and other biocontrol agents from extreme environments in order to come up with isolates that can tolerate the harsh conditions of arid countries.
Collection of Trichoderma
Trichoderma isolates were obtained from potting media, cultivated soil and uncultivated soil. Twenty four Trichoderma isolates were obtained from 84 potting media products originating from Oman, The Netherlands, Estonia, Germany, Finland, Latvia, or UK (trade names are kept anonymous). Isolations from these products were done using direct plating technique as previously described by Al-Sadi et al. [11]. Fifteen Trichoderma isolates were obtained from 45 samples of cultivated (farm) soils planted with date palm, cucumber, tomato, bean, alfalfa, pepper or potato. This was done by collecting approximately 50 g soil sample from the top 15 cm of the rhizosphere of each plant species. The samples were collected from Barka, to the North-West of Muscat and from Seeb during 2013.
Trichoderma isolates (13) were also obtained from 65 uncultivated soil samples with no known history of previous cultivation. Collection of soil samples from uncultivated soil was done by collecting 50 g soil from the top 15 cm of soil (Table 1). The sites from which the samples were collected were 5-17 Km away from the coastal area of Barka and Seeb districts. The sites have no previous history of cultivation with any crop and the temperature ranges from 15°C in the winter to 49°C in summer (avg. 32°C). Collection of soil samples from cultivated and un-cultivated soil was during the period from April to November 2013.
Isolation and identification of Trichoderma
Isolation of Trichoderma from soil samples was achieved using direct plating as described by Al-Sadi et al. [11]. Approximately 100-150 mg of soil sample was spread on the surface of 2.5 % potato dextrose agar (PDA) amended with 50 mg l −1 Rose Bengal. Each soil was plated onto three replicate Petri dishes and the Petri dishes were incubated at 25°C for 5-7 d. Growth of fungal isolates which was typical of Trichoderma species was excised and transferred to 2.5 % PDA amended with 10 mg l −1 rifampicin.
Fungal isolates with typical growth of Trichoderma species were confirmed to the species level using sequences of the internal transcribed spacer region of the ribosomal RNA gene (ITS rDNA). Mycelia were collected from 7-10 day old cultures of Trichoderma species. Mycelia were collected in Eppendorf tubes and kept at −80°C overnight. This was followed by freeze drying of the collected mycelia.
DNA was extracted from 80 mg freeze dried mycelia following a modified protocol of Lee and Taylor [25]. The ITS rRNA gene region of the fungal isolates was amplified using the universal primers ITS1 and ITS4 [26]. The polymerase chain reaction mixture was carried out using PuReTaq™ Ready-To-Go PCR™ beads (HVD Life Sciences, Vienna, Austria), 0.4 μM ITS1, 0.4 μM ITS4, 25 ng DNA and made up to 25 μl with sterilized distilled water. Thermocycling was run with the following settings: heating at 95°C (10 min); then 35 cycles of 95°C (30 s), 55°C (30 s) and 72°C (90 s). The final extension was done at 72°C for 10 min. Amplification of the ITS region was checked out by running 5 μl of the sample on 1.5 % agarose gel in 0.5× Tris-borate-EDTA buffer (TBE) at 120 V for 50 min.
PCR for EF1 gene was conducted using primers EF1-728 F and EF1-986R [20]. The PCR mixture was as described for ITS rDNA. PCR conditions consisted of denaturation at 94°C for 4 min, followed by 35 cycles of denaturation at 94°C for 30 s, annealing at 60°C for 30 s and extension at 72°C for 60 s. This was followed by extension at 72°C for 10 min. PCR products were checked by running 5 μl of a PCR product on 1.5 % agarose gel in 5× TBE at 120 V for 40 min.
PCR products were sequenced at Macrogen Inc. (Korea, Seoul) in both senses using the ITS1, ITS4, EF1-728 F and EF1-986R. The resulting forward and reverse ITS and EF1 sequences were aligned and edited using ChromasPro v. 1.41 (Technelysium Pty Ltd). Then, the obtained sequences for each isolate were compared to sequences available at the National Centre for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov) using BLAST search.
Nine reference ITS sequences representing 9 Trichoderma species were obtained from NCBI. The nine representative sequences were aligned with the sequences of the 52 isolates obtained in this study using Clustal W [27]. A neighbour joining tree was constructed using the Kimura 2 parameter evolutionary model (Mega 5) [28]. Consensus trees were generated using 1000 replications (55 % bootstrap criteria).
The pre-selective amplification product was diluted by adding 210 μl of TE 0.1 buffer (20 mM Tris-HCl, 0.1 mM EDTA, pH 8) to the remaining amount. The selective amplification reaction was as above except using 0.13 μl of 10 μM FAM-6 labeled EcoRI selective primer, 0.63 μl of 10 μM MseI selective primer, 6 μl of diluted preselective amplification and Milli-Q water to a volume of 25 μl. The cycling parameters for the selective amplification were as described by Al-Sadi et al. [16]. Fragment analysis of the PCR products from the selective amplification reactions was carried out at Macrogen Inc. (Seoul) using ABI 3730XL (Applied Biosystems, Carlsbad, CA).
Analysis of AFLP data
Analysis of AFLP data was done to estimate gene diversity, genotypic diversity, genetic distance and genetic differentiation within and among different populations. AFLP alleles in the range of 50 to 500 base pairs (bp) were evaluated using Gene Mapper 4.0 with 0 for absence and 1 for presence of each amplified fragment. The binary data were analyzed using POPGENE version 1.32 [29] which was used to calculate the number of polymorphic loci, Nei's gene diversity [30] and genetic distance and identity within and among the different populations of Trichoderma species. Genetic distance based on Nei's [31] unbiased measurement of genetic distance was also determined between samples and populations of Trichoderma species using POPGENE. A dendrogram was constructed based on Nei's unbiased measures of genetic distance using UPGMA (unweighted pair group method with arithmetic mean; NTSYSpc v. 2.21 m).
Analysis of molecular variance (AMOVA) was used to determine genetic differentiation among the different populations using Arlequin v. 3.1 [32]. AMOVA was conducted only for populations of T. asperellum and T. harzianum because each species included at least 2 isolates from each substratum. | v3-fos |
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} | s2 | Investigation of metabolites accumulation in medical plant Gentiana rigescens during different growing stage using LC-MS/MS and FT-IR
Background Gentiana rigescens, an important medicinal plant in China, has been widely cultivated in Yunnan province, China. Previous studies were focused on analysis and determination of the metabolites isolated from this species, the accumulation of these metabolites during growth period are not yet clear. In this study, samples for the experiments were obtained by tissue culture. FT-IR and LC-MS/MS method were performed to distinguish the variation on the major metabolites in G. rigescens during growing stage when combined with chemometrics. Results Methodology validations were all within the required limits. The metabolites were visually different in tissue culture samples and mature plants. The diversity of metabolites increased proportionally with plant growth. The quantitative analysis showed the content of gentiopicroside was significantly vary during different growing stage. The highest content of gentiopicroside (122.93 ± 7.01 mg/g) was detected in leaf of regenerated plantlet, whereas its content in root significantly increased along with underground parts growth. Moreover, flavonoids mainly distributed in aerial parts showed potential competitive relationship during plant growth. Conclusion The distribution and accumulation of metabolites are associated with different parts and plant growth, which provide potential evidences for the rational application and exploitation of G. rigescens. Electronic supplementary material The online version of this article (doi:10.1186/s40529-015-0094-6) contains supplementary material, which is available to authorized users.
Background
Gentiana rigescens Franch belonging to Gentianaceae is an important medicinal plant in China for treatment of hepatitis, jaundice and dysentery. The root and rhizome of this plant has been officially documented in Chinese Pharmacopoeia as one of raw materials of Gentianae Radix et Rhizoma (Longdan in Chinese), a hepatoprotective agent (State Pharmacopoeia Commission 2010). According to ethnobotanical information, its aerial parts are also used as folk medicine for treatment of fever and rheumatic arthritis or as antiophidica, when prepared with vegetable oil. The phytochemistry and bioactivities of G. rigescens have been intensively studied. More than 100 secondary metabolites with different activities like hepatoprotective, anti-inflammatory, antioxidant and neuritogenic growth have been isolated from this plant (Gao et al. 2010a(Gao et al. , 2010bXu et al. 2006Xu et al. , 2007Xu et al. , 2009a; Wang et al. 2012). Among them, iridoid glycosides is the most abundant components especially gentiopicroside which content is more than 4.5 % and serve as major active ingredient and standard for quality control (Jiang et al. 2005;Pan et al. 2015a;Wang et al. 2012).
As one of well-known traditional Chinese medicine with remarkable medicinal functions, the wild resources have been under heavy threat owing to human activities and environmental pollution. Although G. rigescens have been extensively planted in Yunnan, some disadvantages on cultivation such as continuous cropping obstacle, time-consuming and laborintensive, etc. result in decline of production and quality. Fortunately, plant tissue culture is conducive to the accumulation of biomass and metabolites, in particular with individual metabolites, which amount is multifold higher than control group when treated with appropriate elicitors (Chuang et al. 2014;Huang et al. 2014;Kuzovkina et al. 2014;Kumari et al. 2015;Marsh et al. 2014;Su et al. 2014). However, the efficacy of medical plant, to a large extend, are attributed to synergistic effect of a number of metabolites. The amount of individual metabolites is significantly increased, which might lead to different pharmacological activities and therapeutic effects.
On the other hand, previous studies (Jiang et al. 2005;Pan et al. 2014Pan et al. , 2015aWang et al. 2012) on metabolites of G. rigescens were most focused on quality assessment, phytochemistry, pharmacology, etc. However, metabolites are not only the efficacious properties for maintaining human health, but also play an important role for resistance to abiotic and biotic threats during plant growth (Hall et al. 2008;Wink 2003). To our best knowledge, the accumulation and variation of metabolites in G. rigescens have not yet clear.
Currently, analysis of metabolites based on separation technologies such as gas chromatography-mass spectrometry (Hu et al. 2014), liquid chromatography coupled with photodiode array detector (Yu et al. 2014), mass spectrometry detector (Won et al. 2014) and nuclear magnetic resonance spectroscopy (Hilbert et al. 2015) can rapidly provide complex chemical information and clarify the similarities and differences of bio-samples when combined with chemometrics. However, comprehensive chemical information on metabolites cannot be analyzed in a single chromatogram. Fourier transform infrared spectroscopy (FT-IR) enables to rapid reflect holistic molecular structure-analyte relationships, which is considered as a well-established and non-destructive method for analysis of bio-sample, whereas it fails to recognise the variation of specific compound in sample due to the limited specificity and sensitivity (Karoui et al. 2010;Lohumi et al. 2014;Zhao et al. 2014).
In this study, the variation on distribution and accumulation of metabolites in G. rigescens are investigated based on plant tissue culture. Individual parts of sample during different growing stage are subjected to targeted and non-targeted analysis using FT-IR and liquid chromatography tandem mass spectrometry (LC-MS/MS). Moreover, the biosynthetic pathway of iridoid glycosides is also discussed. The combinative comparison approach can reflect the overall chemical difference during different growing stage, which may provide the useful information for reasonable utilization of resources. KBr (specpure) was purchased from Tianjin FengChuan Fine Chemical Research Institute (Tianjin, China). Methanol and formic acid (assigned purity > 98 %) were LC grade and purchased from Thermo Fisher Scientific (USA) and Dikmapure (USA), respectively. Water was purified to 18.25 MΩ using Milli-Q system from Millipore (USA). All other chemicals for extraction were analytical grade. The standard compounds (1. loganic acid, 2. swertiamarin, 3. gentiopicroside, 4. sweroside, 5. isoorientin and 6. isovitexin) (Fig. 2) were provided by Chinese National Institute for the Control of Pharmaceutical and Biological Products (Beijing, China). Their assigned purity were all >98 %.
Apparatus
Tablet press (YP-2, Shanghai Shanyue instrument Inc) was used to press powder into thin samples. The FT-IR spectrometer (PerkinElmer, USA) equipped with a DTGS detector. IR spectra were recorded from the accumulation of 16 scans in 4000-400 cm −1 range with a resolution of 4 cm −1 .
Separation, quantitation and quantification of metabolites were performed on a Shimadzu Nexera UHPLC tandem mass spectrometry (LCMS-8030, Shimadzu, Japan) equipped with a Shim-pack XR-ODS III (75 × 2.0 mm, 1.6 μm) column, UV detection and triple quadrupole mass spectrometer via an electrospray ionization (ESI) interface. The mobile phase consisted of 0.1 % formic acid in water (A) and methanol (B) was applied at a flow rate of 0.35 mL/min with gradient as follow: initial, 13 % B; 0.31-7.00 min 20 % B linear, 7.01-13.00 min 46 % B linear, 13.01-16.50 min 83 % B linear; followed by a final increase to 90 % in 1 min. After a 3 min wash, the column was reconditioned at 13 % B for 3 min to prepare for the next injection. Injection volume and column temperature were 1 μL and 40°C, respectively. The detection wavelength was set at 242 nm, where all the standards and UPLC profiling showed a satisfactory performance.
High-resolution electrospray ionization mass spectrometry was performed using a Agilent G6550 QTOF (Agilent technologies Santa Clara, CA, USA) equipped with an ESI inter-face. Mass spectra were acquired in both positive and negative modes over the range m/z 100-1000. The capillary voltages were set at 3000 V (positive mode) and 2700 V (negative mode), respectively, and nozzle voltage was 300 V. Sheath gas and drying gas were nitrogen at a flow rate of 3.0 and 14.0 L/min, respectively, nebulizer pressure was 20 psi. The precise molecular mass was determined by the accurate-mass data of the TOF analyzer within a reasonable degree of measurement error, normally with mass errors below 5 ppm in routine analysis, which was sufficient to verify the elemental compositions of the known constituents in G. rigescens.
The quantification of the targeted compounds with low concentration was carried out on multiple reaction monitoring (MRM). The settings of MRM were autooptimized by Labsolutions software (Shimadzu, Japan). The triple quadrupole mass spectrometer parameters were set as follows: nebulizing gas and drying gas were nitrogen at a flow rate of 3.0 and 15.0 L/min, respectively; the interface voltage was set to 4.5 kV; desolvation line (DL) temperature was 250°C and the heat block temperature was 400°C. Reference solutions containing ions of m/z 503.15 and 1004.60 were continuously introduced into the MS system during the analysis procedure to ensure the accuracy of the measured mass.
Sample preparation
Fresh samples were dried at 60°C and ground into fine powder. Then, 2 mg sample was blended with 200 mg KBr powder, ground again and pressed into a tablet. The FT-IR spectra of all samples were collected three times after by subtraction of KBr pellet background.
Sample preparation was based on our previous work (Pan et al. 2015b (0.1 g) was extracted by ultrasonication with 7 mL 80 % methanol for 35 min. The extract solution were filtered through a paper filter. Then, the filtrate were stored at 4°C and filtered through a 0.22 μm membrane filter before injection into the LC system for analysis. Injection volume was 1 μL.
Data analysis
The raw FT-IR spectroscopy were processed by Omnic 8.0 (Thermo Fisher Scientific, USA). The peaks of UV and mass data were picked and filtered by Labsolutions software (Shimadzu, Japan). Principal component analysis (PCA), an unsupervised chemometric approach for classification, was exploited to optimize the complex data set for reflecting relationships among different samples. The PCA was performed by software SIMCA-P + 10.0 (Umetrics AB, Sweden).
Results
Comparative analysis of G. rigescens in different growing stage FT-IR and LC-MS/MS were used to investigate the metabolites variation in both integrity and detail on chemical information in different plant part and growing stage. There are few visual differences in averaged FT-IR spectra of different sample. In order to explore the relationships between metabolites and plant growth, the 1800-600 cm −1 region of the FT-IR spectral data without the interferences of CO 2 and H 2 O were subjected to PCA. A two-dimension (2D) scores plot (PC1 × PC2) was constructed from a data matrix (623 × 54) by PCA which could visually reflect the similarity between IR spectra and samples in this plot where the closer the points, the more similar the spectral data. In PCA, the first and second principal components cumulatively accounted for 92.8 % of the total variance, which suggested that the former two principal components could explain the proportion of the experimental data. In Fig. 3, sample of mature plant and samples during proliferation stage were explicitly separated into two groups. However, samples in the corresponding groups were crossed and could not be classified according to their plant parts or growing stage. These results implied that the whole metabolome based on FT-IR spectra were significant different, whereas these the detailed variation failed to be monitored especially for content of individual metabolites. Moreover, a targeted method based on LC-MS/MS was designed for monitoring variations of iridoid glycosides and flavonoids. The 80 % MeOH extracts of G. rigescens were injected into LC-MS/MS system for analysis. As shown in Fig. 4a-i, peak numbers and their peak areas were visually different in samples, especially for peaks a, 3, 5, 6, b and c, which indicated the accumulation of metabolites varied with plant growth. For example, peak b and c were only found in leaf of mature plant. Furthermore, peak a is one of characteristic marker in chromatogram of callus, whereas it could not detected in chromatogram of mature plant.
Except for peak 1-6 which can be unambiguously identified by standard compounds, other peaks in chromatogram are still unknown. In order to further clarify metabolites variations during growing stage, peak a-g (Additional file 1: Table S1), characteristic markers in chromatogram of samples, were tentatively identified via matching the mass data (high revolution data and MS/MS spectra) with published works on chemical compounds isolated from G. rigescens. According to comparison of mass data of standard compounds, peak b and c could be tentatively assigned as flavonoids while peak d-g were iridoid glycosides. In mass spectra of isoorientin and isovitexin (Additional file 1: Figure S1, see supplement data), the characteristic neutral loss of 90 and 120 Da are correspond to C-glycosidic structure, which could be considered as diagnosed markers. Interestingly, the mass data of peak b and c (Additional file 1: Figure S1) were highly similar with isoorientin and isovitexin, respectively. Besides, the neutral loss of 162 Da, the feature of glucosyl group, Furthermore, a neutral loss of 136 Da which may correspond to the loss of a dihydroxy benzoyl group via a classical McLafferty-type rearrangement (Tan et al. 1996;Xu et al. 2009b) was observed in mass spectrum of peak d-g. By further analyzing the mass data, peak d-g were dihydroxy benzoyl iridoid glycosides. Their mass spectrum and fragmentation pattern are shown in Additional file 1: Figure S2. In mass spectrum of peak a, the product ions at m/z 153 and 109 were correspond to losing a glucose (162 Da) and carboxyl group (44 Da), indicating peak a (m/z 315.0832 [M-H] − C 13 H 16 O 9 ) were tentatively assigned as O-glucosyl-dihydroxy benzoyl acid (Additional file 1: Figure S3) (Xu et al. 2009a). All compounds but peak 1-6 were identified by matching corresponding mass data in previous studies.
Method validation and quantification
Standard solutions of each compounds with seven different concentrations were prepared individually in methanol and were injected into LC-MS/MS system for generation of external standard calibration curves. Calibration curves for each compound were performed by plotting the peak area (y) against the concentrations (x, μg/ml). The correlation coefficients (R 2 ) of each calibration curve were more than 0.9992. The limits of detection (LOD) and quantification (LOQ), S/N (signal-to-noise ratio) of 3 and 10, were determined by serial dilution of each standard solution using the described conditions. The LOD and LOQ for UV detector and mass analyzer, together with standard calibration curves of each standards, were listed in Table 1. Precision was evaluated by intra-and inter-day variation which determined by analyzing mixed standard solutions with known concentration six times within a day and on three consecutive days in triplicate. The intra-and inter-day precision of peak area (expressed in terms of %RSD) were in the range of 0.76-2.27 %. Accuracy was validated by recovery test performed by accurately adding three different amounts (low, medium and high spike) of each standard to the crude sample. The recovery rates of six standards were ranged from 97.3-102.6 % and their RSD values were less than 3 %. Then, six independently samples analysed by repeating the described produce of sample preparation under this chromatographic condition were used to investigate the repeatability. These results are displayed in Table 2.
In this study, the identification of standards in the chromatogram was confirmed by retention times and ion pairs determined by MRM. Quantification depended on the external standard method. The contents of the six standards in G. rigescens during different rowing stage are listed in Table 3. The results showed that the content of the six standards differed greatly in different stage. The lowest contents of all standards were found in callus. Gentiopicroside was the highest yield compound in the whole growth stage. The highest gentiopicroside yield was found in leaf of regenerated plantlet (122.93 ± 7.01 mg/g), followed by root of mature plant (96.78 ± 8.54 mg/g). Interestingly, gentiopicroside yield was reduced and tended to accumulate in root after regenerated plantlet. Furthermore, root did not contain the two flavonoids. The highest content of the two flavonoids were observed in leaf. For isoorientin, the highest content was found in mature plants. On the contrary, the highest isovitexin yield was detected in proliferation stage.
Discussions
According to the results of comparative analysis, the distribution and accumulation of metabolites are associated with plant growth. The whole metabolome in different stage are significantly different. The reason might be attributed to (1) elicitors in medium and (2) environment conditions such as soil, sun exposure time and rainfall, which could also result in fluctuation on the distribution and accumulation of metabolites after transplant (Manukyan 2011;Marsh et al. 2014;Xie et al. 2011). Additionally, the proportion among metabolites vary with plant growth. The proportion of peak a (O-glucosyldihydroxy benzoyl acid) in chromatogram gradually reduce with the increase of other metabolites. Based on the identification of peak d-g, O-glucosyl-dihydroxy benzoyl acid may transformed into dihydroxy benzoyl iridoid glycosides via esterification of iridoid glycosides. The obvious differences are observed in chromatogram of leaf during different stage especially for peak b and c (O-glycosidic derivatives of isoorientin and isovitexin) which only is detected in mature plant. These result implied that the synthesis and transform of metabolites with complex molecular structure tend to be in mature plant with more abundant substance when compared with plant during in proliferation stage. Gentiopicroside is the characteristic compound with the highest amount in G. rigescens, which serve as standard for quality control of G. rigescens (State Pharmacopoeia Commission 2010; Wang et al. 2012). Combined with previous study on Gentiana scabra , another raw materials of Gentianae Radix et Rhizoma, 1.8 higher-fold gentiopicroside content was observed in sample of hair root culture than plants grown in greenhouse. Although leaf in regenerated plantlet contains the highest gentiopicroside yield in this study, it can only be used for industrial extraction of gentiopicroside rather than medical application because the efficacy of herb medicine, to large extend, is derived from synergistic effect of metabolites. The variation on the accumulation of gentiopicroside in different stage is present in Fig. 5a. An interesting phenomenon that gentiopicroside content in root is significant raised with evidently decrease in leaf and stem, when the root start to regenerate. During this stage, root growth rate is far higher than in stem and leaf with the occurrence of gentiopicroside growth, which could be consistent with the results of specifictissue analysis where the distribution of secondary metabolites vary in different tissue. Moreover, gentiopicroside in aerial parts may translocate into root or transform into other metabolites when the root start to regenerate. In leaf, a significant negative correlation is found between isoorientin and isovitexin (Fig. 5b). From the biosynthetic pathway of view, it can be explain that these two flavonoids are competitive relationship in a common biosynthetic pathway. Additionally, isovitexin can also be considered as a precursor of isoorientin and O-glycosidic isovitexin in this pathway. This may explain why the isovitexin first increase during proliferation stage, and then decrease.
Conclusions
In the present study, the combination use of FT-IR, LC-UV-MS/MS and chemometrics was designed for investigation of the variation on metabolites during different growing stage of G. rigescens. For whole metabolome, the molecular structure-analyte relationships are significantly different between plants during proliferation stage and mature plants according to FT-IR analysis. Combined with LC-UV-MS/MS, mature plants contains more abundant secondary metabolites than plants during proliferation stage, whereas the higher content of some characteristic metabolites like gentiopicroside and peak a are observed in plants during proliferation. Moreover, the distribution and accumulation of metabolites, together with biosynthetic pathway, are associated with plant growth and significantly vary during different growing stage. In practical application, the root in mature plants with rich chemical components could be of better quality for medicinal application, whereas leaf in regenerated plantlet would be used for industrial extraction | v3-fos |
2015-09-18T23:22:04.000Z | {
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} | s2 | Trifolium pratense and T. repens (Leguminosae): Edible Flower Extracts as Functional Ingredients
Trifolium pratense (red clover) and T. repens (white clover) edible flowers were investigated for their chemical profile and health properties. The total phenols and flavonoids contents were evaluated. Quercetin, kaempferol, luteolin, rutin, and myricetin were used as markers and quantified by HPLC. The antioxidant effects were investigated by using different in vitro assays. Moreover, α-amylase, α-glucosidase and lipase inhibitory activities were evaluated. T. repens flowers extract showed a good radical scavenging activity in both DPPH and ABTS tests with IC50 values of 10.3 and 21.4 μg/mL, respectively. White clover extract demonstrated promising α-amylase and lipase inhibitory activities with IC50 values of 25.0 and 1.3 μg/mL, respectively. The obtained results support the use of Trifolium flowers as healthy food ingredients.
Introduction
Trifolium is one of the most important genera of the Leguminosae family [1]. Trifolium species are generally known as clover. Its flowers have a sweet and mild licorice flavor and are traditionally used garnish or ingredient in salads, soups, entrees, desserts, and drinks worldwide [2]. They are used not only to improve appearance of meals but also for their nutritive value [3].
Polyphenols are phytochemicals generally involved in defense against ultraviolet radiation or aggression by pathogens. Epidemiological studies suggest that long term consumption of diets rich in plant polyphenols offer protection against chronic disease such as diabetes and obesity. In food, polyphenols may contribute to the bitterness, astringency, color, flavor, odor and oxidative stability [4].
Diabetes and obesity are the biggest public health challenge of the 21st century. Type 2 diabetes or non-insulin-dependent or adult-onset results from the body's ineffective use of insulin or as consequence of low amounts of insulin production from pancreatic β-cells or as peripheral insulin resistance [5].
About 80% to 90% of patient with type II diabetes are also diagnosed as obese. This fact provides interesting evidence of the relationship between obesity and diabetes. Being overweight places extra stress on your body in a variety of ways, including your body's ability to maintain proper blood glucose levels [6,7]. In diabetic patients, free radicals are formed by glucose oxidation, glycation of proteins, and their oxidative degradation. Abnormally high levels of free radicals and the simultaneous decline of antioxidant defense mechanisms can lead to damage of cells, increased lipid peroxidation, and development of insulin resistance and the development of diabetic complications [8]. For this reason, molecules with antioxidant potential may be useful for the adequate maintenance of oxidative levels in blood. One therapeutic approach for management of diabetes type 2 is to decrease post-prandial hyperglycaemia through the inhibition of the carbohydrate-hydrolysing enzymes, α-amylase and α-glucosidase [9]. The α-amylase enzyme is produced by the pancreas and it is also found in saliva while the α-glucosidase acts in the mucosal brush border of the small intestine [10]. Drugs able to inhibit both enzyme such as acarbose, miglitol and voglibose are extensively prescribed; however, they are characterized by several side effects (e.g., bloating, diarrhea, gas, and stomach pain) [11]. Patients with diabetes type 2, especially if they are also obese, are affected also by plasma lipid and lipoprotein abnormalities, which include reduced HDL cholesterol, a predominance of small dense LDL particles, and elevated triglyceride levels. The lipid changes associated with diabetes mellitus are attributed to increased free fatty acid flux secondary to insulin resistance [12]. Diabetes seems to influence the cholesterol absorption efficiency and synthesis with the respective non diabetic state. For this reason, diabetic patients are often affected by high levels of cholesterol in the blood [13]. Pancreatic lipase is a key enzyme involved in dietary fat digestion. Interference with fat hydrolysis results in the reduced utilization of ingested lipids, therefore inhibition of lipases decreases fat absorption that is useful for obese patients [14]. Orlistat, a hydrogenated derivative of lipstatin, is the only pancreatic lipase inhibitor currently approved for a long-term treatment of obesity. Several natural products are able to inhibit key carbohydrate-hydrolysing enzymes [15][16][17] and also pancreatic lipase [18,19]. In this work, edible flowers from two different Trifolium ssp (T. repens and T. pratense) were in vitro investigated for their chemical composition, antioxidant activity, hypoglycaemic potential by inhibition of α-amylase and α-glucosidase, and pancreatic lipase inhibitory properties.
Extraction Procedure
Trifolium repens and T. pratense flowers were obtained from a market in Cosenza (Calabria, Italy) during spring 2013. Samples were cleaned by using distilled water; the petals were separated and kept at room temperature to drain. Then, flowers were extracted at room temperature by ethanol (48 h × 3 times) and evaporated to obtain the total extract (Table 1).
Determination of Total Phenols and Flavonoids Content
The total phenols content was determined by the Folin-Ciocalteau method [20]. The sample was mixed with 0.2 mL Folin-Ciocalteau reagent, 2 mL of water and 1 mL of 15% Na2CO3. After 2 h of incubation at 25 °C the absorbance was measured at 765 nm by using a UV-Vis Jenway 6003 spectrophotometer. The total phenols content was expressed as mg of chlorogenic acid equivalents per g of dry extract ( Table 1).
The flavonoids content was determined as previously described by Yoo, et al. [21]. The levels of total flavonoids content were expressed as mg of quercetin equivalents per g of dry extract.
Radical Scavenging (DPPH and ABTS) Activity Assays
The radical scavenging was investigated by ABTS and DPPH tests. ABTS radical cation (ABTS · + ) solution was mixed with potassium persulphate and left in the dark for12 h before use. The ABTS · + solution was diluted with ethanol to an absorbance of 0.70 ± 0.05 at 734 nm. After addition of extract or Trolox to the ABTS · + solution, the absorbance was measured [22]. A DPPH ethanol solution (1.0 × 10 −4 M) was mixed with sample at different concentration allow incubate in the dark for 30 min. The absorbance was measured at 517 nm. Ascorbic acid was used as positive control [23].
β-carotene Bleaching Test
The β-carotene bleaching test was done following the procedure described by Loizzo et al. [24]. Briefly, a β-carotene solution was added to linoleic acid and 100% Tween 20. The emulsion was mixed with samples (200 μL) at different concentrations. The tubes were placed at 45 °C in a water bath for 60 min. The absorbance was measured at 470 nm at t = 0, 30 and 60 min. Propyl gallate was used as positive control.
Ferric Reducing Activity Power (FRAP) Assay
The FRAP test is based on the redox reaction that involves TPTZ (2,4,6-tripyridyl-s-triazine)-Fe 3+ complex [25]. FRAP reagent was prepared by mixing 10 mM TPTZ solution with 40 mM HCl, 20 mM FeCl3 and 0.3 M acetate buffer. The absorption was measured at 595 nm. The FRAP value represents the ratio between the slope of the linear plot for reducing Fe 3+ -TPTZ reagent by extracts compared to the slope of the plot for FeSO4. BHT was used as positive control.
α-Amylase and α-glucosidase Inhibitory Activity
The α-amylase and α-glucosidase inhibition assays were previously described by Loizzo et al. [26]. A mixture of α-amylase solution and samples at different concentrations was prepared and added to starch solution (25 °C for 5 min). The generation of maltose was quantified at 540 nm by using 3,5-dinitrosalicylic acid. In α-glucosidase assay samples at different concentrations were mixed with a maltose solution (t = 5 min at 37 °C). The α-glucosidase solution (10 units/mg) was added and left to incubate at 37 °C for 30 min. Then, the perchloric acid solution was added to stop the reaction. The generation of glucose was quantified by the reduction of DIAN at 500 nm.
Pancreatic Lipase Inhibitory Activity
The pancreatic lipase inhibition assay was performed as previously reported [27]. Porcine pancreatic lipase was mixed with water in order to obtain a solution with concentration of 1 mg/mL. Then a 5 mM solution of nitrophenyl caprylate in DMSO was prepared. The reaction mixture was prepared by adding 4 mL of Tris-HCl buffer (pH of 8.5), 100 mL of 5 mM nitrophenyl caprylate, 100 mL of sample and 100 mL of enzyme solution. Before adding the substrate the mixture was incubated at 37 °C for 25 min. The absorbance was measured at 412 nm. Orlistat was used as positive control.
Statistical Analysis
The concentration giving 50% inhibition (IC50) was calculated by nonlinear regression with the use of Prism GraphPad Prism version 4.0 for Windows (GraphPad Software, San Diego, CA, USA). The concentration-response curve was obtained by plotting the percentage inhibition versus concentration. Differences within and between groups were evaluated by one-way analysis of variance test (ANOVA) followed by a multicomparison Dunnett's test compared with the positive controls.
Total Phenols and Flavonoids Content and HPLC Profile
T. repens exhibited the highest phenols and flavonoids content with 79.2 mg chlorogenic acid/g extract and 19.4 mg of quercetin equivalents/g of extract, respectively.
HPLC analyses of flavonoids (Table 1) revealed that T. repens contain high level of rutin (45.8 mg/g dry extract) followed by quercetin (10.3 mg/g dry extract). Kaempferol and myricetin are less expressed with values of 0.5 and 1.4 mg/g dry extract, respectively. T. pratense extract contain luteolin as main compound (16.7 mg/g dry extract) followed by kaempferol (0.8 mg/g dry extract) and myricetin (0.5 mg/g dry extract).
Recently, Xiong et al. [28] evaluated the flavonoids profile of ten common edible flowers from China and according with our results identified rutin and quercetin as the main abundant compounds.
Antioxidant Activity
The antioxidant potential of red and white clove extract was investigated by using different in vitro methods stable free radical scavengers: ABTS and DPPH; lipid oxidation β-carotene bleaching test and FRAP test. The use of a multiple approach is strongly recommended with food matrix considering that plant foods contain many different classes and types of antioxidants and that extraction procedure strongly influences the phytochemical composition of the extracts and, therefore, influence the antioxidant effects [29].
Since lipid peroxidation in the body is primarily the oxidative damage of cell membranes, as well as all other systems that contain lipids, in determining the overall antioxidant activity of different compounds, it is necessary to examine their effect on the lipid peroxidation [31]. The effect of natural products on lipid peroxidation can be investigated by using different approaches and a number of different substrates (liposomes, linoleic acid, microsomes, various fatty oils, liver homogenate).
In the β-carotene bleaching test the oxidation of linoleic acid generates peroxyl free radicals due to the abstraction of a hydrogen atom from diallylic methylene groups of linoleic acid. The presence of phytochemical with antioxidant potential can hinder the extent of β-carotene bleaching by neutralizing the linoleate free radical and other free radicals formed in this model [32].
T. pratense showed a promising inhibition of lipid peroxidation with IC50 values of 7.9 and 11.0 μg/mL at 30 and 60 min of incubation, respectively. A lower protection on the β-carotene oxidation was observed when T. repens was applied in the model (IC50 values of 16.1 and 18.4 μg/mL at 30 and 60 min of incubation, respectively).
The reducing potential of phytonutrients contained in both red and white clover was investigated by using FRAP test. Generally, the reducing abilities related with the presence of molecules able to break the free radical chain through donating a hydrogen atom [33]. The ferric reducing ability powers of edible flower extracts expressed as FRAP values μM Fe(II)/g are shown in Table 2. T. repens flower extract exhibited a promising ferric reducing power with FRAP value of 44.2 μM Fe(II)/g.
Inhibition of Key Enzyme Involved in Diabetes and Obesity
The lowering of post-prandial hyperglycaemia through the inhibition of key-enzymes linked to type 2 diabetes mellitus is a critical and often used therapeutic approach. In this work, the ability of red and white clover flower extracts to inhibit α-amylase and α-glucosidase enzymes was investigated and results are reported in Table 3. All extracts exhibited hypoglycaemic activity in a concentration-dependent manner. T. repens extract showed the highest activity against α-amylase with an IC50 value of 25.0 μg/mL. This value is 2-fold lower than the commercial drug acarbose used as positive control (IC50 value of 50.0 μg/mL). The same extract showed also a promising activity against α-glucosidase with an IC50 value of 69.5 μg/mL. A comparable activity against α-glucosidase was observed with T. pratense extract. Data are expressed as mean ± S.D. (n = 3). One-way ANOVA *** p < 0.0001 followed by a multicomparison Dunnett's test: ***p < 0.01 compared with positive control.
The hypoglycaemic potential of Trifolium flower extracts could be ascribed on their flavonoids content since it is well documented that these phytochemical may act as α-amylase inhibitors [34].
Yuan et al. [35] demonstrated that quercetin and luteolin, two flavonoids identified in our samples, may act as non-competitive inhibitors of α-amyalse and that luteolin is more potent than quercetin and rutin. Both compounds are also able to inhibit α-glucosidase with IC50 values of 7 and 21 μM for quercetin and luteolin, respectively [36]. Rutin, the glycosylated conjugate of quercetin, had a stronger inhibition of α-amylase (IC50 value of 0.043 μM) and α-glucosidase (IC50 value of 0.037 μM) than quercetin.
Body mass index has a strong relationship to diabetes type 2 and insulin resistance. For this reason a multiple approach with compounds able to induce hypoglycaemia and reduce the fat absorption is desirable. In this work, we have screened the two Trifolium species for their ability to inhibit lipase. Both showed a promising lipase activity with IC50 values of 1.3 and 2.4 μg/mL for T. repens and T. pratense, respectively (Table 3). Previously, AlRawi et al. [37] investigated the effect of different extracts of Trifolium alexandrinum flowers in a diabetes in vivo model. Extract improve the status of liver in streptozotocin-induced diabetic rats with a potency that follow this order water >n-hexane > ethanol. More recently, Aly et al. [38] demonstrated that the administration of a semi-modified diet containing 10% of T. alexandrinum ad-libitum for 6 weeks streptozotocin-induced diabetic rats induced a reduction of triglyceride, total cholesterol, LDL-cholesterol, and VLDL-cholesterol. These effects may be due to the regeneration of β-cells of the pancreas and potentiating of insulin secretion from surviving cells. The increase in insulin availability may lead to inhibition of lipid per oxidation and control of lipolytichormones. Chedraui et al. [39] investigated the T. pratense derived isoflavone supplementation for 90 days on the lipid profile of postmenopausal women with increased body mass index. The 88.3% of participants that completed the trial evidenced a significant decrease in total cholesterol, low-density lipoprotein cholesterol and lipoprotein A levels.
Conclusions
Obesity is the leading cause of major diseases including type 2 diabetes. At present, the potential use of natural products for the treatment of obesity is still largely unexplored and it might be an excellent alternative strategy for the development of safe and effective anti-obesity drugs. In this study, we have investigated the crude extracts of T. repens and T. pratense flowers. Our in vitro experiments showed that both species, rich source of flavonoids, are able to inhibit key enzymes involved in carbohydrate digestion such as α-amylase and α-glucosidase. An anti-lipase activity was also observed.
Plant foods generally contain flavonoids as glycosides. However, these phytochemicals undergo in vivo to a rapid metabolism by epithelial β-glucosidases [40]. The individual variability in the activity of these enzymes may be a factor determining variation in flavonoids bioavailability and consequently bioactivity. For the above-mentioned reason, further in vivo studies, which evaluate digestion, absorption and metabolism of the putative bioactive compounds, are necessary to establish the healthy properties of these two Trifolium species. | v3-fos |
2016-03-22T00:56:01.885Z | {
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} | 0 | [] | 2015-12-24T00:00:00.000Z | 5286956 | {
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} | s2 | Analysis of Tetracyclines in Medicated Feed for Food Animal Production by HPLC-MS/MS
The use of medicated feed is a common practice in animal food production to improve animal health. Tetracyclines and β-Lactams are the groups that are most frequently added to this type of feed. The measurement of the concentration of the analytes in these types of samples is sometimes due to the matrix characteristic, and manufacturers are demanding fast, precise and reproducible methods. A rapid confirmatory method based on a simple extraction protocol using acidified methanol and followed by high performance liquid chromatography coupled to a tandem mass spectrometer for the quantification of four tetracyclines in feed is presented. Validation was performed following the guidelines of Decision 2002/657/EC. Results indicated that the four tetracyclines can be identified and quantified in a concentration range between 50 and 500 mg/kg with recoveries between 84% and 109% and RSD for precision under reproducible conditions between 12% and 16%. Satisfactory results were also obtained with interlaboratory studies and by comparing the method with an HPLC-Fluorescent method.
Introduction
Meat consumption increases each year and, consequently, so does food production of animal origin [1]. To increase production and reduce cost, animals are raised intensively in farms; big farms require greater control of animal health because illnesses can be easily transmitted from one animal to another and cause large economic losses. Therefore, the use of veterinary drugs in food production is very important for controlling and improving animal health. These substances are not only used for therapeutic treatment but also for prophylaxis.
Pharmaceuticals can be administered to animals in various forms including tablets, suspensions, emulsions, injections, implants and creams. A common practice is the administration of pharmaceuticals for prophylactic purposes through food. Intensively produced animals are often fed with concentrated feed, which are a mixture of various materials (oats, wheat, barley, rye, cottonseed, and crambe) and additives. Various classes of veterinary medicines are administered through feed as prophylactic treatment, including antibiotics (sulphonamides, tetracyclines and β-Lactams) and anti-parasitic agents (coccidiostats and ivermectins). As in humans, the pharmaceutical dose will depend on the species of animal. Given that the same maker produces feed for various species of animals, an exhaustive quality control of the concentration of the pharmaceutical in the feed should be carried out. According to Kools et al. (2008), the estimation of pharmaceuticals used in food production was 6.051 t of active substance for the European Union. Antibiotics was the most frequently used group (5393 t) followed by anti-parasitic agents (194 t) [2]. The study also indicated that within the antibiotics class, tetracyclines and β-lactams were the group used in the highest amounts. Most controls related to veterinary drugs in animal food production are performed on the final food (egg, milk, muscle, liver, etc.). Some controls are also conducted on water for animals, their food, and their faeces, but most of the analyses are for the evaluation of the presence of substances such as pesticides [3,4], nitrofurans [5] and mycotoxins [6][7][8].
The presence of substances such as antibiotics in feed samples is normally assessed by the manufacturer and generally with screening methods. Few analytical methods can be found in the literature for antimicrobials in medicated feed [9][10][11] and most of the methods reported describe analytical techniques for non-medicated feed or residues of antibacterial in food [12][13][14]. Administration of medicated feed to animal food production can only be conducted under veterinary prescription and vigilance therefore control of the correct antimicrobial concentration in the feed is vital to avoid further feed safety problems. Additionally, it should be highlighted that residue of tetracycline in feed for animal food production are not permitted at any concentration.
Based on the common use of tetracycline in food production, the low number of methods available for their analysis in feed for animal food production samples and the manufacture demand, the aim of this research work is to present an reliable and producible HPLC-MS/MS method for the analysis of tetracyclines in medicated feed samples.
Results
To optimize each tetracycline standard solutions of individual compounds at 1 mg/L in 0.1% formic acid in methanol were infused into the MS. This helped to select the precursor and product ions of each of the tetracyclines and the internal standard (IS). The cone voltage and collision energy were optimised to obtain the most intense signal for each ion. Table 1 shows precursor and product ions selected for tetracycline identification, as well as the cone voltage and collision energy employed for each transition. The transition between the precursor ion and product ion 1 and 2 was employed for confirmation of the analytes, and the transition between the precursor ion and product ion 1 was employed for quantification. The selection of the HPLC column and the chromatography method was based on previously described work [15]; however, the gradient was modified to achieve better resolution between the eluted peaks.
The best results were achieved with the simplest extraction protocol which employed acidified methanol; this protocol was previously described by AOAC for the extraction of one tetracycline in feed samples [16]. Once the method was selected, the validation procedure was conducted.
The validation was conducted following the requirement included in the Decision 2002/657/EC [17]. A total of 20 feed samples were analysed to determine selectivity/specificity. The successful quantification of tetracyclines and the absence of interfering peaks at their retention times demonstrated the selectivity/specificity of the method. Figures 1 and 2 show SRM chromatograms of tetracyclines in a blank sample and in a fortified sample at 50 mg/kg. The selection of the HPLC column and the chromatography method was based on previously described work [15]; however, the gradient was modified to achieve better resolution between the eluted peaks.
The best results were achieved with the simplest extraction protocol which employed acidified methanol; this protocol was previously described by AOAC for the extraction of one tetracycline in feed samples [16]. Once the method was selected, the validation procedure was conducted.
The validation was conducted following the requirement included in the Decision 2002/657/EC [17]. A total of 20 feed samples were analysed to determine selectivity/specificity. The successful quantification of tetracyclines and the absence of interfering peaks at their retention times demonstrated the selectivity/specificity of the method. Figures 1 and 2 show SRM chromatograms of tetracyclines in a blank sample and in a fortified sample at 50 mg/kg. The selection of the HPLC column and the chromatography method was based on previously described work [15]; however, the gradient was modified to achieve better resolution between the eluted peaks.
The best results were achieved with the simplest extraction protocol which employed acidified methanol; this protocol was previously described by AOAC for the extraction of one tetracycline in feed samples [16]. Once the method was selected, the validation procedure was conducted.
The validation was conducted following the requirement included in the Decision 2002/657/EC [17]. A total of 20 feed samples were analysed to determine selectivity/specificity. The successful quantification of tetracyclines and the absence of interfering peaks at their retention times demonstrated the selectivity/specificity of the method. Figures 1 and 2 show SRM chromatograms of tetracyclines in a blank sample and in a fortified sample at 50 mg/kg. Reference materials were not available; therefore, the accuracy of the method was calculated in terms of recoveries. The precision, defined as the closeness of agreement between independent test/measurement results obtained under stipulated conditions, was calculated under repeatability and reproducibility conditions, in which case it was called the repeatability or reproducibility of the method. The recoveries and the precision of the method were calculated by employing feed samples spiked with tetracyclines at 50, 100, 150 mg/kg, with six replicates for each concentration, with repeatability analysis conducted on the same day and reproducibility analysis conducted over different days. Recoveries, repeatability, and within-laboratory reproducibility achieved for each of the tetracyclines are summarised in Table 2.
Tetracycline showed the lowest recovery variation between concentrations and chlortetracycline the highest recovery variation. Although tetracycline recoveries were between 84% and 109%, this was considered an acceptable value and was within the limits set up by the Commission Decision 2002/657/EC [17]. The maximum RSD for precision under reproducible conditions accepted for concentrations of 100 mg/kg is 23 and RSD for precision under repeatable conditions should be between 11.5 and 15.6. The lowest repeatability values were achieved for chlortetracycline, with RSD below 9, and doxycycline had the highest RSD (15%). RSD for within-laboratory reproducibility were between 7% (tetracycline) and 16% (doxycycline). Therefore, it could be said that RSD for precision under repeatability and reproducibility conditions are within the limits set up by the Commission Decision 2002/57/EC.
Limit of detection and limit of quantification of the method were calculated and verified with feed samples spiked with the tetracyclines at different concentrations. This was based on a signal to noise ratio above 3 for the limit of detection (LOD), and above 10 for the limit of quantification (LOQ). The LOD and LOQ for this method should be between 1 and 10 mg/kg; however, considering the fact that the extract was diluted ten times before analysis, the LOD and LOQ should be at least ten times lower. On the other hand, the method was optimised for the extraction of tetracyclines at mg/kg levels; therefore, an LOD and LOQ at the range of µg/kg could be interesting for other types of analyses but not in this work. Considering validation results, peak shape, repeatability, reproducibility and accuracy, the LOD and LOQ of the method have been established at 5 mg/kg for all tetracyclines. To verify this, LOD feed samples spiked with tetracyclines at 1, 5, 10 and 20 mg/kg were extracted and analysed, these extract were not diluted, they were injected after filtration. The signal to noise ratio of each concentration for the individual tetracycline was investigated. A signal to noise ratio above 10 was achieved for each tetracycline at 5 mg/kg.
HPLC-MS/MS Analysis
The fact that concentrations of tetracycline in medicated feed are within the range of mg/kg simplifies their extraction for HPLC-MS/MS analysis. This technique has been selected because it is defined as a confirmatory technique by the Commission Decision 2002/657/EC.
The analysis of these antibiotics in medicated feed has been previously described, employing other techniques such as synchronous spectrofluorimetry [18], and HPLC-UV [19,20]. HPLC-MS/MS methods have been also been used for tetracycline in feed, but at trace levels [21,22].
Before establishing the final extraction protocol, previously reported sample treatments for tetracycline analysis in food and feed matrices were tested. Considering that tetracyclines form chelation complexes with different cations, the use of EDTA is a common practice and has been reported for their analysis in food samples such as liver, muscle, and fish muscle [14,18,22,23]. The McIlvaine buffer, a citrate/phosphate buffer, is also commonly used for tetracycline analysis with or without EDTA [13,[22][23][24][25]. These two agents were used separately, combined and with the addition of trichloroacetic acid for the extraction of tetracyclines in animal feed. After this first extraction, the supernatant was mixed with different amounts of ethyl acetate and the organic layer was evaporated to dryness. The dry extract was reconstituted in a 90:10 mobile phase A:B for analysis. However, none of the combinations tested gave satisfactory results according to data reported by the manufacturer.
Tetracyclines dissolve well in alcohol, but methanol is not commonly used for their extraction because its clean-up is difficult. A method reported by Phenomenex for honey samples which employs acidified methanol, 0.833 mL of 1 M HCl in 200 mL of methanol, followed by purification of the extract with SPE, also produced unsatisfactory results.
The best results were achieved with the simplest extraction protocol, which employed acidified methanol; this protocol was previously described by AOAC for the extraction of one tetracycline in feed samples [16]. Methanol was acidified at a higher level than conditions reported by Phenomenex and dilution of the extract into the mobile phase for analysis. It was also noted that an important factor on the extraction of tetracycline from feed samples was the shaking time for this particular method; the best recoveries were achieved for concentrations between 50 and 500 mg/kg by shaking the samples for 20 min in an orbital shaker. Shorter shaking times considerably reduced the recoveries, but higher times did not increase the recoveries.
Comparison between HPLC-MS/MS and HPLC-Fluorescent Detection
The results obtained with validation of the HPLC-MS/MS method were compared with those obtained with an HPLC-Fluorescent method ( Table 2). The main difference between the two methods is detection of the compounds, because the extraction protocol is the same. Data on accuracy were very similar for both methods; at 50 mg/kg, the accuracy for the MS/MS method was from 87% (doxicicline) to 104% (tetracycline) and for the fluorescent method it was from 98% (chlortetracycline) to 108% (tetracycline). Precision under repeatability and reproducibility conditions achieved with the HPLC-Fluorescent method were, in general, three times lower than those obtained during validation of the HPLC-MS/MS method ( Table 2). These results could be probably due to factors such as dilution; the HPLC-MS/MS method required a dilution of the extract prior to its analysis. Additionally, while the HPLC-Fluorescent technique is direct analysis, MS detection required a gas phase of the compounds which was achieved by electrospray ionisation, implying more variation between samples.
Interlaboratory Studies
Feed samples prepared by the manufacturer with known concentrations of individual tetracyclines were analysed by the HPLC-MS/MS method presented and by the HPLC-fluorescent method for comparison. Satisfactory results were achieved; concentrations similar to those added to the feed samples were measured with both methods (accuracy in both laboratories were between 89% and 105%). Additionally, the laboratories took part in different interlaboratory studies; accuracy was between 85% and 102% for concentrations between 20 and 100 mg/kg and values of z-score were between´1.77 and 1.5.
Chemicals, Reagents and Stock Solutions
The chemical and chromatographic reagents used were LC or analytical grade. Tetracycline, chlortetracycline, doxycycline, oxytetracycline and demeclocycline, all with purity greater than 98%, were obtained from Sigma-Aldrich (St Louis, MO, USA). Demeclocycline was used as IS.
To prepare the mobile phase A, 400 µL of formic acid was dissolved in 9960 µL of Milli-Q water, and to prepare mobile phase B, 400 µL of formic acid was dissolved in 99,600 µL of methanol.
Individual stock solutions of tetracyclines were prepared by dissolving 20 mg of each analyte in 20 mL of methanol and stored at´20˝C for six months. These solutions were then mixed together and diluted with methanol to obtain a solution of intermediate concentration of all tetracyclines at 50 mg/L, which was stored at´20˝C for no more than one month. Each day, working standard solutions of all tetracyclines were prepared by diluting each intermediate solution in methanol to obtain a final concentration of 1 mg/L. Stock, intermediate and working solutions of the IS were also prepared and stored under the same conditions as the tetracyclines.
Extraction solution was prepared by dissolving 980 mL of methanol and 20 mL of concentrated hydrochloric acid.
Analysis by HPLC-MS/MS
The HPLC-MS/MS system consisted of an Alliance 2795 HPLC and Quattro Premier XE triple quadrupole mass spectrometer, both from Micromass (Manchester, UK). The software Masslynx 4.1, also from Micromass (Manchester, UK), was employed to acquire the data and control the system. The analyses of the tetracyclines were performed using a Sunfire C18 column (150ˆ2.1 mm i.d., 5.0 mm particle size) from Waters (Milford, MA, USA). Separation of the analytes was achieved by injecting 25 µL of extract and by applying a mixture of component A (0.04% formic acid in water) and B (0.04% formic acid in methanol) on a gradient mode as follows: 0-8 min 0% B, 8-9 min 45% B, 9-14 min 61% B, 14-15 min 0% B, and 15-18 min 0% B. The oven temperature was set at 35˝C, and a flow rate of 0.25 mL¨min´1 was used during the whole run.
Separated tetracyclines were directed into the electrospray source of the MS, which was operated in the positive-ion mode and under the following conditions: capillary voltage 3 kV, source temperature 120˝C, desolvation temperature 350˝C, cone gas flow 49 L/h, and desolvation gas flow 650 L/h. The analytes were identified by their retention times (Rt) and by 2 or more selected reaction monitoring (SRM) transitions.
Sample Extraction for HPLC-MS/MS Analysis
Sample preparation procedure was based on a previous work (AOAC 2009). Approximately 200 g of feed was ground and homogenised in a Moulinex grinder and 2 g of the powder was transferred into a 50 mL disposable plastic centrifuge tube. To extract the tetracyclines form the feed, 20 mL of extraction solution was added, and the tube was closed and shaken for 20 min at 200 rpm on a New Brunswick Scientific model G25 shaker (New Jersey, NJ, USA). The mixture was centrifuged at 2500 rpm on a model 5415D centrifuge from Eppendorf (Hamburg, Germany) and 500 µL of the extract was then filtered through an Ultrafree-MC centrifugal filter from Millipore. The filtered extract was diluted ten times with mobile phase mixture 90A:10B and transferred into an amber HPLC vial that contained a 300 mL micro-insert and was kept at´18˝C until sample analysis by HPLC-MS/MS, which took place within 24 h.
For quantification, blank feed samples (feed without tetracyclines) were fortified by spiking them with different aliquots of a standard mixture of tetracyclines to obtain the following final concentrations: 50, 100, 150, 200 and 250 mg/kg. After fortification, and prior to extraction, samples were shaken on an orbital shaker at 200 rpm for 10 min. In addition to these, two samples containing only the reagents (without feed) were also processed. One was spiked with tetracycline at 100 mg/kg (fortified reagents), and the other was not spiked (reagent blank), it simply contained reagents.
For method the method development feed samples spiked with tetracycline at various concentrations were employed (from 1 to 300 mg/kg). These samples were extracted employing the protocol described above and the linearity of the whole protocol was investigated. Taking into account the fact that concentration of tetracyclines in medicated feed are 100 mg/kg, validation was conducted at 150 mg/kg.
Validation of the HPLC-MS/MS Method
Commission Decision 2002/657/EC establishes the criteria and results interpretation for methods for analysis of samples of food and food-producing animals. Even though the method has been used for the analysis of medicated feed samples, the criteria included in Commission Decision 2002/657/EC were followed for the identification and quantification of chlortetracycline, doxycycline, oxytetracycline and tetracycline in feed samples (EU 2002). However, as maximum residual levels for these substances are not applicable detection limits (CCβ), the decision limit (CCα) of the method was not investigated. On the other hand, trueness/recovery, precision, specificity and applicability/ruggedness/stability were investigated in two different laboratories dedicated to the control of residue of veterinary drugs in food samples.
For validation of the method three batches of matrix-matched samples were employed. Each batch, analysed on a different day, consisted of 21 samples fortified with tetracyclines at concentrations of 0, 50, 100, 150, 200 and 500 mg/kg. Six replicates were employed for levels of 50, 100, and 150 mg/kg, and only one sample was employed for levels of 0, 20 and 50 mg/kg.
For quantification, blank feed samples (feed without tetracyclines) were fortified by spiking them with different aliquots of a standard solution mixture of tetracyclines to obtain the following final concentrations: 50, 100, 150, 200 and 500 mg/kg. After fortification, and prior to extraction, samples were shaken on an orbital shaker at 200 rpm from for 10 min. In addition to these, two samples containing only the reagents (no feed) were also processed. One of these samples was spiked with tetracycline at 100 mg/kg (fortified reagents), and the other was not spiked (reagent blank) and simply contained reagents.
HPLC-Fluorescent Detection
This method was set up in another laboratory for comparison of the results obtained with the HPLC-MS/MS method. The HPLC-Fluerescent system consisted of an Alliance 2695 HPLC and Fluoresecen detected model 2475 both from Waters. A volume of 10 µL of extract was injected into a LiChroCART Purospher STAR RP-8 (4.6ˆ150 mm, 5 µm). The mobile phase consisted of methanol (mobile phase A) and calcium chloride and EDTA buffer at pH 6.5 (mobile phase B) with a flow rate of 0.6 mL/min. The gradient program was as follows: 0 min 30% A, 8 min 55% A, 11 min 60% A, 12 min 30% A, and 17 min 30% A. The detector was operated at an excitation wavelength of 390 nm and an emission wavelength of 512 nm.
The extraction protocol employed for fluorescent detection was similar to that described above. However, in this case, extraction was performed with 20 mL of acidified methanol; after shaking them for 20 min, the extract was filtered and transferred to a 25 mL volumetric flask. The volume was made up to 25 mL with acidified methanol. As mentioned in the sample preparation section, the extract was filtered prior to HPLC-fluorescent detection.
Interlaboratory Studies
For interlaboratory studies, samples were obtained from different sources including feed manufacture and from the Association of American Feed Control Officials (AAFCO) and INTER2000. Medicated feed samples supplied from manufacture contained 70 mg/kg of chlortetracycline, 50 mg/kg chlortetracycline, oxitetracycline 50 mg/kg and 200 mg/kg of tetracycline. Those samples obtained from the Association of American Feed Control Officials (AAFCO) and INTER2000 contained chlortetracycline 80 mg/kg, doxycycline 29 mg/kg, oxytetracycline 400 mg/kg, chlortetracycline 60 mg/kg, chlortetracycline 55 mg/kg and oxytetracycline 28 mg/kg.
Conclusions
The use of veterinary medicine in animal food production is a common practice; pharmaceuticals are used for therapeutic and prophylactic proposals. A simple way to give antimicrobials to the animals is through food; however, few methods exist for the accurate analysis of these legal substances in feed samples. The present work describes a HPLC-MS/MS method for the simultaneous analysis of four tetracyclines in feed samples; the results were compared with an HPLC-Fluorescent method which employed the same extraction protocol. The method produced satisfactory results for concentrations of tetracyclines between 50 and 500 mg/kg. | v3-fos |
2018-04-03T04:29:32.098Z | {
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} | s2 | Identification and Characterization of microRNAs during Maize Grain Filling
The grain filling rate is closely associated with final grain yield of maize during the period of maize grain filling. To identify the key microRNAs (miRNAs) and miRNA-dependent gene regulation networks of grain filling in maize, a deep-sequencing technique was used to research the dynamic expression patternsof miRNAs at four distinct developmental grain filling stages in Zhengdan 958, which is an elite hybrid and cultivated widely in China. The sequencing result showed that the expression amount of almost all miRNAs was changing with the development of the grain filling and formed in seven groups. After normalization, 77 conserved miRNAs and 74 novel miRNAs were co-detected in these four samples. Eighty-one out of 162 targets of the conserved miRNAs belonged to transcriptional regulation (81, 50%), followed by oxidoreductase activity (18, 11%), signal transduction (16, 10%) and development (15, 9%). The result showed that miRNA 156, 393, 396 and 397, with their respective targets, might play key roles in the grain filling rate by regulating maize growth, development and environment stress response. The result also offered novel insights into the dynamic change of miRNAs during the developing process of maize kernels and assistedin the understanding of how miRNAs are functioning about the grain filling rate.
Introduction
As one of the most important grain crops and also a source of feed, food and fuel, maize (Zea mays L.) is cultivated broadly in the world. The maize yield is mainly determined by kernel weight and kernel numbers, among which the kernel weight is affected by the grain filling rate and duration [1]. During the period of maize grain filling, the grain filling rate is closely associated with kernel weight [2]. The genetic variability in plant senescence and grain filling rates needs to be exploited to help stabilize the component of yield [3]. It has been shown that the growth rate increased with rising temperatures [4] and that the decrease of gibberellins or the increase of abscisic acid could enhance the remobilization of carbon to the grains and promote the grain filling rate [5]. Some quantitative trait loci [6] and important proteins [7] have also been identified, which have contributed much to the grain filling rate in maize. miRNAs are fundamental, sequence-specific regulatory elements of eukaryotic genomes. In plants, these 19-24 nucleotide (nt)-long RNA species mediate the expression of endogenous genes at the transcriptional and post-transcriptional levels [8]. The near-perfect or perfect complementarity between the sequence of plant miRNAs and their targets suggests that most of the plant miRNAs have a similarly function with small interfering RNAs [9]. Research analyzing the spatial expression of miRNAs has shown that miRNAs have a tissue-specific expression during plant development [10], which indicates that miRNAs are possibly involved in specifying and maintaining tissue identity. miRNAs play an crucial role in many biological processes of maize, including leaf development [11,12], root development [13], seed germination [14] and response to abiotic stresses [15,16]. The results of deep sequencing showed that miR-NAs also affect the rice grain filling [17][18][19].
Measuring the proposed grain filling rate is not easily integrated into many studies because the grain filling rate is an environmentally modified quantitative phenotype [20][21][22]. Generally, a complicated character is difficult to advance directly, but perhaps it will be more easily to adopt the indirect selection way [2]. From the perspective of reverse genetics, proteomic study has been used to identify special proteins which associated with the grain filling stage and explore the main factors which affected the grain filling rate of maize [7]. Identifying the expression quantity of miRNAs in different grain filling stages would also be important in identifying the miRNA-dependent gene expression regulatory networks of maize grain filling.
Compared with inbred lines, hybrid maize genotypes have a larger cultivated area and more grain yield worldwide. Therefore, using hybrids to inspect the molecular mechanisms of the grain filling rate, instead of inbred lines, is more meaningful for applying genetic manipulations in maize [7]. In this study, the Solexa deep-sequencing technique was performed on four main grain filling stages of an elite maize hybrid, Zhengdan 958, in China. The objectives of this investigation were: 1) to identify maize conserved miRNAs and predict novel miRNAs involved in maize grain filling; and 2) to construct the key miRNA-dependent gene expression regulatory networks of maize grain filling.
Plant materials
An elite commercial hybrid, Zhengdan 958 (Zheng 58 × Chang 7-2), which has been the most widely planted maize hybrid since 2005 in China, was used as the plant material. The hybrid Zhengdan 958 was planted on 5 May 2011 at the farmland of the Henan Agricultural University (Zhengzhou, China; E113°42', N34°48'), where the average temperature is 14.3°C and the average rainfall is 640.9 mm per year. Two replication plots of the hybrid were planted in the field, of each row the length is 4 m, the inter-row space is 75 cm and the within-row space is 25 cm.
To achieve a consistent grain filling rate, the plants were all pollinated themselves on 6 July, then the middle kernels of ears from each plot were collected at 10,17,22,25,28,33,40 and 50 days after pollination (DAP). Three hundred kernels from each replication plot were dried at 70°C for 24 hours and the dry weights were measured. Divide the increment of dry weight by the number of days and kernels between two grain filling stages is the grain filling rate (Fig 1). The corresponding kernels were cut to discard the pericarps and embryos, then the endosperms were stored at −80°C for miRNA and mRNA extraction. According to the change of the grain filling rate in the whole grain filling stages, endosperms obtained at 17, 22, 25 and 28 DAP were applied for further miRNA and mRNA analyses.
RNA extraction, deep sequencing, and data analysis
Total RNA was extracted with the Plant Total RNA Extraction kit (Bioteke Corporation, Beijing, China) by the manufacturer's method, and 2 g endosperms were used for RNA extraction and deep sequencing.
After removing the low-quality reads from the raw data, the appropriate small RNAs were mapped to the reported miRNAs from miRBase (http://www.mirbase.org/). The expression amount of sequence was measured by RPM (reads per million) to get the comparable expression amounts. After normalization, the miRNA expression amount who was < 1 RPM in all four samples was discarded [18].
The software Mireapwas used to manage the unannotated small RNA reads to identify novel miRNAs. One small RNA was deemed to be a novel miRNA only if it accorded with the strict criteria described by Dong Ding [14]. Only those candidates with a minimal folding free energy index (MFEI) > 0.85 were treated as novel maize miRNAs [14]. The 74 novel miRNAs sequences have been deposited into Genbank, NCBI (http://www.ncbi.nlm.nih.gov/genbank/) with the accession numbers of KP192041-KP192114 (S1 Table).
Prediction and functional analyses of maize miRNA targets
The potential targets of miRNAs were calculatedby the psRNA-Target software with default parameters [23]. The maize PlantGDB genomic CD library was served as the database for the target searching. The function annotation of Potential miRNA targets were blasted against GO database using AgriGO with default parameters.
Expression profile of selected miRNAs
Six conserved miRNAs and six novel miRNAs were choosed to establish the sequence results. The reverse transcription and the absence of genomic DNA were performed using the One Step PrimeScript miRNA cDNA Synthesis Kit (TaKaRa, Dalian, China). For doing quantitative real-time PCR (qRT-PCR), the SYBR Premix Ex Taq (Takara, Dalian, China) was used and worked on a Fluorescence detection system (Bio-Rad, Waltham, MA, USA). Primer specificity was verified by the Melt curve analysis. The relative expression quantity of the miRNAs was calculated by the comparative threshold cycle (CT) method. The tubulin gene was performed as an inner control to normalize data among samples. Every sample was performed in technical triplicate. The reverse primer of miRNAs used for qRT-PCR is the Uni-miR qPCR primer in miRNA cDNA Synthesis Kit. The other qRT-PCR primers are listed in Table 1.
Grain filling rate analysis
The grain filling rate of hybrid Zhengdan 958 was measured at several stages of the grain filling (10 to 50 DAP). The grain filling rate showed a step increase from 10DAP and reached its highest level at 23-25 DAP; after 25 DAP, it decreased rapidly until 33 DAP, and then decreased moderately from 33 DAP to 50 DAP (Fig 1). These results implied that the rapid grain filling rate around 25 DAP might make a huge contribution to the dry matter content and the yield of the hybrid Zhengdan 958.
The detected miRNAs in four phases of grain filling
The maximum of grain filling rate occurred at 23-25 DAP in Zhengdan 958 (Fig 1), so we chose the four key sampling stages (17 DAP, 22 DAP, 25 DAP and 28 DAP) assayed by Solexa. In total, there were 25 families containing 173 reported maize miRNAs. After removing the miRNAs with low detectability levels (< 1 RPM at all four sampling phases), there were 77 conserved miRNAs belonging to 17 miRNA families co-detected in endosperm at the four sampling times, 17, 22, 25 and 28 DAP. The detected miRNAs in these samples have a significant variety in relative expression abundance, with over 70,000 RPM of miR168 and 1 RPM of miR162 in the 28 DAP sample. These different expression amounts of miRNAs in the grain filling duration meant that the miRNA target genes may be post-transcriptionally changed in the grain filling of maize. Furthermore, it is not that all the conserved miRNA family members were detected, and the expression levels among miRNA families were different (Table 2), which suggested that the miRNAs might have tissue-or developmental stage-specific expression patterns. Table 1. qRT-PCR primer sequences formaize (Zea mays L.) miRNAs, target genes and tubulin.
Primer
Primer sequence (5 0 -3 0 ) Primer Primer sequence (5 0 -3 0 ) The MFEI is an important criterion for identifying miRNAs from other smallRNAs. In this study, the newly identified maize pre-miRNAs had high MFEI values (0.87-2.36; S1 Table), with an average of about 1.31 [24]. Seventy-four novelmiRNA candidates belonging to 33 families were co-detected at the four sampling times (S1 Table). The novel miRNAs were all expressed at low levels, with 84 RPM being the highest relative abundance. This is consistent with the study in rice grain filling [17]. The expression patterns of miRNAs during maize grain filling Through the deep sequencing, the expression amount of almost all miRNAs was found changing with the development of the grain filling. The detected RPM of the 77 co-detected conserved miRNAs and 74 novel miRNAs were revealed in seven groups (Table 2 and S1 Table). Except for the irregular group (group g), Group I increased linearly from 17 to 28 DAP formed the largest group, represented by 28 out of 77 of the conserved miRNAs. The following group was down-regulated at 22 DAP (group f) and represented 9 out of 77 miRNAs. In novel miR-NAs, those up-regulated at 25 DAP (group c) formed the largest group (17/74). The dynamic expression of these miRNAs, such as group c and group d were closely related with the variation of grain filling rate, might play important roles in controlling many biological processes during maize grain filling by cleaving the transcript of their corresponding target genes or repressing the translation of these genes.
Functional analysis of the target genes of the detected miRNAs
The target genes of the 77 conserved miRNAs and 74 novel miRNAs were predicted with the psRNA Target tool. A total of 162 and 160 miRNA targets were detected from the conserved and novel miRNAs, respectively. The function of these target genes were further annotated by GO program. Only a small part of the novel miRNA targets produced GO results, including signal transduction-related genes and some organelle-specific genes (S2 Table). On the basis of functional annotations, the 162 target genes of the conserved miRNAs (S3 Table) were classified into eight groups (Fig 2), transcriptional regulation (81, 50%), oxidoreductase activity (18, 11%), signal transduction (16, 10%), development (15, 9%), post-translational regulation (8, 5%), stress response (5, 3%), transporter (3, 2%) and uncharacterized (16, 10%).
Expression profiles of selected miRNAs and target genes
Six novel maize miRNAs (miRt4, miRt13, miRt15, miRt17 and miRt21, miRt28) and six conserved miRNAs (miR156, miR162, miR172, miR393, miR396 and miR408) were chosen to verify the sequencing results via the qRT-PCR analysis. These results revealed that the relative expression levels of selected miRNAs in grain filling corresponded to the deep-sequencing data (Fig 3). Of the target gene expression profiles detected, three key miRNA target genes showed opposite expression trends compared with the miRNAs (Fig 4), but the other target genes did not show a clearly opposite expression profile (data not shown). These results may suggest that the expression of these target genes was influenced by other factors in addition to the corresponding miRNAs.
Key period of the grain filling
The grain filling rate directly determines the final grain weight, and it is a key component of the total grain yield. By comparing 10 cultivars of spring wheat's grain yield measured at intervals after anthesis, Nass and Reiser [25] found that the rate of the grain filling was a key factor in determining the final grain weight; however, the duration of the grain filling period was not an important factor. Ignoring the genetic background, in maize inbred lines and hybrids, the maximum of grain filling rate occurs between 21 and 25 DAP [26]. It was also found that the difference of maize kernel weight was mostly decided by the grain filling rate from 16 DAP to 29 DAP [6]. In our research, the maximum of grain filling rate occurred at 25 DAP in Zhengdan 958 (Fig 1). So the study on the four key sampling stages (17 DAP, 22 DAP, 25 DAP and 28 DAP) around 25 DAP by Solexa, which maybe detect many miRNAs that had important effects on the development of maize kernels. miRNAs function on transcriptional regulation during maize grain filling miRNAs have especially important roles in controlling plant development by regulating many transcription factor genes at the post-transcriptional level [27]. For example, the Squamosa promoter binding protein-like (SPL) familyis considered to be the target gene of zma-miR156. Ten out of the 16 SPL family members have been predicted to be miR156 targets [9]. SPL3, SPL4, SPL5 and SPL9 make a secondary contribution to the regulation of flowering [28,29] and appear to function mostly in the control of flowering time and phase change [28]. A point mutation within the miR156 target regin of OsSPL14 in rice generates the plant with a reduced tiller number, increased lodging resistance and enhanced grain yield [30]. The other result also showed that the higher expression of OsSPL14 could lead to increased primary branch number in panicles, and then an increase in rice yield [31]. As another target gene of miR156, OsSPL16 encodes a protein that promotes cell division, also with positive consequences for grain width and yield in rice [32]. In the present study, zma-miR156 increased linearly from 17 to 28 DAP, this is consistent with the result in the seed development process of rice [33], wheat [34] and barley [35]. We also detected the expression pattern of SPL, and found that SPL reduced linearly with the increase of zma-miR156 (Fig 4). Taken together, the higher expression of SPL in the early stage maybe can increase the width and the number of the kernal, and with the development of kernals the lower level of SPL9 and other related genes might prolong the phase associated with the rapid grain filling rate.
miR396 regulates growth-regulating factors (GRFs), which are transcription factors of the plant-specific family. In the leaf primordia, miR396 expresses at low levels throughout the meristem, overlapping with the expression of its target, GRF2 [36]. Over-expression of miR396 was found to decrease the GRFs that has been shown to influence cell proliferation in the meristem and developing leaves [37]. Most of the GRF genes are expressed in actively growing tissues, such as shoot tips and flower buds, but weakly in mature stems and leaf tissues [38]. In this study, the results showed that zma-miR396 increased in the endosperm at the four sampling times, but the expression level was weak, with values less than 30 RPM. During the seed development process of wheat and rice, the expression amount of miR396 was weak too, some of them even less than 1 RPM [33,34].The qRT-PCR results revealed that GRF decreased a little with a slight increase of zma-miR396 (Fig 4). The repression of zma-miR396 maybe leads to the steady expression amount of GRFs, and enhances the development of the corn kernel. miRNA involved in regulating oxidoreductase activity during maize grain filling Oxidoreductases are enzymes that catalyze the transfer of electrons from one molecule to another, with a slow release of energy. Many oxidoreductases play key roles in plant development, such as NADH-ubiquinone oxidoreductase [39], oxalate oxidoreductase [40] and xanthine oxidoreductase [41]. Lu et al. (2013) characterized the laccase gene family and identified 49 laccase genes, of which 29 were predicted to be targets of Populustrichocarpa (ptr)-miR397a [42]. Laccases are often able to catalyze oxidation of lots of substrates, such as phenols and amines [43]. It was also reported that plant laccases assist in wound healing [44], and in forming seed coat cell walls [43]. There are some other evidence showed that overexpression of miR397 can improve rice yield, mainly by increasing the grain size (result from cell division but not cell expansion) and promoting panicle branch [45]. But during the seeds development process of many crops, such as wheat [34], rice [33], and maize in the present study, the expression amount of miR397 are all maintaining a very low level. LAC 17 is the main oxidoreductase gene found in this study, and the qRT-PCR results showed that the relative abundance of LAC 17 increased slowly with the light decrease of miR397 across the four consecutive grain filling stages (Fig 4).
In conclusion, miR397 may play important role in the early time of reproductive stage, but in the later seeds development process it's the LAC genes who supply energy and improve the maize's ability to resist environmental stresses during the grain filling stage.
Other miRNAs involved in regulating maize grain filling
Fatty acid desaturases play an important role in the maintenance of the proper structure and function of biological membranes [46]. In this study, fatty acid desaturases were predicted to be targets of zma-miR169o by psRNA-Target software (S3 Table). zma-miR169o was downregulated at 22 DAP and then increased with the following grain filling stages. Similarly, zma-miR393, which targets the F-box auxin receptor transport inhibitor response 1 (TIR1) [47], was also down-regulated at 22 DAP. The plant hormone auxin regulates diverse aspects of plant growth and development [48]. Studies have shown that TIR1 is an auxin receptor, which mediated auxin/indole-3-acetic acid protein degradation and auxin-regulated transcription [49]. These miRNAs, together with the miRNAs that function on transcriptional regulation and oxidoreductase activity, are all involved in coordinating the development of maize grain filling (Fig 5).
Conclusions
This work showed during developmental stages of the maize grain filling, the dynamic characteristics of miRNAs may be meaningful in more precisely learning the regulatory roles of miR-NAs. miRNA156, 393, 396 and 397, and their respective targets, may contribute to the maize grain filling rate by regulating maize growth, development and environment stress response ( Fig 5). Novel miRNAs were expressed at low levels and the function of the predicted targets was limited (S2 Table).
Author Contributions
Conceived and designed the experiments: JT XJ ZF DD WL. Analyzed the data: XJ ZF PL. Contributed reagents/materials/analysis tools: XJ DD QP. Wrote the paper: XJ JT. Maize Grain Filling-Associated miRNAs | v3-fos |
2019-03-21T13:13:19.293Z | {
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} | s2 | Inhibition of Transpiration from the Inflorescence Extends the Vase Life of Cut Hydrangea Flowers
The relationship between transpiration from the inflorescence and the vase life of cut hydrangea ‘Endless Summer’ flowers was studied. In the defoliated cut flowers, the vase life increased with a decreasing number of decorative florets. Cut flowers having small inflorescences with 189 decorative florets exhibited a lower level of transpiration (7 g·day−1) and longer vase life (15 days) than those having large inflorescences with 422 decorative florets. The stomatal conductivity of the decorative sepals was very low, ranging from 2.7 mmol·m−2·s−1 to 3.3 mmol·m−2·s−1, and approximately 6% of the stomata were observed to be open microscopically. In addition, diurnal change of transpiration from a defoliated cut flower was not observed. These observations indicate that most of the transpiration from the sepals is through cuticular transpiration. The use of defoliated cut flowers that do not bear too many decorative florets and treatments that suppress transpiration from the surface of the decorative sepals would be effective for the vase life extension of cut hydrangea flowers.
Introduction
Vase life is the major factor that determines the marketability of cut flowers, and is strongly affected by water balance, which is determined by a combination of transpiration and water absorption (Ichimura, 2010). When the transpiration rate exceeds the water absorption rate in a cut flower, turgor declines and wilting occurs. Treatments that suppress the stomatal or cuticular transpiration extend the vase life of many cut flowers through maintenance of turgor. For example, in roses, abscisic acid treatment, which induces the closing of the stomata on the leaves, or removal of the leaves results in vase life extension (Carpenter and Rasmussen, 1974;Halevy et al., 1974). Furthermore, the existence of a dark period, a treatment that closes the stomata, improves the water balance of cut flowers (Doi et al., 1999). In anthurium, waxy coating on the spathe extends the vase life of cut flowers (Mujaffar and Sankat, 2003;Paull and Goo, 1985).
Hydrangeas (Hydrangea spp.) are popular ornamen- tal plants cultivated in many countries. Hydrangea inflorescences have 2 types of floret. One is a nondecorative floret, bearing tiny sepals, and the other is a decorative floret, bearing large decorative sepals. The inflorescence of hydrangea is classified into two types: hortensia and lacecap. In hortensia, the decorative florets constitute most of the inflorescence, and in lacecap, decorative florets are situated around the periphery of the inflorescence (Uemachi and Nishio, 2005;Uemachi et al., 2006). In Japan, consumption of cut hydrangea flowers has been increasing in recent years, and the market requires stable production of high-quality cut flowers. Cut hydrangea flowers often wither in a few days. Selection of cut flowers with small inflorescences and the removal of the leaves from cut flowers are known by farmers as effective techniques for extending the vase life of cut hydrangea flowers. Mega (1957) also reported that covering the stem with latex film or removal of the leaves extends the vase life of cut hydrangea flowers. However, the relationship between transpiration from the inflorescences and the vase life of cut flowers has not been studied in hydrangeas. Almost all of the hydrangea cultivars marketed as cut flowers have hortensiatype inflorescences. Transpiration from the decorative florets constituting most of the hortensia inflorescence can have a crucial influence on the vase life of cut hydrangea flowers. Although stomata exist on the abaxial side of decorative sepals, their functionalities have not been studied.
We hypothesized that suppression of transpiration from the inflorescences would be effective for extending the vase life of hydrangea cut flowers. In the present study, the effect of suppression of transpiration of hydrangea inflorescences on the vase life of cut flowers was studied. The stomatal conductance and the opening state of stomata were measured and the role of the stomata in the regulation of transpiration from the decorative sepals is discussed.
Plant materials
'Endless Summer', a cultivar bred as a garden shrub, was used for all experiments. 'Endless Summer' is not sold in the hydrangea cut flower market because of its short vase life. However, since we can easily verify the effect of treatment suppressing transpiration on the vase life of cut flowers, 'Endless Summer' was suitable for the present study. A mother plant for cuttings was purchased at a nursery in June 2010.
At Shinshu University experimental farm, all plants were grown in 32.5-cm-diameter pots filled with 8 L of medium composed of 75% Metro Mix 250 (SunGro Horticulture, Agawam, MA, USA) and 25% vermiculite (v/v) (Asahi Kogyo, Okayama, Japan) under fullsunlight conditions in summer and fall. The plants were grown from December 2010 to January 2011 in a greenhouse heated above 0°C. After February 2011, the plants were transferred to a greenhouse heated above 17°C. In 2012, plants were grown continuously in a greenhouse heated above 0°C. The coloration of the decorative sepals was visually assessed, and cut flowers with approximately 50 cm stems were harvested.
Vase life and transpiration from cut flowers
Leaving 40 cm stems, the end of the cut flower stem was recut under distilled water just after the harvest. The diameter of the recut stem end was measured. Leaves were trimmed to three pairs for the control cut flowers. All cut flowers were kept in conical flasks filled with 300 mL of distilled water. The flask was loosely sealed with parafilm (Pechiney Plastic Packaging Company, Chicago, IL, USA) to suppress evaporation from the vase water surface. Immediately following the preparation of the cut flower, the total mass of the cut flower, distilled water and flask was recorded. The mass was recorded in the same manner at the same time on the following day, and the daily transpiration rate from the cut flower was defined as the decrease in mass in this time period. Cut flowers were placed in an environmentally controlled room held at 25 ± 2°C and 50 ± 5% relative humidity (RH), and maintained under 12-h photoperiods at a light intensity of 10 μmol·m −2 ·s −1 provided by daylight fluorescent tubes (FL40SSN/37; Toshiba Lighting and Technology Co., Yokosuka, Japan). The vase life was terminated when withering and sepal browning became apparent. Decorative florets were counted at the end of vase life in all treatments except the inflorescence-covering treatment.
Measurement of the areas of decorative sepals and leaves
On 31 March, 2011, a cut flower was harvested. Images of 30 decorative florets, copied onto A4 paper, were clipped and weighed. The average area of a decorative floret was calculated using the ratio of the weight of a unit area of the A4 paper and that of the copied paper of a decorative floret. The total sepal area of the whole inflorescence was calculated by multiplying the number of decorative florets by the average area of a decorative floret. Leaf area was calculated in the same manner.
Suppression of transpiration from cut flowers
Four cut flowers for each treatment were harvested on 31 March, 2011. Cut flowers with 3 pairs of leaves were prepared as intact cut flowers. Transpiration from cut flowers was suppressed by 3 treatments: leaf removal, reduction of the number of decorative florets, and covering of the inflorescence. Leaf removal was performed immediately after harvest. Using defoliated cut flowers, the number of florets was reduced as follows: 2 or 4 secondary inflorescences on the first and second nodes of the primary inflorescence axis were removed. Inflorescences of cut flowers from which leaves had been removed were covered with polyvinyl chloride film (Asahikasei, Tokyo, Japan).
Transpiration and the vase life of small and large inflorescences
Five cut flowers bearing small inflorescences and 4 cut flowers bearing large inflorescences were harvested on 31 March, 2011. All leaves were removed from cut flowers just after harvest. Transpiration and the vase life of cut flowers were investigated as described above.
Stomatal conductance and the state of stomata of the decorative sepals
Three cut flowers were harvested from 11 to 18 June, 2012, all leaves were removed and the stem bases were placed in deionized water to be hydrated. Stomatal conductance of the decorative sepal was measured with a leaf porometer (SC-1; Decagon Devices, Pullman, WA, USA) on the day after harvest. One decorative sepal was chosen randomly from 5 secondary inflorescences each on the first and second nodes of the primary inflorescence axis. Stomatal conductance was recorded 2 min after the sensor head had been clipped to the sepal. The average of 5 readings from 5 sepals was cal-Hort. J. 84 (2): 156-160. 2015. culated as the stomatal conductance of the cut flower.
Under the light conditions on the day after harvest, one decorative floret was chosen randomly from each inflorescence and a mold of the abaxial epidermis of the sepal was made with dental paste (EXAFINE; GC Corporation, Tokyo, Japan). A replica of the abaxial epidermis of the sepal was prepared by pouring epoxy resin (Konishi Bond; Konishi, Osaka, Japan) into the mold. Under a light microscope (BH2; Olympus, Tokyo, Japan), more than 400 stomata were observed for each replica, and the percentage of open stomata was recorded. To estimate whether the stomata on the decorative sepal are functional or not, diurnal change of transpiration from a cut flower was studied. The total mass of the cut flower, distilled water and flask was recorded hourly using a digital camera. The decrease in mass per hour was calculated as the transpiration rate per hour from the cut flower. Measurements were continued for 48 h.
Suppression of transpiration extends the vase life of cut hydrangea flowers
In all cut flowers, except for those with the inflorescence covered, rapid progress of wilting of the decorative sepals marked the end of the vase life of cut flowers. The vase life of inflorescence-covered cut flowers was terminated when browning of the decorative sepals was observed. The cut flower characteristics measured immediately after the end of the vase life are shown in Table 1. Numbers of decorative florets on intact cut flowers, defoliated cut flowers, and defoliated cut flowers with 2 or 4 of the secondary inflorescences removed were approximately 366, 422, 222, and 117, respectively. The stem diameters of the cut flowers used in all transpiration suppression treatments were almost identical. Transpiration levels in intact cut flowers, defoliated cut flowers, defoliated cut flowers with 2 or 4 of the secondary inflorescence removed, and with the intact inflorescences covered with polyvinyl chloride film were approximately 28, 20, 14, 7, and 5 g·day −1 , respectively (Fig. 1). Vase lives of those cut flowers were approximately 2, 6, 10, 14, and 15 days, respectively.
Inflorescence size determines the vase life of cut flowers
Large and small inflorescences had approximately 422 and 189 decorative florets, respectively ( Table 2). The diameters of the stems of the cut flowers bearing large and small inflorescence were approximately 5.4 and 4.3 mm, respectively ( Table 2). The transpiration levels of those cut flowers were approximately 19 g·day −1 and 7 g·day −1 , respectively ( Table 2). The vase lives were approximately 5 and 15 days, respectively (Table 2).
Closed stomata dominated the abaxial side of the decorative sepals
The average stomatal conductance of the abaxial side of the decorative sepals ranged from 2.7 to 3.3 mmol·m −2 ·s −1 (Table 3). There was no correlation between transpiration per decorative floret and stomatal conductance. Closed stomata dominated the abaxial sides of the decorative sepals. The percentage of open stomata was 6.3 (Table 4). Obvious diurnal change of transpiration was not observed in the defoliated cut flowers (Fig. 2). Table 4. Percentage of open stomata observed on the abaxial sides of the decorative sepal.
Number of observed stomata Open (%)
491 ± 40 z 6 ± 2 z A replica of the abaxial epidermis of the sepal was prepared the day after harvest. The values are the mean ± SE (n = 3). Table 4. Percentage of open stomata observed on the abaxial sides of the decorative sepal.
using a variety of treatments, elongated the vase life of the cut hydrangea flowers. This result is considered to have been due to the reduction of the water required for maintenance of the water balance of the cut flowers. In addition, extra time prior to wilting would have been generated.
In a wide variety of cut flowers, occlusion of vessels results in disruption of the water balance and progress of the wilting of these flowers (Loubaud and van Doorn, 2004;van Doorn and Cruz, 2000;van Doorn et al., 1989). The stems of the cut flowers used in all experiments were of almost identical diameter, except for the cut flowers bearing small inflorescences. The hydraulic conductivity of the stems of the cut flowers bearing a small inflorescence would be less than those of others; however, in the present study, a negative effect on vase life in cut flowers with thin stems was not apparent.
In cut rose flowers, browning of petals, caused by infection of Botrytis cinerea, is facilitated under highhumidity conditions (Williamson et al., 1995). In the present study, browning of decorative sepals, which was frequently observed in covered inflorescences, may z Three cut flowers were randomly sampled and used for the investigation. y Transpiration rate from a decorative floret was derived from the transpiration rate of the cut flower and the number of decorative florets. The transpiration rate of the cut flower was divided by the number of decorative florets. x Measurements were conducted on the day after harvest. The values are the mean ± SE (n = 5). Table 3. Stomatal conductance of the sepal and transpiration in cut flowers. have been due to the high humidity in the cover and pathogens in the environment. In a previous study on anthurium, an artificial wax coating on the spathe suppressed the transpiration from cut flowers and resulted in extension of the vase life (Mujaffar and Sankat, 2003). Anti-transpirants, materials that coat the surfaces of cut flowers without raising the humidity around them, would be useful for extending the vase life of cut hydrangea flowers.
Although the effect of a difference in hydraulic conductivity of the stem remains to be elucidated, the number of decorative florets can be used as an indicator of the longevity of cut hydrangea flowers. Cut flowers with large inflorescences, carrying approximately 420 decorative florets, had a vase life of 5 days. On the other hand, the vase life of small inflorescences, carrying approximately 190 decorative florets, was approximately 15 days. The Japanese market prefers cut hydrangea flowers with rather small inflorescences (personal communication with market staff), so smallness of the inflorescences would not spoil the marketability of cut hydrangea flowers in Japan.
Some studies of stomata formed on the decorative organ have been reported. Hew et al. (1980) reported that stomata on tepals of orchids do not react to abscisic acid treatment, and concluded that those stomata contribute little to transpiration control of the flower. Azad et al. (2007) studied stomata on the tepals of tulips, and suggested the involvement of stomatal transpiration regulation in flower opening and closing. In anthurium, almost all of the stomata on the spathe are closed, and no correlation was identified between the stomatal density and the vase life of cut flowers (Elibox and Umaharan, 2010). In the present study, most of the stomata formed on the decorative sepals were closed even under light conditions (Table 4), and low stomatal conductance was detected on the abaxial epidermis of the sepal (Table 3). In the defoliated cut flowers, diurnal change in transpiration was not observed (Fig. 2). Thus, most stomata formed on the decorative sepal would not be functional. Transpiration from the decorative sepals would thus be determined by cuticular transpiration.
In the present study, it was suggested that the suppression of transpiration from the inflorescences was effective for extending the vase life of hydrangea cut flowers. We conclude that using cut flowers that do not bear too many decorative florets and treatments that suppress transpiration from the surface of the decorative sepals would be effective for extending the vase life of cut hydrangea flowers. | v3-fos |
2018-12-17T18:04:35.530Z | {
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} | s2 | The Changes of Soil Physical and Chemical Properties of Andisols as Affected by Drying and Rewetting Processes
Soils from a toposequence in northern slope of Mt. Kawi, Malang were sampled to study the effect of amorphous content on the irreversible drying properties of the soils. Water, clay, organic-C, and available P contents were measured at field capacity (KL), after air-drying for 2 days (K2) , air-drying for 4 days (K4), oven-drying at 40 °C for 1 day (Ko), as well as after rewetting K2 (KL2); K4 (KL4), and Ko (KLo). The results showed that water, clay, organic-C, and available P contents changed after drying and rewetting processes. Drying process decreased clay content but increased available P content. Clay and water content of the rewetted samples, especially after oven-drying (KLo) were lower than at initial field capacity (KL), as indication of irreversible properties. In contrast, available P and organic-C content were higher after drying-rewetting processes. Variation of water, clay, organic-C, and available P contents after drying-rewetting processes were significantly affected by respected properties at initial field capacity. These properties tended to change in accordance to Alo+½Feo content. The effect of Alo+½Feo content, however was statisticaly detected only on the water content at KLo (rewetted after oven-dried) and on organic C content at KL2 and KL4 (rewetted after air-dried for 2 and 4 days).
Introduction
Soil management requires a deep understanding on soil properties and characteristics that possibly affect crop growth. The northern slope of Mount Kawi-Butak is dominated by Andisols, which have unique-physical properties due to a high content of amorphous mineral (Nita et al., 2015). The amorphous minerals play significant role in determining soil physical and chemical properties (Van Ranst et al., 2002;Qafoku et al., 2004).
Andisols commonly have irreversible characters after drying. This character is suspected to create some problems during analysis at the laboratory. Drying of soil samples prior to laboratory analysis will certainly change soil properties, which are going to be measured. Variation of soil moisture due to different drying intensities will eventually affect quality of the results.
Many studies have been conducted on the effect of drying duration on soil properties. Most of these studies (Seguel and Horn, 2006;Khan et al., 2007;Blackwell et al., 2009) dealt with the irreversible properties of Andisols only as the effect of drying. No studies, however, examined whether these properties are irreversible if the soil samples are rewetted to the initial moisture condition. Therefore, this study was aimed to elucidate the effect of drying and rewetting processes on the changes of soil properties, and their relationships with amorphous material contents.
Materials and Methods
Five soil samples, classified as Humic Udivitrands (Putra et al, 2015), were collected from a toposequence at the northern slope of Mt. Kawi, Pujon, Malang. Soil samples were taken at field capacity (KL), Since the content of Al o +½Fe o (Al and Fe, extracted from 1 M ammonium oxalate) indicated the occurence of amorphous minerals, soils with varying Al o +½Fe o content were selected (A1= 2.3%; A2=3.7%; A3=4.1%; A4=4.7%; A5=5%) for this study. Data of Al o +½Fe o content were taken from previous study (Nita et al., 2015).
Experiment on the irreversible drying properties comprised of two processes, i.e. drying and rewetting the soil samples. The drying process comprised of three different levels of drying, i.e. drying for 2 days (K2), 4 days (K4), and oven-drying at 40 o C for 1 day (Ko). Then, soil samples (K2, K4, and Ko) were rewetted to the field capacity condition (KL2, KL4, and KLo, respectively). Schematically, drying and rewetting processes are presented in Figure 1. Water content, organic-C, total-N, available P and water-dispersible clay contents were analyzed on each condition (KL, K2, K4, Ko, KL2, KL4, dan KLo) to study the change of soil properties after drying and rewetting. Differences in soil properties between K2, K4, Ko, and KL showed the effect of drying. Whereas the irreversible drying properties were reflected by the difference between KL2, KL4, KLo, and KL. Then, such changes of soil properties were correlated with the Al o +½Fe o content.
Available P content
The drying process has changed the value of available P content of each soil samples. The drying from KL to K4 (4 days drying) increased the available P contents in A2, A3, and A5 soils, but the values decreased again after oven-dried (Ko). The content of available-P in Ko was higher than that of KL ( Figure 2). In general, available P content in soil tended to increase during the drying from 2 to 4 days. This was thought that such drying affected the behaviours of the amorphous materials. The drying process from 2 to 4 days loosened the bond between the amorphous materials and P, so that available P increased. The increase of available P might be due to the release of P which was initialy fixed by the amorphous minerals (Ethan, 2015). The prolonged periods of drought accelerate mineral breakdown producing a higher degree of crystallinity of ferric hydroxides (oxy) and a decrease in binding phosphorus (Baldwin, 1996).
The increase of available P content was also allegedly associated with the increase of soil organic-C content during the drying process. Organic acids that are soluble in organic material will chelate the compound of Al and Fe so that P becomes available. This result was comparable to the study of Peniwiratri et al. (2001), which showed that the provision of organic acids played a role in lowering P retention and increased availability P significantly. Logically, the organic acids that contain many active functional groups, such as the carboxyl group (-COOH) and phenolic (-OH) contribute to the formation of Al-and Feorganic complexes, therefore they will block the retention of P from amorphous minerals. Besides, organic anions of organic acids effectively retrieve or exchange P in the retention by the soil and oxide hydrate Al and Fe. (Nuryani et al., 2000). Meanwhile, a decrease content of available P in Ko was probably due to P-reprecipitation, which was previously released from the amorphous mineral fixation.
Clay content
The clay content kept decreasing along with duration of drying ( Figure 3). The decrease of clay content was followed by the increase of silt and/or sand contents. Drying process caused the clay grains bounded together and formed larger particles, i.e. pseudosands and pseudosilts. In some soil samples, the drying decreased silt content, followed by the increasing sand content. This indicated that pseudosand was formed not only from clay particles, but also from the silt particles.
Soil water content
In this study, the irreversible drying properties on the soil water content was shown by the negative value of the difference between water content measured on dried and rewetted samples in comparison with the initial field capacity (KL). This means that after the soil was dried and rewetted, the water level was lower than the initial KL condition. The results of water content measurement are presented in Figure 4. The irreversible drying properties were shown in A1, A2, A4, and A5 samples. This irreversible water content (KL2, KL4, and KLo) obviously occurred rewetted, in comparison to the initial field capacity. Notes: negative or positive values mean water content at the condition a, b, and c, respectively lower or higher than the initial field capacity condition.
The drying process caused air to captivate the soil particles, so that when soil sample rewetted, air pore blockage prevented the entry of water into the soil pores. Besides, drying process could decrease the surface charge of amorphous materials which in return affecting water holding capacity of the soil. The stepwise regression analysis on the Al o +½Fe o , C-organic, clay, and soil water content (at KL) toward the irreversible drying properties of the water content (Table 1) showed that the soil water content under field capacity condition had the greatest effect on the irreversible drying properties in KL2 (rewetted after air-dried for 2 days) and Klo (oven-dried at 40°C for 1 day). Notes : y = irreversible drying properties of soil water content, x 1 = content of Al o +½Fe o , x 2 = organic-C, x 3 = soil clay content, x 4 = soil water content of the field capacity Water content at field capacity contributed 76%; 61%; and 85% respectively to the water contents of KL2 (rewetted after air-dried for 2 days), KL4 (rewetted after air-dried for 4 days), and KLo (rewetted after-dried 40°C for 1 day). At two days drying process, 24% variation of irreversible drying properties was not significantly influenced by the content of Al o +½Fe o , % organic-C, and % clay. On 4 days drying, effect of the initial water content (KA) was followed by % clay, which indicated an increase in the value of R 2 (from 61 to 76 %), while 24% variations was determined by other factors. On the oven-dried at 40°C for 1 day, 99% variation of irreversible drying properties of water content could be explained by variation of initial water content (85%), Al o +½Fe o content (9%), and % clay (14%). In general, soil containing high amorphous materials (Al o +½Fe o ), would partly lost the capacity to retain water after drying. Drying process might changed the amorphous mineral structures, so that the bond between amorphous minerals and water will be destroyed and cannot produce the same structures even though the soil is rewetted. Woignier et al. (2007) added that the change of allophane microstructures during the drying process would reduce the specific surface area. In this research however, the Al o +½Fe o content only slighly affected (<10%). the irreversible drying properies of water content only after oven-drying process. This suggested that the 2 and 4 days air-drying did not significantly affect the amorphous minerals.
Organic-C content
Data presented in Figure 5 show that organic-C content of the KL2 and KL4 conditions are generally higher than C-organic content at the initial field capacity. The drying process for 2 and 4 days was not able to destroy the bond between organic materials and amorphous clay minerals, so that organic-C content tended to be similar with the field capacity. The increasing content of organic-C in the soil after rewetting process was presumed to be related to C-mineralization process by microbe in the soil. The stepwise regression analysis on the Al o +½Fe o , C-organic, and clay content toward the irreversible drying properties of the water content is shown in Table 2. A number of microorganisms are known to survive during the drying, due to the accumulation of cytoplasmic role as osmoregulator in the cell (Halverson, 2000). This was supported by Franzluebbers et al. (1994) who stated that rewetting of the dry soil would change C, which showed the microorganism's activities in the soil after rewetting process. According to Baldwin and Mitchell (2000), the repetition of drying and wetting over longer time periods will allow bacterial to reproduce rapidly when favorable environmental conditions and can outlive unfavorable conditions by producing a resting stages. Figure 5. Content of organic-C after being dried for 2 days (a), 4 days (b), and oven-dried at 40°C (c), and rewetted, in comparison with the initial field capacity. Notes: negative or positive values mean % organic-C at condition a, b, and c, respectively, were smaller or greater, in comparison with the initial field capacity.
The consistent pattern was found on A5, soil sample containing the highest % Al o +½Fe o . Drying for 2 days and rewetting did not change the content of organic-C. However, after airdrying for 4 days, organic-C has reduced drastically even though the soil was rewetted to initial condition. This meant that on A5, the irreversible drying properties of organic-C have occurred after the soil has been air-dried for 4 days.
The irreversible drying properties of organic-C in this study generally occurred after the soil was dried at 40°C or 1 day. On this condition, it was presumed that drying under high temperature would destroy the bond of organic-C compounds in the soil, so that C would be released in the form of gas. Such rewetting would not be able to restore organic-C content in the soil as at the field capacity. Table 2. Results of the stepwise regression analysis on the irreversible drying properties of C-organic content Stage Organic-C content KL2-KL KL4-KL KLo-KL 1 y = 0.961 -0.171x 1 y = 1.549 -0.345x 1 -R 2 = 0.651 R 2 = 0.624 2 y = 1.118 -0.171x 1 -0.010x 2 --R 2 = 0.835 Notes : y = irreversible drying properties of C, x 1 = content of Al o +½Fe o , x 2 = soil clay content, x 3 = organic-C of the field capacity
Available P content
The results showed that drying and rewetting processes increased P-available in the soil. Such drying might destroyed the bond between amorphous minerals and P in the soil, so that P would be released and consequently increase available P content in the soil. Meanwhile, rewetting could significantly dissolve the released P, which was intially not soluble, and became soluble. This result was similiar to that of Schönbrunner et al. (2012) that the repetition of drying and wetting back process causes the release of phosphorus, where the rate of drying is a major determinant of controlling the release of phosphorus during rewetting process. Figure 6. P-available in the soil after being dried for 2 days (a), 4 days (b), and oven-dried at 40°C (c), as well as rewetted, in comparison with KL condition. Notes: negative or positive values meant water levels at condition a, b, and c, respectively, were smaller or greater, in comparison with the initial field capacity.
The stepwise regression analysis showed that after drying for 2 and 4 days, the content of Al o +½Fe o , C-organic, clay, and P-available in the soil at the field capacity, had no significant effect on the irreversible drying properties of P-available in the soil. Whereas on the samples which were ovendried at 40°C for a day, only P-available at the initial field capacity, had significant effect on the irreversible drying properties of P-available. Andisols may contain considerable amount of total P, but P-ion is strongly bound by amorphous minerals, resulting in a low amount available for plants. Drying process of the soil would break the bond between phosphate ions and amorphous clay minerals, so that the measured P will be released and become available for plants. The rewetting process could not restore the reactivity of the amorphous clay minerals. The increase of P-availability in the soil after submersion can be the results of reduction of FePO 4 .2H 2 O to Fe(PO 4 ) 2 .8H 2 O, desorption as a result of reduction Fe 3+ to Fe 2+ , hydrolisis of Fe(PO 4 ) and AlPO 4 on acid soil, release of occluded-P, and /or anion exchange (Ethan, 2015).
Clay content
The previous drying process caused the clay particles formed larger size of soil particles, i.e. pseudosilt and pseudosand, so that the clay particles would decrease. Figure 7 showed that all soil samples had inconsistent values during the rewetting process, but in general, such rewetting could not restore the decreased clay particles after the soil samples were drying. It was presumed that the pseudosilts and pseudosands formed during drying process, were difficult to re-dispers after rewetting samples following drying process.
Results of the stepwise regression analysis (Table 3) on the influential factors (content of Al o +½Fe o and clay percentage of the field capacity) toward the irreversible drying properties of % clay showed that only the percentage of clay had significant effect on the irreversible drying properties of clay in the soil during the drying for 2 days. In which, % clay has contributed 77.2% to the irreversible drying properties of clay in the soil. Meanwhile, during the drying for 4 days and oven-drying at 40°C for a day, the tested variables, both solely or simultaneously, have no significant effect on the irreversible drying properties of clay in the soil. Figure 7. Percentage of clay particles after being dried for 2 days (a), 4 days (b), and oven-dried at 40°C (c), as well as rewetted, in comparison with KL condition. Notes: negative or positive values meant water levels at condition a, b, and c, respectively, were smaller or greater, in comparison with the initial field capacity condition.
Conclusion
Water, clay, organic-C, and available P contents changed after drying and rewetting process. Drying process decreased clay content but increased available P content. Rewetting process after air-drying was unable to restore water content and % clay at initial field capacity (KL). In contrast, available P and organic C contents were higher after drying-rewetting process. Variation of water, clay, organic-C, and available P contents after drying-rewetting process was significantly affected by respected properties at initial field capacity. These properties tended to change in accordance to Al o +½Fe o content. The effect of Al o +½Fe o content, however was statisticaly detected only on the water content at KL4 (rewetted after 4 days air-drying) and on organic C content at KL2 and KL4 (rewetted after air drying for 2 and 4 days). | v3-fos |
2019-04-23T13:28:07.895Z | {
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} | 0 | [] | 2015-02-10T00:00:00.000Z | 127242526 | {
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"Environmental Science"
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"Agricultural And Food Sciences"
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} | s2 | Pollution Index and Ecological Risk of Heavy Metals in the Surface Soils of AmirAbad Area in Birjand City , Iran
Background: In the present era, the concentration of heavy metals in the environment is increasing. Due to the deleterious effects of these metals on human health as well as their dangerous consequences on ecosystem, special attention should be paid to remove them from the environment. Objectives: The purpose of this study was to assess the ecological risk of heavy metals including lead (Pb), cadmium (Cd), copper (Cu), zinc (Zn), chromium (Cr) in surface soils of an Amir-Abad Area in Birjand City, Iran. Materials and Methods: Soil Samples were collected from a depth of 0-20 cm at 16 stations with different users. The samples were passed through a 2-mm sieve after air drying. To determine the concentration of heavy metals, the samples were extracted by acid chloride and nitric acid and total concentrations of toxic elements were read using the atomic absorption spectrophotometry. The pollution index and ecological risk assessments were calculated for each element. Results: The results showed that the ecological risk of surface soil for the users of the road-residential was high (1370.72) and notable (505.04), and the agricultural land use and livestock had the moderate ecological risk and dairy farm had low ecological risk. When the results of this study were compared to world standards, it was suggested that the areas with the road-residential areas were considered to be dangerous to health; this was directly related to developments of technology and pollution. Conclusions: It can be concluded that residential-road land uses show the considerable pollution index and ecological risk.
Background
An ecological risk assessment is the process to evaluate the likeliness of an environment to be impacted as a result of exposure to one or more environmental stressors. It is a flexible process, not only to organize and analyze data, information, assumptions, and uncertainties but also evaluate the likelihood of adverse ecological effects (1). However, the heavy metals are included as earth's crust forming components and also are naturally present all around the ecosystem. Their concentration can considerably increase via human activities (2). Nevertheless, many researchers have studied the adverse effects of heavy metals on various ecosystems in the past two decades.
Exposure to dust containing heavy metals leads to varied issues, including physical and mental retardation, decreased intelligence quotient, reduced concentration, headaches, cancer, increased blood pressure, renal and liver problems related to the nervous system, general weakness, and dysfunction of internal organs or aggravates via other diseases, and in some cases leads to death (18).
The study area was located on the west side of Birjand, 5 km off Birjand-Kerman road in South Khorasan Province. The potential sources of pollutants in this area were from agriculture and animal husbandry activities, urban activities, the presence of small shops and casual works and also passing one of the main roads of province along this residential area. There is also an industrial estate that can be considered as one of the essential human pollutant sources in environment (17).
Objectives
The purpose of this study was to assess the pollution index and ecological risk of heavy metals including lead (Pb), cadmium (Cd), copper (Cu), zinc (Zn) and chromium (Cr) in surface soils of the Amir-Abad Area, Birjand City, Iran.
Sampling
As the Figure 1 shows, the grid map is used to select the samples in the study area. Five sampling points at each sampling station (fourat the corners and one at the center of the grid) were collected.
The samples were collected at 16 stations with different land uses between 0 and 20 cm soil depths, at each station, 5 samples with 3 replications were collected using the plastic spatula after removing the debris, rock pieces and physical contaminants.
A composite sample of 1.5 kg weight was prepared after mixing the 5 samples obtained from each station. Geographical locations of points were determined by global positioning systems. The samples were passed through a 2-mm sieve after air drying and to determine the concentration of heavy metals, the samples were extracted by acid chloride and nitric acid and total concentrations of toxic elements were read using the atomic absorption spectrophotometry (18).
Calculation of Ecological Risk
The ecological risks of heavy metals were calculated using the following equations (19).
Equation 2. Equation 3.
Where"Cs" is the concentration of study metals, "Bn"is natural background value. "PI"is contamination index, "Er" is the indicator of each element's ecological risk and RI is the determinative of the total ecological risk.
The toxic response factor for a given compoundisshown by "Tr", "Er" is the potential risk index for given substance and "RI" is the potential ecological risk index for each area.
The results were analyzed after calculating the ecological risk for each element and the total ecological risk was evaluated. The following ranges of "RI" values were considered in the present study; low ecological risk RI < 150, moderate ecological risk 150 ≤ RI < 300, high ecological risk 300 ≤ RI < 600 and considerable ecological risk RI > 600 (19).
To calculate the background values in different studies, these values were chosen from previous researches (15), and to assess the amount of ecological risk, the "RI" and "Er" values were calculated using the equation2.
Results
The toxic metals via human activities can lead to soil pollution. These heavy metals are one of the most important pollutants that can cause serious problems to human health, plants and other organisms by entering the food chains (4). Table 1 depicts the comparison between the average concentration of the elements in the study area and the average concentration in the earth's crust. The results showed that the concentration of all elements except Cr were higher than the average of background values.
Equation 1 was used to assess the ecological risk of soil pollution via pollution index. Contamination levels were classified into six categories based on the pollution severity.
The results in Table 3 showed that most of the samples indicated low to moderate pollution. However, some users, especially residential-road areas demonstrated very high pollution.
Discussion
The results of varied concentrations and their respective ecological risks are shown in Table 4. The average lead concentration was 59.46 mg/kg, which was higher than its average in the earth's crust. The concentration of Pb was higher than the earth's crust in all the stations except stations 2 and 3 (Tables 1 and 2). Generally, lead is released from smelting, motor-vehicle exhaust fumes and corrosions of lead pipe work. (20).
The average copper concentration was 60.15 mg/kg, which was higher than its relative concentration in the earth's crust. However, this was true only for the station 2 and 10 (Table 1 and 4). Both these stations caused the total concentration of this element to overpass than its average in the earth's crust. Cupper is extensively utilized in electrical cables, cooking appliances, pipes, chemical factories, metal melting furnaces, pigments and fertilizers (21). Although it is one of the essential elements for humans, but its overdoses could lead to neurological complications, hypertension, liver and kidney dysfunctions and even death (22).
The average Cd concentration was 1.53 mg/kg, which was higher than the earth's crust. Except the second station, the concentration of Cd in other stations was higher than the earth's crust (Tables 1 and 4). Cadmium occurrence in the environment is from both natural and anthropogenic sources. Environmental levels are greatly enhanced by the existing industrial operations as Cd is commonly used as a pigment in paint, plastics, ceramics and glass manufacturing companies. Cadmium is highly toxic, producing symptoms such as nausea, vomiting, respiratory difficulties, cramps and loss of consciousness at high doses. Chronic exposure to this metal can lead to anemia, anosmia (loss of sense of smell), cardiovascular diseases, renal problems and hypertension (17).
The average zinc concentration was 94.09, which was higher than the average concentration of the earth's crust, but it was lower in station 2 to 6, 15 and 16 (Tables 1 and 4). This element is essential for growth of humans, animals and plants and is potentially dangerous for biosphere if present in high concentrations. It is often found in limestone. The main sources of pollution are industries and the use of liquid manure, composted materials and agrochemicals, such as fertilizers and pesticides in agriculture (23). Anemia, muscle pain, stroke, blood diseases and even death can be caused by zinc overdoses (17).
The average chromium concentration was 79.63 mg/ kg, which was lower than the average of the earth's crust, but at stations 9 and 10 it was higher than the average of the Earth's crust (Tables 1 and 4). The major sources of chromium are textile factories, tanneries, pharmaceuticals and metals. Pigments containing oil compounds and greases also contain some amount of chromium (4). Chromium is considered as an essential trace element for the maintenance of an effective glucose, lipid and protein metabolism. High doses of chromium cause liver and kidney damage and chromate dust, which is carcinogenic (24). Table 4 shows the result of ecological risk of heavy metals in surface soils of different land uses. The ecological risk of agriculture and livestock land use was moderate and as indicated by the ecological risks of each element (Er), cadmium is responsible for the pollution. The ecological risk of road and dairy farm land uses were low and road-residential land uses (station 9 and 10) demonstrated high and considerable ecological risk where Cd > Pb > Cu > Cr > Zn were sequentially the most responsible elements. In the study of heavy metals (Cu, Cr, Pb, Ni, Cd, Zn, Fe, Mn and Li) for the determination of the ecological risks in Tehran city also demonstrated the high ecological risk at all samples (25).
The calculated potential ecological risk index at the Golestan Province, Iran, indicated that approximately 68% and 5% of the studied samples had medium and high pollution levels, respectively, whereas a moderate and high potential ecological risk covered about 90% of this province (26).
Population growth and modernization increase the contamination of soils and environment; therefore, it is essential to refine the soil and continually monitor the heavy metals. The average concentrations of Pb, Cu, Zn and Cd in surface soils of the study area were higher than their concentrations in the earth's crust indicating the presence of heavy metals in anthropogenic soils. The pollution index revealed that most of the samples were in moderate or not polluted areas, but was very high with considerable ecological risk in residential-road land uses. | v3-fos |
2015-03-21T21:52:17.000Z | {
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} | s2 | Body condition score and its correlation with ultrasonographic back fat thickness in transition crossbred cows
Aim: The aim was to study the effect of the transition to body condition score (BCS) and ultrasonographic back fat thickness (USG BFT) in crossbred cows. Materials and Methods: A total of 101 multiparous crossbred cows in advanced pregnancy from organized dairy farm were taken up for study. The cows were grouped according to transition stage, i.e. far off dry (FOD), close up dry (CUD) and fresh (F). BCS was estimated by using the five point visual BCS technique with 0.5 increments. The USG BFT was measured by real-time ultrasound using a portable Sonosite instrument. Results: In cows with BCS 2-2.5, the BFT of F period was significantly lower than FOD period. In cows with BCS 3-3.5, the mean BFT at F period was significantly reduced as compared to FOD and CUD period. The overall correlation coefficient between BCS and BFT for different transition stages was 84%, 79% and 75% for FOD, CUD and F period, respectively. Conclusion: The USG BFT gives an accurate measure of fat reserves in cows. The cows with BCS of ≥3.5 entering the transition period are more prone to lose body condition and hence require better and robust management during the transition period.
Introduction
The body condition scoring (BCS) being a subjective technique is used at regular intervals for assessing the condition of livestock. It is particularly helpful in assessing the body fat reserves of farm animals by visual and manual inspection of the thickness of fat cover and prominence of the bone at the tail head and loin region [1-4]. The BCS system being non-invasive, quick and inexpensive is accepted universally to estimate the degree of fatness [5]. BCS is particularly useful as an aid to dry cow and pre-calving management with the main objective that the cows calve down uneventfully and enter the lactation stage safely [6]. It is also strongly related to milk production and the duration of the postpartum anoestrous interval [7][8][9]. As the dairy cows use body energy reserves in the early lactation to cope up with negative energy balance [10][11][12][13][14][15] BCS along with a less common method to assess fat reserves in body tissues i.e. measurement of back fat thickness (BFT) by using real-time ultrasound are more promising approaches to ensure an uneventful transition of dairy cows.
As the cow transition from less demanding non-lactating dry stage to highly stressful lactation stage there is obvious energy and mineral deficiencies and the major outcomes of these deficiencies are metabolic disorders, reduction in body condition score and reduced reproduction efficiency. Therefore, it is needed of the hour to have an efficient and easily applicable tool to estimate body tissue reserves in dairy cows [16].
The BCS provides an easy and reliable method to evaluate the nutritional status, efficacy of feeding system and to assess changes in energy reserves [17,18]. Apart from this, now a days it is widely accepted that the BCS status of a dairy cow indicates nutritional quality, milk yield, reproductive performance, animal well-being and overall farm profitability in a dairy herd [19].
Previously various studies on the precision of BCS system including the ultrasonographic (USG) assessment of subcutaneous back fat indicated that BCS values were closely related to the actual measurement of subcutaneous fat [20]. Few studies were done previously on cross bred cows in India relating to BCS and BFT, but comprehensive information regarding their relation to transition period is lacking.
Therefore, the objective of this study was to examine the relationship between BCS and BFT using real-time USG in transition cross bred cows.
Ethical approval
All the procedures have been carried out in accordance with the guidelines laid down by the Institutional Ethics Committee and in accordance with local laws and regulations.
Animals
A total of 101 high yielding multiparous (Milk yield ≥ 25.50 litre/day) crossbred cows in advanced pregnancy from organized dairy farm were taken up for study conducted during August 2013 to September 2014 in Punjab. The cows were grouped according to transition stage, i.e., Far off-dry (FOD): > 10 days following dry off and not <30 days prior to calving Close up dry (CUD): Between 21 and 3 days prior to calving Fresh (F): 3-30 days in milk Same 101 cows were followed up throughout the study to evaluate the changes in body condition score and back fat thickness.
Body composition
Body condition score (BCS) was estimated by using the five point visual BCS technique with 0.5 increment [21] described in Figure 1.
Back fat thickness (BFT)
Subcutaneous BFT was measured by real-time ultrasound using a portable Sonosite instrument. BFT was measured in B-mode using 5-10 MHz linear transducer at 7.5 MHz frequency. BFT in the rump or thurl area was measured as the thickness of the layer of sub cutaneous fat between the skin and the fascia trunci profunda located above the gluteus medius muscle. The transducer was placed vertically to an imaginary line between the pins (tuber Ischia) and hooks (tuber coaxe) at the sacral examination site (9-11 cm cranial to the pins) [22] after shaving of site and application of coupling gel (Figure-1).
Image measurement and interpretation
Images were measured at a depth of 4.7. Captured back fat images were freezed and measured using inbuilt measurement calliper protocol in the instrument.
Both BCS and BFT were estimated on the same day at each stage of transition. BCS and USG BFT was measured at all the three periods, i.e. FOD, CUD and F period in order to observe and calculate any significant change in BCS and BFT.
Feeding and management
Animals were fed in head to head system in mangers. Feeding involved 45 kg green fodder (Maize, Pearl millet and Sorghum during summer; Egyptian clover and Oats during winter), 6 kg of wheat straw and 2 kg of concentrates per day during last 90 days of gestation. During lactation, the feeding involved 45 kg green fodder, 8 kg wheat straw and 3 kg of concentrates per day.
Statistical analysis
The USG BFT was presented as mean ± standard error. The statistical analysis was carried out using SPSS (16.0). ANOVA followed by Duncan's multiple range test was used to estimate significant difference between BFT at different transition period (FOD, CUD and F) at p≤0.05. The correlation between BCS and BFT was estimated by Microsoft Excel.
Results
The mean USG BFT of cows with different body condition scores for different time periods (FOD, CUD, F) is presented in Table-1. In cows with BCS 2-2.5, the BFT of F period was significantly lower than FOD period but did not differ significantly from FOD to CUD period.
In cows with BCS 3-3.5, the mean BFT at F period was significantly reduced as compared to FOD and CUD period. In cows with BCS group 1-1.5 and 4-4.5, the mean BFT reduced from FOD to CUD to F period but did not differ significantly. There was no cow having BCS 4.5 and 5.
Out of 38 cows with BCS 2-2.5, 1 cow at CUD and 5 cows at F periods had a BCS of <2 (Table-2). Fifty-four cows had BCS 3-3.5 at FOD period (Table-2). Out of these 54 cows, 11 and 24 cows reduced to BCS 2-2.5 at CUD and F period respectively. All the four cows with BCS 4-4.5 at FOD period reduced to BCS 3-3.5 at CUD and F period.
The overall correlation coefficient between BCS and BFT for different transition stages was 84%, 79% and 75% for FOD, CUD and F period, respectively.
Discussion
To the author's knowledge, this is the first study to evaluate the effect of transition period on BCS and BFT concurrently in crossbred cows. Although studies relating BCS and BFT were done previously, but there was the absence of literature regarding evaluation of the changes in BCS or USG BFT at different transition stages. In the present study the BCS was evaluated at three predefined transition stages in crossbred cows on 1-5 scale with 0.5 increments, as a single BCS does not give any indication of whether a cow is gaining or losing body reserves over a period. Furthermore, BFT was concurrently used in this study to validate the BCS, as during the transition it is difficult to judge accurately the real condition of the animal due to weight gain associated with fetal growth. In our study, the cows with BCS >3.5 were more affected with further change in BCS and BFT in subsequent stages. Similar to our findings Bernabucii et al. [23] reported higher reduction in high BCS cows from late pregnancy to first 30 days in milk, than the cows with average and good BCS. This may be attributed to increased resistance of adipose tissue to insulin that predisposes the dairy animal to mobilize non-esterified fatty acid (NEFA), thus potentially creating a vicious cycle of NEFA mobilization and dry matter intake (DMI) reduction during late prepartum period. This is why high BCS animal have lower DMI and more rapid decrease in BCS during the prepartum period than animal of average or good BCS [24]. USG for BFT was evaluated at the most accepted site, i.e. between pins and hooks. Previously Domecq Number of cows [26] reported that only 24.7% of cows entering the dry period with BCS under 3.5 lost BCS during the dry period, whereas 76.6% of cows over 3.75 lost BCS during the dry period. This difference may be due to the feeding management and environmental differences.
Conclusion
From this study, it is concluded that cows having BCS 3-3.5 during start of the dry period should be fed balanced energy ration so that they can maintain their condition and cross transition period uneventfully. USG BFT should be concurrently used as an aid to BCS for assessment of body fat reserves in transition cows.
Authors' Contributions
SNSR designed the experiment. RS carried out the study along with CSR. SNSR and RS analysed the data and prepared the manuscript. CSR reviewed the manuscript. All authors participated in scientific discussion. All authors read and approved the final manuscript. | v3-fos |
2017-06-25T15:23:14.578Z | {
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} | 0 | [] | 2015-07-30T00:00:00.000Z | 13174456 | {
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} | s2 | Optimization protocol for the extraction of 6-gingerol and 6-shogaol from Zingiber officinale var. rubrum Theilade and improving antioxidant and anticancer activity using response surface methodology
Background Analysis and extraction of plant matrices are important processes for the development, modernization, and quality control of herbal formulations. Response surface methodology is a collection of statistical and mathematical techniques that are used to optimize the range of variables in various experimental processes to reduce the number of experimental runs, cost , and time, compared to other methods. Methods Response surface methodology was applied for optimizing reflux extraction conditions for achieving high 6-gingerol and 6-shogaol contents, and high antioxidant activity in Zingiber officinale var. rubrum Theilade . The two-factor central composite design was employed to determine the effects of two independent variables, namely extraction temperature (X1:50–80 °C) and time (X2:2–4 h), on the properties of the extracts. The 6-gingerol and 6-shogaol contents were measured using ultra-performance liquid chromatography. The antioxidant activity of the rhizome extracts was determined by means of the 1,1-diphenyl-2-picrylhydrazyl assay. Anticancer activity of optimized extracts against HeLa cancer cell lines was measured using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay. Results Increasing the extraction temperature and time induced significant response of the variables. The optimum extraction condition for all responses was at 76.9 °C for 3.4 h. Under the optimum condition, the corresponding predicted response values for 6-gingerol, 6-shogaol, and the antioxidant activity were 2.89 mg/g DW, 1.85 mg/g DW, and 84.3 %, respectively. 6-gingerol and 6-shogaol were extracted under optimized condition to check the viability of the models. The values were 2.92 and 1.88 mg/g DW, and 84.0 % for 6-gingerol, 6-shogaol, and the antioxidant activity respectively. The experimental values agreed with those predicted, thus indicating suitability of the models employed and the success of RSM in optimizing the extraction condition. With optimizing of reflux extraction anticancer activity of extracts against HeLa cancer cells enhanced about 16.8 %. The half inhibition concentration (IC50) value of optimized and unoptimized extract was found at concentration of 20.9 and 38.4 μg/mL respectively. Optimized extract showed more distinct anticancer activities against HeLa cancer cells in a concentration of 40 μg/mL (P < 0.01) without toxicity to normal cells. Conclusions The results indicated that the pharmaceutical quality of ginger could be improved significantly by optimizing of extraction process using response surface methodology.
Background
Herbs and natural products are precious sources of medicinal compounds and their benefits and importance for healing have been well recognized since ancient times. The characteristics and health effects of natural bioactive compounds, especially from plant sources including spices, have been extensively investigated. Phytochemicals are important compounds found in medicinal plants that are not essential for the normal functioning of the human body, but are active and exert positive effects on health or in amelioration of diseases. Many phytochemicals have been identified though a great many are yet to be identified [1]. According to a report by the World Health Organization, 80 % of the population in developing countries depends on traditional medicine for their primary health care, and 85 % of traditional medicine is derived from plant extracts [2]. In Malaysia, herbs and spices are generally consumed raw and fresh as vegetables (salad), especially by the Malay community. Ginger (Zingiber officinale Roscoe) is one of the most widely used spices in the world, especially in Malaysia and locally was known as Halia. Owing to its universal appeal, ginger has spread to most tropical and subtropical countries from China and India, where ginger cultivation has been prevalent, possibly since prehistoric times [3]. In ancient times, ginger was highly valued for its medicinal properties and it played an important role in primary health care in ancient India and China. Ginger contains a variety of pungent and biologically active compounds, primarily 6-gingerol, 6-shogaol, zingerone, phenolics, and flavonoids [4]. Between identified components, 6-gingerol was reported as the most abundant bioactive compound in ginger with various pharmacological effects including antioxidant, analgesic, anti-inflammatory and antipyretic properties [5][6][7][8].
The result of recent studies showed that 6-shogaol with lowest concentration in ginger represent more biologically actives compared to 6-gingerol [9][10][11] Dugasani et al. [12] reported 6-shogaol as a potent anti-inflammatory and antioxidant compounds in ginger. Various methods for the analysis of 6-gingerol and 6-shogaol in ginger extract have been reported [13][14][15] but, among these, highperformance liquid chromatography (HPLC) is most widely utilized. Extraction prior to component analysis is the main step for the recovery and isolation of bioactive phytochemicals from plant materials. Analysis and extraction of plant matrices are important processes for the development, modernization, and quality control of herbal formulations [13]. In general, the first step of complete extraction is the selection of plant parts and careful preparation of plant extracts, and a thorough review of the existing literature to learn about the most suitable protocols for a specific group of compounds or plant species. Traditionally, the extraction of 6-gingerol and 6-shogaol compounds is accomplished by reflux or Soxhlet extraction [16]. However, prolonged extraction at high temperature may degrade the 6-gingerol and 6-shogaol compounds, and involves high energy cost. Bhattarai et al. [17] recently reported that in acidic media and under high extraction temperature 6-gingerol can be degraded to 6-shogaol. Generally, the widespread use of ginger as a spice, dietary supplement, tea, cream, household remedy, as well as an ingredient of various herbal formulations, requires standardization of ginger formulations. A model for optimizing the most relevant operational parameters is required in order to achieve higher extraction yield. Response surface methodology (RSM) is a collection of statistical and mathematical technique that used to optimize the range of variables in various experimental processes with reducing the number of experimental runs, cost and time compared to other methods. Zingiber officinale var. rubrum Theilade is distributed mainly in Peninsular Malaysia, where it is known locally as halia udang, halia merah and halia bara. To the best of our knowledge, no other studies have been undertaken to optimize extraction condition of 6-gingerol and 6-shogaol from Z.officinale.var.rubrum Theilade. The aim of this study was to optimize the conditions for the extraction of a Malaysian ginger variety Zingiber officinale var. rubrum Theilade namely Halia bara to achieve high 6-gingerol and 6-shogaol contents and high antioxidant and anticancer capacity by using response surface methodology with a central composite design (CCD).
Plant materials
Z.officinale var. rubrum Theilade rhizomes were collected from Bentong, Pahang, Malaysia. The samples were identified by herbarium of department of biology, faculty science, University Putra Malaysia. Rhizomes were washed with pure water and were soaked in a Mancozeb solution (0.3 %) for 30 min and were cut into 3-5 cm pieces containing 2 to 3 buds. After cutting, all pieces were planted 6 cm deep into the small pots filled with about 1 kg peat moss. Rhizomes were grown in a glasshouse for two weeks. Afterward, seedlings with 2 or 3 leaves were transplanted into polyethylene bags filled with a soilless mixture composed of burnt rice husk and coco peat (1:1). Ginger is a semi-shade loving plant and needs shade for growth and rhizome production. Then, the plants were grown under glasshouse conditions at the glasshouse complex of Universiti Putra Malaysia (UPM) where daily irradiance was approximately 790 μmol/m 2 /s (light intensity in outside was 1150 μmol/m 2 /s). Relative humidity was 70 ± 5 % and average temperature was 28 ± 1°C. The plants were harvested after nine month, with the leaves, stems, and rhizomes separated. The rhizomes were shade dried and were powdered using grinder. These powdered materials were used for further analysis.
Extraction
The optimization procedure for the extraction process focusing on the extraction temperature (X 1 : 50-80°C) and extraction time (X 2 : 2-4 h) was devised based on two factor central composite design, as summarized in Table 1. Rhizomes of Z.officinale var. rubrum Theilade were harvested and washed with water and shade dried. Ten grams of dried rhizomes were extracted with absolute ethanol (100 mL) for 2-4 h at 50-80°C using a reflux apparatus ( Table 1). The ginger extracts were filtered through Whatman No.1 filter paper and kept at −20°C for future analysis.
Ultra High Performance Liquid Chromatography (UHPLC) analysis
The UHPLC system (Agilent, Model 1200) with Agilent C 18 (4.6 × 250 mm, 5 μm) column was used for 6-gingerol and 6-shogaol analysis. In this system two mobile phases including: (A) water and (B) acetonitril (CAN) were used. The column temperature, flow rate and injection volume were adjusted at 48°C, 1 mL/min, 20 μL. The UV absorbance was measured at 280 nm. To prepare the standard solution 6-gingerol and 6-shogaol (0.0625, 0.125, 0.250, 0.500 and 1 mg/mL) were dissolved in HPLC grade methanol. The linear regression equation were calculated with Y = aX ± b, where X was concentration of 6-gingerol and 6-shogaol and Y was the peak area of 6-gingerol and 6shogaol obtained from UHPLC. Identification of the compounds was achieved by comparison of retention times with standards, UV spectra and UV absorbance ratios after co-injection of samples and standards. System suitability requirements: Perform at least five replicate injections of 6-gingerol and 6-shogaol. The requirements of the system suitability parameters are : (1) Symmetry factor (A s ) is not more than 1.5, (2) Percentage of relative standard deviation (RSD) of the retention time (t r ) for 6-gingerol and 6-shogaol standards is not more than 2.0 %.
1,1-Diphenyl-2-picrylhydrazyl (DPPH) assay
The free radical scavenging activity of Z.officinale var. rubrum Theilade extracts were determined according to the Mensor et al. [18] with some modification. DPPH was dissolved in methanol to give final concentration of 2 mM. Following that, 1 mL of DPPH solution was added to different concentration of curry leaf extracts (20, 40, 60 80 and 100 mg/mL). The mixture was shaked gently and incubated at 28°C in a dark room for 40 min. For the control, methanol was used as a blank. The absorbance of the samples was read at 517 nm using spectrophotometer. BHT (butylhydroxytoluene) and αtocopherol, were used as positive controls. The scavenging activity was calculated using the following formula: Determination of anticancer activity Retrieve the frozen cells from liquid nitrogen cell storage tank and thaw the cells in cyrovials rapidly. Carefully transfer the contents of the cyrovial to a centrifuge tube and add 10 ml of pre-warmed media slowly to the cell suspension. Spin down at 1000 rpm for 10 min and gently re-suspend pellet in 10 ml fresh media into culture flask. Incubate in 37°C humidified incubator supplemented with 5 % CO 2 . After 24 h, the old medium was discard one day after seeding and adds 2-3 ml PBS to cover all surface and discard. Add 1.5-2 ml trypsining solution to cover the flask surface and leaved at room temperature for 3 min until most of the cells detach. to each well and mix thoroughly by pipetting 10-20 times to dissolved the blue formazan crystals. The absorbance of samples was read at 570 nm using ELISA reader.
Experimental design
RSM software with central composite experimental design (3-level, 2-factorial) was used to investigate and validate extraction parameters affecting the extraction yields of 6-gingerol (Y 1 ), 6-shogaol (Y 2 ) and antioxidant activity (Y 3 ) of Z.officinale var. rubrum Theilade rhizomes extracts. In this study, 14 experiments were designed and carried out in duplicate with different range of the independent variables, reflux temperature (X 1 : 50-80°C) and extraction time (X 2 : 2-4 h). In order to conduct the experimental design and the statistical analysis the Design Expert software (version 6.0) was used. Analysis of variance (ANOVA) and response surface analysis were used to determine the statistical significance of the model. The adequacy of the model was predicted through the ANOVA (P < 0.05) and regression analysis (R 2 ). The relationship between the response and independent variables was demonstrated using response surface plot. Initially, a second-order polynomial model was set up to predict the response variables. The equation is given below: Where Y is the predicted dependent variable; b 0 is a constant that fixes the response at the central point of the experiment; b 1 , b 2 , b 1 2 , b 2 2 , and b 1 b 2 are the linear, quadratic, and interaction coefficients, respectively. Graphical and numerical optimizations were performed to obtain the optimum conditions and predicted values for the response variables based on the response optimizer.
Results and Discussion
Effects of extraction conditions on 6-gingerol and 6-shogaol content The reflux extraction was designed based on two-factor CCD consisting of extraction temperature (X 1 : 50-80°C) and extraction time (X 2 : 2-4 h) at five levels each ( Table 1). The result of response surface methodology demonstrated significant (P < 0.05) regression relationships between the independent variables and response variables. A high content of 6-gingerol (2.74 mg/g DW) in the rhizome extract was observed for treatment 3 ( Table 2). The current regression analysis also indicated that more than 80 % of the variations could be explained by the models. Analysis of variance for predicted extraction model of 6-gingerol implies that the model is highly significant with a good coefficient of determination (R 2 = 0.97). The result indicated significant (P < 0.01) quadratic and linear effects of the extraction temperature and time on 6-gingerol content (Y 1 ). However, no interactive effect was observed for the independent variables. The predicted model obtained for Y 1 is as follows: Lack of fit test for the model describes the variation in the data around the fitted model. If the model does not fit the data well, the value of lack of fit will be significant and then proceeding with investigation and optimization of the fitted response surface is likely to give misleading results [19]. In current study, the "Lack of Fit F -value" of 4.12 implies that the Lack of Fit is not significant relative to the pure error ( Table 3).
The response surface plot in Fig. 1a shows the relationship between the 6-gingerol content and the extraction temperature, as well as time, illustrating that as the temperature (47.1-82.8°C) and time (1.8-4 h) increased, the 6-gingerol content increased. Upon increasing the extraction time from 2 to 4 h at 80°C, the 6-gingerol content increased from 1.79 to 2.74 mg/g DW.
The result of previous study demonstrated that ß-hydroxy keto presence in gingerols structure is a sensitive to high temperature and promotes dehydration of gingerols at high temperature [17]. The present results are consistent with observations by Bak et al. [16] who reported that when ginger was extracted at room temperature, the 6-gingerol Analysis of variance for predicted extraction model of 6-shogaol implies that the model is highly significant with a good coefficient of determination (R 2 = 0.93) ( Table 3). Significant (P <0.05) quadratic effects of the extraction temperature and time on the 6-shogaol content (Y 2 ) were observed. The predicted model obtained for Y 2 is as follows: The model F-value of 15.58 obtained for the 6-shogaol content implies that the model is significant, with only a 0.07 % probability that such a large "model F-value" can occur owing to noise. The "Lack of Fit F -value" of 1.39 implies that the Lack of Fit is not significant for the predicted model (Table 3). In the current study, treatment 3 yielded a high content of 6-shogaol in the ginger extract, with a value of 1.59 mg/g DW. The predicted content of 6-shogaol for this treatment was 1.63 mg/g DW, which was close to the experimental value (Table 2). Figure 1b shows the response surface relationship between the 6shogaol content and the extraction temperature and time. The obtained results were consistent with previous studies, which reported that the 6-shogaol content increased with higher drying and extraction temperatures and the lowest 6-shogaol content was achieved when the freeze-dried ginger was extracted at a low temperature (30°C), whereas the highest 6-shogaol content was obtained when the ginger was dried and extracted at a high temperature (80°C) [17]. The results demonstrate that the amount of 6-shogaol in rhizomes extract depends more strongly on the extraction temperature than the extraction time. Figure 2 shows UHPLC chromatograms of ginger ethanol extract and standards.
Effects of extraction conditions on antioxidant activity
The DPPH stable free radical method is an easy, rapid, and sensitive method for evaluation of free radical scavenging antioxidants. The results of the DPPH assay showed that the antioxidant activity for all the extracts was more than 62.5 % ( Table 2). The DPPH activity was particularly high for the extracts subjected to treatment 3 (80°C, 4 h), with a value of 89 %. On the other hand, the regression equation obtained using the antioxidant activity (Y 3 ) as the response variable was also significantly (P < 0.05) related to the variation of the independent variables. The coefficient of determination (R 2 ) obtained was 0.96 (Table 3). Significant (P < 0.05) linear and quadratic effects of the extraction temperature and time on the antioxidant capacity were n.s non significant ** = significant at p < 0.01 a b Fig. 1 Response surface plot showing the relationship between the 6-gingerol (a) and 6-shogaol (b) content with the extraction temperature and time observed. The predicted model obtained for Y 3 is given below: The model F-value of 15.79 obtained for the antioxidant activity implies that the model is significant, and the "Lack of Fit F -value" of 1.24 implies that the Lack of Fit is not significant for the predicted model. Figure 3 shows the response surface plot for the relationship between the antioxidant activity (DPPH) and the extraction temperature and time. An increase in the DPPH activity was observed with increasing extraction temperature and time. The increase in the DPPH activity may be due to an increase in the 6-gingerol and 6-shogaol content in the extract.
Correlation between 6-gingerol, 6-shogaol and DPPH activity
Previous studies reported that the major bioactive constituents of ginger are gingerols and shogaols with high pharmacological activities [20,21]. Herein, a significant (P < 0.01) correlation between the 6-gingerol and 6shogaol content and antioxidant capacity of the ginger extract (R 2 = 0.95 and 0.90) was observed (Fig. 4), which is in agreement with observations by Ali et al. [22], who reported that ginger extract with a high 6-gingerol and 6-shogaol content exhibited high free radical scavenging activity. Recent study by Pawar et al. [23] and Guo et al. [24] showed that there is an strong correlation between antioxidant activity of ginger and 6-gingerol content. Herein, 6-gingerol was also found to exhibit the most potent antioxidant properties, whereas 6-shogaol was the least potent. The results obtained in the current study provide additional evidence to support the assumption that gingerols are responsible for the antioxidant activity of ginger rhizome [25,26]. The potent pharmaceutical quality of 6-gingerol may be attributed to its chemical structure. The predicted results were highly consistent with the experimental results obtained using the optimum extraction conditions predicted by the model, which validates the RSM model with good correlation.
Optimization of response
In order to obtain ginger extract with a high content of 6gingerol, 6-shogaol, and high antioxidant activity, the optimal reflux extraction conditions were determined based on the combination of both responses. Multiple graphical and numerical optimizations were carried out to determine the optimum level for the independent variables with desirable response goals. One optimal condition was obtained for all responses, which was reflux extraction at 76.9°C for 3.4 h. Under the optimum conditions, the corresponding predicted response values for 6-gingerol, 6-shogaol, and the antioxidant activity were 2.89 mg/g DW, 1.85 mg/g DW, and 84.3 % respectively. Table 4). The results of response surface analysis for the 6-gingerol and 6-shogaol content and antioxidant activity were verified by comparing the predicted values (2.89 mg/ g DW, 1.85 mg/g DW, and 84.3 %) with the experimental values (2.92, 1.88 mg/g DW, and 84.0 %). The obtained results from verification experiment were in consent with the predicted values, because not significant (P > 0.05) difference was observed between the verification experimental and the predicted values.
Evaluation of anticancer activity of optimized and unoptimized ginger extract
Optimized and unoptimized extracts of Z.officinale var. rubrum Theilade rhizome were used in order to evaluate the anticancer activity against HeLa cancer cell lines. Preliminary screening showed that rhizomes extracts exhibited a significant anticancer activity against HeLa cancer cells at concentration of 40 μg/mL with the inhibition rate of 51.8 and 62.3 % from unoptimized and optimized extracts, respectively (Fig. 5a). HeLa cells showed 71.7 % inhibition when treated with tamoxifen (positive control) at the concentration of 40 μg/mL. Furthermore, with optimizing of reflux extraction anticancer activity of extracts were enhanced about 16.8 %. The half maximal inhibitory concentration (IC 50 ) value of optimized and unoptimized extract was found at concentration of 20.9 and 38.4 μg/mL respectively. The IC 50 value for tamoxifen was observed at concentration of 16.4 μg/mL. As shown in Fig. 5b optimized and unoptimized extract of Z.officinale var. rubrum Theilade rhizome showed 70.13 and 69.43 % of viability at concentration of 40 μg/mL, respectively. According to the obtained results, optimized and unoptimized extracts showed non toxic effects at the concentrations bellow 120 μg/mL. 6-gingerol and 6-shogale were reported as a potent anticancer compound in ginger [27][28][29][30].
The results of previous studies showed that 6-shogaol is able to kill fifty percent of Hela cancer cell line at concentration of 14.75 μM [31]. Then, it could be conducted that enhancement of anticancer activity of optimized extract could be related to rising of 6-gingerol and 6-shogaol content in extract.
Conclusion
Response surface methodology was successfully implemented for the optimization of the experimental conditions for achieving high 6-gingerol and 6-shogaol content and antioxidant activity in ginger extracts. The results indicate that the extraction temperature and time affected the extraction yields of 6-gingerol and 6-shogaol significantly, and consequently the antioxidant activity of the extracts. Reflux extraction at 76.9°C for 3.4 h was determined to be the most efficient condition for the extraction of 6gingerol and 6-shogaol from Z.officinale var. rubrum Theilade rhizome to provide high antioxidant activity. Optimized extract showed a more distinct scavenging activity against the DPPH and also showed significant anticancer activities toward HeLa cancer cell lines in a concentration of 40 μg/mL without toxicity to normal cells. | v3-fos |
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} | s2 | Genetic–geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping
Key message Publically available SNP array increases the marker density for genotyping of forage crop,Lolium perenne. Applied to 90 European ecotypes composed of 716 individuals identifies a significant genetic–geographic correlation. Abstract Grassland ecosystems are ubiquitous across temperate and tropical regions, totalling 37 % of the terrestrial land cover of the planet, and thus represent a global resource for understanding local adaptations to environment. However, genomic resources for grass species (outside cereals) are relatively poor. The advent of next-generation DNA sequencing and high-density SNP genotyping platforms enables the development of dense marker assays for population genetics analyses and genome-wide association studies. A high-density SNP marker resource (Illumina Infinium assay) for perennial ryegrass (Lolium perenne) was created and validated in a broad ecotype collection of 716 individuals sampled from 90 sites across Europe. Genetic diversity within and between populations was assessed. A strong correlation of geographic origin to genetic structure was found using principal component analysis, with significant correlation to longitude and latitude (P < 0.001). The potential of this array as a resource for studies of germplasm diversity and identifying traits underpinning adaptive variation is highlighted. Electronic supplementary material The online version of this article (doi:10.1007/s00122-015-2556-3) contains supplementary material, which is available to authorized users.
Introduction
Grassland ecosystems account for approximately 40 % of the terrestrial land mass of our planet and are of critical importance to carbon sequestration, the bio-geochemistry of soils and the maintenance of biodiversity (Tilman et al. 1996;Jones and Donnelly 2004). Perennial ryegrass (Lolium perenne L.) is a dominant species of temperate grassland ecosystems, covering a broad range of environmental conditions (day length, moisture, altitude, soil type and chemistry, etc.). Understanding the patterns and magnitude of genetic diversity in the allogamous forage grass species L. perenne is thus a useful first step towards identifying loci under selection for multiple ecological traits, and also serves as a gateway for gene discovery in other grasses, with which it shares considerable synteny . To date, genomic resources in Lolium have been relatively poor, but NGS is rapidly facilitating the development of high-density marker assays, such as the Illumina GoldenGate assay developed by Studer et al. (2012).
The genetic diversity in wild populations (ecotypes) has previously been studied in L. perenne (Balfourier et al. 1998(Balfourier et al. , 2000Bolaric et al. 2005a, b;Cresswell et al. 2001;McGrath et al. 2007;Skot et al. 2005;Yu et al. 2011). These have all used techniques, such as AFLP, RFLP and RAPD, whereby only a low marker density was assayed and/or a limited number of populations surveyed. QTLs have been discovered in ecotypic populations for commercially important traits, such as heading date (with its association to digestibility) and submergence resistance (Skot et al. 2005;Yu et al. 2011), demonstrating that these natural populations offer opportunities to discover new marker/trait associations.
Studies of natural populations are increasingly turning towards high-density, genome-wide approaches to understanding genetic diversity (Brumfield et al. 2003;Garvin et al. 2010). The reasons for this are threefold: firstly, because such approaches provide extra resolution over older marker technologies-enabling fine-scale changes in population structure and/or history to be uncovered (Luikart et al. 2003;Morin et al. 2009). Secondly, these technologies lend themselves readily to association genetics studies of complex adaptive traits (Syvänen 2001) and, finally, due to the relative ease with which these assays can be established (Vignal et al. 2002). The advent of next-generation DNA sequencing (NGS) has enabled researchers to rapidly access genome-wide information for their study organism, regardless of whether a full genome sequence exists (Kircher and Kelso 2010;Morozova and Marra 2008). This provides a rich resource which can be mined for genetic markers-thousands to millions of single nucleotide polymorphisms (SNPs) can be putatively identified in silico for a modest outlay in NGS coverage. With access to highdensity SNP genotyping technologies, these markers can be used to screen large populations at a genome-wide level in timeframes which would be impossible with other markers such as SSRs or AFLPs (Brumfield et al. 2003;Willing et al. 2010). The genomic abundance and amenability to cost-effective high-throughput genotyping have meant that SNPs are developing into the most widely used class of genetic marker in the analysis and dissection of inherited complex traits, particularly those that contribute to adaptive, ecological variation (Bergelson and Roux 2010).
SNPs can be utilised using different methods: direct sample sequencing with techniques such as restriction site associated DNA sequencing (RAD; Baird et al. 2008) or genotyping by sequencing (GBS; Elshire et al. 2011) or by SNP array platforms. Each technique has its advantages which are applicable depending on the experimental design and overall aim (Thomson 2014). With the falling costs of sequencing, barcoding samples for NGS sequencing allows an accessible method of SNP genotyping with no prior sequence knowledge or reference genome. However, the bioinformatic analysis has greater demands in terms of pipeline integration and in computing power and storage capacity for the generated data. Furthermore, the reduced representational libraries in the form of RAD tags and GBS are heavily dependent on imputation to fill missing data (Huang et al. 2009). In contrast, once the initial sequencing, probe selection and marker validation has resulted in the creation of an SNP array, array-based genotyping provides a reproducible technique across users and laboratories. Sequencing-based methods are also often prone to loss of shared loci across experiments, whilst array-based markers perform relatively consistently (though individual markers may be monomorphic or null in given populations). The resulting genotypes are thus easy to compare to previous data and experiments due to the same SNPs being typed. Unlike NGS techniques, the analysis of array platform data is possible with a desktop computer with minimal memory/ storage requirements.
We report here on the creation and validation of a publically available custom Illumina Infinium SNP genotyping microarray for L. perenne represented by 2185 validated SNP markers and its application to screening a large European ecotype population of over 700 individuals. We assess the population structure of this collection and note the strong correlation of genotype to geographic origin, which suggests the value of this array for studies of population genetics and adaptive trait variation in ryegrass.
Next-generation sequencing
To identify putative SNP loci which could be used to construct an Infinium assay, we conducted Illumina RNAseq of five diverse genotypes of L. perenne which were contributed as clonal replicates (tillers) by the researchers referenced below. The five genotypes selected were: AberMagic (an IBERS synthetic forage variety, R. Hayes, pers. comm.); a Chromosome 3 substitution line with Festuca pratensis ; a mother plant from the IBERS late heading recurrent breeding population (R. Hayes, pers. comm.); a "stay-green" amenity variety (Thorogood et al. 1993) and an early flowering ecotypic sample from France previously described in Skøt et al. (2007). These genotypes thus represent a selection of L. perenne from wild to highly selected "domesticated" lines. As we were not concerned with gene expression (only SNP detection), a single individual was grown for each genotype. Each individual was harvested at the young (3-4 weeks post-germination) stage and total RNA isolated from both total above and below ground biomass using Trizol extraction (Sigma Aldrich). The above/below ground extracts were pooled for each individual genotype at equimolar concentrations prior to Illumina RNAseq library construction, to provide as much coverage of the transcriptome at equivalent life history stages (flowering tissue was ignored as the genotypes used display significant variation). Aliquots of 2 µg of total RNA per genotype were used to prepare libraries as per the Illumina mRNA-seq protocol (mRNA-Seq 8-sample Prep Kit (RS-100-0801). Each library was sequenced in a single lane of an Illumina GA-IIx platform at GenePool (University of Edinburgh) using paired-end 2 × 56 bp sequencing. Read count averaged 41 million reads per genotype (20.5 million pairs), with the lowest output being the amenity genotype with 13 million pairs and the highest AberMagic (50.5 million pairs). Raw FASTQ data for these libraries are available through the NCBI short read archive (http://www.ncbi. nlm.nih.gov/sra), accessions SRR2034619-SRR2034623.
Sequence assembly and SNP detection
Reads were imported into the Genomics Workbench version 4.5.1 package (CLC Bio Ltd.) and a reference transcriptome was assembled de novo using the reads from AberMagic, since it generated the highest read coverage. De novo assembly in Genomics Workbench uses the de Bruijn graph method with a k-mer value assigned based on the scale of data input (for 2.75 Gbp as here, a k-mer of 23 is assigned). The maximum bubble size for conflict resolution within the graph was set at 50. Repeat regions within the graph were resolved using scaffolding based on paired-end sequences. Following initial contig assembly, reads were mapped back to contigs, requiring 50 % match at 80 % similarity across the read. Ambiguous read mappings (reads mapping to more than one contig) were discarded from the mapping. Insertion and deletion penalties were set at 3 and mismatch penalty at 2. Contigs from the initial assembly were removed if no reads mapped. This step was included to resolve conflicts by generating a consensus based on the most common base for each position.
This assembly produced a total of 55,181 contigs which were used as the reference for read mapping of the five genotypes. This Transcriptome Shotgun Assembly project has been deposited at DDBJ/EMBL/GenBank under the accession GDAT00000000. The version described in this paper is the first version, GDAT01000000. BLASTx annotation of contigs (Altschul et al. 1990) was performed within the Genomics Workbench package using a local copy of the non-redundant (nr) protein database (downloaded circa August 2011). Individual mappings were produced for each genotype (as above, but employing 50 % match at 95 % identity across each read), which were then mined for the presence of SNPs. Non-specific read mappings (reads mapping to >1 contig) were ignored (to avoid identification of SNPs within multigene families), and a minimum quality score of 20 was requested surrounding the putative SNP (quality score for the SNP itself was requested as 30 or higher). To further increase stringency and avoid issues with sequence error, a minimum read coverage of 50 was requested for each SNP. Minor allele variant detection threshold was set at 25 % for similar reasons. Despite the stringency of these criteria, a total of 53,149 putative SNPs (within 11,892 unique contigs) were identified across the five genotypes.
Infinium assay design
Despite the high number of putative SNPs identified, not all the putative SNPs identified were suitable for construction of Infinium probes: firstly, we needed to maximise the likelihood that markers would be informative across a broad range of material. Secondly, we needed to account for the possibility of misassembly during the de novo contig construction and remove sequences which might be present in high copy number. To address the first issue, we subselected markers which showed evidence of polymorphism in two or more of the accessions, reducing the possibility that a particular marker might not show polymorphism in wider L. perenne collections. For example, whilst we included the chromosome substitution line of King et al. (2002) because of its relevance to IBERS breeding programmes, the Festuca material might otherwise contribute a significantly higher number of polymorphisms (though in the event, this material showed a similar number of variants to AberMagic itself, with the natural L. perenne ecotype displaying the most polymorphism).
With regard to the possibility of misassembly in the contig data, we, therefore, excluded any contigs displaying evidence of frameshift (multiple hits to the same match) within their BLASTx result. Further filtering on BLAST identifier was then applied to remove likely organellar or retroelement sequences (as suggested by Illumina), which are likely to be present in high copy number or overrepresented in DNA extracts used for genotyping.
Finally, a minimum flanking sequence of 50 bp is required around the SNP for Infinium probe design (60 bp preferred), which would exclude some SNPs positioned close to the ends of contigs. Although Infinium technology is more tolerant of the presence of other SNPs within the probe sequence, we decided to err on the side of caution and also eliminate any SNPs within 50 bp of each other. Custom PERL scripts were designed to mine the contig FASTA file based on the SNP report tables produced by Genomics Workbench and isolate SNPs with sufficient flanking sequence which were >50 bp away from any other 1 3 SNP. These filters reduced the number of possible SNPs to 4513 (spread across 2943 contigs). A custom PERL script was then employed to extract the flanking 50-60 bp around each marker and annotate the SNP itself with the format [allele1/allele2]. This provisional SNP probe set was uploaded to the Illumina Assay Design Tool (ADT) and the SNPs assessed for probe designability. SNPs with designability scores of 0.6 or higher were selected for inclusion in the final array design, producing an initial assay of 3775 putative SNPs in total. Subsequent validation steps (described below) reduced the final marker set to 2185 SNPs.
Plant material
A bi-parental mapping population (Hegarty et al. 2013), consisting of 193 progeny and two parents (AberMagic × Aurora), was selected to use as a basis of marker validation via allele heritability. In addition, six progeny and two parental replicates were included to assess genotyping error rate.
The ecotype collection used for array validation was formed from L. perenne seed collected at various sites across Europe (Table 1) and subsequently germinated. Accessions were selected from an existing seedbank kept at IBERS, Aberystwyth, in order to represent a range of geographical locations (latitude, longitude and altitudes) as well as environments and land management conditions. Plants from each accession were allowed to polycross to bulk seed for each location. Plants and seed were maintained at IBERS, Aberystwyth University. Leaf tissue was harvested from individual Lolium plants and DNA was extracted using QIAGEN 96 plant tissue extraction kit. A total of 716 individual L. perenne ecotypes from a range of locations and environments across Europe were used, with 8 individuals within each of 89 accessions and four individuals from one accession.
Genotyping and assay validation
Genotyping was performed as per the manufacturer's guidelines using the Illumina Infinium iSelect custom assay (Illumina, San Diego, CA, USA). There was a 91 % assay conversion rate resulting in 3425 putative SNPS on the final array (2334 in unique contigs). The L. perenne ecotype population of 716 individual plants (in addition to five randomly selected replicates) was genotyped using the custom Infinium assay and the data used to produce a cluster file for allele calling. Clustering was initially performed using automated cluster assignment within Illumina's Genome Studio software. However, comparison of the clustering of the SNPs was inconsistent and manual reassignment of cluster position was required. This was independent of the original GenTrain score and, therefore, we were unable to manually reassign the cluster position to only SNPs with a GenTrain score below a certain threshold. Therefore, although laborious, all SNPs were visually inspected by one person for their original automated AA/ AB/BB cluster positions and manually reassigned where appropriate. This also included the exclusion of SNPs with poor performance in this genetically diverse population. Markers were excluded where the average intensity (R mean) for each cluster was below 0.2 or cluster separation was less than 0.3. Markers were reviewed where cluster separation ranged between 0.3 and 0.45 (guidance from clustering algorithm metrics from Illumina). Markers were also excluded where there were missing data for more than 10 % of 716 samples, leaving 2501 markers at this stage. The wide range of genotypes used at this stage will maximise the general utility of the selected probes for further studies, because any interference due to genetic polymorphism resulting from genetic distance between the sequenced plants and the tested individuals will lead to exclusion from the array at this stage.
Although the original 5 individuals that were sequenced for the identification of SNPs were genotyped on the array, the comparison of the RNA sequence data to the genomic DNA SNP array proved difficult due to lack of information on allelic expression bias. Therefore, to further validate the markers, the cluster positions of the 2501 markers on the ecotype samples were exported and applied to the biparental mapping population that had also been genotyped on the array. This enabled use of heritability of alleles within a segregating population to be employed as confirmation of marker behaviour. Of the 2501 markers, 43 markers had more than four parent-parent-child heritability errors and were subsequently excluded, leaving a total of 2458 markers for further analysis on the ecotype population.
Thus, following reassignment of cluster positions or exclusion of markers using all 716 samples 2458 loci were exported. 239 had a minor allele frequency less than 5 % and were, therefore, excluded. Markers were also tested for observed heterozygosity (Ho) excess using GenePop (Raymond and Rousset 1995) in each of the 90 accessions. 34 markers with a probability less than 0.5 for Ho excess were also excluded to minimise genotyping errors. Following these exclusion parameters, a final validated set of 2185 SNP markers (spanning 1606 unique contigs) was available and used to assess the genetic diversity in the ecotype panel. Marker details have been uploaded to dbSNP (http://www.ncbi.nlm.nih.gov/SNP/) under accessions ss1751856902-ss1751859086 and are due for public release in Autumn 2015. Probe details are thus also provided in Supplementary Data Table 2. Marker names follow the convention "ContigX_Y" where X is the contig number as in the NCBI Transcriptome Shotgun Assembly (accession GDAT00000000) and Y is the base position of the SNP within that contig. Users may freely employ these probes in their own assays; alternatively IBERS offer access to the existing array as a genotyping service (contact corresponding author).
Genetic diversity analysis
Data exported from Genome Studio (Illumina) were converted to allele specific presence. For the A alleles for each SNP, AA individuals were coded as 1, AB as 0.5 and BB and missing data were 0, and vice versa for the B alleles.
Missing data were, therefore, coded as 0 for both the A and B alleles and were, therefore, not imputed. Allele frequencies for each marker within accessions were calculated by summing the values for the genotypes (as described above) for each individual within an accession for each SNP and divided by the number of individuals in the accession. Principal component analysis (PCA) was performed on these relative allele frequencies using R (version 2.15.3). Markers contributing the most to PC1 and PC2 were identified via the absolute loading of each marker to the respective PC. For each PC, the BLASTx annotation for the top 50 markers was investigated (Tables 3, 4). Diversity measures were calculated within each of the accessions using GenAlEx (Peakall and Smouse 2006). Distribution of variation between geographic regions (as observed and defined following PCA and Supplementary Fig. 1) between accessions and within accessions was calculated using AMOVA within GenAlEx. This was reported as percentage of variation and measures of Phi PT . Phi PT is used for codominant data as it suppresses intra-individual variation (Teixeira et al. 2014). AMOVA between neighbouring regions was also performed, treating each region as a single population (1 df) to compare to a previous study speculating at the divergence pattern and migration of L. perenne across Europe (McGrath et al. 2007).
Population structure was inferred using an unbiased Bayesian approach Markov chain Monte Carlo (MCMC) clustering of samples via STRUCTURE v2.3.4 (Pritchard et al. 2000). The data were assessed for prior values of K ranging from 1 to 10 with burnin and MCMC iterations settings at 25,000 and 25,000, respectively. For each value of K, 3 replications were performed. STRUCTURE Harvester v.0.6.93 was then used to identify the optimal value of K (using ΔK value; second-order rate of change in log probability between successive values of K) (Earl and Von-Holdt 2012) with CLUMPP used to generate a consensus between runs (Supplementary Fig. 2). Probability of individual membership to group 1 was used to correlate with longitude of sample site origin.
Performance of the array
The Lolium Infinium beadchip assayed 2185 markers with call rates that exceeded 99 % in 86 out of 90 ecotype accessions. The remaining four accessions had average call rates ranging from 97.8 to 98.7 %. As these call rates were consistent between individuals in the accession and across sample replicates, these data were included. Reproducibility of sample replicates was extremely high, with accuracy greater than 99.9 %.
Genetic diversity
The Infinium platform was used to quantify the diversity present in 90 geographically referenced ecotype accessions, represented by 716 individual genotypes, spanning 21 countries and across a range of geographical conditions in Europe (Table 1). As seed for each sample site was germinated and polycrossed within accession at Aberystwyth seed bank, the individuals from each accession would be expected to display greater observed heterozygosity than expected under normal population genetics assumptions due to the self-incompatibility complex in L. perenne. The allele frequencies across individuals in an accession (population), however, are representative of those in the sampled location. Allele frequency was, therefore, used to represent the sample locations across Europe in analyses.
The distribution of the genetic variation was also considered and partitioned based on the outcome of the PCA and geographic-genetic correlations (see below; Fig. 1a; Supplementary Fig. 1). The variation was compared between four regions, between accessions within region and between individuals within accessions using Phi PT (analogous to F ST ). The regions were defined by groupings observed in the PCA plot ( Supplementary Fig. 1). Whilst some genetic variation was partitioned between regions, the greatest diversity (68 %) was attributed to between individuals within an accession (Table 2). Phi PT showed greater variation between populations within regions (Phi PR ), compared to between regions (Phi RT ). A more focused analysis of the distribution of variation between the different regions found similar levels (73-74 %) of within accession variation in the East and West group. The greatest within-population variation was found in the North group, at 76 %, and the least variation in the South (69 %). The regional Phi PT values reflect the between-population variation and indicate that this is highest in among accessions in the Southern group.
Population structure in European Lolium perenne ecotypes
To understand the broad genetic diversity and distribution across Europe, unbiased PCA was performed on the allele frequency for each of the 2185 SNPs within each of the 90 sample locations (accession) (Fig. 1a). PCA uses no prior information on the genotypes in construction of the plot, but despite this the observed distribution bears a striking resemblance to the geographic distribution of the original sampling sites. An East-West distribution was observed on PC1, in addition to a strong UK and Iberian divide on PC2. A strong correlation (R 2 ) of 0.798 was found for PC1 to longitude (P < 0.001) and 0.712 for PC2 to latitude (P < 0.001) (Fig. 1b, c). Significant correlations were also observed between altitude and PC2 (−0.347, P < 0.001). Ecotypes from the UK were found to cluster in the upper left quadrant of the PCA plot, with particular similarity of accessions originating from England and Ireland. Accessions from Scottish islands and Wales were more divergent. A strong Iberian cluster was observed, with exception of one Portuguese accession (PT4; Ba13132) and the inclusion of an Italian accession (IT6; Ba13470). The centre of the PCA plot shows divergence of accessions along PC2 approximately split by the Alps Mountain range. Accessions originating from Eastern Europe are found on the right hand side of the plot, with particular extremity shown by those collected from Bulgaria.
The population structure of the European ecotypes was also examined using STRUCTURE. The optimal number of subgroups (K) within this large collection of individuals was found using Structure Harvester to be two (Supplementary Fig. 2). These data are presented as a scatterplot of individual genotype probability of membership to group plotted against the longitude of the sample site (Fig. 2). In agreement with the PCA, there was significant strong correlation of probability of group membership to longitude (R 2 = 0.782, P < 0.001). The notable outlier (small probability of group 1 membership and low longitude value) was PT4, which was expected given the clustering in the PCA plot (Fig. 1). A small secondary peak was also observed at 4 subgroups ( Supplementary Fig. 2). Two of these groups had significant correlation to longitude (R 2 = 0.766, P < 0.001) and latitude (R 2 = 0.737, P < 0.001). The probability of an individual's group membership was averaged for each region, as defined by the PCA plot ( Supplementary Fig. 1). High probabilities were found for each group (group 1, average probability to South region of 0.57; group 2 to North region of 0.59; group 3 to East region of 0.72; group 4 to West region of 0.80) suggesting that the secondary peak at K = 4 was reflective of the PCA plot.
Identification of primary genetic-geographic markers
To identify the markers contributing to the most prominent genetic structure and variation, the top 50 markers (as determined by their loading) for PC1 and PC2 were identified (Tables 3, 4). Markers within the same contig were commonly seen to have a similar rank within a principal component. This occurred for contigs 35543, 40624 and 7394 in the top 50 of PC1 and for 7 contigs in the top 50 markers contributing to PC2, indicative of closely linked markers behaving similarly as would be expected for robust array SNP probes. The BLASTx annotation for the contigs in which these markers were located was then assessed to determine if putative adaptive transcripts could be identified. Further showing that transcript/loading associations were robust, we observed that several contigs had the same annotation: for example, contigs 35,543 and 40,624 (Table 3) both returned a hit to formate-tetrahydrofolate ligase, and this was represented by 6 markers in the top 50 for PC1. A similar occurrence was seen for PC2 with an aarF domain containing protein kinase identified as a best hit from 3 markers contained in 2 contigs (7729 and 49,805).
Creation of an SNP resource for Lolium perenne
Based on NGS transcriptome sequencing, we have created a publically available resource of 2185 high-quality genetic markers which can be used for rapid genotyping of L. perenne. This significantly increases the number of
among accessions within region) where AR is between regions; AP is between accessions within region; WP is between individuals within accession
Individuals divided into four regions as described by PCA ( Fig. 1 and defined in Supplementary Fig. 1 SNPs assayed on a single array from the previously published 768-plex Illumina GoldenGate array (Studer et al. 2012), which are complementary with our marker set (a v2 assay is being developed with many of these SNPs included). The assay described in this paper provides a new resource to elucidate the selective forces operating on the genomes of naturally occurring perennial ryegrass. A better understanding of these evolutionary forces will have implications for the development of new resilient grassland systems in the context of climate smart agriculture. A publically available SNP genotyping resource will also enable a population-based approach to conservation genetics and higher resolution study of the population structure of L. perenne. Conversion of NGS transcriptome sequence variants into validated SNP probes was ~64 % successful, which appears to be consistent with similar assays based on NGS data (van Bers et al. 2012;Verde et al. 2012). Given the de novo nature of this transcriptome assembly, the heightened stringency measures taken in selecting putative SNPs was indeed necessary and, if repeated, could now take into account the existence of recent, more in-depth NGS assemblies such as the annotated transcriptome of Ruttink et al. (2013) or the draft L. perenne genome currently in progress. Regardless, the assay represents a significant increase in SNP resources for Lolium and highlights the value of developing fixed platforms which can be used to assay the same markers across a broad range of material.
Population structure of Lolium perenne across Europe
This study reveals the genetic structure of European L. perenne populations and demonstrates strong correlations between genotypes and geographic origin despite no prior knowledge. Previous studies on L. perenne have reported a population structure (Skot et al. 2005;Yu et al. 2011;Bolaric et al. 2005a, b;McGrath et al. 2007;Balfourier et al. 1998Balfourier et al. , 2000. Balfourier et al. (1998Balfourier et al. ( , 2000 reported an association of geographic origin to genetic diversity, initially via 120 populations but only across 12 loci marker set and then from 28 populations using cpDNA identifying 15 haplotypes. Similar results were reported by McGrath et al. (2007). However, the link to geography has not been as clearly defined as in this study. Our results provide a greater resolution as a consequence of a larger marker set and sample size. Similar genetic-geographic correlations have been seen previously across Europe in >3000 human genotypes with a high density (500 k) SNP array (Novembre et al. 2008). Substructuring of L. perenne populations due to geography may be indicative of either adaptation to different ecological habitats, or due to changes in allele frequency resulting from population subdivision (i.e. isolations by distance and/or from glacial refugia): potentially a mixture of both. Divisions of the L. perenne population across both latitudinal and longitudinal gradients have been proposed previously in limited sample population sizes and with a reduced marker set using isozyme analysis (Balfourier et al. 1998) and chloroplast DNA haplotyping (Balfourier et al. 2000). L. perenne has been suggested to have arisen in the Middle East and subsequently migrated to Europe, with the Alps acting as a barrier to gene flow between North and South Europe (Balfourier et al. 1998(Balfourier et al. , 2000. However, this scenario would be expected to result in a diversity gradient from West to East due to the sequential sampling of allele frequencies from the wave of advance and result in lower diversity in the Western regions. This study, however, found comparable diversity between accessions in East and West regions (Table 2), which does not support this theory.
The alternative scenario is one of the repeated population expansion and contraction due to periodic glacial cover, in which L. perenne populations were forced back to Western, Eastern and Central refugia along the Mediterranean prior to subsequent re-expansion to Northern latitudes. Populations in each refugium diverge during the glacial maxima and then interact with divergent allele frequencies mixing in areas of expansion overlap, resulting in clines that run approximately East to West. Our study supports this scenario due to comparable diversity in East and West regions, and greater diversity in the Central/Southern region and lowest between accession diversity in the North as indicated by Phi (PT) ( Table 2).
Evidence has also been previously provided to support the migration from South to North Europe via comparisons of geographic groups using AMOVA, whereby no variation was found between Near Eastern and Southern European ecotypes, nor Western and Southern European ecotypes (McGrath et al. 2007). AMOVA on these data between neighbouring regions identified variation between all neighbouring populations (Supplementary Table 1) unlike the previous study. McGrath et al. (2007) also found no variation when comparing populations north and south of the Alps. In this study, despite the close geographic proximity of some accessions in northern Italy and Switzerland, the genetic divide is disproportionately large, as observed from PCA, supporting the theory of a physical population barrier dictated by the altitude of the Alps. The differing results are probably a reflection of number of markers used and number of sample populations used, together these have given a greater resolution of genetic diversity and association with geography.
Two ecotypes, PT4 and IT6, were found to be outliers based on their genotypes, compared to their geographic origin (Fig. 1). Their actual geographic sample site was found to be of low altitude and coastal. Therefore, it is proposed that these ecotypes may have been transported via (sea) trade routes from their "genetic" origin to their current geographic location. PT4 (Ba13132) has previously found to be genetically outlying from other L. perenne Portuguese accessions based on AFLP analysis (Cresswell et al. 2001), supporting the results in this study. This suggests that the resolution of the SNP resource offers the potential to distinguish recent migrations due to human activity from those undergone as the species spread from refugia.
This study, as one of creation, validation and investigation of L. perenne ecotype diversity, has been able to unexpectedly provide a greater resolution of the European colonisation of perennial ryegrass, which deserves further and more detailed analysis. This, coupled to chloroplast data, may answer some of the questions regarding the migration history of L. perenne raised by Balfourier et al. (1998Balfourier et al. ( , 2000.
Diversity of ecotypes
The greatest proportion of the variation identified in this large ecotype collection was found between individual plants (Table 2). This is not unexpected due to the outbreeding nature and the self-incompatibility complex in L. perenne (Thorogood et al. 1993). It is also comparable to between individual variation of 61 and 82 % previously found in European and Irish L. perenne ecotypes, respectively, based on cytoplasmic markers across 78 accessions (McGrath et al. 2007). Bolaric et al. (2005b) also reported 68 % within European cultivars and 74 % within Polish ecotypes.
Identification of markers contributing to geographic division
A number of markers within the same contigs were identified as having a similar loading to a principal component, as would be expected in the case of genuine associations of genotype with geographic location. This was highlighted by examples in the top 50 markers for PC1 and PC2 in Tables 3 and 4, but was common through the rankings. Markers associated with the East-West divide (PC1) are listed in Table 3. To identify transcripts putatively associated with the geographic split and thus possibly adaptive variation, the BLASTx annotations of the RNAseq contigs from which these markers were derived were investigated further. Whilst a majority of the sequences returned no hit or hits to predicted proteins only, several contigs were identified which may be indicative of adaptation to environment. These included six SNPs across two contigs having a greatest similarity to formate tetrahydrofolate ligase, which has been associated with CO 2 metabolism (Dupont 2008) and to photorespirational response to stress (Cai et al. 2011). Subsequent analysis has demonstrated that these two contigs are actually the same transcript, overlapping by 20 bases (which would have been insufficient for contig merging in the assembly parameters used here). Reassembly of contigs to a draft L. perenne genome sequence is ongoing and annotations will be updated accordingly. Several other transcripts showed multiple markers associated with the PC1 divide: adenylyl cyclase-associated protein and a 66 kDa stress-related protein both had two SNPs within the same contig present in the top 50 markers. The former of these has been associated with auxin-regulated cell proliferation (Ichikawa et al. 1997) and also in blue light signalling (Iseki et al. 2002)-another marker in a transcript encoding NPH1-2 is associated with blue light response (Sakai et al. 2011). The 66 kDa stress-related protein has a WD40 functional domain, which has been linked to developmental signalling pathways in plants (van Nocker and Ludwig 2003). Interestingly, the same markers within this latter transcript also appear in the top 50 contributing to PC2, suggesting a strong association of the transcript with geographic diversity. Other transcripts associated with developmental pathways and/or stress responses are also observed to contribute to PC1: histidine-containing phosphotransfer protein 2 has been demonstrated to play a role in cytokinin signalling in Arabidopsis (Hutchison et al. 2006), whilst GSK-like kinases are known to be involved in multiple developmental and stress signalling pathways in plants (Choe et al. 2002). A transcript encoding gammatocopherol methyl transferase was also identified: tocopherols are essential micronutrients in plants and act to protect against oxidative stress (Koch et al. 2003). Several transcripts involved in import/export are also identified (major facilitator superfamily protein, importin subunit), along with transcripts involved in cell wall lignification (laccase).
Markers contributing to PC2, or the North-South axis, tell a similar story. Markers were identified in transcripts linked to plant growth/development: cysteine proteinase (Grudkowska and Zagdanska 2004), Pur-alpha transcription factor (a general regulator of cell cycle gene expression; Trémousaygue et al. 2003) and a cell division cycle protein. Stress-related transcripts are also identified, including the same 66 kDa protein as for PC1. Two markers are identified in a contig encoding an aarF/ABC1 domain protein: interestingly, this family of proteins has been implicated in tocopherol biosynthesis, a process also putatively affected in PC1 and a possible response to oxidative stress (Martinis et al. 2013). A transcript encoding delta(24)sterol reductase was also identified: again, sterols play a role in antioxidant activity in plants and cycloartenol synthase (involved in the production of sterol intermediates) was also identified on PC1. Hydroquinone glucosyltransferase was also identified on PC2 and phenolic hydroquinones also have antioxidant properties, suggesting a putative general role for these compounds in plant adaptation. It should be noted that sterol levels also play a role in cold tolerance in plants (Palta et al. 1993), and we also observe a marker in a transcript encoding a trehalose-6-phosphate synthase, which is also implicated in cold tolerance (Li et al. 2011). Finally, and distinct to the observations for PC1, several transcripts were observed to be involved in cytoskeletal development (myosin, villin) and Ca 2+ -mediated signalling (CBL-interacting protein, annexin).
The pathways identified on both PC1 and PC2 are all strong candidates for adaptational responses to environment. However, further research will be needed to see if specific haplotypes are indeed associated with phenotypic changes that would suggest adaptation. It is also possible that these markers represent founder effects as the L. perenne subpopulations spread from refugia.
Potential applications of the iSelect assay
This analysis, based on genome-wide nuclear marker technology, improves the resolution with which the population substructure can be assessed, offering a clearer understanding of how the migration of L. perenne across Europe may have occurred. In addition, there is potential to identify the genomic regions strongly differentiating the different subpopulations and thus untangling the effects of migration and adaptation. This latter point is of particular importance in the face of global issues of climate change and food security-if the geographic correlations observed are tied to ecological habitat, then genomic regions can potentially be identified that are involved in local adaptation which can be mined for useful traits needed in L. perenne breeding programmes (and possibly used for gene discovery in other grasses). The next steps will be to identify the extent of linkage disequilibrium within L. perenne to determine the power of this marker set to perform genome-wide association studies (GWAS) of adaptive traits, as well as to determine the amount of ecological diversity which has been captured within existing breeding programmes. Large-scale genotyping has the potential to significantly improve the rationale of conservation, characterisation and utilisation of crop genetic resources (McCouch et al. 2012). In the case of perennial ryegrass, the iSelect array developed in this study can potentially be used to explore existing variation in ryegrass collections, manage seed multiplication and enhance quality control procedures. This assay also provides a means to identify core collections for ryegrass ecotypes for multi-environment field testing to identify candidate genes underlying quantitative traits responsible for adaptation to changing climatic conditions.
Conclusion
This publically available resource significantly expands on the marker density previously available for genotyping the agriculturally important forage crop species, L. perenne. The validated markers have allowed a greater resolution of the genetic-geographic population structure and diversity available in the ecotypic population in Europe. These populations, along with the array, will provide a mechanism to identify the markers, genes and traits to respond to the demands of a rapidly changing climate.
Author contribution statement WP & MH designed the research. MH conducted the NGS analysis, SNP discovery and assay design. TB conducted genotyping and genetic diversity analyses. RM advised on population genetics analysis. TB, MH & WP wrote the paper. RM provided critical review of the paper. IT collected, stored and catalogued germplasm for the ecotype collection. | v3-fos |
2016-05-12T22:15:10.714Z | {
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} | s2 | An indica rice genotype showed a similar yield enhancement to that of hybrid rice under free air carbon dioxide enrichment
Although the rice growth response to FACE (free-air CO2 enrichment) has been widely studied and is considered important within the scientific community, few studies have attempted to examine the effects of FACE on the yield of indica rice, which is typically the parent of indica hybrids in China. The effects of FACE on the yield, yield components, biomass, N uptake and leaf photosynthesis of Yangdao 6 Hao (an indica rice) in China were examined over 2 years. The grain yield increased over 30%, the panicle number increased 12.4% on average, and the spikelet number per panicle also showed an average increase of 8.2% at elevated CO2. FACE caused a significant enhancement in both the filled spikelet percentage (+5.9%) and the individual grain weight (+3.0%). Compared with three prior FACE studies on rice, a similar enhancement of yield in hybrid indica was shown under FACE, with much a higher value than for the japonica rice cultivar (approximately + 13%) because of indica’s stronger sink generation and N uptake capacity, which help coordinate the C/N balance to avoid photosynthetic acclimation. The high enhancement of the indica rice yield under FACE holds promise for improved cultivar selection for future food security.
Yangdao 6 Hao has large panicles, a high yield potential, resistance to disease and pathogens, and an anti-lodging ability, which suggest that this cultivar may be an important gene resource for rice breeding 14 . Hence, we chose this cultivar as the study subject. The aim of this study was to investigate whether the indica rice under consideration has a similarly strong response to elevated [CO 2 ] as hybrid rice using FACE (free air carbon dioxide enrichment) treatment.
Results
Effects of CO 2 on grain yield. FACE significantly increased the grain yield of the rice (P < 0.01) ( Table 1). The enhancement of the grain yield was 36.2% and 29.6% in 2012 and 2014, respectively. There was a strong effect of year on the yield response (P < 0.05) ( Table 1), but interactions between CO 2 and year were not detected.
Effects of CO 2 on yield components. As shown in Table 1, the panicle number per m 2 was increased to a similar extent (13.5% for 2012 and 11.2% for 2014, P < 0.05) under elevated [CO 2 ], and there was no significant interaction between CO 2 and year. The number of spikelets per panicle increased by 9.6% for 2012 and by 6.8% for 2014, and there was a strong year effect (P < 0.01). There was no interactive effect of CO 2 × year on spikelets per panicle (Table 1).
For the filled spikelet percentage, FACE rice showed a similar increase in the two years (5.8% for 2012 and 5.9% for 2014). The individual grain weight increased by 3.5% and 2.3% for FACE vs. ambient plants in 2012 and 2014, respectively ( Table 1). The interaction between CO 2 and year was not detected for the two yield components.
Effects of CO 2 on phenology, shoot and tiller biomass, and plant height. There was no change in phenology upon reaching 50% panicle emergence and grain maturity ( Table 2). In contrast, FACE significantly increased the shoot and tiller biomass and plant height at maturity. When averaged across years, the shoot and tiller biomass and plant height were increased by 29.0%, 14.3% and 4.5%, respectively. There was no interactive effect of CO 2 × year on phenology, shoot and tiller biomass or plant height ( Fig. 1 and Table 2).
Effects of CO 2 on gas exchange. There was a significant stimulation of flag leaf photosynthesis with elevated [CO 2 ] (relative to ambient) observed at the mid-filling stage for plants grown under either ambient or FACE conditions ( Fig. 2A). There was no difference in the net photosynthetic carbon assimilation rate of plants grown under ambient and FACE conditions when measured at the same [CO 2 ] (590 μ mol mol −1 ), indicating that the photosynthetic efficiency was not reduced by elevated [CO 2 ], even at the mid-filling stage ( Fig. 2A). The leaf temperatures were not different during measurement. The stomatal conductance and transpiration were not significantly different under ambient CO 2 and FACE conditions, although there was a declining trend due to the elevated [CO 2 ] (Fig. 2B,C). Considering the meaningless in stomatal conductance and transpiration with elevated [CO 2 ] for plants grown under ambient conditions, we did not show these parameters. N uptake. Averaged across two years, the N uptake in the FACE condition was increased by 15.9% during the vegetative stages (from transplanting to heading) and 15.7% during the reproductive stages (from heading to maturity) (Fig. 3). There was a clear variation between the two growth periods (Fig. 3), but the CO 2 effect and stage interactions were not significant.
Discussion
The 2-year FACE study showed that elevated [CO 2 ] increased the yield of Yangdao 6 Hao by over 30% (Table 1), which was a similar enhancement to that of hybrid rice in previous reports of China FACE 9,11 . This value is far higher than the range reported in inbred japonica rice FACE studies 5,8,10,12 . Undoubtedly, this study reveals the potential for taking full advantage of higher [CO 2 ] levels for inbred rice varieties. The FACE condition significantly enhanced the panicle density by 12.4% in Yangdao 6 Hao (Table 2), 10.3% in Shanyou 63 and 7.8% in Liangyoupeijiu 9,11 , all of which are smaller than the 18.8% increase in Wuxiangjing 14 in China Wuxi FACE 8 . The different responses to FACE among these varieties may be associated with differences in the dimensions of the leaf laminae 9 . Compared to rice cultivars with small and erect leaf blades (e.g., Wuxiangjing 14), Yangdao 6 Hao, Shanyou 63 and Liangyoupeijiu, with large and drooping leaves, would suffer more from mutual shading during crop development, thus presumably resulting in a weak stimulation of CO 2 induction for tillering and the resulting panicle number 9 .
In the present study, the number of spikelets per panicle in Yangdao 6 Hao increased by 8.2%, which was slightly lower than in hybrid indica but higher than in japonica under FACE conditions ( Table 2). Shimono et al. reported that the N uptake before the heading stage was closely correlated with the spikelet density rather than the [CO 2 ] and the cultivar type 10 . N uptake by Yangdao 6 Hao increased by 15.9% before the heading stage under elevated [CO 2 ]. The enhanced N uptake before heading was beneficial to increasing the spikelet number for Yangdao 6 Hao under FACE (Tables 1 and 2). In addition, the substantial enhancement in panicle size in this study was supported by the corresponding responses of plant height (Fig. 1A) and shoot biomass (Fig. 1B, Table 2) to elevated CO 2 , which were consistent with the findings that the height and tiller biomass were correlated positively and significantly with panicle size 15 . The spikelet number per panicle is the result of the difference in the number of differentiated and degenerated spikelets 8 . It is well accepted that cytokinins are mainly produced in the plant root and distributed in the shoot by the transpiration stream 16,17 , which impacts rice spikelet formation and development. The decreased spikelet number of japonica rice varieties with a low response to elevated CO 2 in China FACE (Table 2) may be attributed to the decrease in root activity that reduces cytokinin synthesis 18,19 . 6 Hasegawa et al. 12 Yang et al. 8 Liu et al. 9 Yang et al. 11 Table 2 and Fig. 1 in this paper This condition is unlikely to be the case for Yangdao 6 Hao, in which the spikelet number per panicle and the N uptake of the vegetative and reproductive stages were significantly increased by the elevated CO 2 . These findings suggest that Yangdao 6 Hao can maintain root activity for cytokinin synthesis under elevated CO 2 . However, the potential physiological and molecular mechanisms underlying the different responses to elevated CO 2 require further study. Elevated [CO 2 ] increased the actual grain sink per panicle (filled spikelet ratio × spikelet number × per panicle grain weight) by 18.0% in this study (Table 2), which is slightly lower than in hybrid rice but higher than the values obtained in previous FACE studies 6,8,9 . Obviously, grain-filling abilities are related to photosynthate assimilation after heading. At the mid-filling stage, Yangdao 6 Hao maintained a strong increase in the net photosynthetic carbon assimilation rate and avoided photosynthetic acclimation under elevated [CO 2 ] (Fig. 2A). This response is similar to that exhibited by the hybrid rice Shanyou 63, for which elevated [CO 2 ] resulted in an increased spikelet number and grain weight, increased sink:source ratio, and continued stimulation of photosynthesis up to grain maturity 20 . Overall, these results suggest that the greater response of this rice line to elevated [CO 2 ] may be associated with enhanced panicle sinks relative to sources and the ability to maintain photosynthetic capacity during grain development. Under FACE conditions, these rice lines can avoid the photosynthetic acclimation that is common in C 3 cereals 5,12,20,21 . As a result of the balance between carbon and nitrogen metabolism within the leaf under elevated [CO 2 ], the greater sink and the significant enhancement of N uptake during the filling stage (Fig. 2), these plants avoided the suppression of photosynthetic system genes and the resulting decrease in photosynthetic capacity 20,21 . Maintaining photosynthetic efficiency during the grain-filling stage ensures a strong yield enhancement under FACE conditions. This is the first study to confirm that an inbred indica genotype exhibits a yield enhancement similar to that of hybrid rice under elevated [CO 2 ]. To ensure food security in the future, additional indica genotypes with potentially strong responses to elevated [CO 2 ] should be evaluated to take full advantage of the predicted increases in [CO 2 ].
Materials and Methods
Research site. The experiment was conducted at the FACE facility located in Zhongcun Village (119°42'0"E, 32°35'5"N), Yangzhou City, Jiangsu Province, a typical Chinese rice-growing region 22 . The soil was classified as Shajiang-Aquic Cambiosol with a sandy loam texture. The soil properties at 0-15 cm relevant to this experiment are as follows: bulk density 1.16 g cm −3 , soil organic carbon 18.4 g kg −1 , total nitrogen 1.45 g kg −1 , available phosphorous 10.1 mg kg −1 , available potassium 70.5 mg kg −1 , and pH 6.8 23 . The operation and control systems for the FACE facilities were the same as those used at the Japan FACE site 24 . N was applied as a basal dressing (40% of the total) 1 day prior to transplanting and as a top dressing at early tillering (30% of the total) and at the panicle initiation (PI) stage (30% of the total) at 22.5 g N m −2 . Phosphorous (P) and potassium (K) were applied as a compound fertilizer at 9 g P 2 O 5 m −2 and 9 g K 2 O m −2 ; both P and K were applied as a basal dressing 1 day before transplanting.
Photosynthetic gas exchange measurement. Before the measurements, we measured the Chl content in 5-6 flag leaves per treatment plot non-destructively using a Chl meter (SPAD-502, Konica Minolta Optics, Inc., Japan). We then used two leaves with representative Chl content for the gas exchange measurements with a portable photosynthesis system with blue and red LED light sources (LI-6400, LI-COR Bioscience, USA). This measurement was conducted between 09:30 and 14:30 h on September 21, 2014 (mid-filling stage); the block temperature in the cuvette was fixed at 28 °C, and the photosynthetic photon flux density was fixed at 1,800 μ mol m −2 s −1 , with a flow rate of 500 μ mol s −1 . A 6400-01 CO 2 injector attached to the main system was used to control the [CO 2 ] in the cuvette. P N at Rice sampling and biomass measurements. The rice plants were sampled at the heading stage and at grain maturity. Six hills per plot were randomly selected and destructively sampled. The samples were separated into green and senescent leaves, stems (including leaf sheaths), and panicles.
All the plant parts were oven-dried at 80 °C to constant weight before being weighed. The N content in plant tissue was measured using an elemental analyzer (PE 2400, Series II CHNS/O, US). The N uptake was determined by multiplying the N content by the biomass of the panicles, stems and leaves.
The grain yield and yield components were measured according to Zhu et al. 20 . At the maturity stage, the grain yield component characteristics (i.e., panicles per m 2 , spikelet number per panicle, filled spikelet percentage and individual grain weight) were tested using six hills of rice. In addition, a 1.5 m 2 area of rice was harvested at ground level and separated into straw and grain components. The collected grains (seeds) were soaked in 1.00 specific gravity tap water, and the number of sunken and floated grains were counted to determine the filled spikelet percentage. The dry weight of the ripened (sunken) grains was measured after they were oven dried at 80 °C for 72 h. The weight per grain and grain yield were expressed by incorporating a 14% moisture content basis 8 .
Statistical analysis. The experimental design was a split plot arranged within a randomized complete block with 3 replications (three rectangular paddy fields). Using the software Statistical Package for the Social Sciences 19.0 (SPSS Inc., Chicago, USA), we first performed an analysis of variance for the main factors of [CO 2 ] and year on the yield and its components, including biomass and plant height, as shown in Table 1 and Fig. 1. We also performed an analysis of variance for the main factors of [CO 2 ] and stage on N uptake, illustrated in Fig. 3. In addition, post hoc comparisons were performed to detect the effects of [CO 2 ] on the gas-exchange parameters, as shown in Fig. 2. | v3-fos |
2016-03-14T22:51:50.573Z | {
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} | s2 | Protective Effect of Lycium ruthenicum Murr. Against Radiation Injury in Mice
The protective effect of Lycium ruthenicum Murr. against radiation injury was examined in mice. Kunming mice were randomly divided into a control group, model group, positive drug group and L. ruthenicum high dose (8 g/kg), L. ruthenicum middle dose (4 g/kg), L. ruthenicum low dose (2 g/kg) treatment groups, for which doses were administered the third day, seventh day and 14th day after irradiation. L. ruthenicum extract was administered orally to the mice in the three treatment groups and normal saline was administered orally to the mice in the control group and model group for 14 days. The positive group was treated with amifostine (WR-2721) at 30 min before irradiation. Except for the control group, the groups of mice received a 5 Gy quantity of X-radiation evenly over their whole body at one time. Body weight, hemogram, thymus and spleen index, DNA, caspase-3, caspase-6, and P53 contents were observed at the third day, seventh day, and 14th day after irradiation. L. ruthenicum could significantly increase the total red blood cell count, hemoglobin count and DNA contents (p < 0.05). The spleen index recovered significantly by the third day and 14th day after irradiation (p < 0.05). L. ruthenicum low dose group showed a significant reduction in caspase-3 and caspase-6 of serum in mice at the third day, seventh day, and 14th day after irradiation and L. ruthenicum middle dose group experienced a reduction in caspase-6 of serum in mice by the seventh day after irradiation. L. ruthenicum could decrease the expression of P53. The results showed that L. ruthenicum had protective effects against radiation injury in mice.
Ethical Statement
All procedures involved in the handling and care of animals were in accordance with the China Practice for the Care and Use of Laboratory Animals and were approved by the China Zoological Society (permit number: GB 14923-2010). . The remaining reagents were analytically pure, and the water used was purified. HPLC was performed using an Aglient 1200 High Performance Liquid Chromatograph (Agilent Co., Santa Clara, CA, USA); a medical electronic linear accelerator (23EX, Varian, Palo Alto, CA, USA); and a UV-2550 ultraviolet spectrophotometer (Shimadzu Co., Tokyo, Japan). A TGL-16 B high speed freezing centrifuge was obtained from the Shanghai Anting Scientific Instrument Factory (Shanghai, China). An RT-2100C Enzyme-labelled meter was sourced from Shenzhen Rayto Life Science Share Co., Ltd. (Shenzhen, China). Finally, the BC-2300quasi automatic three classification blood cell analyzer used was purchased from Shenzhen Mindray (Shenzhen, China). P53 mouse anti-rabbit monoclonal antibody, Universal PV9000 immunohistochemistry Kit, repair solution of citric acid, phosphate buffer and DAB chromogenic reagent as well as antibody dilution were purchased from Beijing Zhongshan Golden Bridge Biotechnology Co., Ltd. (Beijing, China).
Extraction of L. ruthenicum
The first 300 g of fruits of L. ruthenicum was extracted 20 times with 6000 mL water. The procedure was conducted in a 70 °C water bath in a dark room for 4 h using a 10 L beaker with its opening sealed by Parafilm. Second, vacuum concentration at 70 °C was conducted so that each milliliter of the decoction contained an extract of 400 mg of the crude drug. The extraction of L. ruthenicum was preserved at 4 °C in the dark, ready for experimental testing.
Proanthocyanidins B2 and Total Anthocyanin Detection
L. ruthenicum (10 g) was measured accurately into a 200 mL brown bottle placed in a 70 °C water bath in a dark room for 4 h. It was then cooled, and the mixture was filtered through a microporous membrane and then immediately subjected to high-performance liquid chromatography. The following chromatographic conditions were used to determinate Proanthocyanidins B2: column, Diamonsil 5 μL C18, (250 × 4.6 mm); detection wavelength, 280 nm; column temperature, 30 °C; sample load, 20 µL; flow rate, 1 mL/min and a gradient elution of mobile phase A (2% acetate) and mobile phase B (acetonitrile) ( Table 1). Total anthocyanins: L. ruthenicum (10 g) was measured accurately into a 200 mL brown bottle placed in a 70 °C water bath in a dark room for 4 h. It was then cooled, filtered, and samples (2 mL) were added to 48 mL KCL-HCL (0.2 mol/L KCL: 0.2 mol/L HCL = 25:67) in a volumetric flask (10 mL). The buffer solution was taken as zero, and the absorbance was measured at a wavelength of 526 nm. The procedure was repeated three times.
Animals and Experimental Treatments
A total of 180 4-6 week old male Kunming mice (25 ± 2 g) of SPF grade were provided by Gansu University of Traditional Chinese Medicine Animal Center (SCXK2011-0001, Gansu, China). The animals were adapted for a week at 23 ± 2 °C with a constant humidity of 55% ± 5% under a cycle of 12 h of dark, and given ad libitum access to water and food pellets. Ten animals were housed per cage with separated rooms to ensure each of them can be restrained in a single space so as to avoid restraint stress. All experiments were approved by the School of Medical Science, Medical College of Qinghai University and conducted according to good laboratory practice (GLP) for drugs.
Sixty mice were randomly divided into six groups: control group, model group, positive group (amifostine, 150 mg/kg, body weight/day), L. ruthenicum high dose (8 g/kg body weight/day, LH), L. ruthenicum middle dose (4 g/kg body weight/day, LM), and L. ruthenicum low dose (2 g/kg, body weight/day, LL) group used for the experiment on the third day after radiation. In the same way, another 120 mice were used for the experiments on the seventh and 14th days after radiation. Different doses of L. ruthenicum extract were administered intragastrically to the mice for 14 consecutive days. Model and control groups were orally administered with normal saline. The positive group was administered an intraperitoneal injection of amifostine. Before experiments, animals were immediately anesthetized via enterocoelia injection with sodium pentobarbital (50 mg/kg).
Irradiation
The Qinghai University Affiliated Hospital was used for the irradiation experiments. All mice, except the control group, were restrained in special boxes and exposed to 5.0 Gy total-body X-radiation at a dose rate of 300 cGy/min. The source-to-animal distance was 100 cm. Radiation time: 100 s.
Blood Cell Count
On the 3rd, 7th, and 14th day after radiation, respectively, 20 μL ocular blood was taken from all mice using a centrifuge tube with EDTA-2Na. Blood cell count (leucocytes-WBC, erythrocytes-RBC, hemoglobin-HGB and thrombocytes-PLT) was determined by use of a hemocounter.
Thymus and Spleen Index
On the 3rd, 7th, and 14th day after radiation, respectively, the thymus and spleen were removed from all mice. The thymus and spleen index was calculated by dividing organ weight by body weight (BW): Thymus index (%) = thymus weight (g) / BW (g) × 100% Spleen index (%) = spleen weight (g) / BW (g) × 100%
DNA Contents of Bone Marrow Cell
All mice, on the 3rd, 7th, and 14th day after radiation, respectively, were sacrificed by cervical dislocation. The bone marrow was taken from the whole femoral bone by flushing with 10 mL 0.005 mol/L CaCl2 until the femoral bone became white. The bone marrow was placed in a 5 mL centrifuge tube at −20 °C for 30 min, and then centrifuged at 2500 r/min for 15 min (12 cm rotor diameter). The supernatant was discarded and the sediment applied to 5 mL 0.2 mol/L HClO4 and fully mixed. Water bath heating lasted 15 min, followed by flowing water cooling. The bone marrow solution was filtered by filter paper and determined at 260 nm using an ultraviolet spectrophotometer.
Caspase-3 and Caspase-6 Contents
On the 3rd, 7th, and 14th day after radiation, respectively, blood was taken from all mice using a centrifuge tube. For this purpose, blood samples were taken from the eyeball of animals. The blood was centrifuged at 3000 r/min for 10 min to separate the serum. Caspase-3 and caspase-6 levels in the serum were detected using ELISA. In standard orifices, standard diluents and Str-HRP-Conjugate Reagent (50 µL of each) were added, which already contained combined biotin antibody. In turn, to sample orifices, 40 µL of sample, 10 µL of caspase-3 antibody, caspase-6 antibody, and 50 µL Str-HRP-Conjugate Reagent were added. The plate was covered, sealed, and incubated at 37 °C for 60 min with gentle shaking. The liquid was discarded, and the plate was spin-dried, washed using an automatic plate washer, and patted dry. Chromogen solution A and B (50 µL of each) was added to each well, mixed gently, and incubated for 15 min at 37 °C in the dark. The reaction was then stopped by the addition of 50 µL stop solution, and the optical density (OD) at 450 nm was measured within 15 min.
Immunohistochemistry
The small intestine tissues of mice were placed in 4% paraformaldehyde fixative at 4 °C overnight. The tissue was dehydrated and paraffin embedded. Microtome sections were obtained and mounted on slides. For immunohistochemistry, the slides were deparaffinized in xylenes and then rehydrated for 3 min each in 100% ethyl alcohol, 95% ethyl alcohol, 70% ethyl alcohol, 50% ethyl alcohol, and ddH2O. Antigen retrieval was accomplished by incubating slides in 10 mM sodium citrate and heating in a microwave oven on high for 2 min and on low for 7 min. The slides were cooled in sodium citrate solution for 20 min, washed in TBS-T (Tween) to permeabilize, and then incubated in 3% hydrogen peroxide in TBS for 15 min. The sections were blocked for 1 h in 10% serum (from host of secondary antibody) in 3% BSA-TBS at room temperature and incubated overnight in primary antibody (anti-P53) diluted 1:500 in the blocking solution. A ChemMate TM Envision TM Detection Kit was used for immunohistochemistry according to the manufacturer's instructions. Immunohistochemical images were acquired on a DP71 microscope (Olympus, Tokyo, Japan) and DP CONTROLLER software.
Statistical Analysis
All quantitative data are expressed as mean ± SD deviations. The data were analyzed using one-way analysis of variance (ANOVA) in statistical package for social sciences (SPSS 17.0), and the differences between the means of two groups were compared using LSD tests. The results were considered to be statistically significant when p < 0.05.
Proanthocyanidins B2 and Total Anthocyanidin Detection
The proanthocyanidins B2 and total anthocyanidins in L. ruthenicum were 0.141 g/100 g (Figure 1), were 0.639 g/100 g, respectively. Figure 2 shows that, except for control group, when mice were irradiated on the 10th day, others showed weight decreases compared with body weight before irradiation. The body weight of mice began to increase at six days after irradiation. However, the body weight increase of mice was accelerated by L. ruthenicum and L. ruthenicum could also prevent loss of body weight. Figure 3 shows that compared with the WBC count of the control group the WBC counts of mice in the model group on the 3rd, 7th, and 14th day after irradiation were reduced (p < 0.05). Compared with model, the LH group showed reduced RBC count at three days after radiation (p < 0.05).
Effect of Lycium ruthenicum Murr. on the Hemogram of Mice after Radiation
Seven days after irradiation, the RBC count of mice in positive group and LH, LM, LL group compared with model was increased (p < 0.05). The HGB count of mice in the LH group at three days after irradiation was reduced (p < 0.05), and HGB count in the other groups was higher than the model at seven days after irradiation. However, there was no significant difference in HGB count between the groups at 14 days after irradiation (p > 0.05). Fourteen days after irradiation, PLT count in the model was lower than control group (p < 0.05). Time after irradiation has a significant effect on the HGB and RBC count in each group (p < 0.05). The results indicated that L. ruthenicum treated irradiated groups did not show any significant dose-dependency. Figure 4 shows that the thymus and spleen index of mice in model group at three and seven days after irradiation compared with thymus and spleen index of control group was reduced (p < 0.05). Compared with the model, LH and LM groups showed increased thymus index at three and seven days after radiation (p < 0.05). Fourteen days after irradiation, the spleen index of mice in LM and LL group compared with model was increased (p < 0.05). Spleen index in the model was lower than control group at three, seven, and 14 days (p < 0.05). Time after irradiation has a significant effect on the thymus index and spleen index in each group (p < 0.05). Figure 5 shows that the DNA contents of mice in model group at three days after irradiation compared with DNA contents of LH, LM, LL group was increased (p < 0.05). Compared with model, LM and LL group showed increased DNA contents at seven and 14 days after radiation (p < 0.05). The DNA contents of mice in model group at three, seven, and 14 days after irradiation compared with DNA contents of control group was increased (p < 0.05). Time after irradiation has a significant effect on the DNA contents in each group (p < 0.05). Figure 5. Effect of Lycium ruthenicum Murr. on the DNA content of mice after radiation. n = 10, mean ± SD. a p < 0.05 vs. control group, b p < 0.05 vs. model group.
Effect of Lycium ruthenicum Murr. on Caspase-3 and Caspase-6 of Mice after Radiation
The standard linear regression equations for caspase-3 and caspase-6 were Y = 0.0837X + 0.0287, R 2 = 0.9990 and Y = 0.0678X + 0.0488, R 2 = 0.9980, respectively. Figure 6 shows that there was no significant difference in the caspase-3 contents between the groups at three days after irradiation (p > 0.05). The caspase-3 contents of mice in positive group at seven days after irradiation compared with DNA contents of model group was reduced (p < 0.05). Caspase-3 in the model was lower than control group at seven and 14 days after irradiation (p < 0.05). Fourteen days after irradiation, the caspase-3 contents in LM and LL group was reduced compared with caspase-3 contents in the model (p < 0.05). Three days after irradiation, caspase-3 in model was lower than control group (p < 0.05). Compared with model, LM and LL and positive group showed reduced caspase-6 contents at seven days after radiation (p < 0.05). Caspase-6 in control group was higher than model group at seven days (p < 0.05). Fourteen days after irradiation, caspase-6 in LL group was lower than model group (p < 0.05). Time after irradiation has a significant effect on the caspase-3 and caspase-6 contents in each group (p < 0.05). Figure 6. Effect of Lycium ruthenicum Murr. on the caspase-3 and caspase-6 of mice after radiation treatment. n = 10, mean ± SD. a p < 0.05 vs. control group, b p < 0.05 vs. model group. Figure 7 shows L. ruthenicum had no significant effect on the P53 of mice after three days. However, LL group could significantly reduce P53 at seven days after radiation and LL and LM significantly reduced P53 at 14 days after radiation. The expression of P53 of model group gradually decreased over time.
Discussion
The blood system is the most sensitive target-organ of radiation. The reduction of leukocytes is the most classic indicator of radiation damage [17]. In this study, leukocytes were greatly reduced after irradiation. The erythrocyte, hemoglobin, and platelet counts of mice reached the lowest at seven days after irradiation. However, L. ruthenicum could tolerate the reduction of erythrocyte and hemoglobin at seven days after irradiation (p < 0.05).
As Figure 1 shows, leukocyte progressively increased as time went by. Furthermore, factorial analysis variance confirmed that the time after irradiation could significantly increase WBC count. Except for the leukocyte count in model group, erythrocyte, hemoglobin, and platelet numbers in all groups increased at first and then decreased to the lowest point at seven days after irradiation and significantly recovered at 14 days after irradiation.
Thymus and spleen are the most important hematopoietic organs. Our data showed that thymus and spleen index was reduced after irradiation (p < 0.05), which is consistent with other reports [18,19]. The thymus index at seven and 14 days after irradiation and the spleen index at 14 days after irradiation were increased by L. ruthenicum (p < 0.05). All this showed that L. ruthenicum could have a certain protective effect in mice with thymus and spleen injury induced by radiation. Thymus and spleen index progressively increased as time went by. The comparison of spleen index between L. ruthenicum group and model showed no significant difference at three and seven days after irradiation (p > 0.05), however, spleen index significantly increased at 14 days after irradiation (p < 0.05). This also confirmed that the recovery of radiation injury mice was accelerated by L. ruthenicum. Thymus and spleen are not only hematopoietic organs but also immunity peripheral organs, which represent immune function. The results indicated that the recovery of immune function of radiation injury mice was accelerated by L. ruthenicum. However, the mechanism of cell level is yet to be clearly defined. Mature blood cell responses to ionization radiation exposure show that the function of the hematopoietic system could be damaged by radiation. The lack of blood cell resources, eventually, leads to a decrease in blood cell levels [20]. DNA of bone marrow is an important index that symbolizes the function of the hematopoietic system [21,22]. Our results showed that L. ruthenicum could significantly increase DNA contents in bone morrow and reduced caspase-3 and caspase-6 in the serum at seven and 14 days after irradiation (p < 0.05). Caspase-3 and caspase-6 are apoptotic executioners of the caspase family that [23,24]. The activated caspase-3 cuts PARP (poly ADP-ribose polymerase), which activated the important factors of DNA repair, thus achieving the goals of DNA repair [25][26][27]. The contents of caspase-3 is reduced by L. ruthenicum, which indicates that L. ruthenicum could resist the damage of DNA repair factors. Caspase-6 is unique in the caspase family in that it cuts lamina protein in the process of apoptosis, resulting in nuclear lamina damage so that condensed chromosomes finally lead to apoptosis [28][29][30]. L. ruthenicum could protect chromosomes by reducing the contents of caspase-6 and lamina protein. The DNA damage by radiation may result in the cell cancelation; in addition, the reduction of caspase-3 and caspase-6 would lead to the mass proliferation of tumor cells.
The positive drug amifostine affects the cell apoptosis in double adjustment by increasing the activity of apoptosis factors to the cancer cells and inhibiting the activity of apoptosis factors to the normal cells [31,32]. It is observed that caspase-3 and caspase-6 in the positive drug group also declined, proving that L. ruthenicum could down-regulate the apoptosis of normal cells; hence, protect DNA and enhance the ability to resist radiation. The results of P53 is consistent with caspase. The P53 was increased after radiation and caused cellular apoptosis. However, the expression of P53 of L. ruthenicum group was decreased significantly; then L. ruthenicum could down-regulate the apoptosis of normal cells. In addition, in our pre-experiments, we found that L. ruthenicum can reduce the activity of antioxidant enzymes. L. ruthenicum contains an increased number of anthocyanins that could increase the activity of antioxidants. Free radicals are generated after radiation, that can attack the DNA and induce apoptosis, but in this study, as the figures show, L. ruthenicum can reduce the apoptosis after radiation. We infer that L. ruthenicum acts by directly quenching free radicals caused by radiation, but the concrete mechanism whereby it reduces the activity of antioxidant enzymes and whether it has a double adjustment effect needs further study.
Conclusions
We firstly found that L. ruthenicum has a certain protective effect against radiation injury in mice. In addition, we also reveal that L. ruthenicum can accelerate the recovery of the peripheral blood system and increase the DNA contents of bone morrow, as well as reduce the apoptosis of cells. It can also increase immunological function. Furthermore, we established HPLC conditions for the determination of proanthocyanidins B2 and detected its content in L. ruthenicum, providing a basis for the quality control of L. ruthenicum. In summary, the results of this study provided experimental data for the medical application of L. ruthenicum. Up till now, L. ruthenicum was not only a Chinese herb for traditional medicine, but has also been used as a unique nutritional food, which could be developed and utilized as an effective health product after radiation therapy. | v3-fos |
2016-05-04T20:20:58.661Z | {
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} | s2 | Soil As Levels and Bioaccumulation in Suaeda salsa and Phragmites australis Wetlands of the Yellow River Estuary, China
Little information is available on As contamination dynamics in the soil-plant systems of wetlands. Total arsenic (As) in soil and plant samples from Suaeda salsa and Phragmites australis wetlands was measured in the Yellow River Estuary (YRE) in summer and autumn of 2007 to investigate the seasonal changes in As concentrations in different wetlands. The results showed that soil As levels greatly exceeded the global and regional background values. As levels in soil and the roots and stems of both types of plants were much higher in summer than in autumn, whereas leaf As showed higher level in autumn. Soil sulfur was the main factor influencing As levels in Suaeda salsa wetlands, whereas soil porosity was the most important factor for Phragmites australis wetlands. The contamination factor (CF) showed moderately to considerably polluted levels of As in both wetland soils. Plant roots and leaves of Suaeda salsa had higher As concentrations and biological concentration factors (BCFs) than stems, while the leaves and stems of Phragmites australis showed higher As levels and BCFs than roots. Compared to Phragmites australis, Suaeda salsa generally showed higher translocation factor (TF), while TF values for both plant species were higher in summer than in autumn.
Introduction
Arsenic (As) is ubiquitous in the natural environment [1] due to its natural and anthropogenic origins such as oil exploration, industrial emissions, the applications of insecticides and fertilizers, and sewage irrigation with As contaminated waste [2,3]. Soil As pollution has posed a serious threat to the ecosystems due to its carcinogenic, mutagenic, and teratogenic effects [4,5] and chronic toxicity [6], in particular its higher toxicity to the biota [7]. Moreover, soil As can do harm to human health through biological accumulation in the food chain. Therefore, soil As contamination in the ecosystems has been given increasing attention worldwide [8].
Wetland soils serve as source, sink, and transfer of chemical contaminants [9][10][11]. The retention time of these contaminants (e.g., As) in wetlands could be increased through wetland plants and water flow control, and then it effectively reduces the contaminant diffusion to the surrounding environment via various physical, chemical, and biological processes [12]. Most researchers have focused on As pollution characteristics in wetland soil/sediment [3,5,12,13] and their influencing factors such as soil properties (e.g., SOM, pH value, and Eh) [14,15] and anthropogenic activities (e.g., wetland reclamation, application of fertilizers, and sewage discharge) [13,15]. Roychoudhury [16] investigated spatial and seasonal variations in depth profile of total As concentrations in salt marshes and found few variations in As concentrions along soil profiles in different seasons under natural conditions. However, Bai et al. [5] presented that soil As levles increased from spring to autumn in tidal wetlands due to the flow-sediment regulation of upstream Xiaolangdi reservior. Therefore, it is necessary to investigate and monitor the dynamic variations in As levels in these wetlands with strong hydrological fluctuations to lower As contamination risk. However, few studies have been carried out on As contamination dynamics in the soil-plant systems of wetland ecosystems, especially in estuarine wetlands.
The Yellow River Estuary is one of the larger estuaries in China, which is seriously affected by intense human activities such as the exploration of Shengli oilfield and the flowsediment regulation of upstream Xiaolangdi reservior [5]. The primary objectives of this study were (1) to investigate the dynamic changes in As levels in soil and plant in estuarine wetlands with different plant communities (i.e., Suaeda salsa and Phragmites australis) in the YRE; (2) to assess wetland plant's translocation and enrichment capacities and identify their influencing factors.
Study Area.
The Yellow River Estuary (YRE), located on the south side of Bohai Sea, is one of the most active land-ocean interaction zones among the larger estuaries in the world, and it is also called the "Golden Triangle" due to its great exploitation potential and development [17]. It has a warm temperate monsoon climate with the annual average precipitation of 596.9 mm and the annual average air temperature of 12.9 ∘ C [18]. Most coastal wetlands have been suffering from serious degradation due to less freshwater inputs and intense anthropogenic activities. Since 2002, the flow-sediment regulation has been implemented from June to July of every year by the Yellow River Conservancy Commission to control the water and sediment discharge from the upstream Xiaoliangdi Reservoir [19]. The regulation regime has caused As and heavy metal pollution in the tidal freshwater wetlands and tidal salt marshes [5]. Moreover, the spillage and transportation of petroleum from Shengli oil field also brought serious soil contamination in this region since the oil exploitation in 1964 [20].
Sample Collection and Analysis.
All sampling sites are located in the Yellow River Delta National Nature Reserve. The vegetation type and distribution pattern are dominantly controlled by water and salinity gradients in the YRE. The predominant vascular plants are Phragmites australis and Suaeda salsa [21]. Top 20 cm soils were sampled in both Phragmites australis and Suaeda salsa. In total, 16 soil samples from Phragmites australis wetlands and 25 soil samples from Suaeda salsa wetlands were collected in each of both seasons such as summer and autumn of 2007 in the YRE ( Figure 1).
All soil samples were placed in polyethylene bags and transported to the laboratory and then air-dried at room temperature for three weeks. The air-dried soil samples were sieved through a 2 mm nylon sieve to remove the coarse debris and stones and then ground to fine powder and passed through a 0.149 mm nylon sieve. Another soil core (100 cm 3 ) with three replicates for each sampling site was collected for the determination of soil moisture and bulk density. Meanwhile, plant samples with three replicates were also collected in 0.5 m × 0.5 m plots at each soil sampling site and plant root, stem, and leaf were separated from the whole plant. In total 48 plant samples (including root, stem, and leaf) of Phragmites australis and 75 plant samples of Suaeda salsa were taken. Plant samples were placed in paper bags after clean washing and then transported to the laboratory. All plant samples were oven-dried at 65 ∘ C for 48 h and ground into fine powder. Soil and plant samples were, respectively, digested with an HClO 4 -HNO 3 -HF mixture and an HNO 3 -HClO 4 mixture in Teflon tubes to analyze total concentrations of As in soil and plant. The solutions of the digested samples were determined using the inductively coupled plasma-atomic absorption spectrometry. In the meantime, soil phosphorus (P) and sulfur (S) concentrations in the digested samples were also determined using the same method [5]. Quality assurance and quality control were assessed using duplicates, method blanks, and standard reference materials (GBW07401 for soil and GBW 07602 for plant) from the Chinese Academy of Measurement Sciences with each batch of samples (1 blank and 1 standard for each 10 samples). The recovery of sample spiked with standards ranged from 95% to 99.88%.
Soil organic matter (SOM) was measured using dichromate oxidation method [22]. Soil pH was measured using a Hach pH meter (Hach Company, Loveland, CO, USA) (soil : water = 1 : 5). Salinity was determined in the supernatant of 1 : 5 soil-water mixtures using a salinity meter (VWR Scientific, West Chester, Pennsylvania, USA). The fresh soils were oven-dried at 105 ∘ C for 24 h and weighed for the determination of soil bulk density (BD) and moisture. Soil porosity was obtained from the difference between 1 and the ratio of BD to particle density (2.65 g/cm 3 ).
Contamination Factor (CF).
As pollution in wetland soils was assessed using the contamination factor (CF) [23]. The CF is the ratio of the measured As concentration in the soil ( measured ) to the background baseline value ( background ). In this study, As background concentration (10.7 mg/kg) was obtained based on the environmental background concentrations of the loess materials of the Yellow River [24]. The formula was given: (1) According to Håkanson [23], CF values can be classified into four categories: (a) CF < 1, low contamination factor; (b) 1 ≤ CF < 3, moderate contamination factor; (c) 3 ≤ CF < 6, considerable contamination factor; (d) CF ≥ 6, very high contamination factor.
Biological Concentration Factor (BCF) and Translocation Factor (TF).
Biological concentration factor (BCF) and translocation factor (TF) are widely used to assess the ability of different plant tissues assimilating trace elements from soil and their translocation abilities from roots to aboveground plant tissues, respectively. The BCF and TF formulas are given as follows [25,26]: where the plant tissue (mg/kg) is As concentration in plant tissue (i.e., stems, leaves, and roots) and soil (mg/kg) is As concentration in soil. Consider where aboveground (mg/kg) and root (mg/kg) are As concentrations in the aboveground plant tissues and plant roots, respectively.
2.5. Soil As Storage. Soil As storage (kg As/ha) can be estimated by the following formula: where SAsS is soil As storage; is soil depth (cm); BD is bulk density (g/cm 3 ); and SAsC is soil As concentration (mg/kg) in the given soil layer.
2.6. Statistical Analysis. Pearson correlation analysis was performed to identify the relationships among As concentrations, As storage, and selected soil properties. Oneway ANOVA was implemented to test the differences in plant As, soil As, and selected soil properties between both sampling sites or between both two seasons. Differences were considered to be significant if < 0.05. Statistical analysis was conducted using SPSS 16.0 for Windows (SPSS München, Germany) and Microsoft Excel 2012 software packages.
Soil Characterization in Phragmites australis and Suaeda salsa Wetlands.
Selected properties of the top 20 cm soils in both Phragmites australis and Suaeda salsa wetlands in summer and autumn are summarized in Table 1. As shown in Table 1, soil pH values in Suaeda salsa wetlands were significantly higher in summer than those in autumn ( < 0.05), whereas soil pH in Phragmites australis wetlands did not show significant differences between both seasons ( > 0.05). Lower soil pH values in Suaeda salsa wetlands in autumn were probably attributed to the decreasing root activities and water content [27]. Soils in both wetlands had much higher porosity in summer compared to autumn ( < 0.05). Soil sulfur contents in Phragmites australis wetlands (528.87∼554.20 mg/kg) were significantly lower than those in Suaeda salsa wetlands (609.31∼687.11 mg/kg) ( < 0.05). Zeng et al. [28] presented that soil sulfur level increased with the increasing flooding frequencies, as the pioneer plant, Suaeda salsa, can suffer from more flooding frequencies than Phragmites australis. The average levels of soil moisture, BD, salinity, SOM, and total phosphorus (TP) did not show significant differences between Phragmites australis and Suaeda salsa wetlands and between both seasons.
Soil As Contamination
Level. The mean As concentration ranged from 28.48 to 36.22 mg/kg in Phragmites australis and Suaeda salsa wetland soils with lower spatial variability ( Table 1). The coefficients of variation of As levels in Suaeda salsa wetlands ranged from 6.21% to 12.75%, whereas they varied from 5.68% to 11.73% in Phragmites australis wetlands. All soil samples showed higher As levels exceeding the world guideline (10 mg/kg) [29], of which approximately 68.29% of soil samples had more than three times higher As levels than the worldwide guideline value. Meanwhile, As levels in all soils samples were also much higher than the background value of the loess materials of the Yellow River [24]. Suaeda salsa wetland soils contained significantly higher As storage than Phragmites australis wetland soils in autumn ( < 0.05), whereas no significant differences in soil As storages (SAsS) were observed between Phragmites australis and Suaeda salsa wetlands in summer ( > 0.05). In Phragmites australis wetlands, SAsS exhibited a great decrease by approximately 40% in autumn compared to summer ( < 0.05; Table 1). Despite no significant differences in SAsS between summer and autumn in Suaeda salsa wetlands, a decreasing tendency was also observed from summer to autumn. Contamination factor (CF) was defined as the ratio of As concentration in each sample to the background value [30]. As shown in Figure 2, all CFs of these soil samples exceeded 1, indicating that all sampling sites were suffering from As contamination. As contamination level is higher in summer than in autumn. More than 40% of soil samples from Phragmites australis wetlands and more than 60% of soil samples from Suaeda salsa wetlands showed considerable contamination levels with CFs values exceeding 3 in summer, whereas the CFs values of more than 70% of soil samples were less than 3 in autumn. Table 1 also showed that the mean soil As levels were significantly higher in Phragmites australis and Suaeda salsa wetlands in summer compared to autumn. Meanwhile, we observed that approximately 7% of soil samples from Suaeda salsa wetlands exhibited very high contamination level, implying that some Suaeda salsa wetlands were facing very high As contamination risks. Further studies were still needed to investigate the pollution sources at these sites. Therefore, the coastal wetland soils in the YRE were suffering from high As contamination risk. This might be associated with As accumulation and retention in this region due to natural and anthropogenic activities, such as oil field exploration in the YRE and the applications of pesticides and fertilizers in the upstream agricultural areas [3,31,32]. Bai et al. [5] presented that the flow-sediment regulation regime could bring more As to wetland soils in the YRE. Additionally, Rotkin-Ellman et al. [33] reported that flooding might be one important factor influencing soil As contamination in wetlands.
Relationships between Soil As and Selected Other Soil
Properties. Bai et al. [34] and Farooq et al. [35] presented that SOM could play an important role in affecting soil As contents because SOM could adsorb As and decline greatly its mobility [32]. However, no significant correlations were observed between As and SOM in this study (Table 2). Moreover, As concentration and storage in both wetlands showed a weak negative correlation with SOM, which was associated with higher soil pH values, as As would exhibit higher mobility at higher pH range [14]. This was because the anaerobic carbon decomposition is likely to produce slowly in the flooded areas [36] and thus affected the mobilization of As. Total S contents were significantly correlated with As concentration and storage in Suaeda salsa wetlands ( < 0.05), whereas no significant correlations were observed between them in Phragmites australis wetlands ( > 0.05). The possible explanation is that sulfur might improve plant accumulation capacity of Suaeda salsa to As through improving tolerance caused by a positive effect on thiol metabolism and antioxidant status of plants [37], which could lead to a decrease in soil As concentrations. Higher As concentrations were also observed in plant tissues of Suaeda salsa compared to Phragmites australis (Table 3). However, in Phragmites australis wetlands, As concentration and storage were significantly and positively correlated with soil porosity ( < 0.05), which was highly associated with the fact that As (III) can be oxidized to As (V) with lower toxicity and bioavailability [38], thus improving As accumulation in soil. Additionally, soil pH values and salinity did not show significant effects on soil As due to similar pH values and salinity in these sampling sites.
Levels, Accumulation, and Translocation of Plant As.
As concentrations in various plant tissues (root, stem, and leaf) of Phragmites australis and Suaeda salsa in summer and autumn are listed in Table 3. As concentrations in plants varied with plant species and plant tissues [2]. The leaves of Phragmites australis had the highest As concentration, followed by stems, whereas roots showed the lowest As levels in both seasons. Tsutsumi [39] reported that the absorbed As by root could be transported to plant aboveground parts, causing elevated concentration of leaf As. As for Suaeda salsa, leaves and roots showed higher As concentrations than stems. This is consistent with the results by Madejón et al. [40] and Smith et al. [31], who presented that As accumulation mainly occurred in roots. Generally, almost all plant tissues of Suaeda salsa had higher As concentrations compared to Phragmites australis in both seasons except for lower stem As levels in autumn. As concentrations in roots and stems of both Phragmites australis and Suaeda salsa generally decreased from summer to autumn, which might be caused by As translocation from root to stem and leaf with higher As concentrations in autumn than in summer. Moreover, higher soil As concentrations in summer also contributed to improving plant As levels, as As absorption and accumulation by plants were significantly and positively correlated with soil As [25,41]. BCF and TF values could be used to evaluate the potential capacities of plant species for phytoextraction and phytostabilization [2]. As for Suaeda salsa, the roots and stems showed higher BCFs in summer than in autumn, whereas lower BCFs were observed for the leaves ( < 0.05). In contrast, Phragmites australis roots showed significantly higher BCFs in autumn than in summer ( < 0.05); however, the BCFs of roots and stems of Phragmites australis exhibited similar lower BCFs in both seasons compared to leaves. Compared to Phragmites australis, Suaeda salsa had higher BCFs for all tissues in summer. This indicates that As accumulation in different plant tissues is associated with plant types and seasons ( Figure 3).
TFs of As for Phragmites australis and Suaeda salsa in both seasons are illustrated in Figure 4. TFs of both plant species were higher in summer compared to autumn. Generally, Suaeda salsa had higher TFs (>1) than Phragmites australis (<1) in both seasons. Therefore, Suaeda salsa had higher As-tolerance capability compared to Phragmites australis in this region, as Suaeda salsa could decrease As stress through translocating more As from roots to aboveground parts [32].
Conclusions
Soil As and plant As levels exhibit different distribution patterns. Generally, soil As, root As, and stem As are higher in summer than in autumn, while leaf As shows higher level in autumn for both Phragmites australis and Suaeda salsa. Soil S and porosity can influence soil As concentration and storage in both Suaeda salsa and Phragmites australis wetlands. All soil samples have a potential low or moderate risk of As contamination in the coastal wetlands of the Yellow River Estuary, so much more attention should be paid to controlling and monitoring As contamination level in this region, especially in summer. Suaeda salsa can be served as a native species to control the low or moderate levels of As contamination as Suaeda salsa exhibits higher bioaccumulation and translocation capability than Phragmites australis. Further studies on As forms and behaviors and the phytoremediation processes such as phytostabilization, phyroestraction, and phytotransformation of wetland plants (i.e., Suaeda salsa and Phragmites australis) are still needed to remediate As contamination. Moreover, it is more helpful and meaningful to understand the tolerant threshold values of Phragmites australis and Suaeda salsa to As stress to maintain wetland ecosystem health. | v3-fos |
2019-04-06T13:11:51.417Z | {
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} | s2 | Ozone pretreatment of humid wheat straw for biofuel production
In an attempt to maximize the amount of ozone reacting with lignin inside humid wheat straw, some of the ozone‐reactive lignin degradation products were washed away before a second ozonolysis delignification stage. The total contact time for the two stages was kept the same as that for a one‐stage process for comparison. A significant decrease in the Acid Insoluble Lignin (AIL) content of the straw resulted: from 13.04 wt. % (after a 30‐min one‐stage ozonolysis) to 9.34 wt. % (after a 30‐min two‐stage ozonolysis, separated by a washing step). This significant improvement was accompanied by an increase in released fermentable sugars from an enzymatic hydrolysis. The yield increased from 60% theoretical sugars to 80%. A further improvement in AIL (down to 7.36 wt. %) and released sugars (up to 90% theoretical) occurred when the moisture content (MC) of the straw entering the second stage was adjusted to the optimum value of the straw entering first stage (45 wt. %, predicted from an experimental design). The authors believe this is the first time results are published for the introduction of a two‐stage process separated by a washing step.
Introduction
Securing energy and reducing greenhouse gas emissions are some of the global major concerns of these days. The conversion of abundant lignocellulosic biomass to biofuels as transportation fuels could be the answer for these concerns [1]. Biofuels are considered cleanerburning fuels because they do not add net CO 2 to the atmosphere and they have the potential to cut greenhouse gas emissions by 86% [2]. Lignocellulosic biomass consists mainly of cellulose, hemicellulose, lignin, and pectin [3,4]. Agricultural residues, such as wheat straw, and forest products such as hardwood and softwood, are the main sources of lignocellulosic biomass that can be used for biofuel production. Cellulose and hemicellulose must be hydrolyzed first into their corresponding monomers (sugars), followed by a fermentation step using special microorganisms to convert the sugars to fuels such as ethanol [5][6][7]. Hemicellulose can be easily hydrolyzed using dilute acids while cellulose needs more extreme conditions [8]. Cellulose and hemicellulose can both be hydrolyzed using cellulase enzyme mixtures consisting of at least three major types: endo-glucanase, exoglucanase, and ß-glucosidase. These enzymes are working in a synergistic fashion to achieve hydrolysis [9]. Low corrosion problem, energy consumption, and toxicity are the main advantages of enzymatic hydrolysis process over acid hydrolysis [10].
The presence of lignin and the cellulose crystallinity present a protective barrier that prevents plant cells from being attacked by many microorganisms such as fungi and bacteria. Therefore, the structure of lignin and of crystalline cellulose must first be altered or broken down so that enzymes can easily access and hydrolyze cellulose and hemicellulose. This can be achieved using chemical, physical, biological, or mixed pretreatment processes [11][12][13].
Ozonolysis pretreatment has shown its efficiency in the degradation of lignin in lignocellulosic biomass [14][15][16][17][18][19][20]. Ozone is highly reactive toward compounds incorporating conjugated double bonds and functional groups with high electron densities, such as lignin. It preferably attacks lignin rather than cellulose or hemicellulose. Ozonolysis of lignin releases soluble compounds of smaller molecular weight, mainly organic acids such as carboxylic and acetic acids, which can result in a drop in pH from 6.5 to 2. The range of ozonolysis products is influenced by the structure of the lignocellulosic biomass as well as its moisture content (MC) [21].
Water content in nonsubmerged humid lignocellulosic biomass has a major effect in the ozonolysis process. Water induces cell wall swelling and consequently provides an access for ozone to functional groups of lignin. It also acts as a solvent of ozone and of some delignification products (lignin fragments). At low MC, lignin mostly reacts with gaseous ozone. Despite large amount of supplied ozone, lignin degradation is almost negligible due to the rather small contact surface area between ozone and lignin. On the other hand, when the MC is very high, similar consequences occur because ozone is now absorbed and decomposed in the bulk of the water [22].
The objective of this research was to improve the ozonolysis delignification of humid, nonsubmerged, wheat straw. It was surmised that performing the ozonolysis process in two stages with an intermediate washing step would remove many of the delignification products (lignin fragments, such as carboxylic acids), enabling ozone gas to oxidize newly exposed lignin in wheat straw rather than further degrading the lignin fragments. To the best of the authors' knowledge, no work on this matter has been reported in the literature. Acid insoluble lignin (AIL) content for both untreated and ozonated wheat straw was used as a measure of the effectiveness of the delignification process. Three parameters were studied: the Initial Water Content (IWC) of the humid straw entering first stage, the Washing Starting Time (WST; contact time during the first ozonolysis stage), and the Washing Contact Time (WCT; immersion time of wheat straw in distilled water during the intermediate washing step).
Materials
Wheat (Triticum sativum, Soft White Superior) was harvested from a farm in Ontario, Canada in 2010. Dry bales of straw were milled using a Retsch Cutting Miller type SM 100 (Comeau Technique Ltee/Ltd., Vaudreuil-Dorion, Quebec, Canada) with a 2-mm outlet sieve. The milled wheat straw was stored in sealed plastic bags at room temperature, for a maximum of 3 months. Working with oak sawdust, Neely [16] stated that the optimum range for IWC should be 25-35 wt. %, while Vidal and Molinier [17] working with poplar sawdust obtained an optimum water content of 70 wt. %. Therefore, the IWC was studied in the range 30-70 wt. % in this research. It was adjusted by mixing the required amount of distilled water to 5 g (oven dry weight) wheat straw humid consistency. The humid straw was transferred right away to the ozonolysis reactor.
A cellulase mixture (NS22086) consisting mainly of endo-glucanase, exo-glucanase and βglucosidase enzymes, and βglucosidase (NS22118) were kindly donated by Novozymes Bioenergy [23]. The activity of the cellulase mixture (NS22086) was measured using LAP 009 procedure of NREL [24] and was found equal to 106 FPU/mL. Figure 1 shows a schematic diagram of the ozonolysis reactor set-up for this project. Compressed oxygen gas from a cylinder went through an ozone gas generator (model GL-1; WEDECO, Xylem Water Solutions, Toronto, Ontario, Canada). Ozone concentration in the outlet stream from the ozone generator was measured using OZOCAN analyzer (Ozocan Corporation, Scarborough, Ontario, Canada). A total gas flow rate was set at 1 L/min containing 3 wt. % of ozone. It entered the reactor at the bottom where humid straw had been preloaded. Unreacted ozone in the outlet gas from the top of the reactor and in the bypass streams was destructed by passing the gas through a manganese dioxide catalyst (Ozocat Corporation). The Polytetrafluoroethylene (PTFE) reactor, with a diameter of 3.5 cm and height of 20 cm, was fitted at its bottom with a stainless steel mesh (sieve number 80) and a mesh holder, acting as a holder of the humid straw and as distributor of the ozone/oxygen gas. The top part of the reactor contained a similar arrangement to prevent the straw from moving to the ozone destruction zone.
Ozonolysis
When ozonolysis was done in two stages, the ozonated straw from the first stage was removed from the reactor after a set WST. It was mixed with 100 mL of distilled water for complete immersion during a set WCT. This step was called the intermediate washing step. The aqueous suspension was then filtered through a glass microfiber filter under vacuum, and the straw was dried at 318 K. It was then either stored in a freezer at 253 K until subsequent enzymatic hydrolysis and/or analyses, or adjusted for IWC before being used in a second ozonolysis stage at the same conditions as the first one. At the end of the second stage, the straw was also filtered, dried, stored, hydrolyzed and/or analyzed.
Design of experiments
Wheat straw with an IWC of 50 wt. % and fiber size <2 mm was ozonated in one stage with a total contact time of 5, 15, 30, 60, 120, or 180 min, respectively. The ozonolysis time that caused significant delignification (low AIL content) without using an excessive amount of ozone gas was chosen as the total reaction time for a one-stage or a two-stage process.
Three parameters were studied on their influence the AIL content of straw. The IWC parameter was evaluated at 30, 50, and 70 wt. %, the WCT was 1, 3, and 5 min, and the WST was 1/3 or 2/3 of the total ozonolysis time determined above. A mixed-level factorial design (3 × 2 2 ) with two center points was used, and experiments were done in a random sequence. STATGRAPHICS ® Centurion XV software (Statpoint Technologies, Inc., Warrenton, Virginia, USA) [25] generated an equation predicting the effect from each of the three parameters, and from their interactions, on the AIL content of the ozonated wheat straw. Confidence functions for experimental AIL were calculated at 97.5% probability.
Enzymatic hydrolysis
Enzymatic hydrolysis was performed on untreated and ozone-treated wheat straw at both fiber sizes of <2 mm, according to LAP 009 procedure of NREL [24], using a cellulase mixture (NS22086; 5% wt./wt. dry straw) plus βglucosidase (NS22118; 0.6% wt./wt. dry straw). Two grams of oven-dried straw were suspended in 250 mL Erlenmeyer Flasks were placed in an air incubator at 320 K and 68 rpm. Samples of 1.5 mL of the suspension were taken after 2, 4, 16, 40, 64, 88, 112, 136, and 160 h. They were centrifuged for 5 min at 2000 g, and the supernatant was tested for total reducing sugars (glucose equivalents) using the Dinitrosalicylic acid (DNS) method [26]. The hydrolysis yield compared the amount of reducing sugars experimentally released by the enzymatic hydrolysis of the cellulose and hemicellulose in wheat straw to the theoretical amount of reducing sugars expected to be released from the complete degradation of cellulose and hemicellulose (calculated from values reported by Mckean and Jacobs [27]) of 34 wt. % cellulose and 25 wt. % hemicellulose).
Results and Discussion
Determination of total ozonolysis (contact) time Figure 2 shows that the AIL content of the ozonated wheat straw dropped rapidly from 20.5 wt. % to 13 wt. % in the first 30 min of a one-stage ozonolysis process but decreased very slowly after 60 min of ozonolysis time. The high rate of delignification in the first 30 min could indicate that most of ozone gas reacted with lignin present on the surface of the wheat straw. As the ozonolysis process continued, ozone gas might have reacted with some lignin decomposition fragments, and it might have become harder for ozone gas to reach lignin in the deep cavities of the wheat straw fibers. The delignification process could also have been slowed down due to the effect of demoisturizing of wheat straw due to the ozone/oxygen gas stream flow. An ozonolysis time of 30 min was chosen as the reference one-stage process and as the total reaction time for any subsequent two-stage process because a significant delignification of wheat straw was achieved at that time without using an excessive amount of ozone gas.
Regression model analysis
Experiments were then performed to determine when to start the intermediate washing step (WST, or length of the first ozonolysis stage) from the above total two-stage contact time of 30 min, and how long the washing step should last (WCT). Instead of a full 3-level factorial design, the STATGRAPHICS ® Centurion XV software allowed us to use a 3 × 2 2 mixed-level factorial design, evaluating WST and WCT in a 2 2 factorial, IWC at 3 levels, and two center points (increasing the number of degrees of freedom of the error to 6) in a minimum of runs. Table 1 shows the result of the 14 runs. Although the lowest average experimental AIL content of ozonated wheat straw after the second stage of the process is shown to occur at runs #8 and 11, when IWC was set at 50 wt. % and WST at 20 min, WCT did not seem to have a substantial effect on delignification because the higher values of the AIL confidence functions were close to 12 wt. %, similar to other experimental AIL values. Increasing the IWC to 70 wt. % drastically reduced the average total delignification (AIL increased to 16 wt. %). Decreasing the IWC to 30 wt. % also reduced total delignification when compared with results of 50 wt. % IWC. Decreasing ozonolysis time of the first stage (WST) from 20 min to 10 or even 15 min, at IWC of 50 wt. %, also reduced total delignification (AIL increased to around 11-12 wt. %). A similar reduction occurred when IWC was set at 70 wt. % but the effect seemed much less profound than when IWC was set at 30 wt. %.
The STATGRAPHICS ® Centurion XV software calculated the regression equation which fitted the data for this mixed-level factorial design. It calculated a value of 1.0 for the variance inflation factor for each of the single effects (IWC, WST, WCT) and for the interaction effects (IWC 2 , IWC × WST, IWC × WCT, WST × WCT), indicating a lack of confounding among these effects.
Validation of the DOE results
The analysis of variance (ANOVA) for AIL is shown in Table 2, where the variability in AIL is partitioned into separate pieces for each of the effects. Three effects had P-values less than 0.05: IWC, the interaction term IWC 2 , and WST. This indicated that these terms were significantly different from zero at the 95.0% confidence level. Although the other terms showed to be nonsignificant from the standardized Pareto chart, they were kept in the model because they had a strong interaction on AIL. The correlation matrix for estimated effects showed an almost perfectly orthogonal design, indicating that clear estimates could be obtained for these effects. The coefficient of determination (R 2 ) statistic indicated that the fitted model explained 96.4% of the variability in AIL. The adjusted R 2 statistic, which is more suitable for comparing models with different numbers of independent variables, was 92.3%. No indication of serial autocorrelation in the residuals occurred at the 5.0% significance level, as was revealed by the Durbin-Watson statistic. Consequently, the fitted model with values of the variables specified in their original units was: (1) The accuracy of Equation 1 was also validated by comparing the experimental AIL values used to generate this equation to those predicted from it. Table 1 shows that the maximum standard deviation between those two sets of data was 1.76 wt. %. Figure 3 shows the model predictions of the response surface for the AIL content of ozonated wheat straw when two of the studied parameters were varied from their lowest experimental value to their highest one while the third parameter was fixed at its middle value. When WCT was fixed at 3 min of contact washing (Fig. 3A), maximum delignification (lowest AIL content of 10 wt. %) occurred when IWC was 45 wt. % and WST was 10 min. Figure 3B shows a similar trend in the response surface when WST was fixed at 15 min, proving that the greatest effect on AIL content came from IWC. Although a longer first ozonolysis first step (WST) led to some improvement in delignification, WCT had the smallest effect on the process (Fig. 3C). This might mean that lignin fragments produced by reaction with ozone almost instantaneously diffused from the treated wheat straw to the bulk of the washing water. The software-calculated values of the parameters for maximum delignification were found to be for IWC at 45 wt. %, WST at 20 min, and WCT at 80 sec. Working at these values, the AIL content dropped from 20.5 wt. % for untreated wheat straw to 9.34 wt. % (data not shown). To verify whether increasing WST past 20 min could further decrease the AIL content, an experiment done at the optimum conditions but with WST of 25 min did not result in a substantial AIL decrease (data not shown). These results show significant improvement over those obtained by García-Cubero et al. [18], who reported an AIL content of 11.2 wt. % reached after 2.5 h of a single ozonolysis stage with very similar operating conditions, that is, water content equal to 40 wt. %, ozone/ air flow rate equal to 1.5 L/min, ozone concentration of 3 wt. % and wheat straw fiber size of 3-5 mm. The same conclusion was achieved when comparing to results of Bule et al. [19], who achieved an AIL content of 13.0 wt. % after 120 min of a single ozonolysis process using 3 g wheat straw with particle size of 0.25 mm, and with 5.3 wt. % ozone concentration at a flow rate of 2 L/min.
Although this drop in AIL content was considered a significant improvement in the delignification of wheat straw, it was believed that the process could be further improved since the water content of the wheat straw entering the second stage was 72 wt. %, much higher than the optimal value predicted for wheat straw entering the first stage, due to the intermediate washing and filtration step. After adjusting to 45 wt. %, the AIL content of treated wheat straw after the second ozonolysis stage further dropped to 7.36 wt. %. This proves how influential the water content of the straw is on delignification by ozone.
Enzymatic hydrolysis of wheat straw
Enzymatic hydrolysis of the delignified wheat straw after ozonolysis was performed to verify the veracity of the improved process. Figure 4 shows how much sugars were released from untreated and ozonated wheat straw during their hydrolysis by cellulases. Untreated wheat straw (control) showed a steep increase to about 15% of the sugars theoretically present in the straw, in the first 5 h of hydrolysis. This might represent a period during which cellulases access any exposed cellulose surfaces produced during milling of the straw. After that period, cellulases seem to find it harder to reach the cellulose and hemicellulose inside the wheat straw, possibly due to the presence of lignin. A plateau of around 23% theoretical was reached in about 50 h.
When hydrolysis occurred on wheat straw that was delignified at the optimum values of IWC (45 wt. %), WST (20 min), and WCT (80 sec), (called "optimum" on Fig. 4), the sugar yield was about 1.3 times higher than for straw ozonated in one step (called "one step") and four times more than for untreated wheat straw. It demonstrates that a two-stage delignification process with an intermediate washing step was more effective than a one-stage process for the same total treatment time because many of the lignin acid fragments are washed away, allowing ozone to attack more of the lignin present in the straw during the second contact stage. The highest sugar yield (around 90% theoretical) occurred when the water content of straw entering the second stage was further adjusted to 45 wt. % (called "enhance"). The fact that a slight drop in AIL content from 9.35 wt. % (for "optimum" straw) to 7.36 wt. % (for "enhance" straw) can result in a 10% increase in sugar yield proves that removing lignin provides better access to the straw cellulose and hemicelluloses.
Conclusion
The ozonolysis pretreatment of wheat straw in two stages, coupled with an intermediate washing step, improved the extent of delignification compared to the commonly used one-stage delignification by ozone. Maximum delignification of wheat straw was achieved with an IWC in the straw of 45 wt. %, a 20-min first stage of ozonolysis (WST), and a washing time (WCT) of 80 sec. When these conditions for a two-stage approach was used, the straw AIL content was reduced from 13.05 wt. % (for 30 min in a one-stage process) to 9.34 wt. %, and the sugar yield of the wheat straw increased from 60% theoretical to 80% theoretical.
The IWC of wheat straw was shown to have the most significant effect on the ozonolysis delignification process compared to the other two parameters, that is, WST and WCT. Adjusting the water content of straw, prior to entering the second stage, to the optimal predicted IWC value of 45 wt. % further improved the delignification process (AIL content decreased to 7.36 wt. %) and the hydrolysis into fermentable sugars (sugar yield) increased to 90% theoretical.
We have successfully proven that 30-min of a two-stage delignification process by ozone, coupled with a quick intermediate washing step and a readjustment of the straw water content to 45 wt. %, significantly reduced the lignin (AIL) content of humid nonsubmerged wheat straw from 13 wt.% to 7 wt. %. Because lignin was no longer present to preferentially bind with the cellulases, the cost of supplying enzymes for the hydrolysis will drastically be reduced. In this improved delignification process, approximately one quarter of the ozone used by a onestage process would actually be required, representing another huge cost reduction. | v3-fos |
2019-03-30T13:13:49.793Z | {
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} | s2 | GENETIC DIVERSITY BETWEEN LARGE WHITE AND NIGERIAN INDIGENOUS BREED OF SWINE USING POLYACRYLAMIDE GEL ELECTROPHORESIS (PAGE)
Sixty-two pigs (32 large white pigs and 32 Nigerian indigenous pigs were used in this study. Biochemical techniques were used in analyzing the blood serum samples obtained from the pigs using Polyacrylamide Gel Electrophoresis. A total of 14 loci were scored for the Nigerian Indigenous pigs and 10 for the Large White breed. The results of the molecular characterization with SDS-PAGE were analysed using PAST Package to determine genetic similarity coefficient and construct phylogenetic dendrogram. The within breed comparism of Nigerian indigenous pigs showed 62% similarity while the Large White breeds showed 65% similarity. For the between-breed comparism, the Nigerian indigenous breeds and the Large White breeds were 48% similar. The moderate genetic similarity observed in the Nigerian indigenous pigs and the Large White pigs indicates a reasonable level of genetic dilution in both breeds.
INTRODUCTION
Indigenous pigs have played an important role in smallholder farms and local populations for a long time (Mutua et al., 2011). In relation to biodiversity, local pigs seem to be losing its reservoir of genes that could be an asset for future use (Rangsun et al., 2013). In recent years, pig production in Nigeria has switched from local backyard systems to exotic industrialized production. The conservation of indigenous and exotic pigs in Nigeria as a genetic resource and vital components within the livestock sectorhave some challenges.
Genetic diversity is an asset for the future development of livestock production in Nigeria. The genetic characterization of local pigs in Nigeria should be the first step in considering the sustainable management or conservation of a particular population. Compared with the exotic pigs, the indigenous pigs have received very little research attention and are even in danger of extinction probably because of the little attention given to their characterization and research on genetic characterization is still at its rudimentary stage (Okeudo et al., 2007).
The genetic characterization of the domestic animals is part of the Food and Agricultural Organization global strategy for the management of farms (FAO, 2012). This strategy places a strong emphasis on the use of molecular methods to assist the conservation of endangered breeds and to determine the genetic status of breeds. Molecular markers have played some roles in the characterization of genetic diversity (Toro et al., 2006). Electrophoresis is one of the methods for the study of genetic diversity and has severally been used to establish the genetic distances among breeds and/or populations .
Today, there is concern, on on the rate of extinction and disappearance of animal genetic resources (AnGR), thus, succeeding generation may inherit a narrow genetic base, unless present generation rise to the challenge (Vincent et al., 2014). Studies on genetics and preservation of indigenous breeds are crucial to the defining and http://dx.doi.org/10.4314/as.v13i3.5 registering of genetic resources. The genetic characterization of the Nigerian indigenous Pigs in the present study will provide a baseline data for the government and global programmes for the total conservation and preservation of Nigerian indigenous Pigs genetic resources. Therefore, this investigation was carried to evaluate the genetic diversity within and between breeds, in-addition to determining the genetic similarity between the Large White breed and the Nigerian indigenous breed using Polyacrylamide Gel Electrophoresis (PAGE).
MATERIAL AND METHODS
The experiment was carried out at the piggery unit, University of Nigeriab Teaching and Research farm Nsukka. Nsukka is in the derived savanna ecology on Longitudes 6 0 25 I and latitude 7 o 24 I at an altitude of 430m above sea level. The climate is a humid tropical setting with a relative humidity range of 56.01 -103.83%. Average diurnal minimum temperature range between 22 -24.7 o c while the average maximum temperature range between 33 -37 o c (Ndofor-Foleng et al., 2015). Annual rainfall ranges between 1680 -1700mm.
The Parent Population
The breeds of the pigs used for the study were the Nigerian indigenous Pigs and the Large White breed of swine. The local breeds were purchased from local pig farmers within the middle belt of Nigeria (Gboko) while the Large White breed was obtained from the piggery unit, University Of Nigeria Teaching and Research Farm. The pigs used were quarantined for one week to check and monitor their health conditions. They were also left to acclimatize before introducing them into the experimental units. Thirty-two non-pedigreed and unselected random bred males and females of the Nigerian indigenous pigs and Large White breed each formed the base population for the study.
Management of Experimental Animals
The selected parents which were gilt placed on 2.4 -2.6kg quantity of feed especially for gilts which is the best strategy for maximization of litter size. They were allowed to get to full sexually maturity before the males were introduced into the breeding units at a ratio of 1male : 3females. After breeding, the animals were monitored till farrowing. The pregnant gilts were fed with a commercial diet of about 13-14% crude protein, 3400 k cal/kg digestible energy according to Frank et al. (1995). The feed was increased in the first one to three days after farrowing with about 0.5kg/day. Proper management and hygiene were ensured. Routine vaccinations were promptly carried out. After farrowing, data collection was made on individually basis.
DNA Extraction and Genotyping Blood Sample Collection and Serum Preparation
Blood for molecular typing was collected from each of the two breeds of pigs bred. This was achieved by means of 22guage hypodermic needle. Three mls whole blood was withdrawn from either the tail vein or ear veins and diluted with 2mls saline water in a sample bottle. The two combinations was gently rocked before taking them to Classic Biomedical Laboratory within Nsukka town where it was left to stand for about 1hour before centrifugation at 2500rpm for 10minutes.
After centrifugation, the serum/supernatants were collected using a micropipette in a separate 2ml tube and stored in the refrigerator before transporting to Biotechnological laboratory, Obafemi Awolowo University (OAU) inside a cooler packed with ice block which lasted until delivery for the analysis proper. The residual erythrocyte was discarded since haemolytic sera were not well separated. However, the samples were analysized as described by Adeleke et al. (2011). Protein polymorphisms were then analysized by sodium dodecyl sulphate-polyacrlamide gel electrophoresis (SDS-PAGE). Electrophoresis protocols were maintained throughout the analysis.
Gel Preparation
The preparation of the denaturing gel (SDS-PAGE) was carried out. The composition of the gels were: 1.5 Tris-Hcl, PH 8.2 (2.5ml) was dispensed into an Erlenmeyer flask, 4ml Acrylamide / Bis (30%), 100μl SDS stock (10% w/v), 50μl Ammonium persulphate (10%), 5μl tetramethylethylene diamine (TEMED) was all dissolved in 3.5ml distilled water for 10ml solution for the resolving gel. The electrophoretic kit was assembled and the first part of the gel (resolving gel) was done (Nowakowski et al., 2014). After which the comb were properly aligned in order for the wells to be properly formed. The surface of the gel was covered with distilled water during polymerization to smoothen the gel surface and mainly to expel air bubbles. After denaturing gel was the stacking gel. After proper polymerization of the two layer gels, it was later wrapped with nylon to prevent water from contaminating and it kept overnight in a fridge for proper preservation till the next day.
Sample Preparation For SDS-PAGE
Ten μl of the protein sample in a well labeled Effendorf of micro tubes was diluted with 40μl of sample buffer (SDS-reducing buffer) and was heated at about 95 o c for 5 minutes in a water bath. The heated protein samples in the micro tube were later cooled for loading into the electrophoretic chambers already containing the stacked gel (below) and resolved gel (on top). In the electrophoretic chamber, there were 10 wells and each had the capacity to hold 15μl sample. For each serum/protein sample, 10μl of the cooled sample (serum + buffer solution) of each of the different breeds were loaded into the electrophoretic wells one after the other. The separation of protein was carried out with the aid of Bio-Rad electrophoretic power supply at 150milivolt in a running buffer (PH 8.3) 1 hour or a little more depending on the speed of migration of the sample (Thermo Fisher Scientific, 2010).
Coomasie-Blue Gel Staining For Sds-Page:
After electrophoresis had been carried out, the gels were carefully removed or detached from loading chambers by placing it first inside the slightly diluted SDS reducing buffer to detach properly from the glass slides and it was left for some minutes before distilled water was further used for washing after which it was destained / fixed with staining solution (Coomasie-blue stain) for clarity of the protein bands. The gel was later scanned with a HP table scanner for future reference (Thermo Fisher Scientific, 2010).
Statistical Analysis.
Individual gels were placed under a light beam which allowed the bands to be seen clearly and were scored visually for presence (1) or absence (0) of protein bands (Ige et al., 2014). The position of the molecular weight marker assisted in scoring the protein bands on each gel. Data generated were subjected to statistical analysis using of PAST (Palentholgical statistics) to generate dendogram that measure genetic similarity.
RESULTS AND DISCUSSION
The SDS-PAGE gels scanned allowed the bands to be scored and the results displayed in plate 1 and 2. Plate 1 and 2contains 10 lanes (1-10) each of different pig serum samples obtained from large white breed and Nigerian indigenous breed. The gels obtained from each of the population do not differ distinctively from each other. The results of the band counting were subjected to statistical analysis using PAST package (Palenthological Statistics) to draw dendogram (Figs 1 and 2) which measures genetic diversity within the population. Genetic diversity refers to the total number of genetic characteristics in the genetic makeup of the two breeds of pigs. It serves as a way for populations to adapt to changing environments (Zhang and Graham, 2011).
The dendrogram of all the pig population sampled showed a moderate level of genetic similarity (fig 1 and 2). This moderate genetic variation indicated that the population is not under the influence of natural selection. The importance is that the population is losing its high genetic variation which is sometimes referred to as heterozygousity (Amos and Balmford , 2001); which is a measure of the populations' ability to adapt to environmental changes and stress and thereby enabling them to survive in the same condition (Ige et al., 2014). The dendrogram of the pig sample from the large white population showed 2 major clusters A & B ( fig.1) and indicated a genetic similarity of 65% among some of the population sampled. On the other hand, 100% similarity was found among some of the Large White pigs. This is an indication that some of the Large White pigs are adequately protected from impurities or external influences which affects its genetic composition.
The dendrogram (Fig 2) of the Nigerian local pig indicated a genetic similarity of 62% among the population sampled. The highest similarity index observed among the pig population was 92% while the lowest was 42%. From the genetic distances using UPGMA, the dendrogram obtained for the populations of all the pigs indicate a relatively moderate genetic similarity (62-65%) which compared favorably with the results obtained from microsatellite DNA markers analysis in korean and Chinese Native pigs (Kim andChoi, 2002, Yang et al., 2003) as well as the results obtained from characterization of indigenous pigs in South Western Nigeria using blood protein polymorphism for pigs sampled from 4 locations (Akinyem et al., 2014). The genetic distance among these populations should vary reflecting the differences in domestication model and history in the two breeds. However, this was not the case in this study, as the average genetic distance in large white populations was slightly higher than that in the Nigerian indigenous populations. High genetic variation is very important in pig management ( Adeola and Omitogun, 2012). This kind of baseline information on the genetic relatedness among genetic resources of Nigerian indigenous pigs is useful for designing a breeding programme as well as conservation. This result obtained in this study is not surprising as Zhang and Graham (2011) reported that the average heterozygosity was lower in pig than in human and other livestock. Domestic animal diversity is unique and cannot be replaced. As a matter of fact, biotechnology may attempt to improve breeds but not to replace loss of diversity. Biotechnological study can only detect loss of genetic diversity faster but will not be able to regenerate diversity if it is lost (Ige et al., 2014). 2,3 4,5,6,7,8,9,10 denotes animals sampled 0.7 ,0.8… denotes similarity coefficient The Nigerian indigenous pigs from Gboko, Benue state though with relatively high geneticsimilarity are found to be diluted with the exotic breeds owning to the fact they are allowed to roam about, scavenge and fend for themselves. The Nigerian indigenous Pigs may go into extinction due to genetic dilution. There is need for proper conservation of indigenous stock for upgrading having in mind their good potentials like high survivability, disease resistance, heat tolerance etc. which will invariably increase pork availability even to the moderate populace and at the end increase and improve protein availability of common Nigeria.
CONCLUSION
The present result shows that there is uncontrolled interbreeding among pig breeds in some areas in Nigeria. This has lead to the narrowing of the gene pool, to render previous selection efforts futile. However a large sample is required so as to be able to monitor gene flow in a population in future. However, Pig genomic diversity within populations is quite variable.
From the gel electrophoretic profiles obtained using SPS-PAGE of serum proteins, there appears to be high level of genetic similarity on both breeds. For the Large White obtained from the University Farm, there is moderate level of cross breeding between the commercial lines available (leading to genetic dilution) in the farm. As a result of very moderate genetic similarity obtained between the Nigerian indigenous pigs, it could be concluded that there is an urgent need for genetic conservation of the local pigs in Nigeria to avert indiscriminate breeding which might end up in genetic erosion. The use of SDS-PAGE in analysizing protein polymorphism from pig blood samples is a tool for assessing genetic diversity and genetic status of unknown populations, but needs to be confirmed with more genetic loci as isozymes or hypervariable satellite DNA. | v3-fos |
2016-05-12T22:15:10.714Z | {
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} | s2 | Coupled enzymatic hydrolysis and ethanol fermentation: ionic liquid pretreatment for enhanced yields
Background Pretreatment is a vital step upon biochemical conversion of lignocellulose materials into biofuels. An acid catalyzed thermochemical treatment is the most commonly employed method for this purpose. Alternatively, ionic liquids (ILs), a class of neoteric solvents, provide unique opportunities as solvents for the pretreatment of a wide range of lignocellulose materials. In the present study, four ionic liquid solvents (ILs), two switchable ILs (SILs) DBU–MEA–SO2 and DBU–MEA–CO2, as well as two ‘classical’ ILs [Amim][HCO2] and [AMMorp][OAc], were applied in the pretreatment of five different lignocellulosic materials: Spruce (Picea abies) wood, Pine (Pinus sylvestris) stem wood, Birch (Betula pendula) wood, Reed canary grass (RCG, Phalaris arundinacea), and Pine bark. Pure cellulosic substrate, Avicel, was also included in the study. The investigations were carried out in comparison to acid pretreatments. The efficiency of different pretreatments was then evaluated in terms of sugar release and ethanol fermentation. Results Excellent glucan-to-glucose conversion levels (between 75 and 97 %, depending on the biomass and pretreatment process applied) were obtained after the enzymatic hydrolysis of IL-treated substrates. This corresponded between 13 and 77 % for the combined acid treatment and enzymatic hydrolysis. With the exception of 77 % for pine bark, the glucan conversions for the non-treated lignocelluloses were much lower. Upon enzymatic hydrolysis of IL-treated lignocelluloses, a maximum of 92 % hemicelluloses were also released. As expected, the ethanol production upon fermentation of hydrolysates reflected their sugar concentrations, respectively. Conclusions Utilization of various ILs as pretreatment solvents for different lignocelluloses was explored. SIL DBU–MEA–SO2 was found to be superior solvent for the pretreatment of lignocelluloses, especially in case of softwood substrates (i.e., spruce and pine). In case of birch and RCG, the hydrolysis efficiency of the SIL DBU–MEA–CO2 was similar or even better than that of DBU–MEA–SO2. Further, the IL [AMMorp][OAc] was found as comparably efficient as DBU–MEA–CO2. Pine bark was highly amorphous and none of the pretreatments applied resulted in clear benefits to improve the product yields. Electronic supplementary material The online version of this article (doi:10.1186/s13068-015-0310-3) contains supplementary material, which is available to authorized users.
Background
Second-generation biorefineries based on the exploitation of lignocellulose as the main carbon source, have the potential to produce a variety of products, including bio-fuels, value-added chemicals, materials, heat and electricity [1][2][3]. However, laboratory scale experiments often report limited product yields due to the complex structure and high crystallinity of the feedstock. As known, lignocelluloses are mainly composed of cellulose, hemicelluloses, and lignin. Cellulose and hemicelluloses are carbohydrate polysaccharides while lignin is a complex aromatic polymer [4]. In combination, these three main components form a complex structure of vegetal biomass. In a typical biomass conversion process, the raw material is pre-treated to improve the accessibility of polysaccharides for their further conversion into monosaccharides. This is typically performed via processing of biomass in environmentally harmful chemicals, such as sulfuric acid that facilitates the hydrolysis and extraction of sugars leaving most of the lignin in the solid residue. Alternatively, lignin can be removed by the use of alkaline solutions or organic solvents, leaving solids rich in sugar polysaccharides. Already, a number of pretreatment methods based on the use of different solvents, e.g., acids, alkali, organic solvents and/or other techniques like steam explosion, ammonia fiber explosion, etc. have been introduced for lignocellulose disruption and are well reviewed [5][6][7][8][9][10][11]. The lignin-rich residues obtained from an acid pretreatment can be used as low-value boiler fuel to produce heat and electricity [12]. Moreover, lignin can also be considered as a valuable source of carbon and if selectively removed and recovered it can be used to produce high value derivatives ( [5,6,13]). After completed pretreatment, enzymes can be used to further degrade and hydrolyze the polysaccharides into monosaccharides which can then be used to produce various products such as alcoholic fuels (e.g., ethanol, butanol) via fermentation [14][15][16][17].
If the applied pretreatment is inefficient, the downstream hydrolysis and fermentation are likely to give low product yields [12]. Pretreatment is, therefore, a very important step in lignocellulose conversion processes. Thus, the refinement of lignocellulose pretreatment technologies is necessary to further facilitate enzymatic degradation of polysaccharides, improve product yields, and move closer to an economically viable lignocellulose biorefinery.
Ionic liquids (ILs), salts composed of organic cations and either organic or inorganic anions [18]; these neoteric solvents have lately attracted significant attention due to their ability to dissolve a wide range of organic and inorganic compounds, including lignocellulosic materials [19,20]. Because of their unique physicochemical properties and potential for associated environmental benefits, ILs are considered to be of interest as potential alternatives to the traditional lignocellulose pretreatment solvents and a variety of ILs have been applied in fractionation and dissolution different lignocelluloses [6,8,[21][22][23]. Nevertheless, many ILs are expensive [24] and biomass treatment was in many cases performed at rather low temperatures and with retention times of up to several days [6]. Thus, design of low-cost ILs [24] that efficiently work at high temperatures and with a short processing time is of interest. Among the investigated ones, the use of inexpensive acidic ILs that can be produced on bulk scale is potentially a sustainable approach of lignocellulosic biomass conversion without addition of catalyst [25,26].
Chemical composition of different lignocelluloses
The composition of structural carbohydrates, lignin and extractives of different lignocelluloses used in this study are presented in Table 1. The values in Table 1 are comparable to those reported in the literature [7,[35][36][37]. Softwood substrates, i.e., spruce and pine, are rich in glucomannans, while both birch (a hard wood substrate) and reed canary grass are rich in glucoxylanes (Table 1). On the contrary, pine bark contains high amounts of arabinoglucans (Table 1). As expected, lignin content of softwood substrates was higher than that of hardwood and reed canary grass. Nevertheless, pine bark displayed the highest lignin content of 40.3 % (dry wt). Pine bark was also exclusively rich in extractives [19.4 % (dry wt)] while the extractives content of other substrates was maximally 4 % (dry wt) ( Table 1).
Enzymatic hydrolysis of (S)IL-treated and non-treated Avicel cellulose
In Initial experiments, a model crystalline cellulose Avicel was treated with various IL solvents at a severity factor (SF) of 2.5 and subsequently subjected to enzymatic hydrolysis. As control, Avicel was hydrolyzed without any pretreatment. After 48 h of enzymatic hydrolysis, the glucose yields (g glucose released/g maximum available glucose) were 0.
Enzymatic hydrolysis of non-treated, acid pre-hydrolyzed, and IL-treated lignocellulose substrates Soft wood substrates
In case of softwood substrates such as spruce wood and pine stem wood, an acid pre-hydrolysis was not beneficial for the subsequent enzymatic degradation (Figs. 2a, b, 4a, b). The GPRs (~0.6 g L −1 h −1 ) and the glucose yields (11-13 %) were similar for the enzymatic hydrolysis of nontreated and the solids of acid pre-hydrolysis (S-APH).
Compared with both non-treated and acid pre-hydrolyzed, softwood substrates originating from IL treatments were readily degraded by enzymes-hydrolysis rates were significantly enhanced and high sugar conversions were observed (Figs. 2a, b, 4a, b). Upon enzymatic hydrolysis of (S)IL-treated substrates, the GPRs and glucose yields were enhanced to a maximum of 1.1-2.7 g L −1 h −1 and 28-75 % for spruce wood, and 1.3-3.6 g L −1 h −1 and 39-93 % for pine stem wood. In addition, the hemicellulose recovery 61 and 71 % from the enzymatic hydrolysis of (S)IL spruce and pine, respectively, were slightly higher than that of 57 and 65 % recovered from the combined acid pre-hydrolysis and enzymatic hydrolysis.
DBU-MEA-SO 2 was the best solvent for the pretreatment of softwood substrates, followed by DBU-MEA-CO 2
Hardwood substrate
Acid pre-hydrolysis of hard wood such as birch was beneficial and improved the subsequent enzymatic hydrolysis (Figs. 2c, 4c). The GPR increased from 0.5 to 0.7 g L −1 h −1 and the glucose yields from 10 to 20 % in S-APH samples compared to non-treated birch wood. Similar to softwoods, enzymatic hydrolysis of (S)ILtreated birch wood was highly efficient. A maximum GPR of 1.4-4.3 g L −1 h −1 and glucose yields of 47-96 % were obtained from the enzymatic hydrolysis of (S)IL-treated birch wood (Figs. 2c, 4c). In fact, the hemicellulose recovery max 92 % from the enzymatic hydrolysis of (S)IL-treated birch wood was comparably higher than the 56 % recovered from the combined acid pre-hydrolysis and enzymatic hydrolysis of birch wood. The tendency of (S)ILs efficiency for birch wood was similar to that of softwood substrates, but the sugar yields (glucose 95-96 %, overall 93-94 %) were similar irrespective of whether they were DBU-MEA-SO 2 or DBU-MEA-CO 2 (Fig. 4c). However, the GPR maximum 3.3 g L −1 h −1 for the DBU-MEA-CO 2 -treated birch wood was lower than the 4.3 g L −1 h −1 of DBU-MEA-SO 2 -treated substrate. The glucose yields for the [AMMorp][OAc]-treated birch wood also reached as high as 91 %, but the maximum GPR was only 2.3 g L −1 h −1 .
Agricultural residues
Surprisingly, unlike any investigated lignocellulose substrates, no sugars were released from the enzymatic hydrolysis of non-treated reed canary grass (Figs. 3a, 5a). However, acid pre-hydrolysis of reed canary grass significantly improved its subsequent enzymatic degradation. Enzymatic hydrolysis of S-APH of reed canary grass resulted in 47 % glucose yield with a GPR of 1.8 g L −1 h −1 .
The hydrolysis efficiency of reed canary grass was further enhanced by (S)IL treatments. Upon enzymatic hydrolysis of (S)IL-treated reed canary grass, a maximum GPRs of 2.1-4.6 g L −1 h −1 and glucose yields of 55-97 % were obtained. For reed canary grass, both SILs DBU-MEA-SO 2 and DBU-MEA-CO 2 were similarly efficient in terms of GPRs and yields. Even though, IL [AMMorp][OAc] was as efficient as SILs still the GPRs for [AMMorp][OAc] treated reed canary grass were slightly lower than for the S-ILs-treated substrates. However, at less sever treatment conditions (i.e. SF 2.5), DBU-MEA-CO 2 was better solvent than other (S)ILs, resulting a 4.3 g L −1 h −1 GPR and 94 % glucose yield. Nonetheless, the hemicellulose recovery from the (S)ILs-treated reed canary grass 71 % was lower than the 90 % of recovered from the combined acid pre-hydrolysis and enzymatic hydrolysis.
Pine bark
Enzymatic hydrolysis of non-treated pine bark was readily degraded, as smoothly as samples pre-treated with either acid or any ILs, by cellulase enzymes (Figs. 3b, 5b) giving a GPR of 1.5 g L −1 h −1 and glucose yield of 77 %. Compare to non-treated, acid pre-hydrolysis or (S) IL treatment of pine bark had no or only minimal effect on its subsequent enzymatic hydrolysis. Treatment with S-ILs slightly beneficial and improved GPRs max. 2.2 g L −1 h −1 and glucose yield max. 88 % g L −1 glucose.
However, the hemicellulose recovery 88 % and overall sugar yield 83 % obtained from the acid pre-hydrolysis were significantly higher than obtained from either nontreated (17 or 45 %) or (S)IL-treated (23 and 53 %).
Separate hydrolysis and fermentation of different lignocelluloses after treatment with either sulfuric acid or a SIL DBU-MEA-SO 2
Hydrolysates obtained from the enzymatic hydrolysis of DBU-MEA-SO 2 treated or acid pre-hydrolyzed substrates were readily fermented to ethanol. Glucose present in the hydrolysates was completely consumed and converted to ethanol within first 10 h of fermentations (Fig. 6). Ethanol concentrations of 1.2, 1.3, 1.8, 3.5, and 2.7 g L −1 were obtained from the fermentation of enzymatic hydrolysates of acid pre-hydrolyzed spruce wood, pine stem wood, birch wood, reed canary grass, and pine bark, respectively. The corresponding values for the DBU-MEA-SO 2 treated substrates were 3.2, 4.6, 7.2, 7.6, and 3.5 g L −1 , respectively. Even though the overall sugar production was higher for the combined acid and enzymatic hydrolyzed pine bark (Fig. 5b), still the overall ethanol production 3.4 g L −1 (0.7 g L −1 from acid hydrolysates and 2.7 g L −1 from enzymatic hydrolysates) did not exceed that obtained from the hydrolysates of IL-treated substrate (Fig. 6). Evidently, hemicellulose sugars of acid pre-hydrolysates were not consumed by the microorganism S. cerevisiae and requires an engineered strain that could use not only glucose but also other lignocellulose derived sugars.
Non-treated and acid pre-hydrolyzed substrates
The acid pre-hydrolysis procedure, used in our study is known to produce enzymatically digestible biomass, did not benefit the subsequent enzymatic hydrolysis of especially softwood substrates. This observation is, however, consistent with observations reported by Ungurean et al. [2]. Compared to non-treated, less sugars were released from the enzymatic hydrolysis of acid pre-hydrolyzed fir wood [2]. However, the main role of dilute acid pretreatment is to solubilize hemicellulose from the biomass and to make cellulose more accessible for cellulases [2] which is also evident from our study (see Additional file 1: Tables S1-S5). The resistance of acid pre-hydrolyzed material to the hydrolytic enzymes was probably due to the changes in substrate crystallinity and increased enzyme binding capacity of lignin-the major feature that affects enzymatic degradation process [38].
Li et al. [39] investigated the efficiency of dilute acid treatment of lignocellulose substrate. Results indicated that both non-treated and dilute acid-treated samples display no changes in cellulose structure. Also, significant amount of lignin remained in the acid-treated material. Upon enzymatic hydrolysis, cellulases tend to bind on the lignin-rich surfaces-lignin can irreversibly adsorb cellulases [40] causing loss of cellulose degradation. In addition, acid treatment of spruce wood altered the lignin structure leading to increased enzyme adsorption [41,42]. Moreover, after acid treatment, lignin or lignin carbohydrate complexes may condense on the surface of cellulose fibers [43], thus rendering the fibers less accessible to enzymes. However, the positive effect of acid pretreatments of birch wood and canary grass could be attributed to their lignin content which contained less lignin than the softwood substrates (Table 1). However, the inhibition of enzymes lignin did not comply for pine bark. Although pine bark contained high amounts of lignin (40.3 % dry wt.), the non-treated substrates were readily degraded by cellulase enzymes.
Effect of IL treatments
Anugwom et al. [27,28] investigated the efficiency of SILs MEA-DBU-SO 2 and MEA-DBU-CO 2 for the fractionation of woody biomass (i.e. spruce and birch) and reported that both these solvents could remove lignin and produce glucan enriched pulps. However, SILs MEA-DBU-SO 2 was a better solvent than MEA-DBU-CO 2, since it was capable of removing more than 90 % of lignin present in the native substrates whereas MEA-DBU-CO 2 could remove only up to 50 % [28]. Furthermore, regeneration of substrates via addition of water as anti-solvent (which is performed in our study) could reject the ILs soluble lignin in the solution [44]. Thus, creating a large cellulose accessible surface area for the subsequent enzymatic degradation with no lignin related enzyme inhibition. The improved enzymatic degradation of MEA-DBU-SO 2 was more likely due to its capacity in selectively removing high amounts of lignin rather than its effect on cellulose crystallinity. In case of MEA-DBU-CO 2 , the improved enzymatic hydrolysis is believed to be due to its synergistic effects. MEA-DBU-CO 2 is not only capable of removing lignin but also could reduce cellulose crystallinity as evident from the experiments with Avicel cellulose. However, MEA-DBU-CO 2 treatment of soft wood substrates was less effective probably due to its low lignin removing capacity. Nevertheless, despite the potential, recovery and reuse of ILs are important to make the process economically feasible. ILs are still more expensive than the conventional pretreatment solvents [6]. The recycling of ILs up to 10-20 times was claimed to allow for process costs per cycle comparable to conventional solvents, hence making ILs as cheaper alternatives as reusable solvents [45]. ILs are comparatively easy to recycle by simply removing the anti-solvent using techniques such as evaporation or distillation [19,46,47]. The lowvolatile nature of ILs permits distillation of the volatile substances, thus allowing for recovery [48,49]. It has been already shown that the ILs can be recovered and reused at least up to 5-7 times without decline in their efficiency [22,49]. However, recovery and reuse of ILs are often a question considering scaled up production of ILs. Nonetheless, ILs that have undergone cellulose regeneration are composed of not only dissolved IL and the anti-solvent but also contain soluble biomass compounds (e.g., lignin, soluble carbohydrates with low molecular weight, degradation products, extractives and others) that were not precipitated in the regeneration step. Recovery of these dissolved compounds is important; for instance, the recovered lignin may potentially serve as a raw material in the production of polymeric materials, and can be tedious.
Influence of IL treatment conditions on enzymatic hydrolysis
The conditions used for the IL treatments (Table 2) were selected to gain more information about the impact of treatment temperature and residence time on the IL treatments effect on subsequent substrate hydrolysis efficiency.
At a constant amount, i.e., 5 (w/w) % of biomass loading and upon fixed (S)IL pretreatment time, increasing pretreatment temperature favored and greatly enhanced the enzymatic digestion of lignocellulose substrates similar to observations by Hou et al. [50]. After IL treatment of birch and pine wood, at moderate conditions, the substrates were swollen but not dissolved [51]. It is believed that, at low pretreatment temperatures, the IL molecules mainly swell and disrupt cellulose I lattice, with no appreciable amount of cellulose chains being released into the IL solution. It is also speculated that, at low temperatures, the multilayered structures of plant cell wall and lignin network inhibit dissociation of cellulose chains [50]. However, at higher temperatures, the plant cell walls were destroyed and cellulose chains were released into the IL solution and the highly crystalline cellulose I was transformed into less crystalline cellulose II [52]. Hence, evidently, the highest amount of reducing sugars (and best glucose production rates) was obtained for the substrates treated at 160 and 180 °C (Figs. 2, 3, 4, 5). Shorter (S)IL treatment time (instead of 90 min 60 min) an increase in temperature (from 160 to 180 °C) had no significant effect in terms of subsequent enzymatic hydrolysis. In conclusion, high temperatures and short residence time upon pretreatment of lignocelluloses gave good results.
In general, from our study it was clear that, except or pine bark, lignin is a major barrier and plays an important role in the sugar extraction from lignocellulose substrates. There was a very close correlation between effect of efficiency of pretreatment solvent and lignin content of the lignocellulose. For example for lignin-rich soft wood substrates, lignin-specific SIL DBU-MEA-SO 2 was the most efficient pretreatment solvent. Nevertheless, in case of the species with low lignin content (hard wood and reed canary grass), DBU-MEA-CO 2 or [AMMorp] [OAc] was the best pretreatment medium . Evidently, the differences in the substrate lignin content have an impact on the results of any pretreatment as reported before [53].
Conclusions
The potential of different (S)ILs as pretreatment solvents upon conversion of several lignocelluloses into bioethanol was investigated. It was demonstrated that (S)IL treatments could significantly improve the enzymatic hydrolysis of biomass. SILs were in relative terms better pretreatment solvents, especially in case of softwood substrates. The SIL DBU-MEA-SO 2 was the best pretreatment media for woody substrates liberating both glucose and hemicellulose sugars. Nevertheless, in case of Pine bark, the combined acid treatment and enzymatic hydrolysis gave better results than what could be achieved with any (S)IL preprocessing. However, hydrolysates obtained from the enzymatic hydrolysis of (S)ILtreated lignocelluloses were readily fermented to ethanol and the yields were up to four times higher compared to the case when combined acid and enzymatic hydrolysis was employed. Thus, (S)IL-mediated preprocessing of lignocellulosic biomass can offer advantages over conventional acid treatments.
However, even though the (S)ILs investigated in this study were highly efficient, still challenges remain in their applications such as recovery of any (S)IL-degraded species (notably lignin and sugar polysaccharides) and potentially challenging recycling of (S)ILs.
Substrates
A variety of lignocellulose materials, including those of soft wood, hard wood and agriculture residues were targeted in the current study. Norway spruce wood, pine stem wood, birch saw dust, pine bark, and reed canary grass were the species studied. The substrates were first air dried at room temperature until a constant weight and moisture content less than 10 (w/w) %, was achieved. Afterwards, they were milled and sieved to an even particle size <1 mm using a Wiley mill and stored in sealed plastic bags at room temperature until further use. The dry-matter content of the substrates was determined using a Sartorius MA30 Electronic Moisture Analyzer (Germany) through heating by infrared rays and determination of weight loss. Along with native lignocellulose materials, a commercial microcrystalline cellulose substrate Avicel ® PH-101 (Sigma-Aldrich) was also used in the investigation for the sake of comparison.
The chemical composition of lignocelluloses in terms of structural carbohydrate content, lignin and extractives were analyzed according to National Renewable Energy Laboratory (NREL) analytical procedures [54,55].
Ionic liquids
SILs DBU-MEA-SO 2 and DBU-MEA-CO 2 were prepared as described in Anugwom et al. [27,28]. An equimolar mixture of DBU and MEA was bubbled with either SO 2 or CO 2 gas under rigorous stirring and the reactions were performed until the complete formation of SILs.
The new IL [AMMorp][OAc] was prepared as follows: Amberlite IRA-400(R-OH) (10.0 g in deionized water) was loaded in a chromatography column (20 × 1.5 cm) and then 1.0 M sodium acetate solution (100 mL) was passed through the column to facilitate ion exchange. After, the column was thoroughly washed with deionized water until the eluent pH ~7 was obtained. The corresponding bromide precursor, N-allyl-N-methylmorpholinium bromide (4.44 g in 50 mL deionized water), solution was carefully loaded and passed through the column followed by deionized water (50 mL). The eluent containing [AMMorp][OAc] was collected and water evaporated. Then the IL was dried at 60 °C under high vacuum (4 × 10 −2 mbar) to remove residual water.
Pretreatment procedures
Pretreatment of different cellulosic substrates (50 mg) with either various IL solvents (950 mg) or 1 (w/w) % H 2 SO 4 (950 mg) were performed in 12 mL borosilicate glass tubes with polytetrafluoroethylene (PTFE)-lined screw caps. A pressure reactor (Teflon lined stainless steel, homemade, 500 mL) with silicon oil was preheated to a desired treatment temperature using a furnace (T max < 1100 °C) equipped with B 180 controller and NiCr-Ni thermocouple (Nabertherm Muffle furnace, Model No. LVT 9/11, Germany). Glass tubes with cellulosic substrates and ionic liquids were then immersed into the preheated reactor and closed tightly. The reactor was then placed in the furnace and the desired reaction conditions were set (Table 2). After treatment, the reactor was removed from the furnace; the tubes were removed from the reactor and allowed to cool to room temperature. The IL-treated cellulose rich substrates were then precipitated by simply adding 6 g of anti-solvent (in our case deionized water) to the pretreated solutions. Afterwards, the solids were separated by vigorous mixing and centrifugation for 7 min and 3000 rpm (Allegra ® 25R centrifuge, BECKMAN COULTER, USA). The IL rich supernatants were decanted and the solids were subsequently washed as described above, using 3 × 6 g anti-solvent and 1 × 6 g 50 mM citrate buffer pH 5.8. These are hereafter referred to as regenerated substrates. In the case of lignocelluloses pre-hydrolyzed with H 2 SO 4, the solid and liquid fractions were separated by centrifugation. The collected liquid fractions (acid hydrolysates-AHs) were stored at -80 °C and the solids were washed with deionized water and citrate buffer as mentioned earlier.
The obtained regenerated substrates from IL treatments and the solids from acid pre-hydrolysis (S-AH) were then lyophilized (Alpha 2-4 LSC Freeze Dryer, Martin Christ Gefriertrocknungsanlagen GmbH, Germany) to remove any residual liquids, thus avoiding uneven dilutions upon their enzymatic hydrolysis.
To compare the efficiency of different treatments used in this study, the parameter severity factor (SF) was employed, which incorporates the treatment time and temperature (see the equation below). It is generally used to assess various individual lignocellulose pretreatment strategies [56].
In the above equation, t is the treatment time in minutes, T is the treatment temperature, T ref is the reference temperature (i.e., 100 °C) and 14.75 is an empirically determined constant.
Enzymatic hydrolysis
Enzymatic hydrolysis experiments of non-treated and regenerated cellulosic substrates were carried out in 12 mL glass tubes with 930 mg of 50 mM citrate buffer pH 5.8 and 20 mg of Cellic CTec2, activity 128.6 FPU/g, state-of-the-art enzyme mix (Novozymes). Hydrolysis reactions were performed for 48 h in a shaking incubator SF = log (t · exp((T − T ref )/14.75)) (IKA ® KS 4000, control IKA ® -Werke GmbH & Co. KG, Germany) set at 50 °C and 200 rpm. At defined time intervals (4, 24, and 48 h after the addition of enzymes), samples of 50 μL (enzymatic hydrolysates-EHs) were collected from the hydrolysis systems and stored at −80 °C.
Separate hydrolysis and fermentation
Lignocellulose samples, 0.25 g (dry weight), were pretreated at a severity factor of 4.1 ( Table 2) with either the SIL DBU-MEA-SO 2 (4.75 g) or 1 (w/w) % H 2 SO 4 (4.75 g) in 10 mL glass tubes. Hydrolysis of regenerated substrates 0.3 g, obtained after the treatments and lyophilization, was performed in the presence of citrate buffer pH 5.8 (5.58 g) and enzyme (0.12 g) mix. Thus, the pretreatments and enzymatic hydrolysis experiments were performed (as described in earlier sections) with an increased overall reaction volume, but in equal concentrations. After enzymatic hydrolysis, the solid and liquid fractions were separated by centrifugation and the sugarrich liquid fractions were used for ethanol fermentations as described below.
The yeast S. cerevisiae, Thermosacc inoculum was prepared in a 2 L cotton-plugged shake flask with 1 L YPD medium (10 g L −1 yeast extract, 20 g L −1 peptone, 20 g L −1 d-glucose). The medium was inoculated and incubated with agitation (200 rpm) at 30 °C and the cells were harvested in late exponential growth phase by centrifugation (Hermle Z206A, Hermle Labortechnik GmbH, Wehingen, Germany) at 1500g for 5 min. The harvested cells were concentrated and re-suspended in an appropriate amount of sterile water to achieve a cell density of 27 g L −1 (dry weight). Fermentations of liquid hydrolysates, obtained from both the acid pre-hydrolysis and enzymatic hydrolysis, were performed in 12 mL screw capped plastic tubes. Sugar-rich liquid hydrolysates (2.3 mL of each) were added to the tubes along with 0.05 mL nutrient solution (75 g L −1 yeast extract, 37.5 g L −1 (NH 4 ) 2 HPO 4 , 1.875 g L −1 MgSO 4 ·7H 2 O, 119.1 g L −1 NaH 2 PO 4 .H 2 O), and 0.15 mL of yeast inoculum. Thus, the fermentation broths contained a total liquid volume of 2.5 mL and had a yeast cell density of 1.6 g L −1 dry weight. After inoculation, the tubes were incubated at 30 °C and stirred (at 200 rpm) in an orbital shaking incubator (IKA-Werke) for 24 h. Samples of 100 µL were collected at defined time intervals and stored at −80 °C until further analysis.
Analysis
Samples collected from different experiments of this study were centrifuged (Centrifuge: Thermo Scientific, Germany) at 21,000g for 5 min and the supernatants were used for chemical analysis by either using ion | v3-fos |
2017-06-26T02:25:42.715Z | {
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} | s2 | Downy mildew disease promotes the colonization of romaine lettuce by Escherichia coli O157:H7 and Salmonella enterica
Background Downy mildew, a plant disease caused by the oomycete Bremia lactucae, is endemic in many lettuce-growing regions of the world. Invasion by plant pathogens may create new portals and opportunities for microbial colonization of plants. The occurrence of outbreaks of Escherichia coli O157:H7 (EcO157) and Salmonella enterica Typhimurium (S. Typhimurium) infections linked to lettuce prompted us to investigate the role of downy mildew in the colonization of romaine lettuce by these human pathogens under controlled laboratory conditions. Results Whereas both EcO157 and S. Typhimurium population sizes increased 102-fold on healthy leaf tissue under conditions of warm temperature and free water on the leaves, they increased by 105-fold in necrotic lesions caused by B. lactucae. Confocal microscopy of GFP-EcO157 in the necrotic tissue confirmed its massive population density and association with the oomycete hyphae. Multiplication of EcO157 in the diseased tissue was significantly lower in the RH08-0464 lettuce line, which has a high level of resistance to downy mildew than in the more susceptible cultivar Triple Threat. qRT-PCR quantification of expression of the plant basal immunity gene PR-1, revealed that this gene had greater transcriptional activity in line RH08-0464 than in cultivar Triple Threat, indicating that it may be one of the factors involved in the differential growth of the human pathogen in B. lactucae lesions between the two lettuce accessions. Additionally, downy mildew disease had a significant effect on the colonization of EcO157 at high relative humidity (RH 90-100%) and on its persistence at lower RH (65-75%). The latter conditions, which promoted overall dryness of the lettuce leaf surface, allowed for only 0.0011% and 0.0028% EcO157 cell survival in healthy and chlorotic tissue, respectively, whereas 1.58% of the cells survived in necrotic tissue. Conclusions Our results indicate that downy mildew significantly alters the behavior of enteric pathogens in the lettuce phyllosphere and that breeding for resistance to B. lactucae may lower the increased risk of microbial contamination caused by this plant pathogen.
Background
Contamination of lettuce with the human enteric pathogens, Escherichia coli O157:H7 and Salmonella enterica has caused several outbreaks of foodborne disease in the US and other parts of the world [1,2]. Although the persistence of these human pathogens on lettuce in the field has been documented [3][4][5][6], factors that contribute to their survival and potential multiplication on plants remain largely unknown. As for other bacteria that immigrate onto plant surfaces, it is likely that the survival of enteric pathogens is affected by the plant microbial community and various physicochemical stresses that prevail in the lettuce phyllosphere. In addition to moving through stomata to the mesophyll tissue of the leaf [7], where it may be shielded from such conditions as desiccation and UV irradiation, EcO157 may gain access to protective sites that result from the infection by plant pathogens. Lettuce can be infected by a broad range of bacterial, fungal, oomycete, and viral pathogens [8], the prevalence of which greatly depends on environmental conditions and the genotype of the plant itself. Downy mildew, a disease of lettuce caused by the obligate oomycete pathogen, Bremia lactucae Regel, is endemic to many important lettuce producing areas of California [9]. Several outbreaks of EcO157 infections have been traced back to a major lettuce-production region in California [2] in which this enteric pathogen is highly prevalent [10]. B. lactucae survives in crop debris from infected leaf tissue and on weed hosts. Representative symptoms of downy mildew disease on lettuce are shown in Figure 1. In the early stages of plant infection, the pathogen causes angular chlorotic lesions bordered by the leaf veins. Growth of mycelia and the presence of small dense masses of grayish spores are observed mostly on the abaxial surface of the leaves. The infected tissue eventually becomes necrotic and dies [8]. B. lactucae benefits from humidity and cool temperatures and therefore, infection rates of lettuce are high during conditions promoting long durations of morning leaf wetness [11]. The incidence of the disease in the Salinas growing region of Coastal California generally increases in the autumn lettuce crop [12].
Biotrophic and necrotrophic fungi that cause post-harvest decay have been shown in several instances to enhance the colonization of fruit and vegetables by enteric pathogens. Glomerella cingulata infection of apple fruit promoted proliferation of Listeria monocytogenes and EcO157, likely due to a change of pH from 4.0 to 7.0, whereas the reverse effect was observed with Penicillium expansum [13,14]. Alternaria alternata and Cladosporium spp. had a positive effect on S. enterica colonization of tomato fruit [15] and Fusarium spp. prolonged the survival of EcO157 on tomato under storage conditions but not that of L. monocytogenes [16]. These observations suggest that the effect of pathogenic fungi on enteric pathogens in plant tissue may vary depending on several factors in this tri-partite association.
Despite the endemic nature of downy mildew disease in lettuce fields in California and other regions in the United States, and the increased appearance of disease symptoms on plants near harvest maturity i.e. not long prior to the lettuce crop reaching the consumer, the role of B. lactucae infection in the behavior of EcO157 on lettuce has not been investigated. B. lactucae requires free water on the phylloplane for spore germination and invasion of plant cells, a condition that also promotes the survival and multiplication of EcO157 on lettuce [17,18]. Additionally, lesions caused by B. lactucae are known to act as portals to necrotrophic plant pathogens, such as Botrytis cinerea, which colonize the broken tissue as secondary invaders [19]. Our study investigates the potential of downy mildew lesions to serve as a portal for EcO157 and to create a habitat where the human pathogen may thrive opportunistically by gaining protection from environmental insults within the plant tissue.
Results and discussion
Effect of downy mildew disease on EcO157 and S. enterica under wet conditions In order to investigate the growth potential of EcO157 and S. enterica in diseased tissue during presence of free Figure 1 Photographs illustrating in the upper panel, typical downy mildew disease symptoms on the abaxial lettuce leaf surface with chlorotic and necrotic tissue, and white/grey spores of B. lactucae hyphae emerging from the infected tissue. In the lower panel, typical leaf discs of healthy, chlorotic, and necrotic (left to right) tissue of romaine lettuce tissue cultivar Green Towers used as samples for measurement of EcO157 population sizes in our study.
water on lettuce plants, such as may occur during periods of rain, dew or overhead watering, the pathogens were inoculated onto leaves that were then incubated under conditions promoting wetness on their surface. As we observed previously on romaine lettuce [17], both enteric pathogens achieved population increases of approximately 10 2 -fold on the healthy leaf tissue (Figure 2). The presence of necrosis due to infection by B. lactucae ( Figure 1) promoted enhanced colonization by both enteric bacteria since the population sizes on the healthy and infected tissue diverged greatly by 18 h postinoculation. Although we did not test for the possible asymptomatic presence of the oomycete in some of the visually healthy tissue that was used in our study, the disease symptoms clearly resulted in greater population densities of the enteric pathogens than the seemingly healthy tissue. Overall, the population sizes of EcO157 and S. Typhimurium in the lesions increased at least 10 5 -fold over 42 h at warm temperature. This high carrying capacity of the diseased leaf tissue is likely due to the abundant nutrients made available by the oomycete degradation of plant cells and their contents.
Lettuce leaves are rich in a variety of carbohydrates, including sucrose, glucose, fructose, galactose and mannose [20,21]. EcO157 rapidly activates multiple carbohydrate transport systems and utilization pathways upon exposure to lysates of romaine lettuce leaves [22]. Although it is likely that the oomycete itself acquires a large share of the nutrients present in plant cells, the collapsed leaf tissue at advanced stages of the disease such as that inoculated in this study probably supports high rates of multiplication of the human pathogens without overall significant competition by the plant pathogen. Another possibility is that at advanced stages of the disease, the oomycete scavenges plant components, the degradation of which makes substrates available to EcO157. It is noteworthy that leaf damage caused by phytopathogens does not de facto promote colonization by enteric pathogens. For example, S. enterica levels in lettuce shoots also inoculated with lettuce mosaic virus (LMV) were not different than in non-LMV-infected plants and even decreased in infected plants grown under water stress [23]. Additionally, EcO157 cell density on spinach was unaffected by its co-inoculation with Pseudomonas syringae DC3000, a plant pathogen that caused necrotic lesions on the leaves [24]. Thus, factors additional to leakages of substrates from infected cells are at play in the interaction of enteric pathogens with plant pathogens.
Localization of EcO157 by microscopy
Confocal microscopy of downy mildew necrotic lesions clearly illustrates the large masses of GFP-EcO157 cells that result from colonization of these sites compared with the few microcolonies that formed at discrete locations on the epidermis of healthy leaf tissue ( Figure 3A). Of interest also, is the external and internal colonization of the oomycete hyphae that we observed 40 h after EcO157 came in contact with the plant pathogen through inoculation of the necrotic tissue. This is apparent in Figure 3B but more specifically in the single confocal optical scan through the hypha shown in Figure 3C, which reveals that the mass of EcO157 cells is bound by the hyphal cell wall and located internally. It remains unclear however, if the human pathogen invaded the oomycete actively, or if it gained access due to damage and thus, ports of entry, on the hyphae. This important aspect of EcO157-B. lactucae interactions deserves further investigation, particularly in the light of previous studies demonstrating the inhibition of fungi by various bacterial species [25]. If invasion of hyphae by EcO157 can indeed occur, the invaded hyphae may serve as a vessel for enteric bacteria to enter the intracellular space of plants.
Role of plant susceptibility to downy mildew in EcO157 growth
Reports on the role of plant genotype in the microbial community composition of the lettuce phyllosphere have been inconsistent [26,27]. Numerous lettuce cultivars have been developed in order to minimize crop yield losses incurred from plant disease, including downy mildew. Given the highly hospitable environment of downy mildew lesions to EcO157, as illustrated in Figure 2, we investigated the role of plant susceptibility to B. lactucae infection in lettuce colonization by this human pathogen. A commercially released lettuce cultivar Triple Threat and a newly developed lettuce breeding line RH08-0464 were selected to test this hypothesis. Triple Threat is highly susceptible to infection by B. lactuacea [28,29], whereas RH08-0464 has high field resistance to this pathogen that is inherited from the stem-type lettuce Balady Banha [28]. EcO157 proliferated to a significantly greater extent in diseased tissue (either in chlorotic or necrotic, or both types of, tissue) than on healthy tissue on both plant accessions (Table 1). Representative discs of healthy, chlorotic, and necrotic lettuce leaf tissue are shown in Figure 1. The extent of EcO157 colonization of the healthy tissue was not dependent on accession (P values ranged between 0.301 and 0.552) in any of the replicate experiments (Table 1). Although we did not attempt to assess specifically the endophytic EcO157 population sizes in our study, this observation is in line with results from a previous study that failed also to detect an overall effect of lettuce cultivar on the degree of S. enterica endophytic colonization of leaves, despite a significant role of serovar-cultivar interactions [30]. On the other hand, EcO157 metabolic activity during epiphytic and endophytic colonization of lettuce, as assayed with a lux reporter, varied in a cultivar-dependent manner, indicating that plant genotype may affect the human pathogens on the surface or inside healthy leaves [31]. Thus, a range of scenarios remains to be explored regarding the role of cultivar in the contamination of healthy lettuce leaves by enteric pathogens.
Importantly, the EcO157 population increase in diseased tissue in our study was significantly lower on lettuce line RH08-0464 than on the more susceptible cultivar Triple Threat in all three replicate experiments (P < 0.05) ( Table 1). This suggests that a plant factor linked to the dynamics or amount of tissue infection by B. lactucae affects the ability of the human pathogen to fully exploit these lesions for multiplication. The nature of this plant factor remains unclear. It is unlikely that the plant gene(s) that contribute(s) to the resistance of RH08-0464 to B. lactucae infection directly inhibited the growth of EcO157 in the lesions because this type of resistance is expected to be specific to B. lactucae-lettuce interactions. Recently, chromosomal regions associated with broadspectrum quantitative disease resistance to plant pathogens were identified [32,33]. It would be of great interest to determine if broad-spectrum disease resistance may be involved not only in plant interaction with plant pathogens but may be of use also to reduce plant colonization by human enteric pathogens.
Expression of PR-1 in lettuce accessions
Because basal immunity contributes to protection of plants against a broad range of insults, we tested the expression of the gene encoding the antimicrobial PR-1 protein in two lettuce accessions infected with B. lactucae. PR-1 is a major marker of the salicylic acid-mediated pathway of basal defense against microbial infection [34] that is induced in plants also in response to oomycete infection [35,36]. Both healthy and chlorotic leaf tissue were tested for PR-1 expression in the resistant line RH08-0464 and in the susceptible cultivar Triple Threat. Necrotic lesions do not yield sufficient mRNA to allow for transcript measurement by qRT-PCR.
qRT-PCR analysis revealed that accession RH08-0464 had significantly greater expression of PR-1 than cultivar Triple Threat (Figure 4). The high expression of this gene in the healthy RH08-0464 tissue is likely caused by its systemic induction, since PR-1 is the hallmark of systemic acquired resistance [34]. Thus, because the healthy tissue was sampled from leaves that harbored lesions at various stages of the disease, the defense signal induced by the oomycete actively infecting the leaf at other distant sites likely resulted in production of PR-1 in the healthy part of the same leaf. This accumulation of PR-1 may not have affected the growth of the human pathogen on the healthy tissue of the tested accessions since most, if not all, of the bacterial cell population was located on the leaf cuticle and therefore, did not have open access to the plant apoplast as did occur in the lesions. The general trend of PR-1 transcriptional activity agrees with a potential role of B. lactucae-induced basal immunity in the weaker EcO157 colonization of lesions in RH08-0464. A different but not necessarily contradictory hypothesis, may be that EcO157 benefited from an immuno-suppressive effect of B. lactucae on the cultivar Triple Threat, thereby experiencing an environment that enhanced its growth compared with the lesions in the more resistant RH08-0464. This type of symbiotic interaction was observed with co-inoculations of the plant pathogenic P. syringae pv. tomato DC3000ΔhopQ1-1 and S. enterica in Nicotiana benthamiana [37].
Lesion-mediated protection of EcO157 from desiccation
Bacterial cells in the phyllosphere frequently encounter periods of dry conditions when free water is not available on the plant surface [38]. Given that EcO157 cells can become embedded in the downy mildew-infected tissue and that the physicochemical properties of the damaged tissue itself may alter the microenvironment and the physiology of the human pathogen, we sought to determine if EcO157 cells gained protection from desiccation stress on lettuce leaves by localization in B. lactucae lesions. Our experimental set up, using cultivar Green Towers, simulated high relative humidity conditions (90-100% RH) where free water remained at few locations on the leaves at the macroscopic level, and conditions of 65-75% RH where free water was absent from the leaf surfaces macroscopically. EcO157 multiplied over the first 24 h after inoculation on healthy, chlorotic, and necrotic tissue under high RH, with the greatest increase observed in the necrotic lesions ( Figure 5A). The population sizes then decreased between 24 and 48 h post-inoculation, possibly because a certain proportion of the wet sites on the leaves dried up over time after inoculation. At the lower RH of 65-75%, EcO157 populations declined on all types of tissue over time but remained proportionally the greatest in the necrotic lesions with a survival rate at 48 h postinoculation of 1.58% compared with 0.0011% and 0.0028% in the healthy and chlorotic parts of the leaf, respectively ( Figure 5B). It is noteworthy that under the lower RH, the EcO157 cell numbers appeared to stabilize over time after an initial decrease in the necrotic tissue, suggesting that the human pathogen adapted to the conditions in that habitat either physiologically or by reaching protective niches. Contribution of the bacterial plant pathogen, Xanthomonas campestris pv. vitians to the persistence of EcO157 on lettuce in the field, where low RH and water availability on the phylloplane may be important stressors during various times of the day has been reported [3].
Our study is the first to determine the effect of downy mildew, an endemic disease of lettuce in a major vegetable production region of the USA, on the behavior of EcO157 on this crop and to assess various factors that may enhance its persistence in infected leaves. Given the great potential for multiplication and survival of EcO157 in B. lactucae lesions on wet and dry leaves, respectively, and considering that large fluctuations in water availability to bacterial cells likely prevail on lettuce in the field, downy mildew disease may represent an important risk factor of microbial contamination. The higher prevalence of downy mildew on lettuce plants approaching harvest maturity may compound the risk of contamination associated with this disease. Although most of the old lettuce leaves infected with downy mildew are trimmed off during harvest, a fraction of B. lactucae lesions escape visual detection. Additionally, the proliferation and enhanced survival of EcO157 in the infected tissue may create a reservoir from which the pathogen is disseminated or vectored to other sites in the field, as well as contribute to the persistence of the human pathogen in crop debris in the field. Further investigation of the role of downy mildew in the colonization of lettuce by enteric pathogens under field conditions is warranted. Additionally, our observation that EcO157 survives and multiplies at different rates in comparable B. lactucae lesions of two accessions indicates that variability in lettuce gene pool may be explored to develop cultivars that are less hospitable to human enteric pathogens. Such cultivars would be a vital part of an integrated strategy to minimize EcO157 illness linked to lettuce contamination.
Conclusions
The massive proliferation of EcO157 (and S. Typhimurium) under wet conditions in downy mildew lesions on lettuce leaves, and its enhanced persistence in this diseased tissue under conditions of lower RH, suggest that infection of lettuce by B. lactucae may increase the risk of microbial contamination of this crop. Given that differences in EcO157 colonization of diseased tissue were observed in two lettuce accessions with different levels of resistance to downy mildew, breeding lettuce for resistance to this disease may be worth exploring to decrease the burden of enteric illness due to contamination of lettuce.
Strains and media
E. coli serovar O157:H7 strain ATCC 43888, a natural strain that does not produce shiga toxin 1 and 2, and S. enterica serotype Typhimurium strain SL1344, were used in this study. A spontaneous rifampin-resistant strain of E. coli O157:H7 43888 was obtained by selection on Luria Bertani (LB) amended with rifampin at 100 μg/ml. The spontaneous mutant and parental strain were compared in LB throughout all phases of culture and did not show any difference in fitness. S. Typhimurium strain SL1344 is naturally resistant to streptomycin. The strains were grown to stationary phase at 28°C in Luria Bertani broth -half salt (0.5% NaCl), the cells were washed twice in potassium phosphate buffer (KP) (10 mM, pH 7.0), and [28,29]. Green Towers is one of the main cultivars used for commercial production in the USA. Because naturally occurring infection was used, races of B. lactucae that infected the plants were not controlled for. However, based on recent data from the same lettuce growing area, the most frequently detected avirulence genes in B. lactucae were Avr17, Avr37, Avr38, and Avr36 [12].
Inoculation and incubation of inoculated lettuce leaves
Immediately before inoculation with enteric pathogens, leaves that had symptoms of downy mildew at the chlorotic and necrotic stages of the disease were harvested from the potted plants. Each replicate detached leaf was inoculated individually by holding it at its base and immersing it upside down in the inoculum suspension for 3 sec and then briefly draining the excess inoculum suspension, as we previously described [17].
Comparison of EcO157 and S. Typhimurium proliferation on healthy and diseased lettuce tissue was conducted only on the cultivar Green Towers and under conditions of free water on the leaf surface in order to assess the overall effect of downy mildew on their colonization of lettuce; all other experiments in this study were performed with EcO157 only. For comparison of S. Typhimurium and EcO157, the leaves were inoculated with single strains in a suspension of 10 6 cells/ml. For comparison of colonization of various lettuce accessions by EcO157, leaves were also inoculated in a suspension of 10 6 cells/ml. In both types of experiments, the leaves were then incubated horizontally in a single layer in a large plastic tub lined with wet paper towels and covered with a plastic bag, which promoted the presence of free water on the leaves. The tub was then placed in an incubator at 28°C. This experimental set up was devised to test the maximum growth potential of the enteric pathogens on healthy tissue, and on chlorotic and necrotic tissue due to infection by B. lactucae.
In order to investigate the effect of relative humidity on the persistence of EcO157 on healthy and diseased tissue, the leaves were inoculated in a suspension of 2 × 10 5 and 10 7 cells/ml for incubation under high and low relative humidity (RH), respectively. Then, the lettuce leaves were incubated upright in a small container with water at the bottom to maintain leaf turgidity. Half of the containers were covered with a plastic bag tightened with a rubber band around the bottom of the container and the other half remained uncovered. All of the containers were placed in a chamber maintained at 28°C and 65-75% RH. This set up resulted in the leaves in the covered containers being exposed to 90-100% RH, whereas those in the uncovered containers experienced 65-75% RH. By the end of the experiment, free water was absent macroscopically on the leaves under low RH, whereas leaves under high RH still harbored free water at rare locations. RH and temperature in the chamber were monitored with a Dickson TH8P5 Chart Recorder equipped with a remote sensor (Dickson, Addison, IL). Four, eight and six replicate discs were used in the first, second and third replicate experiment, respectively.
Recovery of bacterial cells from leaf tissue and population measurement
Immediately after inoculation and at indicated times, discs 9 mm in diameter of healthy, chlorotic, and necrotic tissue, as illustrated in Figure 1 were sampled from the inoculated leaves with a cork borer #5. Sampling was performed at random from a total of 15 replicate leaves; the three types of tissue were not necessarily taken from the same leaf. The number of replicate discs varied from three to eight depending on the type of experiment and is indicated in figure legends.
To recover bacteria from leaf tissue, each disc was homogenized with a mortar and pestle in 2 ml KP buffer (10 mM, pH 7.0). The homogenate and dilutions were plated onto LB agar containing rifampin (100 μg/ml) or streptomycin (30 μg/ml) for bacterial counts of EcO157 and S. enterica, respectively. For experiments under low RH conditions and in which the population size of EcO157 declined over time, the entire disc homogenate was plated and thus, the detection limit for measurement of population size was one cell per disc of leaf tissue. The plates were incubated at 37°C overnight and colonies counted to assess population sizes per disc of leaf tissue.
Microscopy
Small discs of healthy and necrotic lettuce tissue were sampled from the leaves at 48 h post-inoculation as described above and mounted with AquaPolymount (Polysciences, Warrington, PA) for visualization with a Leica SP5 confocal microscope (Leica Microsystems, Wetzlar, Germany). The green fluorescent signal was obtained from GFP-EcO157 43888 transformed with pGT-KAN, a stably maintained plasmid expressing gfp constitutively from the kanamycin resistance gene promoter [39], which was used in EcO157 in our previous studies [17,40]. The red fluorescent signal was obtained from the autofluorescence of B. lactucae and from the chloroplasts of the leaf tissue. In one instance, the far-red autofluorescent signal of the B. lactucae hyphae was pseudocolored in blue in order to better distinguish them from the GFP-EcO157 cells that colonized some of the hyphae infecting the leaves.
qRT-PCR
Expression of the basal plant defense gene PR-1 was quantified in romaine lettuces Triple Threat and RH08-0464. Discs from uninoculated and nonincubated leaves with natural infection of B. lactucae from the field were harvested from the same plants that were sampled for leaf inoculation. The discs were frozen in liquid nitrogen and stored in the −80°C freezer until used for qRT-PCR. Six discs from each type of tissue were sampled at random from ten leaves. The discs were ground individually using a mortar and pestle in liquid nitrogen before RNA was extracted using the Ambion® TRIzol® reagent and PureLink® RNA kit (Life Technologies, Carlsbad, CA). The RNA was tested for absence of DNA and analyzed by qRT-PCR with the Stratagene Brilliant II SYBR Green kit as described previously [22,41]. Expression of ACT7 was used to normalize the data between samples based on the method by Pfaffl [42]. The sequences of the primers, based on Lactuca sativa nucleotide sequences in GenBank, were: PR-1-F 5′TCGCCACAAGACTTTGTTAATG, PR-1-R 5′GAGGCAAGATTTTCACCATAGG, ACT7-F 5′ GCAATTCAAGCCGTTCTTTC, and ACT7-R 5′GATCC AAACGGAGGATAGCA.
Statistical analysis
All experiments were replicated at least twice with plants harvested from the field at different times. Analysis of variance (ANOVA), t-test, and descriptive statistical analyses were performed with the software JMP v. 11.1.1 (SAS Institute, Cary, NC, USA). Significant differences for multiple comparisons were determined using the Tukey-Kramer HSD (honest significant difference) procedure. | v3-fos |
2019-03-30T13:05:51.577Z | {
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} | s2 | The Occurrence of Cryptosporidium parvum in Dairy Calves and the Influence of Management Practices
Cryptosporidium species infections are associated with the clinical manifestation of diarrhea, which can possibly generate economic losses associated with morbidity and mortality depending on the type of property management used. Additionally, animals with diarrhea eliminate large quantities of oocysts via the feces, thus contributing to the dispersion of oocysts in the environment and favoring the infection of susceptible hosts. The study aimed to determine the rate of Cryptosporidium parvum infection in 79 calves under one year of age at a dairy farm in southern Rio de Janeiro state, Brazil, in association with the cattle raising management practices. During the study period, two different management practices (A and B) were adopted. Under practice A, 21.9% of the samples (7/32) were Cryptosporidium spp. positive according to microscopic diagnosis. After switching to practice B, the percentage of infected animals decreased to 8.5% (4/47). Although diarrhea was reported in 13.9% (11/79) of the calves studied, there was no correlation with Cryptosporidium spp. infection (p>0.05). Cryptosporidium parvum, which is considered to have high zoonotic potential, was identified in this study. This fact is of great importance with regard to public health because of the environmental contamination of the area surrounding the property, which increases the risk to both human and animal populations. Additionally, the implementation of some changes in farm management practices contributed to a decrease in the percentage of infected animals, thereby reducing the dissemination of oocysts in the environment.
Introduction
Dairy cattle production is considered one of the main agricultural activities worldwide. A major problem associated with milk production is related to the sanitary aspects of cattle rearing. Parasitic diseases are particularly highlighted because these have been reported to be the most prevalent [1]. Among the diseases caused by protozoa, cryptosporidiosis has been emphasized given its responsibility for considerable economic losses in the production chain. These losses are related to the disease pathology that can cause severe diarrhea and intestinal malabsorption syndrome in an age-, host immune status-and Cryptosporidium species-dependent manner and can lead to morbidity and even mortality in calves [2][3][4][5][6].
Diarrheal outbreaks among cattle result in financial losses because the symptoms are directly related to reduced weight gain, decreased productivity and increased mortality [7][8][9]. Therefore, bovine cryptosporidiosis is widely studied, given the economic impact of diarrhea on the production chain [10]. Out of 26 valid species of the genus Cryptosporidium, C. parvum is responsible for causing clinical symptoms, especially in calves approximately one month of age [7,8,11,12].
The duration of diarrhea in Cryptosporidium-infected calves depends on several factors, including the level of environmental contamination, virulence, infectivity of the involved species, host susceptibility and age at first infection [13].
The prevalence of C. parvum infection varies widely in cattle, with herd positivity rates ranging from 13-100%, especially before one month of age [11,[14][15][16][17]. This variation in prevalence might be directly influenced by certain factors such as the host age, study area characteristics and study methodology [11,13,15,18].
In Brazil, the prevalence of Cryptosporidium spp. infection in dairy cattle ranges from 0.6-72.13% and C. parvum is most prevalent in animals less than two months of age [19][20][21].
Property sanitation can directly influence the route of cryptosporidiosis transmission. Poor sanitary conditions in the environments where animals are raised, particularly in rearing pens, can increase the animals' infection risk [22]. Therefore, the use of appropriate management practices is required to prevent cryptosporidiosis outbreaks [7]. The use of simple management practices such as raising calves in individual pens have led to reduced infection rates and consequently reduced environmental contamination [22].
Materials and Methods
The C. parvum infection occurrence was studied in 79 Holstein crossbred calves up to one-year-old for a 15-month period. All studied calves were born and raised in the dairy farm at which the study was conducted, that was small in size and located in the Vale do Paraíba microregion (22°42'30.17" S and 43°46'51.80" W), Rio de Janeiro state, Brazil.
The study quasi-experimental design was conducted in this dairy farming property. All 79 Holstein crossbred calves were separated into groups according to their feeding behavior as preweaned and post-weaned calves. The pre-weaned group consisted in calves up to 2-months-old that were feed with milk, bovine ration and hay. The post-weaned group consisted in bovines older than 2-months-old up to one-year-old that were similarly fed as the first group described, except for the milk ingestion.
Two different management practices (A and B) were used during sample collection; which primarily consisted in a different way of housing the calves and the modification in the height of the feeders. In both groups, there were animal with pre-weaned and post-weaned calves.
At the first stool sample collection, the animals were housed in collective rearing pens in a semi-open facility which the sanitary conditions were poor and inadequately managed (Management A), with the drinkers and feeders near the floor. These stalls were generally cleaned once in a day, being constantly humid, due the absence of sunlight incidence. In regard of the cleaning management, sometimes could be seen feces spread all over the floor. The collective pens were located near to a river that crossed the dairy farm. When the rearing pens were washed, the runoff water was drained into the river.
Later, changes to the facilities and calf management practices (Management B) were suggested to the owner. The calves were moved from collective rearing pens of a semi-open facility to individual hutches located in a wider area without humidity. Besides the changes in the facility area, the drinkers and the feeders were installed in a higher place in the rearing pen. However, despite the new facility have changed place, the cleaning management stills the same and the runoff water continued to be drained into the river. This new facility was located near the area where the adult animals were housed.
In both cases, the fecal material was collected directly from the rectal ampulla of the animals, labeled and stored at 4˚C until processing in the Laboratory of Protozoology, Department of Animal Parasitology, Federal Rural University of Rio de Janeiro (Universidade Federal Rural do Rio de Janeiro; UFRRJ).
Most of the collected fecal samples were within the normal range; however, some calves exhibited clinical manifestations of diarrhea. In addition, the occurrence of diarrhea in calves was evaluated and compared it with the positivity occurrence of Cryptosporidium sp. in animals.
In the laboratory, the samples were cataloged, homogenized, filtered, processed according to the sedimentation and flotation technique [23] and analyzed for the presence of Cryptosporidium spp. oocysts using light microscopy with and without phasecontrast.
All positive samples were processed using molecular techniques to confirm the presence of Cryptosporidium spp. infection; for detection and differentiation of the involved Cryptosporidium species and genotypes. The genomic DNA was extracted using the QIAamp DNA Stool Mini Kit (Qiagen®, Venlo, The Netherlands) according to the manufacturer's recommendations, with slight modifications [24].
Polymerase Chain Reaction (PCR) was performed immediately after DNA extraction. Two target genes, 18S and GP60, were used to amplify of the Cryptosporidium spp. genomic DNA. Diagnosis of the infectious species and subtypes collected from the animals was performed via PCR according to the method described in a previous study [24], which used nested PCR reactions with known primers for the 18S gene [25] and for the GP60 gene [26].
All of the primary PCR and nested-PCR products generated during the amplification of both target genes were visualized on a 1% agarose gel stained with Gelred TM [24]. The protocols used for sample purification, genotypic characterization and cloning were conducted according to the method previously described by the authors [21].
To evaluate the effect of the type of livestock management front positivity for Cryptosporidium sp. in dairy calves, a simple logistic regression model was performed to correlate the dependent variable (diagnosis for Cryptosporidium sp.) in dichotomous qualitative levels (negative = 0 and positive = 1) with the variable independent (zootechnical management A = 0 and B = 1), also the dichotomous level for each category evaluated, at a 5% level of significance. Final logistic regression model was analyzed by the likelihood ratio. As null hypothesis, the livestock management does not influence the Cryptosporidium sp. positivity rate in calves. This analysis was performed using the R statistical software package [27].
The Phi (Ø) correlation coefficient was used to assess the relationship between the positivity of animals by Cryptosporidium sp. (negative = 0 and positive = 1) and occurrence of diarrhea in calves (yes = 1 and no = 0), also with the 5% significance level. In this analysis, the null hypothesis is that there is no correlation between the occurrence of diarrhea and infection by Cryptosporidium sp. in dairy calves. It was used for this analysis the statistical program Bio Estat 5.0 [28].
Results
A total of 79 Holstein crossbred calves were evaluated in the present study. During the first fecal material collection period (Management A), 32 calves were evaluated. After performing the suggested modifications, a second fecal material collection (Management B) was performed to evaluate another 47 animals.
The 79 calves from the dairy farm where the study was conducted were evaluated for the presence and absence of diarrhea and accessed via microscopic and molecular techniques for Cryptosporidium spp. infection. A clinical evaluation revealed the presence of diarrhea in 13.9% (11/79) of the calves; however, microscopy revealed that only 2.5% (2/79) of these animals were infected with Cryptosporidium spp. (Table 1). In addition to Cryptosporidium spp., other diarrhea-inducing gastrointestinal protozoa were observed in the fecal parasite tests, including Eimeria spp. and Giardia intestinalis. Eimeria spp. was more frequently present in both animals with feces of normal consistency and those with diarrhea (Table 2). Using microscopy with and without phase-contrast, Cryptosporidium spp. infections were diagnosed in 13.9% (11/79) of the studied calves studied; of these, 21.9% (7/32) belonged to the group under Management A, and 8.5% (4/47) belonged to the group under Management B (Table 1). Yes No + / -Negative --- ---*Data adapted from Couto et al. [21]. Subsequently, all microscopically determined Cryptosporidium spp. positive samples were subjected to diagnostic confirmation via nested-PCR for 18S gene amplification. Among the studied calves, 81.8% (9/11) of the positive microscopic diagnosis were confirmed by nested-PCR; 45.5% (5/11) were from the group under Management A, and 36.4% (4/11) were from the group under Management B (Table 1).
All nine 18S gene PCR-positive samples were sequenced to yield good quality products, thus allowing the identification of three distinct Cryptosporidium species, one of which was C. parvum, a species with high zoonotic potential (Table 1).
After sequencing the samples according to the 18S target gene, all nine Cryptosporidium sp.-positive samples were subjected to GP60 gene amplification for the identification of C. parvum and related subtypes. Of these samples, 44.4% (4/9) exhibited gene amplification, indicating the presence of C. parvum (Table 1).
After sequencing, however, overlapping peaks were observed in the chromatograms; these were most likely due to the presence of multiple sequences amplified within the same sample, thus preventing the reliable identification of C. parvum subtypes. Therefore, DNA fragment individualization was performed via cloning. Subsequently, several colonies were obtained from each sample, of which three were randomly selected for further sequencing with universal primers. A total of 12 sequences were obtained, and of these, all but one sample contained the C. parvum subtype involved in the calves' infections (Table 1).
In this study, 21.9% (7/32) of the calves raised under Management A were infected with at least one Cryptosporidium spp. After changing to Management B, this percentage decreased, and the infection rate was only 8.5% (4/47). After analyze of simple logistic regression, no significant difference (p = 0.10) was detected between the two management types used at the farm with regard to Cryptosporidium spp. infection. Similarly, the OR indicated that although animals raised under Management A were threefold more likely to harbor a Cryptosporidium spp. infection, the confidence interval (CI) showed no relationship between these study variable (CI: 0.80-11.30; Table 3). Similarly, no statistical correlation was observed between Cryptosporidium spp. positivity and the presence of diarrhea in the calves (p = 0.97; Phi coefficient = 0.04). The percentage of Cryptosporidium spp.-positive animals with diarrhea was 18.2% (2/11), which was slightly higher than the percentage in calves without diarrhea (13.2%; 9/68).
Discussion
The difference between the results obtained in the present study, using microscopic and molecular diagnostic techniques remains a controversial subject within the scientific community. Some researchers have reported the high sensitivity of PCRmediated oocyst detection [15,29], whereas others have reported better results when using microscopy [9]. Several hypotheses have been considered to explain the results of the present study. Among the major hipothesis, we can cite the low parasite loads present in some samples, the non-homogeneous oocyst distribution in the fecal material and the presence of inhibitors that might have led to underestimations of the PCR results. Regarding the low parasite loads, some authors [9] mentioned that a low oocyst recovery from fecal material could yield a low percentage of positive results when using molecular techniques.
In addition to the issue of low numbers of oocysts and the PCR-mediated detection of Cryptosporidium spp., is supposed that the heterogeneous oocyst distribution in the feces might occasionally yield false-negative results [30]. These authors also suggested that a large numbers of oocysts observed via microscopy would not guarantee diagnostic confirmation by PCR because the oocysts would have been damaged before and during the extraction process, possibly leading to reduced numbers of the available DNA targets required for PCR and thereby reducing its effectiveness. Another explanation might be the presence of high concentrations of inhibitory substances in the calves' fecal material, which would limit the molecular diagnostic efficiency [31]. Although the present study did not focus on a comparison of the diagnostic techniques, the previous authors suggested that one technique would complement the other.
The 18S and GP60 gene-based molecular diagnoses facilitated the identification of different C. parvum subtypes belonging to the IIa subtype family. In Brazil, studies on human and animal infections with different C. parvum subtypes are scarce. In a study performed in the state of São Paulo, Brazil, [32] the presence of a zoonotic C. parvum subtype (IIaA15G2R1) was diagnosed in capybaras. In another study conducted in several municipalities in the state of São Paulo [33], the zoonotic subtype IIaA15G2R1 was diagnosed in cattle, unlike the results obtained in the present study.
To date, there have been no reports in South America of human infections resulting from members of the subtype IIa family, which are commonly found in cattle. However, a study in Peru reported that children were infected only by the C. parvum subtype IIc family, diagnosing the subtypes IIcA5G3a, IIcA5G3b and IIcA5G3c [34].
On dairy farms, disease associated with C. parvum infection occurs primarily in young calves [35], being reportedly as one of the major species that causes diarrhea, a clinical symptom characteristic of cryptosporidiosis [5,36,37]. In the present study, C. parvum was the only diagnosed infectious Cryptosporidium spp. in calves with diarrhea, a finding that agreed with those of the above-cited authors. However, diarrhea was also observed in Cryptosporidium spp.-negative animals, suggesting that this symptom might be consequent to infections by other gastrointestinal etiologic agents, including Eimeria spp. and Giardia intestinalis [8,38]. Regarding the present study, we also suggest the possibility of false-negative parasitological tests, especially in animals with diarrheal feces because these animals might have eliminated the infective form of the protozoa at a low parasitic load or intermittently, a finding that has also been reported in other research [8].
Concomitant Cryptosporidium spp. and Eimeria spp. infections were only observed in fecal samples of normal consistency, in contrast with the findings of other researchers, who observed a higher co-infection incidence in diarrheic fecal samples. The authors of the current study agree with the hypothesis suggested in a previous research [8], in which the calves likely experienced diarrhea during a period prior to sample collection, after which oocyst shedding of both parasites continued through the collection date regardless of the fecal consistency.
The importance of reducing the exposure of calves to Cryptosporidium genus protozoa, particularly C. parvum, has been described before [39], who highlighted the cattle rearing area sanitation level and infected animal management and care as relevant factors associated with infection. The significance of adequate management practices in dairy farms was also described as potentially important predictors of the prevalence of shedding C. parvum oocysts in dairy calves under 1-month of age [35].
In this study, management practices that were adopted at the farm, particularly the calves' housing location, were evaluated, and a reduction in the percentage of infected animals was observed after some of the management practices were changed along with a change in the rearing pen from location A to location B.
The Cryptosporidium spp. infection percentage (21.9%) observed in the calves is related to the poor sanitation encountered during the use of Management A. These poor conditions included the permanent presence of feces in the pens, which might have favored infection dissemination along with the high environmental humidity. Although not shown the statistical interaction between the type of animal management and Cryptosporidium sp. positivity (P ≥ 0.05), the number of infected animals was twofold higher under Management A. However, for the data analyzed, if the strength of association is reduced for 90% of significance, was observed that animals raised under the condition of Management A were the most affected by this infection. Therefore, it is possible that with a larger sample number, the influence of the management type on the positivity can be better highlighted. It is therefore possible that after transferring the animals to another location (Management B), the observed reduction in the infection incidence (8.5%) might have been related to the reduced environmental humidity and the use of individual pens. These changes might have facilitated a reduction in the percentage of infected calves by minimizing contact between the animals and, consequently, the possible transmission between the animals.
Changes in the placement of the feeders and drinkers within the new facility (Management B) might also have helped to reduce the percentage of infected animals. The feeders and drinkers were placed relatively higher than their locations under Management A, a practice that most likely reduced the likelihood of fecal water and food contamination and, consequently, infection.
The absence of correlation between the occurrence of diarrhea and positivity for Cryptosporidium sp. can be related to other factors inherent to the animals such as the presence of other gastrointestinal parasites and/or concomitant infections.
The incidence of Cryptosporidium spp. infection in dairy cattle was also studied before [40]. The authors of that study evaluated several factors associated with infections in calves, where one of the most relevant was the property management and the use of shared facilities.
During the use of Management A, the feces from calves housed in collective pens were directly discarded into the river that passed through the property. This management practice can lead to several problems, including environmental contamination and the occurrence of possible cryptosporidiosis outbreaks in other areas. A similar situation was observed in Malaysia [2], where the authors described the contamination of rivers near farms due to inadequate cattle manure management practices.
Depending on the animals' parasite loads and the species/ subtypes, disease outbreaks can even occur in humans. This outcome was suggested by the presence of the C. parvum subtype (IIa) family, which has high zoonotic potential, in the Studied farm.
Despite changes in the management practices on the farm, the environmental contamination issue was not resolved. This is because under Management B, the feces from the individual pens were also carried by rainwater to the river that passed through the property, thus maintaining Cryptosporidium oocyst dissemination and continuing to facilitate the potential problem described above. The importance of environmental contamination from the organic waste produced on farms has been reported before in other studies [41,42], and these earlier findings agreed with those described in this study. Although there was a reduction in the percentage of Cryptosporidium spp.-infected calves, further studies are required to demonstrate whether simple changes in the management practices of a particular property could help to reduce the incidence of cryptosporidiosis in dairy cattle. | v3-fos |
2019-03-30T13:04:16.835Z | {
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} | s2 | Prevalence and Intensity of Economically Important Fungal Diseases of Sorghum in South Tigray, Ethiopia
Production and productivity of sorghum is highly threatened by different diseases in South Tigray, Ethiopia. However, the importance of each disease has not been assessed and well profiled to sound management strategy. To determine the occurrence and intensity of diseases survey was carried out in two major sorghum growing districts of South Tigray in 2014 cropping season. Results indicated that 93.7%, 84.8%, 88.6%, 37% and 58% of sorghum fields were infected by anthracnose, leaf blight, long smut, head and loose smuts, and downy mildew, respectively. This indicated that sorghum is suffered from complexes of diseases. The incidence and severity of the former diseases were 69.9% and 53.01%, 55.9% and 38.7%, 23% and 77.2%, 1.9% and 71.7%, and 43.6% and 41%, respectively. Most of the cultivated farmers’ cultivars sown were susceptible at least to one disease putting large area of sorghum production at threat. Therefore, holistic and cumulative integrated approach is required to manage the complex diseases in the surveyed areas.
Introduction
Sorghum (Sorghum bicolar L. Moench) is one of the most important cereal crops supporting the lives of millions of people across the globe and particularly in the developing world. Sorghum is known for withstanding harsh environmental conditions including high temperature, moisture deficit and water stagnation [22]. The most important sorghum producers are the United State, Nigeria, India, Sudan, Ethiopia, Burkina Faso, China, Tanzania and Niger [8]. In Ethiopia, sorghum is among the leading cereal crops contributing a major role in achieving food security. It covers an area of over 1.7 million ha with annual production of more than 3.6 million tones. Sorghum stands first both in area coverage and production in Tigray region with annual coverage and production of about 208, 390 ha and over 0.5 million tone, respectively. The national and regional productivity of the crop is not more than 2.2 t/ha and 2.5 t/ha, respectively [4]. Grain sorghum yields are especially low in Eastern Africa countries as compared to yields in the United States (4.4 t/ha) and well below the genetic potential [19].
Sorghum production in the world including Ethiopia is affected by different biotic and abiotic constraints. Of the biotic stresses, diseases caused by different fungal pathogens play significant role in curtailing its production. The major diseases that affect sorghum include Turcicum leaf blight, (Exserohilum turcicum), downy mildew (Peronoscleropora sorghi), anthracnose (Colletotrichium sublineolum Henn.) [6] and sorghum smuts (covered kernel smut (Sporisorium sorghi Ehrenberg (Link), loose smut (Sphacelotheca cruenta (Kuhn), and long smuts (Tolyposporium entrenbargii (Kuhn)) [19]. In Ethiopia, anthracnose, smuts, grain mold, downy mildew, charcoal rot and few others are important diseases, which are now considered as one of the most destructive diseases of sorghum in most the major growing regions of the country [3,7]. These diseases affects at different parts and stages of the crop that significantly reduce its productivity.
Assessment of the incidence and severity of plant diseases is important to determine the geographic distribution and status of the disease throughout a region in order to prioritize research responsive to the situation. To get an accurate picture on the status of any disease, such studies, should give due consideration to the impact of geophysical and associated climatic and edaphic variations between regions. However, most of the studies do not provide quantitative measurement in terms of disease severity in Tigray. On the other hand, such information is of paramount importance as it can be related to yield loss and hence economic impact of the disease [12,19]. Therefore, the objective of this survey was to determine the geographic distribution, incidence and severity of sorghum diseases in the major growing districts of South Tigray, Ethiopia.
Area Description
Tigray forms the northernmost reaches of Ethiopia and is located between 36 o and 40 o east longitude and 12.15 o and 14 o 57'north latitude. The region has six administrative zones, of which, South zone is among the major sorghum producing areas of the region [4]. The survey program covered the most important sorghum growing districts of Raya valley (Raya-Alamata and Raya-Azebo) in South Tigray ( Figure 1). It is bordered by Hintalo Wajerat district to the north, Afar Region State to the east, Enda-Mekoni and Ofla district to the west and Amhara Region State to the south [20].
Disease Assessment
The survey was carried out in 2014 main cropping season in South Tigray. It was made following the main roads and accessible routes in each survey district, and in each available sorghum field, stops were made at 5 km intervals based on vehicle odometers. A total of 15 peasant associations were assessed in both districts. At least three samples were assessed at each stop within the field depending on the farm size. During the survey, the sorghum crop was between early dough and hard dough stage in most of the fields, although there were some fields with sorghum at maturity stage. For each disease incidences were assessed as the percentage of sorghum plants in a field showing visible symptoms out of 20 randomly selected plants. Furthermore, the severities were Sorghum in South Tigray, Ethiopia determined as average leaf area covered by symptoms for 5-10 randomly selected diseased plants per stop/sample for foliar diseases and head damage for smuts. For foliar diseases, severity was assessed on a 1 to 9 scale where 1 = no disease, 2 = disease affecting 1 to 4% area of top 5 leaves, 3 = 5 to 9%, 4 = 10 to 19%, 5 = 20 to 29%, 6 = 30 to 44%, 7 = 45 to 59%, 8 = 60 to 75%, and 9 = >75% of leaf area affected [19]. In addition, smuts severities were scored considering the average of all plants using modified severity rating scale as used by [10] as follows: 1, no infected florets; 2, < 10% infected florets; 3, 11-20% infected florets, 4, 21-29% infected florets; 5, 30-14% infected florets; 6, 42-52% infected florets; 7, 53-63% , infected florets; 8, 64-74% infected florets; and 9, > 75% infected florets.
The Prevalence, Incidence and Severity of Sorghum Diseases
Subsistence farmers grew most of the sorghum surveyed under low-input cropping systems with long maturing local cultivars (6-8 months). Most of the sorghum planted fields surveyed were ranged from 0.25 to 0.5 ha depending on the land holding of each farmer. Conditions of the sorghum fields varied from well maintained to very poorly maintained farms. During the assessment farmers were able to identify smuts in general without naming the types (such as head smut, loose, long) but for the remaining foliar diseases they named as diseases without recognizing the specific names. Some farmers were mistakenly associated severe leaf disease symptoms with natural signs of crop maturity as well as winds. This study provides the quantitative report on the prevalence and intensity of sorghum diseases in South Tigray, Ethiopia. Accordingly, three leaf diseases; anthracnose, leaf blight and downy mildew and three smuts (covered head smut, long smut and loose smut) were the dominant diseases both in distribution and intensities (Table 1). In addition, rust was found at low frequency in Raya-Azebo district. This indicated that the seriousness of the damage caused by the fungal pathogens where sorghum is grown. Among which, sorghum anthracnose was epiphytotically appeared in all the survey routes putting a considerable sorghum production areas at jeopardy. The overall prevalence of anthracnose was 93.7%. Of which, about 68.1% of the fields were sustained maximum possible prevalence (100%) of the disease ( Table 1). The prevalence of the remaining few fields varied from 75% to 84.6%. This indicated the disease was among the destructive diseases during the season. Similarly, the incidence of anthracnose was reached maximum in most sorghum fields. All peasant associations exhibited 100% incidence in their many fields. The mean incidence of anthracnose was 100% in 27 fields of the seven peasant associations in both districts. The mean incidence of the disease was between 10% and 84.6% for eight peasant associations. The seriousness of anthracnose was explained by the damage (severity) exhibited on the plant. The peak severity (100%) of the disease was registered at eight peasant associations. Similarly, two peasant associations (Selambakalsi and Hadiskigni) exhibited maximum possible mean severity (100%). The mean severity of the anthracnose disease for the remaining peasant associations varied from 10% to 95%. Generally, the overall severity of the disease was 53.01% (Table 1). As a result, farmers are frustrated by the nature and epidemics of the disease during the season. Previous studies revealed that this disease was listed among the leading diseases causing significant yield loss in different sorghum growing areas in Ethiopia [3, 5, and 7]. Chala et al., [5] reported that anthracnose had moderate to severe epidemics in the major sorghum growing areas of Ethiopia. Similarly, the results of this study confirmed the observations of [9], who listed these diseases as constraints to sorghum production in east African countries including Ethiopia. Furthermore, association of severe sorghum anthracnose infection with low and intermediate altitude areas is most probably attributed to the prevailing weather conditions as most areas with intermediate to high temperature. According to Ali and Warren, [2], Thomas,[26], and Hess et al., [11], more intense sorghum anthracnose is associated with high temperature and relative humidity. During the growing season, the occurrence of unseasonal rainfall during the flowering and dough stage coupled with high to moderate temperature (10-27 o C) encouraged the development of the disease. In addition, the high variability of the pathogen populations made most sorghum fields without tolerance [27].
The leaf blight was among the widely distributed and important diseases during the survey season. It was epidemically observed. The distribution of leaf blight was higher in almost all sorghum growing areas of the Raya-Alamata and Raya-Azebo districts. About 54 fields within eight peasant associations sustained 100% of prevalence in both districts (Table 1). Raya-Alamata district was highly affected by leaf blight compared to Raya-Azebo district. All peasant associations were affected by the disease except Hawelti which was nonexistent. Ten out of 15 peasant associations sustained 100% diseases incidence. Similarly, the severity of leaf blight was significant in considerable locations during season. The mean severity of leaf blight was 100% in seven peasant associations. Likewise, the severity of the disease was higher on number of fields. The mean incidence ranged from 5% in Fachagama as high as 100% in Selambikalsi peasant associations. The favorable environmental conditions coupled with cultivation of susceptible sorghum cultivars worsened the problem to maximum. Disease epidemics are favoured by high rainfall and relative humidity, moderate temperatures, and the presence of large amounts of inoculums. In addition, the high intensity of the disease could be due to the availability of different races or pathogen population for leaf blight [14,23]. This study is in line with previous result that leaf blight was among the important diseases in all sorghum growing environments of the country [5]. Generally, the prevalence and intensity of most of the foliar diseases was high in Raya -Alamata compared to Raya-Azebo district. The most possible reason could be due to the disparity in environmental condition, production systems and practices and the variety grown. Sorghum suffers a lot from smuts during the assessment. Three distinct smut diseases of sorghum were recognized during the survey. They were the covered head smut induced by the fungus Sporisorium sorghi, loose smut induced by Sporisorium holci-sorghi and long smut attributed to the fungus described as Tolyposporium ehrenbergii. Among which, long smut was the most commonly occurring and important disease during the survey. It was observed 14 peasant associations except at Gerjelle ( Table 2). The prevalence of the disease was reached 100% in 12 peasant associations. This indicated that the disease was present where sorghum is grown. Similar reports indicated that smuts especially, loose, head smut and long smut was the challenging biotic factors to sorghum production in many parts of Ethiopia [17]. This is because of the occurrence of favorable environment (which usually have intermediate to high temperature and erratic rain fall pattern) responsible for the rapid development of disease. The incidence of long smut was ranged from 5% in most fields to 100% in two peasant associations. Similarly, the mean incidence of most fields was below 15%. The severity of smuts were exhibited by the infection head or panicle caused up to complete crop failure. As a result, most of fields sustained 100% severity ( Table 2). The other smuts group attacking sorghum were covered and loose smuts, but at low prevalence as compared to long smut. The prevalence of covered and loose smuts together was reached 100% in two peasant associations ( Table 2). The incidence of covered kernel smut varies from place to place but in Ethiopia, it was estimated to be about 50% [16,25]. According to Sisay et al., [21] for higher covered smut incidence, optimum temperature of 25°C and half moistened soil during planting are more important than other factors. Smuts are among the damaging diseases of sorghum in Ethiopia [17, 24 and 25]. The use of local cultivars with lower quality might be aggravated the epidemiology of smut. In addition, prevailing weather is another important factor that influences the incidence and severity of plant diseases [13]. Moreover, the movement of spores was facilitated by Sorghum in South Tigray, Ethiopia wind within the farm. In addition to yield reduction, it also adversely affected the quality of grains, when the black masses of chlamydospores contaminated the grain at the time of harvesting and threshing.
Sorghum downy mildew was among the widely occurred fungal diseases in all survey routs in 2014 main cropping season. It was observed in 10 fields out of 15 peasant associations. It was among the commonly observed of the leaf disease, being observed in 66.7% of fields. The incidence of the disease within fields was generally high, with a majority of fields having an incidence range of 10% to 100%. A considerable sorghum fields were severely attacked by downy mildew with maximum possible severity of 100%. Similarly, the mean severity of downy mildew ranged from lowest (2.5%) at Genete as high as 80% in two peasant association (Tao and Hadiskigni) ( Table 2). This study is in line with previous result that downy mildew was among the important diseases in all sorghum growing environments of the country [5]. Generally, the prevalence and intensity of most of the foliar diseases was high in Raya -Alamata compared to Raya-Azebo district due to the environmental condition divergence. In contrast, 27 fields were free from downy mildew due to variability in climatic condition, management practices, and unavailability of initial inoclum.
The Response of Sorghum Cultivars
The infection level of host plants varied depending on the susceptibility level of each cultivar, the management practiced and the environmental conditions in a specific environment. Local cultivars were the most commonly grown in the study area. Farmers preferred local cultivars due to the fact that higher yield and long stalk for their house construction and feed value [15]. However, these cultivars are long maturing up to eight months difficult to grow under low and erratic rainfall condition. About 94.9% of the cultivated area was covered by the local medium to long maturing cultivars. The remaining few varieties was present on demonstrations basis at research sites and farmer training centers at lower frequency. Generally the local cultivars were found susceptible to most diseases occurred during the season. As a result, most sorghum fields were leaved without harvesting. The prevalence of anthracnose, leaf blight, downy mildew and smuts on local cultivars ranged from 97.1%-100%, 73.9%-100%, 26.1%-93.8% and 75%-100%, respectively. Similarly, the incidences of these diseases were higher on local cultivars ( Table 3). The mean severities for the foliar diseases were varied from 10-67.5%, 73.9-100%, and 33%-60%, respectively. The cultivar Degalit was the longest maturing (8 months) [15] and found susceptible to most identified diseases. This was followed by the relatively short maturing cultivar Abo-Ere (6 months) with relative susceptible. The medium maturing cultivars such as Kodem and Jamuye were susceptible to most diseases but with less intensity than Abo-Ere and Degalit. The higher epidemics or epiphytotic of anthracnose was uncommon despite the frequent occurrence from lowered to moderate infection leaves. Farmers growing the local cultivars were frustrated by the unusual epidemics of anthracnose, leaf blight and downy mildew makes wiped-out sorghum fields without tolerance during the year. In addition, the mono-cropping systems in the area could be contributed to disease pressure in positive or negative ways [1]. The early maturing improved varieties (3-4 months) [18] were found susceptible to leaf blight and downy mildew exhibited mostly 100% prevalence and incidence. Most of the local cultivars and one improved variety were found susceptible to smuts. This study revealed that almost all farmers preferred their own local cultivars for many reasons such as high yielding (> 6 t/ha), having long stalk used to feed for livestock and used for construction of different houses as well as fences. However, these local cultivars are long maturing (6-8 months) [15] and susceptible to most diseases. Therefore, introduction of high yielding improved varieties with acceptable disease resistance from international and national nurseries and awareness creation for farmers to protect against these diseases is of a great concern. In general, anthracnose, leaf blight, downy mildew and smuts (long, covered head and loose) were among the destructive diseases during 2014 cropping season in both districts. The occurrence and the infection of more than one disease for a single plant exacerbated the yield diminution to maximum and wiped-out sorghum local cultivars without tolerance. Therefore, producers can have an impact on the severity of these diseases by choosing from a number of management strategies including host plant resistance, cultural practices (adjusting planting date, use of disease free seeds, rotation) and judicious use of fungicides [1]. However, using genetically resistant wheat varieties is panacea, the ultimate universal answer, cost effective and environmentfriendly mode of protection [1]. Furthermore, the use of gene pyramiding in variety development has paramount importance for such diseases for a broad resistance along with periodic disease monitoring and surveillances responsive for the pathogen variation or races. It is also very important to use integrated management tactics and risk forecasting that operate on different aspects of the disease etiology, such that they complement each other and can be applied together in farmers' fields collectively to provide farmers with maximum economic return.
Conclusion
Sorghum production is suffered from different fungal diseases mainly anthracnose, leaf blight, downy mildew and smuts. The combination effect of these complex diseases caused up to complete annihilation of the crop. The long and medium maturing local cultivars were found susceptible compared to the early maturing improved varieties. Therefore, development of integrated diseases management strategies needs due emphasis for sustainable sorghum production. | v3-fos |
2019-04-06T13:10:23.181Z | {
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} | s2 | Nitrogen addition and mowing affect microbial nitrogen transformations in a C4 grassland in northern China
C . W a n g a,b, K . B u t t e r b a c hB a h l b,c, N . H e d, Q . W a n g a, X . X i n g a & X . H a n a,e aState Key Laboratory of Vegetation and Environmental Change, Institute of Botany, The Chinese Academy of Sciences, Xiangshan Nanxincun. 20, Beijing 100093, China, bInstitute for Meteorology and Climate Research, Atmospheric Environmental Research, Kreuzeckbahnstr.19, Garmisch-Partenkirchen 82467, Germany, cInternational Livestock Research Institute, Old Naivasha Rd. P.O. Box 30709, Nairobi, Kenya, dKey Laboratory of Ecosystem Net Work Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Datun Road Jia 11, Beijing China, and eInstitute of Applied Ecology, Chinese Academy of Sciences, Wenhua Road 72, Shenyang 110016, China
Introduction
During the last century, accelerating industrialization and agricultural activity increased nitrogen (N) deposition dramatically in most parts of the world (Galloway et al., 2008). In northern China, rates of atmospheric N deposition are likely to increase by 2-5 g m −2 year −1 above pre-industrial rates by 2050 (Galloway et al., 2004). For the terrestrial biosphere, the enrichment of N by direct fertilizer application and atmospheric N deposition has been shown to increase plant growth, net primary productivity and biomass accumulation at a global scale (Elser et al., 2007;LeBauer & Treseder, 2008;Xia & Wan, 2008) and to increase the mobility of N (Vitousek et al., 1997). It may also alter the rates and the pathways of soil-plant N cycling and associated hydrological and gaseous losses (Aber et al., 1989). Correspondence The extent to which increased N inputs will drive changes in plant productivity and species composition over the next century will, however, depend on N retention in ecosystems (Zavaleta et al., 2003). Nitrogen retention and reduction of N losses may also be linked to N fertilizer addition, because this increases plant productivity and extends the time over which roots remain active. However, the addition of inorganic N can also inhibit the decomposition of soil organic matter because inorganic N is incorporated into recalcitrant compounds that are formed during lignin degradation (Berg & Matzner, 1997). On the other hand, mowing accelerates the N cycle (Güsewell et al., 2005) and promotes increased above-and below-ground plant growth and root exudation (Leriche et al., 2001) and this may increase the risk of N losses. Other effects of hay harvesting or mowing are linked to changes in the above-ground community structure (Knapp et al., 2002), which, in turn, affect N uptake patterns by the vegetation. Above-ground biomass removal can also reduce C inputs to the soil significantly, resulting in substrate limitation to microbes (Wan & Luo, 2003). Biomass removal may therefore mask the N fertilizer effects on soil microbial properties. In addition, reduced vegetation cover after hay harvesting or mowing may change the soil boundary layer near the surface, increase the energy absorbed and emitted by the soil, and amplify the diurnal soil temperature range. Finally, plant removal can increase evaporation while decreasing transpiration, resulting in an unpredictable net effect on soil moisture. Therefore, N fertilizer addition and changes in land management may interactively affect soil microbes under future climatic conditions. Agricultural restructuring and conservation priorities have led to the abandonment of farmland in China and elsewhere. Thus, during the last decade, restoration of croplands to grasslands has been observed across grassland systems of Inner Mongolia in northern China, with grasslands or steppe representing the typical climax vegetation type in this arid and semi-arid environment (Christensen et al., 2004). Mowing of grassland is an important management practice in the area. Nitrogen availability and microbial N transformation processes are key characteristics for the evaluation of this management practice because they greatly affect steppe productivity. However, few studies have evaluated their relative importance and interaction in old fields in China.
This paper complements our previous work at the same experimental site (Wang et al., 2011), which addressed questions on nutrient availability and clipping for three different plant communities (grass, grass-herb and herb dominated) separately. In contrast, the current study is a 4-year study, focusing on grass dominated patches. The specific objectives of this study were to evaluate the individual and combined effects of mowing and N addition on (i) in situ net N mineralization and (ii) microbial biomass and activities. Because annual rainfall as well as that occurring during the growth period is highly variable we also hypothesized that (iii) effects of mowing and N fertilization are more pronounced in years with greater annual precipitation than in dry years.
Site description
The experimental site is located in Dunlun county (42 ∘ 27 ′ N and 116 ∘ 40 ′ E), a semi-arid area in Inner Mongolia, north China. The mean annual precipitation in this region is 382.2 mm. The average annual temperature is 2.1 ∘ C, with monthly mean temperatures ranging from −17.6 ∘ C in January to 19.0 ∘ C in July, according to a long-term observation period at Duolun Restoration Ecology Experimentation and Demonstration Station (Wang et al., 2011). The soil at the sites is a chestnut soil (Chinese classification; Wang et al., 2011) or Calcic Luvisol (FAO;IUSS, 2007). Soil and plant characteristics were measured before start of the experiment in August of 2005 and reported by Wang et al. (2011). In the study area, large parts of the natural steppe were converted to cropland in the 1960s. As a restoration measure, about 80% cropland was abandoned in 1995 and either remained without any further management or has been used for hay production or grazing.
Experimental design
Twenty-four 4 × 4 m 2 plots were established in 2005. Four different treatments organized in a randomized block design were investigated: (i) control, (ii) addition of N fertilizer, (iii) mowing of above-ground biomass and (iv) a combination of mowing and N fertilizer addition. Mowing was carried out at the end of August in 2006August in , 2007August in , 2008August in and 2009, and removed all above-ground biomass above 3 cm. Fertilizer as NH 4 NO 3 was added before the rains in mid-July of 2006-2009 at a rate of 10 g N m −2 to the fertilizer treatments. Our previous paper reported the data from the growing season (from May to October) in 2008 (Wang et al., 2011).
The top (0-10 cm) layer of mineral soil was sampled from all 24 plots in June, July and August to determine net N mineralization, nitrification and ammonification rates for each year. Potential microbial biomass carbon (MBC) and N (MBN), as well as microbial respiration (MR), were measured once a year only in the middle of August (see later) when the most vigorous microbial activity occurred in this area (Liu et al., 2009). Soil temperature and soil moisture were measured at a depth of 10 cm (Wang et al., 2011).
Sampling and measurements
The buried soil core technique was used to measure in situ net N turnover during the growing season for each year. The detailed techniques were described by Wang et al. (2011). Above-and below-ground biomass was measured before the mowing treatment each year. Two 2 × 0.5 m 2 subplots in each plot were clipped at the soil surface to measure above-ground biomass in the middle of August during 2006-2009. After the harvest, two soil cores with a diameter of 6.5 cm at 0-15-cm depth were sampled in each plot to determine root biomass. Root samples were placed in a cooler and transported to the laboratory. In the laboratory, the cores were soaked in deionized water and residual soil was washed from roots over 0.5-mm sieve. Plant and root materials were oven-dried at 65 ∘ C for 48 hour and weighed. Inorganic N was determined in each sieved soil sample after extraction of 10 g dry soil with 50 ml 2 mol l −1 KCl solution (see Wang et al., 2011 for details). The process and methods of potential microbial biomass and respiration measurements were as described by Wang et al. (2011) and Vance et al. (1987). All results were expressed on an oven-dried soil basis (105 ∘ C, 24 hour). Soil organic carbon (C) was measured with the potassium dichromate-vitriol oxidation method and soil total N was measured by Kjeldahl digestion (Cabrera & Beare, 1993).
Statistical analysis
The seasonal mean values used in this study were calculated from the monthly mean values, which were first averaged from all measurements in the same month. A three-way anova was used to examine the effects of year, mowing, N addition and their possible interactions, on microbial N transformation, biomass and respiration. If a significant inter-annual variability was demonstrated (year effect P < 0.05), repeated measures anova (rmanova) was used to examine the mowing and N addition effects on microbial N transformation for each growing season for each year (Tables 2, 3). After observing that the interaction between the data and treatment was significant, the effect of the treatment was tested separately. The responses of soil properties (microbial N turnover, microbial biomass and inorganic N content) to mowing or N addition or a combination of both were tested with a two-way anova. All the data were statistically analysed with SAS V.8.1 (SAS Institute Inc., Cary, NC, USA).
Effects of mowing and N addition on soil temperature and moisture
Probably because of limited measurement of soil temperature and soil moisture over time, significant effects of mowing and N fertilization were only observed at some measuring times. There was a trend for mowing to increase soil temperature at 10-cm depth by 0.8 ∘ C ( and 2009, resulting in marked effects on annual average soil moisture contents; this was most pronounced in the N addition plots (P < 0.05). Soil temperature also varied markedly across the 4 years (P < 0.001); this was most pronounced for the mown plots (P < 0.001).
Soil and plant characteristics
Mowing and N addition + mowing significantly increased soil total organic C content by 39 and 50%, respectively, after 4 years ( Table 1; P < 0.05). However, there were no significant effects found in total N content among the mowing, N addition and mowing + N addition treatments (Table 1; P > 0.05). Increased total soil organic carbon therefore resulted in the C:N ratio increasing significantly after mowing (Table 1; P < 0.05). Nitrogen addition decreased pH values significantly by about 0.6 units (P < 0.05), but increased above-ground net primary production (ANPP, P < 0.001) and below-ground net primary production (BNPP, P < 0.01) to around 90 and 400 g m −1 , respectively. N addition + mowing significantly increased ANPP (P < 0.05) but no effects were found for BNPP (Table 1; P > 0.05).
Above-ground biomass (including standing litter)
Nitrogen addition increased ANPP (314 ± 25 g m −2 ) significantly by 48%, but there was not an effect of mowing on ANPP in either the non-fertilized or fertilized plots over the 4 years (Table 1, Figure 2a; P < 0.01). Nitrogen addition had no effect on standing litter biomass, while mowing and N + mowing significantly reduced standing litter over the 4 years (2006)(2007)(2008)(2009) (Figure 2b; P < 0.01). Nitrogen addition significantly increased the total above-ground biomass (ANPP + standing litter, 685 ± 56 g m −2 ) by 46.3% only in 2008, which was the second wettest growing season after 2006 (Figure 2c; P < 0.05). In the other 3 years, N addition had no effects on total above-ground biomass (P > 0.05), but significantly increased ANPP in 2006, 2008 and 2009 (P < 0.01). Mowing significantly reduced total above-ground biomass by 65.8 and 75.9% in 2007 and 2008, respectively (P < 0.05). In particular, ANPP was significantly larger in 2008 after N addition treatment than in the other 3 years (P > 0.05). However, mowing had no effects on ANPP in rainy (2006 and 2008) or drought (2007) years (P > 0.05).
Soil ammonification, nitrification and net N mineralization rates
There was strong intra-and inter-annual variability in net N transformation (ammonification rate, nitrification rate and net N mineralization rate), which could be inferred from the significant time (rmanova) and year effects (three-way anova; Table 2, Figure 3) that we recorded. However, significant differences among treatments with regard to ammonification, nitrification and net N mineralization were found only in 2006 and 2008 (Figure 3; P > 0.05) and the mowing + N addition and N addition treatments for ammonification rate in 2007.
Over the entire observation period of 4 years, mowing increased the nitrification rate significantly by 106% (P < 0.001). Also, N addition stimulated rates of nitrification and net N mineralization by 286% (P < 0.001) and 149% (P < 0.01), respectively ( Table 2). The mowing and N addition interaction affected the ammonification and net N mineralization rates (P < 0.05). The year × mowing and year × N addition had interactive effects on the nitrification (P < 0.001) and net N mineralization rates (P < 0.01). There were also three-way interactive effects (year × mowing × N addition) on the ammonification and net N mineralization rates (P < 0.01).
Soil microbial biomass and respiration
In 3 of the 4 years no significant differences in MBC were found among the four treatments (Figure 4; P > 0.05). Only in 2006 (the first year of N fertilizer addition and also the year with the largest precipitation rate during the growth period) mowing + N addition decreased MBC significantly by 21% (P < 0.01). Fertilizer N tended to increase MBN, specifically in the non-mowed plot, with differences being mostly significant at P < 0.05. However, a significant (P < 0.05) reduction in the MBC:MBN ratio was found only in the first year of N fertilizer application (2006) (Figure 4).
Mowing + N addition reduced microbial respiration (MR) significantly in 3 of the 4 years (range 43.8-89.9%), but not in the driest year (2009). In the first treatment year (2006) mowing decreased MR by 93.6% (P < 0.01) and qCO 2 by 85.7% ( Figure 5, P < 0.01), but in the following years these effects diminished.
Driven by the large variability amounts of rainfall in the growing period across the year, substantial inter-annual variability in all of the microbial variables (Table 3, P < 0.001) was observed. When averaged across the 4 years, N addition significantly decreased MBC by 12% (P < 0.05) and increased MBN by 12% (P < 0.05). Mowing marginally decreased MBC and MBN, both by 10% (P = 0.05), and decreased MR and qCO 2 significantly by 28% (P < 0.001) and 23% (P < 0.01), respectively. The interactive effects of N addition and mowing were evident only for MBN (P < 0.01) and the MBC:MBN ratio (P < 0.05) ( Table 3), but not for MR and qCO 2 .
Effects of nitrogen addition
Although the effect of N additions on soil microbial activity and ecosystem N cycling is a major focus of ecosystem research (Hassink, 1992;Fisk & Fahey, 2001;Maly & Sarapatka, 2002;Chu & Lin, 2007;Treseder, 2008;Wang et al., 2011), information on the effects of N addition on N cycling in semi-arid grassland ecosystems remains limited, especially for systems in central and eastern Asia. During the past decade, restoration of croplands to grasslands has become an important management practice in northern China. Use of natural grasslands for agriculture can result in large losses of soil organic matter and nitrogen. Thus abandoned cropland provides not only a valuable case study for N cycling and microbial activity but an important challenge for the practice of ecological restoration now and in the future. Dijkstra et al. (2005) found for a grassland ecosystem in central USA that N fertilizer stimulated net N mineralization. They argued that the stimulation resulted from either faster decomposition or reduced N immobilization by litter with larger N concentrations when the soil was wetter. In our study in old fields of northern China we also found an overall stimulation of net microbial N turnover rates by N additions over 4 years. Furthermore, microbial biomass N was also increased for the N-fertilized treatments during that time.
Both findings indicate that microbial N turnover and the microbial community is severely N limited at our sites, which agrees with findings for tall-grass prairie systems in North America (Garcia & Rice, 1994). The overall trend of stimulation of microbial N cycling at our site across years is remarkable because the amounts of precipitation in the growing season were very variable across the four study years between 2006 and 2009. This is in contrast to results for the year 2008 as reported by Wang et al. (2011) for the same site. However, the data of 2008 were collected from three different patches, including herb or grass-dominated patches and mixed herb-grass patches. Even though data for 2008 still do not reveal a stimulating effect of N additions on microbial biomass N, all other years show such a stimulation effect. Even in dry years such as 2009, when the annual precipitation (176.1 mm) was only approximately 50% of the 55-year mean precipitation (348 mm), a stimulating effect of N addition on microbial N turnover and MBN could be demonstrated. This shows that multi-year experiments are needed to evaluate microbial community responses to changes in nitrogen availability.
So far the effect of N additions on potential changes in microbial activity has been largely neglected (Treseder, 2008). This might be because N addition negatively affected microbial growth in several field and laboratory studies (Soderstrom et al., 1983;Nohrstedt et al., 1989). Results from our experiment showed that the microbial biomass and respiration had changed significantly after 4 years of N fertilizer addition to mown fields. In addition, N fertilizer without mowing significantly decreased potential MBC and MR. Reductions in MBC and MR, plus our findings that at treatment sites with N addition MBN was significantly increased while the MBC:MBN ratio was significantly reduced, may indicate a shift in the microbial community structure, although this was not studied here. In view of the narrowing of the MBC:MBN ratio, which was most pronounced in the first year of fertilizer input, we suggest that at our site the soil microbial community shifted in response to N additions from being fungi-to bacteria-dominated. This interpretation is in agreement with findings for temperate grasslands and pastures where reductions in abuscular mycorrhizal fungi (Bradley et al., 2006) or decreased fungal fatty acid methyl ester abundance (de Vries et al., 2007;Rousk et al., 2011) were found in response to N additions. In contrast to our study, Pietikäinen et al. (2005) found that N addition did not affect microbial N but considerably increased plant N in a sub-arctic meadow. In our study we also found that N addition increased plant productivity by more than 30% in the second and third years of the experiment (Figure 2). Thus, the stimulation of soil microbial N turnover following N fertilization is probably not only a response to increased soil N availability but also a feedback to N-induced increases in plant growth. This interpretation is in line with the work of Hu et al. (2001), who found for grassland ecosystems that stimulation of plant growth in response to elevated CO 2 exacerbated nitrogen constraints on microbes so that N additions are required to avoid a reduction in microbial decomposition.
Mowing effects
Above-ground biomass removal can reduce C inputs to soil significantly and lead to significant N loss, resulting in substrate limitation to microbes (Wan & Luo, 2003). However, against our expectation of negative impacts of mowing and litter removal on microbial N turnover, we found that mowing increased nitrification rates and did not affect the average ammonification and net N mineralization rates throughout the study period of 4 years. Mowing may result in increased soil temperature and, at humid temperate grassland sites, soil moisture values (Bardgett et al., 1998;Tix et al., 2006), but these effects could not be demonstrated in our study because we had too few measurements. Another mechanism related to how plant removal may interact with soil N cycling was revealed by Zak et al. (1994). These authors demonstrated that the removal of plant material with a large C:N ratio facilitated rapid N cycling by limiting carbon input to the soil, thus maintaining rapid N turnover in the microbial community in an old field in Minnesota, USA.
Our results showed that over a 4-year period mowing decreased MBC and MBN on average by 9.8 and 10.2% (Table 3). However, mowing only decreased MBN during the whole growing season in 2008 (Wang et al., 2011). These findings are in contrast to a study for an upland grassland in England where mowing enhanced soil microbial biomass (Bardgett et al., 1998). However, our observation of a decline of MBC and MBN after mowing is further backed up by the observed significant reduction in microbial respiration (28% less than the control) and a decrease of the qCO 2 by 24%. This indicates that responses of microbial C and N dynamics to mowing differ markedly between moist and semi-arid temperate grasslands. Also in other grassland ecosystems with a vegetation period restricted by environmental constrains, such as a sub-arctic meadow at Kilpisjärvi, Finnish Lapland, it was found that mowing reduced microbial respiration and the metabolic quotient of the microbial community in both fertilized and unfertilized treatments (Stark & Kytöviita, 2006). A smaller metabolic quotient indicates a more efficient use of substrates by microorganisms, where a greater fraction of substrate C is incorporated into microbial biomass and less C per unit biomass is lost through respiration (Ilstedt et al., 2003). The reduction of microbial availability of C that is mediated by mowing is likely to result from a decreased plant C flow to soil in the form of root exudates and the production of new below-ground plant root litter (Bargett et al., 1999).
Interactive effects of N addition and mowing
Land management practices such as hay harvesting may significantly influence the direct impacts of N addition on the soil environment and on soil microbial N transformation responses to N addition . Above-ground biomass removal by mowing may mask the N fertilizer effects on soil microbial communities by reducing plant litter input and root exudation and thus reducing soil microbial biomass and activities. In our study a significant effect of N fertilizer on microbial respiration could not be demonstrated either for mowed or for uncut plots. Nitrogen fertilizer applied to old fields did effectively promote plant growth. However, the removal of up to 90% of plant litter by mowing probably resulted in a depletion of labile C sources in the topsoil and, together with increased N uptake by the plants as a response to mowing, soil microbes may have become C as well as N limited. This explains our finding that microbial respiration did not increase. This interpretation is in line with the studies by Johnson et al. (2000) and Stark & Kytöviita (2006), who found that fertilizer increased in situ soil respiration (plant plus microbial respiration) but did not affect the microbial respiration measured in the laboratory from sieved soil samples. Results from our experiments indicate that 4 years of continuous N fertilizer application without mowing led to significant changes in microbial N transformation in the old field ecosystem we studied, resulting in an increase in rates of net N mineralization. However, mowing significantly masked this N fertilizer effect on soil microbial turnover rates.
Conclusions
In conclusion, the experiment that we conducted in an old field of northern China showed that over a 4-year period (2006)(2007)(2008)(2009) mowing and N addition simultaneously increased N transformation. However, mowing and N addition showed strong interactive effects: while mowing decreased microbial biomass N (MBN), MBN was increased by N fertilizer addition. This indicates that expected further increases in atmospheric nitrogen deposition to the study region or possibly large-scale N fertilization for increasing ecosystem productivity will accelerate N cycling, thereby increasing the risk of N losses to the environment. Adaptation of grazing or mowing regimes are, according to our findings, possible options to keep N and C cycles tight even under assumed increases in N deposition and fertilization, because mowing in combination with N fertilization increased ANPP but did not affect significantly MBN or other microbial N cycle characteristics. However, in view of the significant effect of the inter-annual variability of the amount of rainfall in our semi-arid study region, management plans must be multi-year, because the key microbial characteristics that were measured in our study fluctuated significantly across years. | v3-fos |
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} | s2 | Assessment of African Star Apple (Chrysophyllum albidum) Fruit Damage Due to Insect Pests in Ibadan, Southwest Nigeria
Damage of fruits by insect pests is one of the major problems faced by fruit sellers in many parts of the country. African star apple Chrysophyllum albidum G.Don. is one of the indigenous fruits that are highly damaged by insect pests during the fruiting season and in storage. A survey of markets and environs were carried out in Ibadan metropolis during the fruiting seasons for two years to determine the associated insect pests and the extent of damage done to C. albidum. Samples of ripe fruits were randomly collected from seven markets and homestead trees at different locations in Ibadan metropolis. Samples were examined in the laboratory at the Federal College of Forestry for damage and the causative agents were identified. Collections made periodically from green fruits to ripening in orchard at Forestry Research Institute of Nigeria showed that infestation of unripe fruits was by scale insects Coccus hesperidum L. while the ripe fruits were mainly attacked by fruit flies (Drosphillla spp. and Cerattis capitata Weid). Infestations were most severe in the market samples than the homestead tree samples. Severity of infestation ranged between 10-35% of the sampled fruits during the periods of the study. There were no significant differences (p>0.05) in the number of fruit fly species collected from different markets or from trees in the sampled locations. There were positive and negative correlations between the ripeness of fruits and attack by fruit flies and scale insects respectively.
INTRODUCTION
African star apple Chrysophyllum albidum, G.Don Sapotaceae is a common tree that distributed in the tropical rain forest and coastal region of West Africa. It is primarily a forest tree species and its natural occurrences have been reported in diverse ecozones in Nigeria, Uganda, Niger Republic, Cameroon and Cote d'lvoire (Bada, 1997).
The plant often grows to a height of 36.5 m though it may be smaller (Bada, 1997). The African star apple fruit is a large berry containing 4-5 flattened seeds or sometimes fewer due to seed abortion (Keay, 1989).
The plant recently has become a crop of commercial value in Nigeria. The fleshy pulp of the fruits is eaten especially as snack and relished by both young and old (CENRAD., 1999). The fleshy and juicy fruits, which are popularly eaten, are the potential source of a soft drink (ICRAF., 2007;Okafor, 1981). The fruits are also suitable for the production of fruit jams and jellies (Ureigho and Res. J. For.,9 (3): 87-92, 201587-92, Ekeke, 2010. It is reported as an excellent source of vitamins, irons, flavours to diets and raw materials to some manufacturing industries (Adisa, 2000;Bada, 1997;Okafor and Fernandes, 1987;Umelo, 1997).
The bark, foliage and fruit of some Chrysophyllum species are also used in traditional medicines. The African star apple is produced commercially in West Africa (Amusa et al., 2003;Falade and Aworh, 2004).
Ecologically, the tree has an efficient nutrient cycling and the high rate of mineralization of the leaves improves the quality of the top soil. Adesina (2005) and Achinewhu (1983) reported that fruit pulp of Chrysophyllum albidum contains 21.8 mg/100 g ascorbic acid and the skin contains 75 mg/100 g while Edem et al. (1984) reported 446 mg and 239 mg/100 g for pulp and skin respectively.
In spite of deforestation, which has resulted in substantial loss of these indigenous fruit trees, the remaining few ones which are being conserved are now undergoing domestication problem (Adisa, 2000). However, the joy of good fruit harvest by individual farmer or forest dweller is shorter-lived. This is because substantive percentages of the harvested fruits are lost due to post-harvest and marketing problems (Ladipo, 1994). The plant is susceptible to attack by various pests and diseases leading to low germination, seedling mortality and reduction in quantity and quality of fruit yield (Adelaja, 1997). Insect pests are one of the major constraints that have limited the quantity and quality of fruits produced in the country. However, there is limited information on the level of damage done by insect pests on C. albidum fruits. This study is therefore aimed at identifying the insects that cause damage to C. albidum in Ibadan metropolis, determine their extent of damage and estimate fruit loss due their attack.
MATERIALS AND METHODS
Market survey: Surveys were conducted for two years in seven fruits markets in Ibadan during the harvesting periods of C. albidum. However, Oja-aba market was not sampled during the first year due to logistic problems. Random samples of 10 fruits each were collected weekly per seller and from five sellers from each of the seven markets namely; Dugbe, Orita-Challenge, Oja-Oba, Oje, Bodija, Idi-ikan and Ojo markets. The sellers were interviewed using questionnaires on the sources of their C. albidium fruits, insect damage and control methods applied against insect pests. The fruits were bulked for each market, carried to the laboratory at the Federal College of Forestry Ibadan and were dissected to observe for larval presence. The mean number of larvae per fruit was determined for each market. The Larvae were maintained in the damaged and reared in cages to adult hood for proper identification. The emerged adult insects were identified at the National Horticultural Research Institute of Nigeria (NIHORT) Ibadan using available keys.
Field sampling for insect pests attacking C. albidum on farm: Fruits on ten trees randomly selected in the C. albidum orchard in the Forestry Research Institute of Nigeria (FRIN) Ibadan were sampled fortnightly by collecting ten fruits per tree. Fruit collections were made from unripe to ripe stages. The fruits were given arbitrary rating of 1-3 according to their level of ripeness. i.e., 1 = Unripe, 2 = Ripening and 3 = Ripe. During sampling, the canopy of each tree was divided into 2 strata and fruits were taken from five points along the circumference of each stratum; thus totaling ten fruits/tree. Fruits from each tree were bagged, labeled and taken to the Laboratory at NIHORT, Ibadan for insect isolation and identification.
Res. J. For., 9 (3): 87-92, 2015 Ten ripe fruits were also collected weekly from homestead trees at five local government areas in Ibadan metropolis. They include; Oluyole, Ido, Ibadan south east, Ibadan south west and Ibadan North local government areas. Three trees were sampled per Local Government. Fruits from each location were bagged, label appropriately and taken to the laboratory at FRIN for insect isolation and identification. External observation of the fruits was made before dissecting for fruit fly larval assessment. Any insect encountered both externally and internally was recorded. The larvae found in the fruits were reared to adulthood within the fruits in the rearing cages and were identified using available keys.
Statistical analyses: Descriptive statistics was used for variable assessed in the market survey, Data collected on the number of insect larvae found on dissected fruit were subjected to Analysis of Variance (ANOVA) and Duncan Multiple Range test was used to separate the means of significant tests. Correlation analyses were conducted separately between scale insect and fruit fly populations and the level of ripeness of C. albidum fruits.
RESULTS AND DISCUSSION
Insects of two dipterous genera were identified to be causing damage to the Chrysophyllum albidum fruits at market, the homestead trees and star apple orchard in Ibadan. The dipterous species were Drosophilla spp. (Diptera; Drosophyllidae) and Ceratitis capitata Weid (Diptera; Tephridae). Drosophilla were more prominent than Ceratitis but the latter caused more damage to C. albidum fruits. Scale insects Coccus hesperidum L. (Homoptera; Lecomidae) were identified on green fruits collected from FRIN orchard. These decreased as the fruits ripened. Although some fruits did not show any external signs of damage, fruit fly larvae were isolated from them when dissected. This corroborated the answers to the questionnaire administered to sellers whereby they claimed to be ignorant of the probable ways of insect infestation.
Market samples showed that Dugbe had the highest fruit flies attack with 30 and 35% of larvae infestation on the first and second year respectively. This was followed by Idi-ikan market 30 and 32% for first and second year respectively (Table 1). Fruit Samples collected from markets had more larval infestation than those collected from homestead trees. Percentage of attacked fruits ranged between 15-30 and 10-35% for fruit samples of homestead trees and markets samples respectively.
The results of the homestead trees showed that infestation was higher at Oluyole Local Government with maximum of 25 and 30% fruit damage followed by Ibadan north local government 18 and 21.66% for first and second year, respectively ( Table 2). The trend in the First Res. J. For., 9 (3): 87-92, 2015
%) ----------------------------------------------------------------------------------------------------Locations
First First results indicated that the fruit fly population was increasing with time since no control measure was applied as reported by the fruit sellers. The mean population of C. capitata larvae/fruit ranged from 1.0-1.8 and 1.8-3.3 for first and second year respectively while the mean population of Drosophilla larvae/fruit ranged from 0.5-2.8 and 2.0-4.2 for first and second year respectively in the various markets sampled (Table 3). Thirty percent (30%) of the traders indicated that they purchase their fruits from nearby villages, while 70% purchased from suppliers who transport the fruits from the villages to the various markets. All the sellers claimed to have purchased clean fruits. However, market observations indicated poor storage system. The fruits were often exposed and thus subjected to further attack by the fruit flies. This contributed to higher infestation recorded on the samples collected from the market. The present investigation revealed that fruit flies are limiting factors to the quantity and quality of marketable Chrysophyllum albidum fruits based on the level of damage observed.
In the orchard, insects identified on green fruits (especially around the fruit stalk) were the scale insects C. hesperidum. They were absent on fully ripe fruits when various periods of sampling were compared (Table 4). The numbers of damaged fruits, scale insects and fruit flies showed significant differences between the earlier and later sampling periods (t = 3.19, p<0.01; 2.13, p<0.04; 2.46, p<0.02, respectively). Correlation analysis of scale insect population against level of ripeness indicated that the number/fruit decreased with level of ripeness of the fruit (r = -0.84; p<0.02). Fruit attack by scale insects in the orchard may have contributed to infection by rot fungi, especially in the region of fruit stalk where the scales were attached prior to ripening. The number Res. J. For., 9 (3): 87-92, 2015 of fruit fly larvae in the fruits increased as the fruit ripened (Table 4) and was positively correlated with the level of ripeness of the fruits (r = 0.82; p<0.003). The result of the increased population of fruit fly larvae with the increased level of the fruits ripeness agrees with the observation made by Dhouibi et al. (1995), Umeh et al. (1998) that citrus fruit attack by C. capita increases with the increase in the level of ripeness. The preference of ripe fruits are linked to changes in the physio-chemical properties of such fruits (Umeh et al., 2009) making them more attractive to the fruit flies Drosophilla sp. was predominant over C. capitata, this also agrees with observation made by Umeh et al. (2002) on the study of insect pest of Chrysophyllum albidum fruits in south west Nigeria. There was no significant differences (p<0.05) in the number of Drosophilla sp. collected at different markets or locations of the homestead trees. However, C. capitata showed a significant difference only at the 5th week (p>0.05) at both market and homestead tree samples.
CONCLUSION
Therefore, Intensive efforts should be geared towards providing the basic information needed for designing a suitable integrated pest management strategy for the crops in the field. Fruit sellers should be educated on the appropriate methods for preserving fruits to reduce pest infestation and thus mitigate economic losses. | v3-fos |
2015-09-18T23:22:04.000Z | {
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} | s2 | Risk Factors for Salmonella, Shiga Toxin-Producing Escherichia coli and Campylobacter Occurrence in Primary Production of Leafy Greens and Strawberries
The microbiological sanitary quality and safety of leafy greens and strawberries were assessed in the primary production in Belgium, Brazil, Egypt, Norway and Spain by enumeration of Escherichia coli and detection of Salmonella, Shiga toxin-producing E. coli (STEC) and Campylobacter. Water samples were more prone to containing pathogens (54 positives out of 950 analyses) than soil (16/1186) and produce on the field (18/977 for leafy greens and 5/402 for strawberries). The prevalence of pathogens also varied markedly according to the sampling region. Flooding of fields increased the risk considerably, with odds ratio (OR) 10.9 for Salmonella and 7.0 for STEC. A significant association between elevated numbers of generic E. coli and detection of pathogens (OR of 2.3 for STEC and 2.7 for Salmonella) was established. Generic E. coli was found to be a suitable index organism for Salmonella and STEC, but to a lesser extent for Campylobacter. Guidelines on frequency of sampling and threshold values for E. coli in irrigation water may differ from region to region.
Introduction
Fresh produce is part of a healthy diet and its consumption should be further encouraged. Daily consumption of five or more portions of fruits or vegetables decreases the risk of heart disease and stroke [1,2] and consumption of whole fruits lowers the risk of diabetes [3]. However, most fruits and many vegetables such as leafy greens are typically consumed raw. If these are microbiologically contaminated they also present an increased risk for foodborne illness. Several outbreaks illustrate that the microbial safety of fresh produce should not be neglected. E. coli O157:H7 outbreaks occurred in the US with strawberries in 2011 [4], romaine lettuce in 2011 [5], bagged spinach in 2006 [6], as well as an outbreak of Salmonella with peppers in 2008 [7]. In Europe a number of cases of E. coli 0157 were epidemiologically linked to fresh produce including watercress in England [8], iceberg lettuce in Sweden [9] and lettuce in Iceland and the Netherlands [10]. Another notorious incident was the E. coli O104 outbreak with sprouted fenugreek seeds in 2011 in Germany and the rest of Europe [11]. Leafy greens eaten raw as salads were involved in seven salmonellosis outbreaks reported in the EU in the period 2007-2011, involving 268 human cases in total [12]. Campylobacter is the most important cause of bacterial gastroenteritis reported cases in EU and is usually associated with broiler meat [13]. However, apart from Salmonella and Shiga toxin-producing E. coli (STEC), Campylobacter has been highlighted as a relevant microbial risk for raw vegetables, fruits and minimally processed packaged salads [14,15]. Campylobacter is a known water borne pathogen [16,17] and often present in wild birds, thus with potential of fecal contamination to crops growing in the fields, as was reported in an outbreak of campylobacteriosis associated with peas [18]. Domestic and wild animals are reservoirs of E. coli O157 and Salmonella in the agricultural production environment and may contaminate fresh produce on the field, either directly or via contaminated agricultural water, as illustrated by several recent outbreaks [4,[7][8][9].
Washing, including washing in water with sanitizers, will not accomplish more than 2 log reduction of bacteria (including pathogens) present on fresh produce [19][20][21][22][23][24][25][26]. In addition, the washing procedure may damage sensitive products, such as berries, thereby decreasing the quality and shelf life by increasing the sensitivity to spoilage and mold growth [27,28]. Profound knowledge of the contamination sources and pathways for introduction of bacterial pathogens in primary production of fresh produce is needed to focus on prevention of contamination events [29]. Irrigation water quality is of major importance for fresh produce quality, since it may be both a source and route of microbial contamination [30][31][32][33]. In case manure is used as an organic fertilizer, control of the composting process is also a critical point [32]. Combination of cattle rearing and fresh produce production is identified as a potential risk factor [34,35]. Climatic factors, i.e. increased temperatures and flooding events, were shown to be associated with a decreased microbiological quality and safety of leafy greens [30,32,36]. Most of these studies focused on one particular geographical region. The main objective of the present study is to investigate whether and which factors could be identified as universal risk factors for pathogen contamination of fresh produce across farms in various countries with variable climate and agro-technical management practices. For this purpose leafy greens, strawberries and their primary production environment (soil, water, contact surfaces) were analyzed for the presence of Salmonella, STEC, Campylobacter and the amount of generic E. coli using a similar sampling plan at a variety of farms in Belgium, Brazil, Egypt, Norway and Spain within the framework of the European Veg-i-Trade project, executing research on the topic of microbiological (and chemical) safety of fresh produce in a global context.
Sampling Plan
In total, 3330 samples were taken from contact surfaces (524) including boxes, hands, blades, conveyers belts and tables, fertilizer (72), leafy greens (824) including lettuce, spinach and basil, strawberries (170), seeds (54), soil (1037) and water (649) including irrigation water from the source or reservoir, the tap, sprinkler or dripper and rinsing water for harvested crops on 45 farms in five countries (Belgium, Brazil, Egypt, Norway and Spain) [30][31][32]34,[36][37][38][39] (Table 1). In the case of farms producing leafy greens, the sampling was repeated throughout the crop growth cycle: at planting, two weeks before harvest, one week before harvest and at harvest. In case of strawberries, the multiple sampling rounds were conducted over the production season, of which the timing depended on the country. Contact surfaces were swabbed: an area of 50 cm² or the whole hand surface, 200 g of fertilizer was taken 200 to 300 g soil samples were taken (usually three were pooled but not in all studies), three crops of lettuce were pooled, 1 kg of strawberries was sampled and three samples of 100 g spinach were pooled and 5 L irrigation or rinse water was taken. After mixing, subsamples of 25 g for solid samples and 25 to 1000 mL in case of water (volume depending on the microbial load) were used for pathogen detection.
Microbiological Analyses
Details of the methods used for sampling and microbial analysis in the various countries can be found in prior description of these studies on a country level i.e. Belgium [30,34], Brazil [32], Egypt [31], Norway [38] and Spain [36,37]. Generic E. coli was enumerated in all studies and in all of the 3330 samples by equivalent methods including ISO 9308-1:2000 [40], APHA 1998 [41] [50] for STEC O157 or more broadly for non-O157 STEC using GeneDisc ® PCR screening for the simultaneous occurrence of stx1/2 toxin genes and eae/aggR adhesion genes, followed by isolation from presumptive STEC positive samples by plating on ChromID and CT-SMAC using the approach described in ISO 13136:2012 [51]. Positive PCR results were followed by culture isolation of the STEC strain. The presence of the virulence genes in the isolate were confirmed by PCR.
Agro-Technological Practices and Information on Climatic Conditions
Agro-technological practices were assessed during the farm visit by visual inspection and a questionnaire interview (e.g., as described by [32] and [35]). Climatic parameters were retrieved from the closest weather station. Flooding was defined as an event of excessive rainfall causing the fields to be inundated with accumulated rain water and/or water from overflowing natural water bodies such as nearby rivers within one week of sampling.
Statistical Analyses
All analyses were performed with SPSS Statistics version 21 at a significance level of 5 % (p = 0.050). The 95% confidence intervals for pathogen prevalence were calculated according to the Wilson score method without continuity correction [52]. Significant differences in the prevalence of pathogens were determined with the Mann-Whitney U test for continuous variables (E. coli counts and climatic parameters) and with the Chi-squared test of independence for categorical variables (agro-technical parameters). The presence/absenceof pathogens determined by culture was also modelled by multiple logistic regression according to the purposeful selection method [53]. Briefly, the significant main effects were determined by adding all covariates univariably in the logistic regression. All those with p < 0.250 were included as potential main effects in one multivariable model on which stepwise backward likelihood ratio selection was performed. All omitted variables were added one-by-one to the obtained model and those with p < 0.050 were kept. The assumption of linearity was checked for all continuous variables by adding the quadratic term as a main effect to the regression model. Then, all possible interactions were tested univariably and those with p < 0.250 were added together for forward LR model selection. Main effects were never eliminated, even if they lost their significance in the presence of the interaction. The Hosmer and Lemeshow test was used to check if the model fitted well to the data. The Cook's distance and standardized residuals were plotted to check for highly influential data points and biases in the predictions. Sensitivity and specificity of the model were checked by Receiver Operating Characteristic (ROC) curve analysis. ROC curves are graphical representations of the sensitivity and specificity for each possible cut-off value of the test variable [54]. The area under the ROC curve (AUC) is the summary statistic which gives an idea of the overall diagnostic performance of the test, with the AUC ranging from 0.5 for meaningless to 1.0 for perfection. In our case, the AUC indicates the ability to predict the presence of pathogens.
Occurrence of Pathogens and Generic E. coli
Within the framework of the EU FP7 Veg-i-Trade project the microbiological sanitary quality and safety of leafy greens and strawberries were assessed in the primary production in Belgium, Brazil, Egypt, Norway and Spain by the enumeration of E. coli and the detection of Salmonella, STEC and Campylobacter in these products and in their primary production environment. Although a substantial number of analyses were carried out, only few bacterial pathogen detections were observed within the combined data set.
The overall prevalence of Salmonella in all samples analyzed (n = 1605) was 2.5% (95% confidence interval (CI): 1.8%-3.4%) ( Table 2). Salmonella occurred most frequently in fertilizers (7.4% (2/27)), probably due to insufficient control of the composting process of manure used as organic fertilizer [55]. Irrigation water was second most contaminated (3.1% (12/387)) with Salmonella, probably because monitoring of the microbial water quality, and if necessary application of water treatment, was not (widely) applied by farmers [35]. The prevalence in the other sample types was similar, between 1.8% and 2.9%. This relatively high prevalence in fresh produce was caused by the study in Egypt, sampling small scale farmers providing local market, which showed a considerably higher incidence of Salmonella in fresh produce than the other studies. All (5/5) of the Salmonella positive strawberries and seven out of the 12 Salmonella positive lettuce samples were from Egypt [31]. STEC was isolated by culture in 0.7% of all samples (n = 1545) (95% CI: 0.4%-1.3%), most often from irrigation water samples. It should be noted that positive PCR signals for both stx and eae genes were obtained for much more samples (68 positives), but subsequent culture confirmation of STEC proved difficult (11 isolates obtained) [34,38]. It has been acknowledged that the culture isolation procedures for STEC are difficult and prone to failure, in particular in samples with high numbers of competing microbiota [56][57][58]. Moreover, STEC strains may easily loose stx genes, as early as during the first sub-cultivation step [59]. In this manuscript, only culture confirmed results were regarded as positive. Campylobacter was isolated at an overall prevalence of 8.6% (95 CI: 6.5%-11.4%) (n = 509), again mostly from water sources. Pathogens were mainly isolated from the production environment rather than from the leafy greens or strawberries themselves sampled at these fields, as noted by other studies [14,60,61]. No pathogens were detected on seeds (n = 27) and contact surfaces (n = 72) such as hands, boxes used at harvest, etc.
The detection of pathogens varied according to the geographical region. Amongst other reasons such as differences in environmental pressure and climate, this may be affected by the different status of implementation of good agricultural practices and national measures, guidelines or support available to these farmers involved [62,63]. In general (i.e., taken all samples together), isolation of Salmonella, STEC and Campylobacter occurred from samples which also contained significantly higher counts of generic E. coli (p < 0.001, p = 0.046 and p < 0.001, respectively). When considering the results separately per sample type, E. coli also performed well as an index organism because the presence of pathogens was usually significantly associated with elevated E. coli numbers, except for fertilizer samples in association with Salmonella and soil samples with STEC ( Table 3). The performance of E. coli as an index organism was better (AUC > 0.8) for Salmonella than for STEC and Campylobacter, in all sample types. Moreover, E. coli had a better functionality to serve as an index organism in water samples than in soil and fresh produce (leafy greens or strawberries) samples in the present study. Remarkably, although the isolation of STEC was significantly more frequent from water samples with elevated generic E. coli levels, this was not the case in soil, where generic E. coli had no significant predictive ability for STEC. The relation of generic E. coli with a pathogen may thus also vary on the environmental setting (i.e., the sample type). The presence of Campylobacter in fresh produce exhibited a significant but reverse association with E. coli: this pathogen was isolated more frequently when no or low levels of E. coli were present. In general, it should be noted that even when significant and positive correlations existed, these were never completely consistent. Detection of 100 % of the pathogen positive samples was not possible with any E. coli threshold value, because pathogens were occasionally isolated from samples which were negative for generic E. coli. To illustrate: in our study, 15% (6/40) of all samples positive for Salmonella had E. coli numbers below the detection limit (<10/g, except for the Spanish analyses and <1/100 mL for all water analyses) and this was 23 % (10/44) for Campylobacter (<10/g or <1/100 mL for all analyses). For STEC, no samples were positive by culture (0/11) when generic E. coli was below the detection limit. Since the detection limit for solid samples was tenfold higher in the Spanish study [37], for three Salmonella positive samples E. coli was < 100/g instead of 10/g. When data processing is done according to the investigated regions and the sample type, interesting findings can be reported (Figure 1). If the threshold value is put at 100 E. coli per g leafy greens or strawberries, between 50% (Egypt and Spain) and 100% (Brazil) of the fresh produce samples which tested positive for Salmonella would be identified by exceeding this E. coli threshold. But at the same time this limit would affect in total 0.6% (Belgium) to 25% (Egypt) of the fresh produce samples, most of which would be false-positive, resulting in food waste and an economic burden of loss or further testing for pathogens. Given the low counts of generic E. coli on strawberries, the threshold of 100 CFU/g would be too high; 15 CFU/g would be more appropriate. If the threshold value is put at 100 E. coli per 100 mL irrigation water, between 0% (Belgium) and 100% (Egypt and Norway) of water containing Salmonella would be rejected for irrigation, but this limit would result in a high rejection rate of the currently used water sources, ranging from 19% (Belgium) to 83% (Egypt). Pathogens present in irrigation water may not be transferred to the fresh produce if the contact between water and produce is restricted, for example by drip irrigation, and the threshold value for acceptable water quality may be set higher if such risk reducing strategies are employed [64]. Alternatively, to improve the microbiological quality of the water, the water could be subjected to various treatments (filtration, chemical decontamination, UV irradiation, sonication, etc.) before application as irrigation water [65,66].
Figure 1.
Pathogens were associated with higher generic E. coli counts (in log CFU/g or 100 mL), exemplified here by showing all Salmonella analyses per sample type (except for seeds and contact surfaces, since these were always negative). The horizontal red line indicates the threshold of 100 CFU E. coli per gram or 100 mL to show the potential impact of setting this value as a limit. Outliers are presented as circles (1.5 to 3 times the interquartile range below the 25th percentile or above the 75th percentile) or as asterisks (more than three times the interquartile range).
Risk Factors for Increased Likelihood of Finding Pathogens
A number of agro-technical factors were investigated individually for a significant relation with the occurrence of pathogens (Table 4). Specific countries, elevated generic E. coli numbers, flooding events and specific irrigation water sources (categorized as surface water, collected rainfall water, borehole water or municipal potable water) were associated with a higher probability of occurrence of all pathogens: Salmonella, STEC and Campylobacter. Salmonella was most often found (6.2%, 32 positive out of 513 samples) when surface water was the irrigation water source, while Campylobacter (20.8%, 30/144) and STEC (1.7%, 10/581) were more often isolated when collected rainfall water was the irrigation water source. Specific sample types and elevated average daily temperatures at the day of sampling were significantly linked with the presence of Salmonella and Campylobacter but not with STEC. Increased likelihood of STEC and Campylobacter was observed in case farmers combined cultivation of fresh produce crops with animal production. The use of (insufficiently) composted manure as a fertilizer and the use of flood irrigation was associated with increased Salmonella prevalence. Lower precipitation at the day of sampling, absence of any disinfection treatment of the irrigation water and storage of irrigation water in open reservoirs (ponds) was correlated with elevated Campylobacter isolation rates.
Prediction of Pathogen Occurrence Based on Significant Microbiological and Agro-Technical Factors
Multiple logistic regression was performed to investigate which factors are of major influence on the presence of pathogens when all factors are considered simultaneously, what is the extent of their impact and whether there are interactions between the significant main effects (Table 5). This analysis showed that the probability of Salmonella occurrence was determined by the numbers of generic E. coli, the country in which the data were collected, the source of the water used for irrigation water and the occurrence of a flooding event. Presence of STEC was predicted by the numbers of generic E. coli and the occurrence of a flooding event. Prevalence of Campylobacter was impacted by the country, the type of storage of irrigation water, open field farms vs. greenhouses and the sample type (lettuce, strawberries, water and soil). Table 5. The prevalence of Salmonella and STEC was estimated to increase in case of higher generic E. coli counts (Figure 2a and Figure 3). The odds ratio (OR) ranged from 2.3 to 2.7, meaning that an increase of 1.0 log CFU per g or per 100 mL of generic E. coli doubles to triples the odds of finding pathogens. There were no interactions of E. coli counts with other factors, meaning that this effect applied to all countries involved in the present study and all sample types included (i.e., produce, soil and water). Salmonella and Campylobacter prevalence differed significantly between countries and thus the risk estimates are specifically adjusted for each country. Detection of Salmonella was more likely if surface water was used for irrigation, followed by ground water, next collected rainfall water and it was least likely if municipal potable water was used (Figure 2b). Our study confirmed once more that surface water is most frequently contaminated with pathogens relative to other irrigation water sources such as rain and ground water [33,67,68]. When sampling within one week of a flooding event, the odds for Salmonella presence increased 10.9-fold ( Figure 2c) and that for STEC 7.7-fold ( Figure 3). Storage of irrigation water in open reservoirs prior to use was significantly associated with increased likelihood of Campylobacter detection (OR = 3.5). In particular water samples contained significantly more often Campylobacter than fresh produce samples (OR ≥ 12.5) and samples (of any type) taken in greenhouses showed significantly less Campylobacter than samples taken in open field farms (OR = 0.2), but there was an interaction between sample type and the farm type (open fields vs. greenhouses). This means that the ORs of sample type and farm type are not constant but vary depending on the value of the other factor. Specifically for this model, it means that the probability of finding Campylobacter was higher for irrigation water in open field farms than irrigation water in greenhouses, but Campylobacter prevalence was lower in leafy greens from open fields than leafy greens grown in greenhouses ( Figure 4). Irrigation water in greenhouses presented a lower risk for Campylobacter, which could be explained by the more often use of reclaimed water (reuse of water after disinfection treatment) and/or the use of municipal potable water. However, the fresh produce itself grown in greenhouses seems to be more likely to finding Campylobacter than upon cultivation in open fields. This might be due to the exclusion of birds, lower exposure to solar UV radiation and the usually higher relative humidity in greenhouses enabling prolonged survival of microorganisms in general, and of Campylobacter in particular [69,70].
Risk factors for pathogen contamination could be identified but the small number of samples from which pathogens were isolated, impaired the estimation of their quantitative effects by multiple logistic regression models. Data sparseness was observed as an unequal distribution of the data over all different factor combinations. The probability of rare factor combinations was very low relative to the sample size of this study, occasionally resulting in frequencies lower than five or even zero. For example, flooding events within one week of sampling only occurred in three out of the five individual country surveys with relatively rare frequencies (12/694 for Belgium, 36/260 for Brazil and 5/1103 for Spain), resulting in the low overall frequency of flooding of 1.8% (53/2879). Due to practical limitations in sampling and testing in the participating countries and intrinsic variability in primary production systems in place at the farms who participated on a voluntary basis in these surveys, the combined dataset was unbalanced because unequal amounts of data for all agro-technological and microbiological parameters was obtained per individual country. For example, one or two sources of irrigation water typically dominated in a specific country, with differences among the countries, resulting in partial data separation of the irrigation water sources according to country. Due to the low prevalence of pathogens in fresh produce, data sparseness issues were aggravated. (Table 3). (Table 3). Consequently, while the (qualitative) identification of the risk factors is robust, the estimated odds ratios should be regarded as preliminary estimates, which need to be confirmed or revised after further (local or regional) data collection. Nevertheless, the identified risk factors are clearly strongly influencial risk factors on the global level which require attention in the primary production of berries and leafy greens to control and prevent the occurrence of pathogens on this fresh produce. Since the logistic regression models combined additional risk factors with the generic E. coli count, the predictive value for the presence of pathogens was increased in comparison to the simple use of a universal E. coli threshold value (larger AUC, into account the identified risk factors can either improve the sensitivity (detecting more pathogen positive samples) or improve the specificity (reducing the number of false positives) of the performance of testing for an index organism as a surrogate for the pathogen itself. The main advantage in using the logistic regression model in comparison with solely the generic E. coli numbers lies in the increased specificity at a fixed sensitivity, which also translates in a higher AUC (Table 3). For example in our dataset: by setting a limit of 10 generic E. coli per 100 mL water, 92% of the samples containing Salmonella were justly rejected because they also contained ≥10 E. coli per 100 mL (i.e., sensitivity of 92%), but at the same time 38% of the Salmonella negative water samples were also rejected for irrigation because they too contained ≥ 10 E. coli per 100 mL (i.e., 62% specificity). By using additional information in the logistic regression model at 92 % sensitivity, the specificity was increased to 74% and now only 24% of the Salmonella negative water samples were rejected.
Conclusions
In this study, climatic parameters and factors (average daily temperature, daily precipitation and flooding of the fields) were shown to be significantly correlated with the presence of pathogens in the fresh produce production environment in univariable analysis, but with the exception of flooding, their relative importance to other microbiological (i.e. generic E. coli levels) and agro-technological factors (e.g., greenhouses) was too little to be retained as significant in the multivariable analysis. Other studies have identified the amount precipitation within three days prior to sampling as one of the most important risk factors for Salmonella detection in the fresh produce fields [71] and surface water used for irrigation [68], although the former revealed a positive and the latter a negative correlation. It should be noted that the use of weather parameters from the day of sampling may not be optimal and longer term definition of weather parameters may be more appropriate [72].
This study also showed that elevated E. coli numbers had moderate to good predictive value on presence of pathogens Salmonella and STEC, but much less for Campylobacter. Campylobacter species can reside intracellularly in protozoa such as Acanthamoeba polyphaga, which may allow prolonged survival and even multiplication in environmental waters. This may explain the weaker relationship with fecal indicator organisms such as E. coli [73]. No defined number of generic E. coli in for example strawberries, leafy greens or water was shown to serve as a threshold value to distinguish between safe and unsafe produce or irrigation water. Instead it was shown that taking into account the status of defined risk factors (i.e., the country of sampling, the sample type, a flooding event) will enhance the functionality of predicting the presence of pathogens in fresh produce and could contribute to more efficient and risk-based testing for index organisms (or pathogens) in the quest to ensure safety of the fresh produce. It is however recommended that further data are collected in the various regions of the world with regard to microbiological quality of fresh produce and the production environment to further underpin and confirm the results of the present study in relation to risk factors and their estimated (quantitative) impact on safety of the fresh produce. It is known there is considerable variation in weather conditions over the years which may influence the microorganisms in the agricultural environment [74]. In addition, geographic regions differ in their organization and management of the fresh supply chain which will also impact on the finding of risk factors. Moreover, to which extent the risk factors have been tackled already by defined control procedures and assurance activities (including microbiological monitoring) in place varies considerably on a global level. The relation of E. coli with pathogens is complex, whether E. coli may function as a suitable index organism or not depends on the pathogen, the climate and seasonality, the geographic region, the sample type (soil, water, fresh produce) and the presence of animal and human reservoirs, which is illustrated by the fact that contradictory results have been obtained in previous studies [31,68,[75][76][77][78].
In conclusion, this study combined data sets from different countries but equivalent sampling plans and contributed to the better understanding of key factors on a global level that need attention in good agricultural practices on the farm. This study also showed testing for E. coli numbers can provide information on the likelihood of finding pathogens and thus serve as an index organism to reliably assess food safety of fresh produce, testing and sampling needs to be driven by information on adoption of food safety practices, local weather conditions and incidents, which may vary upon the regional location of the farm. | v3-fos |
2018-12-27T12:17:44.213Z | {
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} | s2 | Interactive comment on “ Environmental soil quality index and indicators for a coal mining soil ”
Assessment of soil quality is one of the key parameters for evaluation of environmental contamination in the mining ecosystem. To investigate the e_ect of coal mining on soil quality, opencast and underground mining sites were selected in the Raniganj Coafield 5 area, India. The physical, chemical, biological parameters, heavy metals, and PAHs contents of the soils were evaluated. Soil dehydrogenase (+79 %) and fluorescein (+32 %) activities were significantly higher in underground mine (UGM) soil, whereas peroxidase activity (+57 %) was higher in opencast mine (OCM) soil. Content of As, Be, Co, Cr, Cu, Mn, Ni, and Pb was significantly higher in OCM soil, whereas, Cd was 10 higher in UGM. In general, the PAHs contents were higher in UGM soils probably due to the natural coal burning in these sites. The observed values for the above properties were converted into a unit less score (0–1.00) and the scores were integrated into environmental soil quality index (ESQI). In the unscreened index (ESQI-1) all the soil parameters were included and the results showed that the quality of the soil was 15 better for UGM (0.539) than the OCM (0.511) soils. Principal component analysis was employed to derive ESQI-2 and accordingly, total PAHs, loss on ignition, bulk density, Be, Co, Cr, Ni, Pb, and microbial quotient (respiration: microbial biomass ratio) were found to be the most critical properties. The ESQI-2 was also higher for soils near UGM (+10.1 %). The proposed ESQI may be employed to monitor soil quality changes due 20 to anthropogenic interventions.
Introduction
Coal, a combustible rock rich in carbon, is a crucial component of the energy mix that fuels the globe. In many countries, more than 70 % of the electricity generation comes from coal. For more than 150 years, coal has been an important source of energy for both developing and industrial societies. Coal mining is one of the core industries and Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | environmental sustainability (Masto et al., 2007a). Integrated soil indices based on a combination of soil properties provide a better indication of soil health than individual properties. Moreover an integrated index is essential for quantitative comparison of different soils. Several indices have been proposed to assess soil quality, which were mostly microbial in nature and for agricultural soils. Indexing involves three main 5 aspects: (1) choosing appropriate indicators for a minimum data set, (2) transforming the indicators to scores; and (3) combining the scores into an index (Sinha et al., 2009). Soil quality indices are useful to differentiate between degraded status of soils (Morugán-Coronado et al., 2013). Studies on soil quality indices involving soil contaminants are limited. Thus, the present study was aimed to assess the physical, 10 chemical, biological parameters along with heavy metal and PAH contents of soils near an opencast and underground coal mine. The other objective was to integrate all these parameters into a comprehensive environmental soil quality index (ESQI). 15 Raniganj Coalfield is primarily located in the Asansol and Durgapur subdivisions of Bardhaman district, West Bengal, India. Raniganj Coalfield covers an area of 443.50 km 2 and has total coal reserves of 8552.85 million t. Eastern Coalfields (ECL) reported its reserves as 29.72 billion t that make it the second largest coalfield in the country (in terms of reserves). Surface soil samples (0-0.15 m depth) were 20 randomly collected from the settlements near an opencast mine (Sonepur Bazari) and underground mine (North Serasole) of Raniganj Coalfields. All together 32 samples were collected from the opencast mining (OCM) site and 17 samples from underground mining (UGM) site. A portion of fresh soil samples were refrigerated for analysis of soil biological parameters. The rest of the samples were air dried ground and passed 25 through 2 mm sieve for further analysis.
Soil analyzes
The methods described by Tandon (1993) and Baruah and Barthakur (1999) were used to determine the following soil properties: bulk density (BD) (soil core method), maximum water holding capacity (by equilibrating the soil with water), porosity (derived from bulk density), pH and EC in water (1 : 2.5, soil / water ratio), soil organic carbon 5 (by potassium dichromate oxidation), and loss on ignition. Active microbial biomass carbon (AMBC) was measured by the glucose nutrient induced respiration method (Islam and Weil, 2000). Soil dehydrogenase activity was determined using the method of Klein et al. (1971). Phenol oxidase and peroxidase were measured with L-DOPA (L-3, 4 di hydroxy phenyl alanine) as substrate in acetate buffer (Robertson et al., 10 1999). Basal soil respiration (BSR) was measured as the CO 2 evolved from moist soil, adjusted to 60 % WHC, over an incubation period of 10 days at 25 ± 1 • C, in the dark (Islam and Weil, 2000). Soil metabolic quotient (AMBC/SOC) was calculated. Specific maintenance respiration rates (qCO 2 ) were calculated as BSR per unit of active (BSR/AMBC) microbial biomass carbon (Anderson and Domsch, 1990;Islam 15 and Weil, 2000). Phosphatase enzyme (p-nitrophenyl phosphate method, colorimetry); fluorescein diacetate hydrolase activity (FDA) of the soil was determined by the method described by Dick et al. (1996). For analysis of soil heavy metal content, the soil samples were digested in a microwave (ETHOS, Milestone, Italy) as per USEPA 3051A method (USEPA, 2007) and filtered. The metals in the filtrate were determined by ICP-20 OES (iCAP 6300Duo, Thermo Fisher Scientific, UK). For soil PAH analysis, samples were extracted using 1 : 1 hexane: acetone mixture in microwave as per the USEPA method 3546 (USEPA, 1995). The concentrated extract was analyzed by GC-MS system (Varian 450 GC and 240 MS) for 16 PAHs. 25 Two types of indexing system was followed to derive the environmental soil quality index (ESQI).
Environmental soil quality indices
Where, S denotes score of observed soil parameter, n is the number of parameters included in the index.
5
Principal component analysis (PCA) was used to select the appropriate properties and their weighing factors. PCs with eigen value ≥ 1 and explained at least 5 % of the variation of the data are examined (Sharma et al., 2005). Under a particular principal component (PC), only the variables with high factor loadings were retained for indexing. High factor loadings were defined as having absolute values within 10 % 10 of the highest factor loading (Andrews et al., 2002a). When more than one variable was retained under a single PC, multivariate correlations were employed to determine if the variables could be considered redundant and, therefore, eliminated from the ESQI (Andrews et al., 2002b). If the highly loaded factors were not correlated then each was considered important, and thus, retained in the ESQI. Among well-correlated 15 variables, the variable with the highest factor loading (absolute value) was chosen for the ESQI. Each PC explained a certain amount of variation (%) in the total data set; this percentage provided the weight for variables chosen under a given PC. The final PCA based ESQI equation is as follows: (Sinha et al., 2009), with an asymptote tending to 1 and another tending to 0.
Where x is the soil property value, a is the maximum score (= 1.00) of the soil property, x 0 is the mean value of each soil property, b is the value of the slope of the equation.
5
The slope was −2.5 for the "more is better curve" and +2.5 for the "less is better curve" to obtain a sigmoidal curve tending to 1 for all the proposed properties.
Statistical analysis
The data were expressed as mean values and compared statistically by t test; P significance is presented. The ESQI was done using PCA (Andrews et al., 2002b). 10 For computation, SYSTAT-12 package was used.
Basic soil properties and biological parameters
Soil bulk density, porosity, water holding capacity, pH, and electrical conductivity were not significantly differed between the OCM (open cast mine) and UGM (underground 15 mine) soils ( and fluorescein (+32 %) activities were significantly higher in UGM soil, whereas peroxidase activity (+57 %) was higher in OCM soil. Different soil may inactivate enzyme reactions by complexing the substrate, by reacting with protein-active groups of enzyme-substrate, or by reacting with the enzyme substrate complex or indirectly by altering the microbial community, which synthesizes enzymes. Enzyme activity may 5 either increase or decrease due to environmental contaminants. Heavy metals affect microbial metabolism by altering the normal enzyme activities, particularly inhibition of a specific enzyme and the effects can be dramatic and systemic (Christensen et al., 1982). The presence of different heavy metals and PAHs in coal contaminated soils might have altered the soil enzyme activities (Masto et al., 2007b).
Most of the elements are enriched in OCM soil probably due to the relatively higher land disturbances and coal dispersion in OCM site. Among the elements, the content of Co and Cr was > 50 % higher in OCM soils, these elements might have originated from 20 the coal. The rate of release of Cr into the global atmosphere from coal combustion is estimated to be in the order of a few thousands of tons per year. The mean Cr content of coals is only 20 mg kg −1 worldwide (Huggins et al., 2000).
Cd was slightly higher in the UGM soils. In Yatagan, Turkey, Yapici et al. (2006) reported that exploration of coal minerals contributed for Cd concentration in the local 25 biota. The Zn content was not affected significantly between the OCM and UGM sites probably the soil Zn is originated from vehicular activities. Tyre treads and tyre dust et al., 2011), thereby it is likely that the contamination of both OCM and UGM soils with Zn is from vehicular activities.
Soil PAHs
Among the soil PAHs, acenapththylene and phenanthrene were not significantly affected between OCM and UGM soils (Table 3). Naphthalene (+26 %), fluorene (+66 %), 5 anthracene (+43 %), fluoranthene (+44 %), pyrene (+52 %), benz(a)anthracene (+41 %), chrysene (+50 %), benzo(b)fluoranthene (+66 %), benzo(k)fluoranthene (+69 %), benzo(a)pyrene (+62 %), and total PAHs (+24.3 %) were significantly higher in UGM soils. Acenaphthene (+43 %), benzo(g,h,i)perylene (+89 %), and dibenzo(a,h)anthracene (+94 %) were significantly higher in OCM soils. In general the PAHs contents were higher in UGM soils probably due to the natural coal burning in these sites. The said coal mine has experienced mine fires and mining operations were closed for quite a few years. Tsibart et al. (2014) 180 mg kg −1 ), but the high-molecular-weight PAHs (benz(ghi)perylene, benz(a)pyrene, benz(k)fluoranthene) were revealed only in charry peat horizons. During coal burning the organic compounds in the coal are partially cracked to smaller and unstable fragments. These fragments, mainly highly reactive free radicals with a very short average lifetime, lead to more stable PAH formation through recombination reactions 20 (Mastral and Callén, 2000). Further, fluoranthene and pyrene are enriched in UGM soils, and are commonly considered as typical pyrogenic products derived from high temperature condensation of lower molecular weight aromatic compounds (Li et al., 2010). PAHs are emitted in the gas and solid phases. Both these PAHs can travel in the atmosphere and settle down on soil, water bodies and other environmental media. 25 Natural mine fire as well as domestic use of coal for cooking in the UGM site might have contributed to elevated PAHs content in the UGM soils. Natural coal fires were not reported in the OCM sites of the present study. Domestic coal burning is also not present in OCM site as the OCM is away from residential area.
Environmental soil quality index
Individual soil parameter values were normalized on a scale from 0 to 1 based on two types of curve: "more is better" (POR, WHC, and pH. SOC, DHA, FDA, AMBC, BSR, 5 PHOH, POH, ACP, AKP, AMBC/SOC); "less is better" (BD, EC, LOI, heavy metals, PAHs, BSR/AMBC). More is better was designated for pH as the mean pH in both these soil was < 7.0. Less is better was designated for loss on ignition, as it indicates the quantum of coal contamination. The calculated scores were integrated in to ESQI by two indexing methods as below.
Unscreened transformation (ESQI-1)
The index is the summation of the scores obtained by individual indicators, divided by the total number of indicators, here all the soil parameters has equal weightage.
Principal component analysis based index (ESQI-2)
All the soil variables were included for principal component analysis. The first five PCs had eigenvalues > 1.00 (Table 4). The highly loaded variable under PC-1 was total PAHs and was included in the ESQI. Likewise in PC-2, LOI, dibenzo(a,h)anthracene, indeno(1,2,3,c,d)pyrene, and benzo(g,h,i)perylene were highly loaded. As these 5 parameters are highly correlated (r > 0.700) among themselves and the total PAHs were already included in the ESQI, only LOI from PC-2 was included in the index. Similarly Be, Co, Cr, Ni, and Pb from PC-3 was included from PC-3, all these elements were correlated among themselves, therefore the weight corresponding to PC-3 was equally divided among these elements. BD, POR, and WHC were highly loaded from This is probably one of the first studies where total PAHs has been used as a soil quality indicator. In line with PAHs, the LOI was also included in the ESQI. The LOI could be an indirect measure of the coal contamination in the soils, the LOI observed in the soils is much higher than the normal soils. As coal is an organic matter, it contributes to soil 20 LOI and PAHs. The soil PAH is very important in contamination and human exposure point of view. PAH profile in UK soils, indicates that benzo[a]pyrene is a good surrogate marker, being ubiquitous in sites contaminated with PAHs and providing a consistent indicator of the amount of PAHs in contaminated soil (HPA, 2010). Fluoranthene is suggested as a complementary indicator to benzo(a)pyrene (Bostrom et al., 2002).
Heavy metals are ubiquitous pollutants coal has also been reported as one of the source of heavy metal pollutants especially Cr, Ni, and CO ( some of these elements are enriched in the coal. The bulk density is an important parameter which affects the soil productivity of the coal-mined land because it indicates the suitability of the soil for root proliferation, water-holding capacity, and long-term nutrient availability. It is found to affect the entire biological reclamation process by influencing moisture retention capacity, and porosity. The ratio BSR / AMBC is most 5 appropriately used as an index of adversity of environmental conditions for the soil micro flora and has valuable applications as a relative measure of how efficiently the soil microbial biomass is utilizing carbon sources, and the degree of substrate limitation for the soil microorganisms (Wardle and Ghani, 1995). Soil microorganisms divert more energy from growth to maintenance as stress increases and thus the ratio of respired 10 C to biomass C can be a much more sensitive indicator of stress. The BSR / MBC ratio indicates the carbon turnover rates in the soils, the importance of soil organic carbon in improving the overall soil quality has been reported widely (Debasish et al., 2014;Fialho and Zinn, 2014; Lozano-García and Parras-Alcántara, 2014). Paz-Ferreiro and Fu (2013) reviewed the limitations of using soil biochemical, microbiological, and 15 biological properties for soil quality evaluation. The ESQI-2 obtained using the PCA is presented in Fig. 1b, where the contribution of each soil indicator parameter on calculated ESQI is also shown, which gives an insight into the cause for the measured ESQI. The ESQI is higher in UGM (+10.1 %) than OCM soil. Total PAHs and LOI are the limiting parameters in UGM (−39.6 %) and 20 OCM (−143 %) soils, respectively.
In general, the UGM has comparatively less environmental impacts than opencast mining. As underground mining operations take place below ground, they generally do not create as much air pollution, contribute less to groundwater, surface water and soil pollution, and are not as visually intrusive. Similar soil quality studies on mining area 25 showed that reclamation of mine soil through plantation could improve the SQI score (Asensio et al., 2013). | v3-fos |
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} | s2 | De Novo Assembly of the Pea (Pisum sativum L.) Nodule Transcriptome
The large size and complexity of the garden pea (Pisum sativum L.) genome hamper its sequencing and the discovery of pea gene resources. Although transcriptome sequencing provides extensive information about expressed genes, some tissue-specific transcripts can only be identified from particular organs under appropriate conditions. In this study, we performed RNA sequencing of polyadenylated transcripts from young pea nodules and root tips on an Illumina GAIIx system, followed by de novo transcriptome assembly using the Trinity program. We obtained more than 58,000 and 37,000 contigs from “Nodules” and “Root Tips” assemblies, respectively. The quality of the assemblies was assessed by comparison with pea expressed sequence tags and transcriptome sequencing project data available from NCBI website. The “Nodules” assembly was compared with the “Root Tips” assembly and with pea transcriptome sequencing data from projects indicating tissue specificity. As a result, approximately 13,000 nodule-specific contigs were found and annotated by alignment to known plant protein-coding sequences and by Gene Ontology searching. Of these, 581 sequences were found to possess full CDSs and could thus be considered as novel nodule-specific transcripts of pea. The information about pea nodule-specific gene sequences can be applied for gene-based markers creation, polymorphism studies, and real-time PCR.
Introduction
Pea (Pisum sativum L.), an important crop cultivated worldwide [1], is a valuable model system in plant genetics. Since Gregor Mendel's famous experiments, several scientific discoveries have occurred in modern pea genetics; these new insights include information regarding genetic control of compound leaf development [2,3] and the molecular basis of symbiotic interactions with beneficial nitrogenfixing bacteria (rhizobia) [4][5][6]. The study of pea gene polymorphism in relation to agronomically important traits is essential to both basic and applied research on this crop plant [7,8]. Unfortunately, the large size (more than 4 Gb) (http://data.kew.org/cvalues/) and complexity [9] of the pea genome hamper its sequencing as well as the discovery of this crop plant's genetic resources, both of which are desperately needed for molecular and genomics-assisted breeding [8,10].
As an alternative to whole genome sequencing, analysis of transcriptomes by RNA sequencing can provide extensive information about expressed genes [11,12]. Because nextgeneration sequencing technologies are applicable to all organisms, including those for which information about genome organization is insufficient or lacking, considerable progress in pea transcriptome sequencing has been achieved over the last few years. Massive amounts of transcriptomic data have been obtained in the form of high-quality sequence reads that have been used for molecular marker creation, whole genome map construction [13][14][15][16][17], and characterization of host-pathogen interactions (pea-Sclerotinia sclerotiorum) [18]. All these data (as well as additional unpublished pea transcriptome sequencing results) have been uploaded to the NCBI Sequence Read Archives (SRA) (http://www.ncbi.nlm.nih.gov/sra/) as raw reads. Assemblies have been created for some of these data and deposited in the NCBI Transcriptome Shotgun Assembly (TSA) database, allowing users to perform data mining (e.g., BLAST searching) and to study pea gene polymorphism.
Several genes have tissue-specific expression, however, and can therefore only be studied through analysis of the appropriate tissue. One such example involves symbiotic genes necessary for the establishment and development of nitrogen-fixing nodules which are predominantly expressed in those temporary plant organs. To date, only a few samples from pea nodules have been sequenced (available as raw SRA archives), and only one assembly built from a mixture of sequencing reads from different organs (including nodules) is present in the TSA database (see Table 1 for available pea nodule transcriptome sequencing results). Because this assembly was based on nodules harvested at a very late stage of symbiotic nodule development (3-month-old plants), it presumably contains insufficient information on nodulespecific transcripts. Consequently, sequences of nodulespecific genes of pea are still limited.
The aim of our work was thus to sequence the transcriptome of young pea nodules, construct an assembly, and analyze the resulting assembly for unique sequences. Along with nodules, we harvested root tips to analyze their transcriptome content as well.
Biological Materials.
Seeds of pea laboratory line SGE [19] were surface-sterilized with concentrated sulfuric acid (98%) (15 min on a shaker), washed 10 times with autoclaved distilled water, and germinated on Petri dishes containing sterile vermiculite for 3 days. The germinated seeds were then planted individually into 200 mL ceramic pots containing quartz sand, watered with 100 mL of 2x nitrogen-free mineral nutrition solution [20], and inoculated with an aqueous suspension of Rhizobium leguminosarum bv. viciae RCAM1026 [21] (1 × 10 6 CFU per plant). Plants were harvested 12 days after inoculation; nodules and root tips (5 mm distal portion of the root) were placed in liquid nitrogen, ground into powder, and stored at −80 ∘ C. Material was harvested from a total of 10 plants.
cDNA Library Construction and Sequencing.
Total RNA was extracted from 100 g of material using an RNeasy Plant mini kit (Qiagen, Hilden, Germany). cDNA libraries were constructed and sequenced according to the instructions provided with the Genome Analyzer IIx platform (Illumina, San Diego, CA, USA). After total RNA extraction and DNase-I treatment, mRNAs were captured using oligo (dT) magnetic beads and fragmented. First-strand cDNA was synthesized from these fragments using random hexamer primers; double-stranded cDNA was then generated, purified with magnetic beads, and subjected to end reparation and 3 single adenylation. Sequencing adaptors were ligated to the adenylated fragments, and DNA fragments having adapter molecules on both ends were then amplified. After a quality control step performed on a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA), the cDNA library products were sequenced in a single-read run with 75 bp length reads on an Illumina Genome Analyzer IIx platform.
De Novo Transcriptome
Assembly. Preliminary quality control of the raw sequencing data was performed via the FastQC v.0.11.3 application (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), which indicated that the reads were of acceptable quality. For adapter removing Cutadapt version 1.8.1 [22] was used. Low-quality read removal and trimming were then performed with the assembly program Trinity v.2.0.6 [23] using the "trimmomatic" option with default parameters. Next, contig assembly was performed by Trinity with default assembly parameters, including kmer = 25. As a result, two FASTA files were obtained, one for the nodule sample and one for the root tip sample. Statistical parameters for the assemblies were obtained by running the TrinityStats.pl script included in the Trinity package.
Assessment of Assembly Quality, Differential Expression
Analysis, and Functional Annotation of Contigs. As a step in assessment of assembly quality, the generated reads were mapped to the assemblies with the Bowtie2 program v. 2.2.5 [24]. The contigs were grouped with known pea sequences (obtained from http://www.ncbi.nlm.nih.gov/) using CD-HIT EST from the CD-HIT package (http://cd-hit.org/) [25] with parameters -c 0.80 -n 6.
In order to distinguish the transcripts enriched in nodules as compared to root tips, the reads of both libraries were mapped to "Nodules" assembly with Bowtie2 v. 2.2.5 [24]. The differential expression was calculated using EdgeR package [26] under a negative binomial model, with biological coefficient of variation 0.2 and FDR cutoff value 0.001.
To detect transcripts containing reliable full-length CDS regions two approaches based on similarities of either nucleotide or amino acid sequences were used. For each transcript, BLAST search against NCBI RefSeqGene database was performed in order to find orthologous sequences, and then these sequences were aligned by Smith-Waterman algorithm [30] with a "5-0" substitution matrix. Also, as an alternative approach, we used TransDecoder software [23] for CDS region prediction based on homology search against Swiss-Prot protein database [31].
To extend the annotation of the full-length nodulespecific transcripts, the nucleotide sequences were converted into amino acid sequences and then mapped to the Kyoto Encyclopedia of Genes and Genomes (KEGG) Web Server (http://www.genome.jp/kegg/) [32]. "Nodules" assembly "Root Tips" assembly performed on an ABI Prism 3500 xL system (Applied Biosystems, USA) at the Genomic Technologies, Proteomics, and Cell Biology Core Center of All-Russia Research Institute for Agricultural Microbiology (ARRIAM, Saint Petersburg, Russia). The online tool OligoCalc [33] was used for primer design. Alignments of small sequence sets were generated using Multalin [34]. Translation initiation site prediction was performed using NetStart 1.0 [35].
Results and Discussion
3.1. Sequencing and Assembly. Sequencing generated 52,021,865 reads from the "Nodules" library and 17,684,604 reads from the "Root Tips" library. After removal of adapter and index sequences, 75.1% reads were equal to or longer than 70 bp and 10.2% of reads were shorter than 10 bp for "Nodules" and 74.5% and 11.2% of reads, accordingly, for "Root Tips." The nodule and root tip read sets were assembled individually. A total of 58,397 contigs belonging to 48,628 genes (as termed by Trinity) were constructed from the nodule set, with a mean contig length of 880.81, a median contig length of 620, and an N50 of 1,282. Isoforms were proposed for 4,550 genes. Root tip reads were assembled into 37,287 contigs of 35,081 genes, with a mean contig length of 841.14, a median contig length of 558, an N50 of 1,260, and 1,055 total isoforms. Length distributions of contigs in the two assemblies are presented in Figure 1, and distributions of isoform numbers are shown in Figure 2.
To our knowledge, the appearance of isoforms can be due to either alternative splicing or the presence of paralogous sequences expressed in the tissue. As an illustration of the first case, we were able to detect two splice variants in the "Nodules" assembly for transcripts of the symbiotic gene Ign1, an ortholog of IGN1 (Ineffective Greenish Nodules 1) of Lotus japonicus (Regel.) K. Larsen [36] (GenBank accession number KR047192; TR2831|c0 g2 i1 and TR2831|c0 g2 i4 in the "Nodules" assembly). The longer transcript retained the first intron and, according to prediction by NetStart 1.0 [35], could be translated into a protein variant lacking the first 21 N-terminal amino acids. An example of the second case involved ENOD6 (for early nodulin 6; GenBank accession number X63700), which encodes a short protein belonging to a group of nodule-specific cysteine-rich (NCR) peptides [37,38]. BLASTN searching uncovered a group of isoforms (TR2035 from the "Nodules" assembly) derived from paralogous genes encoding cysteine-rich peptides specific for nodules (it should be noted that some of these isoforms could be artificial chimeras containing parts of different transcripts that have extensive segments sharing 100% similarity).
Quality Assessment.
Evaluating the quality of a de novo transcriptome assembly without a reference genome is challenging. We therefore implemented three approaches previously recommended for managing this task [39,40]. First, we used the pea expressed-sequence tag (EST) sequences represented in GenBank as a standard to estimate assembly quality. We aligned 18,576 ESTs against the "Nodules" assembly. Of these, 2,571 ESTs (13.8%) shared no similarity with any contigs of the assembly. Furthermore, 102 ESTs were filtered out on the basis of an E-value cutoff of 1 × 10 −10 . From the remaining 15,903 ESTs (85.6%), we chose hits with maximal coverage of the EST (one per EST) and evaluated their coverage and identity distributions. Among these EST-contig pairs, 94.9% of the ESTs shared more than 90% identity with their corresponding contig fragments.
Following the second recommended approach, we mapped back all reads to contigs in both assemblies; as a result, 89% and 91% of reads in "Nodules" and "Root Tips" assemblies were, respectively, aligned back to the contigs, demonstrating that our assemblies were of acceptable quality.
Third, being interested in symbiosis-specific genes, we searched the "Nodules" assembly for previously unknown pea homologs of symbiotic genes EFD (ethylene response factor required for nodule differentiation) [41], VPY (Vapyrin) [42], and NSP1 (nodulation signaling pathway 1) [43] of Medicago truncatula Gaertn. and SEN1 (stationary endosymbiont nodule 1) [44] of L. japonicus. Long transcripts with high identity were found for all four genes ( Table 2); these transcripts allowed us to design primers flanking coding sequence (CDS) regions and to amplify the corresponding regions in cDNA synthesized from 4-week-old nodules of pea genotypes SGE and Finale. Except for allelic variations of Vpy, Sen1, and Nsp1 that were found between SGE transcriptome International Journal of Genomics 5 International Journal of Genomics and Finale cDNA genotypes, we observed complete sequence correspondence for all four genes, thereby demonstrating the satisfactory quality of the created assembly.
To evaluate the "Root Tips" assembly, we selected genes involved in glutathione biosynthesis: Gsh1 (gammaglutamylcysteine synthetase precursor [AF128455.1]), Gshs (glutathione synthetase precursor [AF231137.1]), and hGshs (putative homoglutathione synthetase [AF258319.1]). BLASTN searching against the "Root Tips" assembly identified one contig (TR9283|c0 g1 i1) completely identical to full-length Gsh1 and one contig (TR8244|c0 g1 i1) completely identical to full-length Gshs except for a single nucleotide polymorphism in the 3 untranslated region. This search also revealed four contigs (TR2244|c0 g1 i1, TR3920|c0 g1 i1, TR13401|c0 g1 i1, and TR25033|c0 g1 i1) representing portions of hGshs (each with 100% identity) that had not been assembled into a contig, probably because of insufficient overlapping of reads due to the low expression levels of this gene in pea root tips. Consequently, despite the good quality of the "Root Tips" assembly, its coverage was insufficient for finding full sequences of rare transcripts; nevertheless, the discovery of partial sequences allows primers to be designed for whole-transcript PCR amplification and transcript-end amplification by rapid amplification of cDNA ends (RACE) methodology.
Annotation of Nodule-Specific Transcripts.
To obtain information on nodule-specific genes, we attempted to select portions of previously unknown sequences of the "Nodules" assembly by clustering them together with pea sequences produced from nonnodular tissues. In addition to our "Root Tips" assembly, the pea transcriptome assemblies created by Franssen et al. [13] and Kaur et al. [14] currently meet this requirement. Using Cd-Hit software, 277,211 sequences of these four pea transcriptome assemblies were grouped into 61,521 clusters (where a cluster is defined according to Cd-Hit as a set of similar sequences created to reduce sequence redundancy and to improve the performance of other sequence analyses). Among these clusters, 10,391 (approximately 17%) were common to all assemblies (Figure 3). The 13,305 nodule-specific clusters included 14,998 contigs belonging to 14,171 genes (i.e., without gene isoforms). These sequences were assigned to GO terms to characterize the nodule transcriptome profile.
The transcripts were first aligned against plant protein sequences in the NCBI nr protein database (24.04.15 release). The following parameters were used: an E-value cutoff of 1 × 10 −20 , the same alignment direction for all high-scoring segment pairs (HSPs) in a hit, and 20 (or more, if of the same E-value) hits for a query. The transcripts were then annotated using Blast2GO software.
The length of a contig is supposedly the critical factor for successful annotation [40]. Only about 30% of sequences less than 1,000 bp long in our "Nodules" assembly were successfully annotated. The efficiency was 56% for sequences ranging from 1,000 to 2,000 bp. Almost all sequences (93%) longer than 2,000 bp were successfully annotated.
One-third of nodule-specific contigs (5,940) were associated with plant proteins in the nr database, with 565,464
D e n o v o R o o t T i p s
F r a n s s e n Figure 3: Clustering the sequences of the "de novo Nodules" assembly (this study) together with pea sequences produced from nonnodular tissues ("Franssen" [13], "Kaur" [14], and "de novo Root Tips" (this study)). total hits. Of these, 3,516 contigs were assigned to 13,697 GO terms. Among biological processes, the most abundant terms were metabolic processes ("organic substance metabolic process", "primary metabolic process", "cellular metabolic process", "single-organism metabolic process", and "nitrogen compound metabolic process") along with "singleorganism cellular process", "biosynthetic process", "establishment of localization", and "single-organism localization" (Figure 4(a)). This distribution reflects the processes occurring in nodules, such as microsymbiont (rhizobia) hosting within cells and nitrogen compound metabolism. Within the molecular function category, contigs were assigned to "heterocyclic compound binding", "organic cyclic compound binding", "ion binding", "small molecule binding", "transferase activity", and "carbohydrate derivative binding" (Figure 4(b)). These terms may be related to metabolite exchange between plants and bacteria, including exchanges with signal molecules. Regarding cellular components, the major GO terms were "cell part", "membrane-bounded organelle", "membrane part", and "organelle part" (Figure 4(c)), which are similarly concerned with the formation and functioning of symbiotic compartments in nodule cells.
It seems also valuable to distinguish the transcripts that are preferentially expressed in nodules as compared to root tips. By mapping the reads of both libraries ("Nodules" and "Root Tips") to "Nodules" assembly via Bowtie2 v. 2.2.5 and calculating the differential expression via EdgeR package with 0.001 FDR cutoff we selected 1081 contigs that represent genes with significantly higher expression level in nodules (Supplementary File 1 in Supplementary Material available online at http://dx.doi.org/10.1155/2015/695947). Still, more detailed analysis, including verification of the results of such "digital expression" analysis by real-time PCR, is needed, along with addition of more time points to the experiment.
Sequences of Nodule-Specific Transcripts.
To identify sequences of novel unreported, highly reliable transcripts International Journal of Genomics 7 Organic substance metabolic process Primary metabolic process Cellular metabolic process Single-organism cellular process Nitrogen compound metabolic process Single-organism metabolic process Regulation of biological process Biosynthetic process Establishment of localization of pea, we analyzed the 14,998 sequences of the "nodule only" clusters using TransDecoder software [23]. As a result, 593 putative full-length ORFs were found in 536 contigs (Supplementary File 2).
As an alternative approach to the identification of full-length transcripts, we aligned the same set of 14,998 sequences of the "nodule only" clusters against plant RNA genes in the NCBI RefSeqGene database. Of these sequences, 8 International Journal of Genomics We aligned each pair using the Smith-Waterman algorithm [30] with a "5-0" substitution matrix and identified aligned fragments corresponding to the CDS regions of hit sequences (as determined by GenBank). We selected 427 alignments (comprising 153 unique pea sequences, some of which aligned to multiple GenBank accessions representing gene isoforms or paralogs) with the following characteristics: (1) full coverage of the hit CDS region by a contig; (2) identity higher than 0.8; and (3) the contig having possible start and stop codons within a 50 bp region. Of these 153 contigs, 45 were not detected by TransDecoder.
In total, we identified 581 novel sequences containing putative full-length CDS in pea nodule transcriptome, among which 536 were found by TransDecoder and additional 45 were detected by alternative approach based on BLAST against known plant mRNA sequences. For annotation of these 581 sequences, homologous genes were found by BLASTN search in Medicago truncatula genome (ver. 4.0) [45] (see Supplementary File 2). Also, KO (KEGG Orthology) identifiers were assigned to the novel sequences, and 109 entries out of 581 (18.8%) were successfully annotated (Supplementary File 2).
In our opinion, our generated "Nodules" assembly adds valuable information, especially with respect to nodulespecific sequences, to the existing knowledge about pea transcriptome: some unique sequences of pea symbiosis-related genes can be identified only in our assembly. An example of this case involves CLE genes, some of which were shown to participate in systemic regulation of nodule formation in several legumes such as M. truncatula, L. japonicus, and Glycine max [46][47][48]. The CLAVATA3/Embryo Surrounding Region-Related (CLE) gene family is composed of numerous genes that contain conserved CLE domains in various plant species and encode short regulatory peptides (CLE-peptides) (for review see [49]). In M. truncatula, two CLE genes, MtCLE12 and MtCLE13, have nodulation-related expression patterns that are linked to proliferation and differentiation [46]. In pea, sequences of CLE genes are not known, but it was shown that overexpression of MtCLE13 gene leads to similar effects (severe reduction in nodulation) in both pea and M. truncatula, proving that MtCLE13 is functional in pea [50]. So we sought for the sequences homologous to MtCLE12 and MtCLE13 (Medtr4g079630.1 and Medtr4g079610.1, resp.) in our nodule transcriptome assembly.
BLASTN search using the Medtr4g079610.1 transcript sequence (encoding Cle13 peptide [46]) as a query against our "Nodules" assembly retrieved the contig TR8317|c0 g1 i1, which contains a full open reading frame (ORF) corresponding to Cle13 of P. sativum; the same search against "Organism Pisum sativum (taxid: 3880)" in the NCBI TSA database returned two partial transcripts: (1) gb|GCMK01019899.1| (TSA: "Pisum sativum Ps 029064 transcribed RNA sequence"), containing only part of the Cle13 ORF, and (2) the apparently chimeric gb|GCMO01040960.1| (TSA: "Pisum sativum Ps 150017 transcribed RNA sequence") containing a portion of the ankyrin repeat gene (similar to Glycine max ankyrin repeatcontaining protein At5g02620-like [LOC100812799]) as well as the 5 -part of the Cle13 transcript. A BLASTN search using the Medtr4g079630.1 transcript sequence (encoding Cle12 peptide [46]) as a query found two contigs: TR116|c0 g1 i1, containing the full ORF of P. sativum Cle12, and TR23484|c0 g1 i1, containing the full ORF of an unknown protein similar to P. sativum and M. truncatula Cle12 and therefore presumably a paralog of P. sativum Cle12. We thus tentatively designated these genes as Cle12a and Cle12b, respectively (Table 3). At the same time, the search against the NCBI TSA database retrieved no significant homologs of Cle12 in pea.
The pea transcriptome assembled after Illumina sequencing is thus a good resource for the study of pea transcripts related to nodulation. It can be used in future investigations focused on pea symbiosis-specific genes. Such potential research targets include genes encoding nodule-specific peptides such as NCR-and glycine-rich protein peptides that have been exhaustively described in M. truncatula [38,51] but not P. sativum, as well as other symbiotic genes expressed in nodules, including Cle peptide-encoding genes.
Also, the present "Nodules" assembly is a convenient tool that can facilitate study of transcription changes in nodules of symbiotic mutants. In pea, several mutant lines with impaired nodule formation were obtained and phenotypically characterized [52][53][54]. RNA sequencing of the whole transcriptome from mutant nodules is considered to be a reasonable approach for further characterization of genes and gene networks that operate during nodule development. In this regard, the present assembly of pea nodule transcriptome can be used as a reference for mapping reads and differential expression analysis. Also, this reference transcriptome is indispensable for annotation of short contigs obtained according to the MACE (Massive Analysis of cDNA Ends) protocol, which implies sequencing of 3 -part of each transcript instead of the whole mRNA [55]. Direct annotation International Journal of Genomics 9 of 3 -parts of transcripts by Gene Ontology or KEGG is often not successful because of dissimilarity of these regions between different species, and the present assembly containing significant number of pea nodule-specific transcripts can therefore serve as a reference for annotation of differentially expressed transcripts revealed by MACE technology.
Conclusions
The aim of the present study was the acquisition of nodulespecific transcript sequences via next-generation sequencing. Using an Illumina platform, we obtained 52 million reads from a sample derived from young pea nodules and more than 17 million reads from a root tip sample. We constructed the assemblies (more than 58,000 and 37,000 contigs from nodules and root tips, resp.) and analyzed the "Nodules" assembly for unique sequences. We identified approximately 15,000 nodule-specific contigs associated with different GO biological function terms. Of these, 581 sequences were found to possess full CDSs and could thus be considered as new nodule-specific transcripts of pea.
Because the ability of pea plants to form symbiotic nodules is an agronomically important trait, information about pea nodule-specific gene sequences can be applied by scientists and breeders for primer design, gene-based marker creation, polymorphism studies, and real-time PCR. These findings will thus benefit both fundamental and applied science. The next challenge for researchers is characterization of pea transcripts specific to another symbiosis formed by leguminous plants: arbuscular mycorrhiza, which is also of great importance to both fundamental science and contemporary sustainable agriculture. | v3-fos |
2019-03-31T13:44:05.435Z | {
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} | s2 | Antioxidant and anti-inflammatory properties of extracts from Allium hookeri root
In this study, antioxidant and anti-inflammatory activities of water, methanol, and ethanol extracts obtained from Allium hookeri root were evaluated. The ethanol extract of A. hookeri was found to possess the strongest reducing power and also exhibited dominant effects on scavenging of nitrites, DPPH radicals, and superoxide radicals. The water extract showed more efficient DPPH and hydroxyl radical-scavenging activities than those of the methanol extract. Furthermore, the inhibitory activity against nitric oxide (NO) production in RAW 264.7 macrophages was evaluated to elucidate the anti-inflammatory properties of the extracts. Results indicated that all the extracts of A. hookeri exerted inhibitory activities against NO production, especially the ethanol extract (IC5029.13μg/mL). Total phenolic and total flavonoid contents were found to be abundant in the ethanol extract, with values of 24.96 mg gallic acid equivalent/g extract and 4.27 mg rutin equivalent/g extract, respectively. Total thiosulfinate content was determined for the first time and a high amount was present in the ethanol extract (14.2 μM/g extract). These results suggest that A. hookeri root has antioxidant and anti-inflammatory properties and could be used as a natural source for the development of pharmaceutical agents or functional foods.
868 potential damages (6). Nitric oxide (NO) is an important mediator which is produced from L-arginine, under the function of nitric oxide synthases (NOS). If it's not suppressed in time, the accumulation of NO will promote an excess inflammation response, and even result in atherosclerosis, diabetes, Alzheimer's disease, asthma, cancer, and other diseases (7,8). Multiple lines of evidence have suggested that materials which exhibited potent inhibitory effect on inflammatory mediator production and synthases expression possess significant anti-inflammatory effect (9,10).
The Allium genus belongs to the larger Alliaceae family, which consists of more than 700 species. It is well known that the Allium species has been used as a flavoring ingredient for thousands years, and quite a few investigations have been conducted to evaluate their chemical characteristics and therapeutic effects (11,12). Among them, garlic (Allium sativum L.) and onion (A llium cepa L.) have been examined widely, and have demonstrated diverse biological qualities, including antioxidant, antihypertensive, and anti-inflammatory effects (5). As one member of the Allium genus, Allium hookeri (A. hookeri) is widely used as a food and a medical material in India, China, and other areas of Asia. Though some investigations on the bioactive properties of A. hookeri have been conducted previously, the works were mainly concerned with the antioxidant and anti-inflammatory activities, so the estimations on the bioactive components are likely inadequate (13)(14)(15). In this study, the antioxidant effects of the water, methanol, and ethanol extracts from the A. hookeri root were evaluated by various assays. The anti-inflammatory activity of the extracts was measured using RAW 264.7 macrophage cell lines. Furthermore, the total contents of three prime phytochemicals, polyphenols, flavonoids, and thiosulfinates were quantified.
Materials
The followings were purchased from Sigma Chemical Co.
Total thiosulfinates
The total thiosulfinate content was determined based on the method of Han et al. (18). An aliquot of sample was placed in a test tube, to which 0.5 mL of 2 mM cysteine was added. The total volume rose to 5 mL with hepes buffer where A0 represents the absorbance of cysteine without extract, and A1 is the absorbance of mixture containing examined extract. B is the dilution factor of cysteine.
DPPH radical scavenging activity
The DPPH radical scavenging activity was evaluated using a method described by Yang et al. (19). Briefly, 2 mL of a 0.1 mM DPPH solution in 95% ethanol, was added to 2 mL of sample at various concentrations and allowed to stand in darkness for 30 min. The absorbance, at 517 nm, was read via a UV-visible spectrophotometer (Ultrospec 5300 pro, Biochrom Ltd., CB, UK). BHA was used as positive control and the scavenging effect was calculated according to equation (2): where A control is the absorbance of the control without the extract, and Asample is the absorbance of the mixture in the presence of extract.
Hydroxyl radical scavenging activity The hydroxyl radical scavenging effect was measured using the method set forth by Smirnoff and Cumbes (20). In brief, 3 mL of the reaction mixture contained 0.3 mL of 20 mM sodium salicylate, 1 mL of 1.5 mM ferrous sulfate, 1 mL of the sample, and 0.7 mL of 6 mM H2O2. The mixture was incubated at 37℃ for 1 hr, and the final absorbance was measured at 562 nm. The scavenging capacity was calculated using formula (2). Vc was prepared in distilled water and used as positive control in current and following assays.
Superoxide radical scavenging activity
The scavenging effect of the superoxide radical was determined using a modified method described by Zhang et al. (21). Samples of 1.5 mL of each extract at different concentrations were mixed with 0.5 mL of the 468 μM NADH and 0.5 mL of the 300 μM NBT. After being shaken vigorously, 0.5 mL of the 60 μM PMS was added, and the reaction was kept at 25℃ for 5 min. The absorbance was read at 560 nm, and the scavenging effect was calculated according to equation (2).
Briefly, 1 mL of the sample was mixed with 1 mL of the 1 mM NaNO 2 , and then the pH was adjusted to 1.
Reducing power
The reducing power was assessed using according to the method of Yen and Chen (24). One millimeter of the sample was mixed with 2.5 mL of 0.2 M phosphate buffer (pH 6.6) and 2.5 mL of 1% potassium ferricynide. The mixture was incubated at 50℃ for 20 min. After being cooled to room temperature, 2.5 mL of 10% trichloroacetic acid was added, and the mixture was centrifuged at 3,000 rpm for 10 min.
Thereafter, 2.5 mL of supernatant was mixed with 2.5 mL of distilled water and 0.5 mL of 0.1% ferric chloride solution.
The results were expressed as the absorbance at 700 nm measured by spectrophotometer.
Cell culture and cell viability assay
Determination of NO production
Nitrite is the stable product of NO in a cell culture medium, and it was measured using Griess reagent mentioned above.
In brief, RAW 264.7 cells were cultured for 24 hr and then pre-treated with various concentrations of the sample.
Thereafter, the LPS (2 μg/mL) was added to initiate NO generation. An aliquot of culture medium (100 μL) was removed, after 20 hr incubation, and mixed with 100 μL of Griess reagent. After 15 min, the absorbance of the mixture was read at 540 nm.
Statistical analysis
Statistical analysis was carried out using the SPSS statistical program (21.0, SPSS Inc., Chicago, IL, USA). The values were evaluated using one-way analysis of variance (ANOVA), followed by post-hoc Duncan's multiple range tests. All data were presented as mean±standard deviation (SD) of multiple measurements. Differences were considered to be significant at the level of p<0.05.
Result and Discussion
Total phenolic and total flavonoid contents Polyphenolic compounds are secondary metabolites with various chemical structures and characteristics. As presented in Previous study has indicated that organic solvents are more efficient than water in the extraction of phenolic compounds due to the less polarity and appropriate solubility (26).
Moreover, the addition of water was demonstrated to increase the polarity of organic solvent and may explain the low amount of phenolic and flavonoid compounds in methanol extract (27). Relatively higher amount of total phenolic content in water extract may due to the high temperature used. Total phenolic and flavonoid contents obtained from A. ampeloprasum L. (methanol extract) were 5.70 mg GAE/g extract and 0.86 mg catechin equivalents/g extract (28).
It was also reported that organic-sulfur compounds partially
DPPH radical scavenging activity
The DPPH radical scavenging assay is widely employed to evaluate the electron or hydrogen donating ability of antioxidants due to its high degree of reliability, stability, and repeatability. As illustrated in Fig. 1 (15). Therefore, the ethanol and water extracts possessed efficient scavenging activity, and the methanol extract also possessed mediated scavenging activity against the DPPH radical. Therefore, it is still unclear that which part of compounds play critical role for the antioxidant activity of water extract.
With respect to methanol extract, the low total flavonoid and thiosulfinate compounds may explain the weak effect.
Hydroxyl radical scavenging activity
As the most reactive radical, the hydroxyl radical is believed to be deeply associated with DNA damage and lipid peroxidation. Fig. 2
Superoxide radical scavenging capacity
Superoxide radical is a highly toxic free radical that can be generated through various biological reactions. It is well known that superoxide radicals are the precursor of hydroxyl radicals and signet oxygen. Therefore, the superoxide radical scavenging assay plays an important role in the estimation of antioxidant capacity. Fig. 3 Inhibitory activity on the NO production As shown in Fig. 7 | v3-fos |
2019-05-16T13:07:12.155Z | {
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} | s2 | STUDIES ON POTENTIAL OF FINGER MILLET (ELEUSINE CORACANA GAERTN. L.) AMYLASES FOR INDUSTRIAL APPLICATIONS
Amylases are of great significance especially in the food, brewing and detergent industry. An attempt has been made to study the characteristics of amylases produced during germination of finger millet (Eleusine coracana Gaertn. L.). Of the 25 genotypes studied RAU8 showed the maximum activity at pH 5 and temperature 60C. This is the first report of optimum amylase activity at 60°C in finger millet. The best activity was observed in seeds geminated for 96 hours. The enzyme extract showed maximal activity till 90 minutes and 82.24% activity was retained even after 120 minutes. The thermostable character of the enzyme and retention of activity of the unprotected enzyme for 2 hours makes it suitable for industrial purposes. Further characterization of the different forms of the amylases may help in isolation of the most robust form which could then be cloned and expressed in microbes to enable large scale production for industrial purposes.
INTRODUCTION
Amylase is an enzyme which breaks down starch (the reserve carbohydrate in plants) and glycogen (the reserve carbohydrate in animals) into reducing fermentable sugars, mainly maltose, and reducing non fermentable or slowly fermentable dextrins (Burtis and Ashwood, 1999).
Amylases are produced by a variety of living organisms, ranging from microbes to plants and
The International Journal of Biotechnology
(1, 4-α-D-glucan glucanohydrolase, glycogenase) are calcium metalloenzymes, unable to function in the absence of calcium. It acts at random locations along the starch chain which makes it faster acting than β-amylase. It breaks down long-chain carbohydrates, yielding maltotriose and maltose from amylose, or maltose, glucose and "limit dextrin" from amylopectin. β -Amylase (1,4-α-D-glucan maltohydrolase, glycogenase, saccharogen amylase) is synthesized by bacteria, fungi and plants. Working from the non-reducing end, β-amylase catalyzes the hydrolysis of the second α-1, 4 glycosidic bond, cleaving off two glucose units (maltose) at a time. During the ripening of fruit, β-amylase breaks starch into sugar, resulting in the sweet flavor of ripe fruit (Burtis and Ashwood, 1999).
Amylases are among the most important enzymes and are of great significance in present day biotechnology especially in bread baking process where addition of the enzyme increases the bread volume and helps to retain its softness (Kanwal et al., 2004). Amylases possess important applications in the food industry. They are mainly used for production of syrup with high glucose content, sweeteners and ethanol. Amylase rich energy food (AREF) which has a high density of nutrients is distributed as weaning food and to pregnant and lactating women for nutritional benefits (http://www.indiamart.com/christy-friedgram-industry/products.html). They are used in the brewing industry for malt preparation, liquefaction of additives, improved fermentability of grain and modification of beer characteristic. The paper industry uses amylase for liquefaction of starch. It is also used as an additive in detergent to increase their cleansing power (Crueger and Crueger, 2005). Commercially α-amylases are produced mostly from fungal sources, some bacteria and also plant sources like barely, millets like sorghum, wheat, and maize.
In view of its importance in industrial application, an attempt has been made to study the characteristics of amylases produced during germination of finger millet (Eleusine coracana Gaertn. L). Finger millet was chosen for the present study as the activities of finger millet malting enzymes are very high and come next only to barley, the world's premier beer grain (National Research Council, 1996). Our endeavor is also aimed in the direction of making this crop commercially attractive so that its inherent properties of drought tolerance, capacity to grow on upland acidic soil etc. Haider et al. (2003) can be exploited. GPU 67, HR 374, IE 7, JWM 1, R + , OEB526, OUAT 2 and VR708. Five genotypes viz. IE 3693, IE 4671, IE 5066, IE 5165 and IE 5870 were obtained from ICRISAT, Patancheru. Three genotypes were obtained from VPKAS, Almora, Uttaranchal. These are VL149, VL315 and VL347. One genotype i.e. RAU 8, was obtained from Igatpuri, Maharashtra.
Seeds
The total amylase was extracted in 0.1M phosphate buffer or 10mM CaCl2. Starch unconsumed was calculated from a standard curve of starch. Starch unconsumed was found to be higher for amylase extracted in phosphate buffer whereas it was lower for amylase extracted in CaCl2. It is known that calcium is required for α-amylase activity (Burtis and Ashwood, 1999).
Based on these results further extractions were carried out in CaCl2.
Maltose assay was used to estimate the breakdown of starch. Levels of amylase were determined by measuring the mg of maltose liberated when incubated with 1% starch. The initial experiments were conducted on the genotype A 404. One gram of dry, dehusked seeds were taken and placed in a 250 ml beaker. A little water was added to aid germination. The beakers were then covered with aluminium foil and kept in an incubator set at 28°C for 72 hr. No illumination was provided. The germinated seeds were ground in 10ml of ice-cold 10mM CaCl2 in a pre cooled mortar. The solution was added gradually till a smooth paste was obtained. This mixture was then transferred to an oak ridge tube and kept at 4 0 C overnight for proper extraction of amylase.
The extract was centrifuged at 7,500rpm in Hermle table top centrifuge (rotor 220.80 VO2) for 15 min. at 4 o C. The supernatant was used as the enzyme source. It was kept at 4 0 C or on ice and used on the same day. A standard curve of maltose was made by taking varying volumes of 0.2% maltose solution. Colour reagent (Bernfeld, 1955) was added and the tubes were capped and placed in boiling water bath for 15 minutes and then cooled in ice water. The OD was read at 540nm in UV-Visible Spectrophotometer (Spectrascan UV 2600) after addition of 9ml distilled water against a blank which had no maltose. Samples were prepared in duplicates and average of two reading was taken. A standard curve of maltose was prepared by plotting mg of maltose on X axis and OD540nm on Y axis. This curve was used for deduction of maltose released by different extracts.
Amylase was assayed as per standard procedure (Bernfeld, 1955). The following were added in the order : 1 ml buffer, 400 µl 1% starch, 500 µl distilled water (DW) and 100 µl extract (100 µl DW for Blank). The tubes were capped and incubated at 50 0 C for 15 min. 1ml of color reagent was added to each tube and kept in boiling water bath for 15 min and then cooled in ice water.
Finally 9ml of DW was added to each tube. The absorbance was measured at 540nm.
Amylase activity was determined at various pH values using different buffers such as sodium acetate buffer (0.2 M, pH 3.6-5.6) and sodium phosphate buffer (0.1 M, pH 5.8-8.0). For each pH, set of 3 test tubes (1 blank & test sample in duplicate) was prepared. Once the optimal pH had been determined the amylase activity was determined at different temperatures ranging from 25 0 C to 75 0 C (with an interval of 5 0 C). The optimum germination time was checked from the seeds germinated for different durations. The seeds were germinated for 24, 48, 72, and 96 hours.
RESULTS AND DISCUSSION
The A 404 extract was found to be active over a broad range of pH viz. 3.8 to 7.8 (pH 3.8 -5.4 in acetate buffer and pH 5.8 -7.8 in phosphate buffer). The optimum pH was found to be 4.6.
Below pH 4.6 the activity of amylase decreased drastically, whereas there was gradual drop in activity above pH 4.6. Similar results have been obtained by other workers (Nirmal and Murali Krishna, 2003), , (Mar et al., 2003) and this appears to be characteristic of several cereal α-amylases (Nirmal and Murali Krishna, 2003), (Rao et al., 2005). It is known that the endosperm environment where starch is primarily stored and broken down is acidic in nature (Dicko et al., 2000), therefore, amylases have their optima in acidic pH.
The optimum temperature for amylase activity was found to be 50 0 C. Maltose release was observed up to 75 0 C, with some loss of activity. Such high temperatures for optimal enzyme activity have been observed in other grains also (Nirmal and Murali Krishna, 2003), (Rao et al., 2005), (Terashima et al., 1995) Also, seeds were germinated for 72 hours were found to possess highest amylase activity which points towards peak breakdown of stored starch.
Twenty five genotypes were then tested for amylase activity at the optimized conditions for A 404. The incubation time was increased to 30 min. Fig. 1. shows the difference in activity of different genotypes.
One gram dehusked seeds of each genotype had been taken for germination and amylase extract preparation. The variation in amylase activity observed was very significant so it was investigated whether the number of seeds per gram had any correlation with amylase activity. Fig. 2 shows a correlation graph between the number of seeds per gram and amylase activity.
The scatter diagram shows that there is no correlation between number of seeds/1g from which the extract was prepared and the amylase activity/g of seeds. Thus, amylase activity may be a genotype specific trait.
Since RAU 8 showed the best amylase activity (Fig. 1) it was taken up for further studies to obtain the optimum conditions for its activity. Studies on effect of different pH showed the presence of two peaks of activity (Fig. 3). The first peak is at pH 5.0 and second much lower peak at pH 7.0.
Amylases are known to exist in different forms (www.gmocompass.org/eng/databases/enzymes/80.amylase.html, 29.11.2012) like α, β and γ and exhibit maximal activity at different pH. In our study the complete extract has been taken. It is expected that multiform of the amylases would be present and they would exhibit their maximal activity at different pH. However, the maximal activity was obtained at acidic pH corroborating our findings with A 404. Generally, the optimal pH for α-amylase is 6.7 to 7.0, for β-amylase it is 4.0 to 5.0 and γamylase has the most acidic pH optimum at around pH 3.0 (www.wikipedia.org/wiki/Amylase, 29.11.2012) The optimum pH for pure soy bean β-amylase has been shown to be in the range 5.0 to 6.0 (Gertler and Birk, 1965). It has also been shown that α-amylase is inactivated at a low pH whereas β-amylase remains stable at a low pH of 4.8 (Bilderback, 1973). The optimum pH of plastidic α-amylase was found to be 6.2 and that of β-amylase was 4.6 in pearl millet leaves (Pennisetum americanum) (Vally and Sharma, 1995). The α-amylase of African finger millet has been shown to display maximum catalytic activity at pH 5.4, whereas β-amylase was active at pH 6.0 . Thus, it appears that β-amylases which are almost exclusively found in higher plants are generally more active in acidic environments.
The optimum temperature of the amylase activity of the RAU 8 extract was studied at optimum pH 5.0. Fig. 4 It has been reported that in African finger millet the α-amylase displays maximum catalytic activity at around 45ºC whereas the optimum temperature for β-amylase activity is between 50°C and 55ºC ,. Another study (Kolawole, 2009) showed that showed that β-amylase from African finger millet seed malt had temperature optima of 50ºC. In yet another study (Nirmal and Murali Krishna, 2003) the optimum temperature for amylases α-1, α-2 and α-3 from finger millet was found to be in the range 45°C to 50°C. The α and β-amylase enzymes obtained from maize (Zea mays) malt had optimal temperature 50°C and 90ºC, respectively (Biazus et al., 2009). The α and β-amylases, isolated from Sorghum bicolor cv. (Feterita) malt, had maximum activity at temperature 70°C and 50°C, respectively (Mawahib et al., 2010).
Thus, it appears that amylases are generally thermostable with β-amylase being more tolerant to higher temperatures than α-amylases. However, this is the first report of optimum amylase activity at 60°C in finger millet. Further work to characterize the form of amylase exhibiting such high heat tolerance is warranted.
Germination entails breakdown of complex carbohydrates to simple sugars. Different forms and levels of amylases may be present at different stages of germination. The effect of germination duration on amylase activity in RAU 8 was studied at the optimum pH 5.0 and two incubation temperatures viz. 50°C and 60°C. The amylase activity observed after 24, 48 and 72 hour of germination was almost the same (Fig. 5). The best activity was observed in seeds geminated for 96 hours and the activity declined thereafter. This indicates that maximal starch breakdown is completed by 96 hr and the energy requirements thereafter might be met by photosynthetic products in natural conditions. Earlier studies have found the highest α-amylase activity in African finger millet malt flour germinated at 15ºC for 9 days and at 20ºC for 6 days, while the highest β-amylase activity was displayed in the malt flour germinated for 5 days at 30ºC . Finger millet seeds germinated for 72 hours were found suitable for amylase activity in yet another study (Nirmal and Murali Krishna, 2003) β-amylase was found to be catalytically active in African finger millet seed malted for 96 hours (Kolawole, 2009). Other reports exist showing varying degree of germination time (3-5 days) for best amylase activity in different crops (Mawahib et al., 2010), (Nerkar et al., 2011), (Usha et al., 2011), (Prakash and Deshwal, 2013).
Thus, not only does the germination time affect the production of amylase but it is also affected by the temperature of germination which in the present study was 28°C. The knowledge of the most suitable duration of germination and temperature of germination are important for generation of high quality malts during the brewing process.
Once it was established that extract from seeds germinated for 96 hour showed maximum activity at pH 5.0 and incubation temperature of 50°C/60 o C, the length of incubation for amylase activity was studied. The extract was incubated with the substrate (1% starch) for different time periods at 50 o C. The results obtained are shown in Fig. 6.
Maximal activity was obtained after incubation for 15 min. Thereafter, the activity was almost constant till 90 min. There was a gradual decline till 105 min and a sharper decline thereafter. Enzymes exhibit their activity in vivo in ideal microenvironments. Their activity in vitro is affected by many factors such as pH, incubation, salts etc. The pH (5.0) and incubation temperature (50°C) had been standardized for in vitro conditions in the present study. Such high temperatures are not normally experienced by plants and it is not known whether germination of finger millet takes place at 50°C. Therefore, the activity pattern reported is a reflection of the stability of the enzyme in vitro. In the cell the products formed are removed constantly and the reaction moves in the forward direction. This does not occur in vitro. The accumulation of the end products i.e. maltose and maltodextrins, may have an inhibitory effect on the amylases which is reflected by the decline in activity after 90 min. The decline in activity could also be due to the degradation of the enzyme in vitro after a certain period. It has been reported that African finger millet malt extracts incubated for up to 4 hours retained about 84 and 64% of α-amylase activities . In the present study 82.24% activity was retained even after 2 hours (Table 1). The α-amylase isolated from Heliodiaptomus viduus (Gurney) has been shown to retain its full activity at 30ºC for 2 hours. However, it became inactive at 60ºC after 2 hours and at 70ºC after 1 hour (Prakash and Deshwal, 2013). Therefore, it is possible that incubation at lower temperature would have shown higher activity levels for a longer time in the present study. In the The results presented in this study would greatly help the brewing, detergent and baking industry in using RAU 8 seeds as a source of amylase. Further characterization of the different forms of the amylases present may help in isolation of the most robust form which could then be cloned and expressed in microbes to enable large scale production for industrial purposes.
However, since different forms of amylases exhibit different properties it would be better to use the whole extract of germinated seeds. A demand from the industry for finger millet grains would translate into a valuable source of income for marginal farmers as the plant grows well on degraded soils in poor moisture conditions, thus requiring little or no input in terms of fertilizers and irrigation -the two major financial constraints of poor farmers. | v3-fos |
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} | s2 | Oviposition behaviour and larval development of Anastrepha fraterculus from Argentina in citrus
Citrus peel physicochemical attributes are considered the main components conferring partial or even total resistance to fruit fly (Diptera: Tephritidae) infestation. Fruit fly females adapt their ovipositional strategies to overcome such resistance. Here, we explored the effects of citrus species (Rutaceae) on the ovipositional behaviour of the South American fruit fly, Anastrepha fraterculus (Wiedemann), and on its immature development. Particularly, we investigated the effects of (1) citrus species on oviposition behaviour and immature development, (2) citrus species on oviposition preference and on the location of the eggs at different depth in the citrus peel, and (3) harvest season and post‐harvest storage time on oviposition behaviour and immature development in lemon. Citrus species influenced ovipositional behaviour and affected survival of immature stages. Females laid eggs in lemon [Citrus limon (L.) Burm.], orange [Citrus sinensis (L.) Osbeck], and grapefruit (Citrus paradisi Macfadyen). In orange and lemon, larvae were found dead close to the oviposition areas, suggesting chemically mediated resistance mechanisms. Under choice conditions, females preferred grapefruit over lemon and bigger clutches were found in the layers where embryonic development is favoured. Unsuitability of lemon as a medium to complete development was neither affected by harvest season nor by storage time of the fruit after harvest. The physical and chemical characteristics of the peel were distinctive to each citrus species and may have affected the specific levels of resistance of these citrus species to infestation by A. fraterculus.
Introduction
Within insect-plant interactions, host location, host recognition, oviposition, and the capacity of the host to sustain immature development determine the suitability of a given plant as a host. In holometabolous insects, in which the larvae cannot move from host to host, adult female decisions are crucial for offspring survival.
When the host is a crop and the insect is a pest, the outcome of such interaction has applied implications. One typical example are true fruit flies (Diptera: Tephritidae), which represent a serious threat in fruitproducing regions. Their impact is attributed to the damage caused by larval activity in the fruit and the restrictions to access pest-free markets (Malavasi et al., 1994). Understanding insect-plant relationships for each fruit fly species and possible host plant species is fundamental to determine the correct host status of a given commercial fruit for a given fruit fly species (Aluja & Mangan, 2008) and, consequently, to assess the risk of pest introduction during trade.
Citrus fruits (Rutaceae) are mostly reported as poor hosts or non-preferred host for fruit flies (Back & Pemberton, 1915;Muthuthantri & Clarke, 2012). Peel physicochemical attributes are considered as the main components that confer partial or even total resistance to fruit flies (Back & Pemberton, 1915;Greany et al., 1983;Spitler et al., 1984;Papachristos et al., 2008). The gum secretion and the hardened calluses that drown the eggs and larvae (Bodenheimer, 1951;Spitler et al., 1984), and the toxic effect of flavedo chemical substances, mainly the essential oils (Back & Pemberton, 1915;Greany et al., 1983;Salvatore et al., 2004;Papachristos et al., 2008), are proposed as the major resistance mechanisms. The peel elasticity and the thickness also contribute to resistance Muthuthantri, 2013) and interfere with the ovipositional behaviour of the female (Greany, 1989;Leyva et al., 1991;Birke et al., 2006). If the albedo is thick, the larvae can avoid the toxicity of the flavedo in their way to the pulp (Greany, 1989;Leyva et al., 1991;Birke et al., 2006). This has been reported for Ceratitis capitata (Wiedemann) (Papachristos et al., 2008) and for Anastrepha ludens (Loew), the long ovipositor has been accounted for its capacity to develop in citrus (Birke et al., 2006). In contrast, Anastrepha suspensa (Loew) only lays its eggs in the flavedo layer of the grapefruit (Citrus paradisi Macfadyen) peel Eskafi, 1988;R€ ossler & Greany, 1990) and cannot avoid toxic essential oils with concomitantly high egg and larval mortalities (Ortu, 1978;Greany et al., 1983Greany et al., , 1985. Maturation and post-harvest storage time lead to physical and chemical changes that affect fruit immunity and concerns plant regulatory organizations. Particularly in citrus, the chemical composition of the peel changes quantitatively and qualitatively during maturation, greatly affecting its toxic properties (Attaway et al., 1967(Attaway et al., , 1968Greany et al., 1983;Greany, 1989;Flamini & Cioni, 2010). Changes in the chemical composition also occur when the fruit is removed from the plant and stored before commercialization. This has been associated with a decrease in the amount of aldehydes, alcohols, and coumarins present in extracts of lemon, Citrus limon (L.) Burm., peel (Salvatore et al., 2004).
Given the quarantine and therefore economic relevance of the exact host determination, there are several protocols for determining host status (Couey & Chew, 1986;Cowley et al., 1992;APPPC (Asia and Pacific Plant Protection Commission), 2005;Follett & Neven, 2006;Aluja & Mangan, 2008). Although recent studies argue that the best approach is to work under field conditions (Aluja & Mangan, 2008), laboratory tests are useful when their aim is to determine the mechanisms involved in host resistance to pest infestation. In addition, laboratory tests are useful to explore if the resistance offered by the plant is lost by chemical and physical changes after harvest (Salvatore et al., 2004;Mangan & Moreno, 2012).
In the case of lemon and A. fraterculus, development was not completed in field and laboratory infestation trials . Moreover, field surveys and packing house inspections found no evidence of naturally occurring infestations . Those results were taken as evidence for the non-host status of this citrus species. In spite of this, the mechanisms involved are still poorly understood. In particular, it was not assessed whether females lay eggs in this fruit and, if oviposition occurs, what depth of the peel is preferred.
Considering that in Argentina A. fraterculus is present in areas of citrus production, our objective was to analyse the insect-plant relationship between three citrus species and this fruit fly. Particularly, we investigated the effect of: (1) citrus species on oviposition behaviour and immature development, (2) citrus species on oviposition preference and on the location of the eggs at different depth in the citrus peel, and (3) harvest season and post-harvest storage time on oviposition behaviour and immature development in lemon. In all cases, we determined the chemical composition of the citrus peel.
Insects
Adult females of A. fraterculus were obtained from a colony established at the Agriculture Zoology laboratories of Estaci on Experimental Agroindustrial Obispo Colombres (EEAOC), Tucum an, Argentina. This colony was initiated in 1997 with pupae obtained from infested guavas (Psidium guajava L.), collected in the vicinity of Taf ı Viejo, Tucum an province (northwest Argentina) (Jaldo, 2001). At the beginning of the trials, it had ca. 100 generations under artificial rearing. Rearing follows the procedures described in Jaldo et al. (2001) and Vera et al. (2007) with oviposition occurring through a cloth covered with a thin silicon layer. To ensure that most of the experimental females were already inseminated, we took females from the rearing cages during their peak of oviposition and from which egg hatchability was confirmed to be above 80%.
Plant material
Species and varieties. The citrus species used were lemon [C. limon (L.)] cv. Eureka, grapefruit (C. paradisi Macfadyen) cv. Foster seedless, and sweet orange [Citrus sinensis (L.) Osbeck] cv. Valencia, Lemon was harvested from two localities: the experimental field at EEAOC (26°47 0 15.45″S, 65°11 0 23.72″W) in Las Talitas, Tucum an (experiments 1 and 2), and the commercial orchard El Rodeo in Burruyac u Department, Tucum an (26°39 0 28.56″ S, 64°55 0 25.36″W) (experiment 3). For the latter experiment, fruit was harvested when it was light green at two different times (referred to as summer and winter fruit). Grapefruit was harvested from the experimental field at EEAOC. Sweet orange was harvested from the commercial orchard El Carmen, in San Isidro de Lules Department (26°55 0 16″S, 65°19 0 33″W), Tucum an. In all cases, fruits were randomly selected from various plants. Special caution was taken to avoid collecting damaged fruit or fruit with symptoms of illness or pests. The number of harvested fruits and the time they were stored depended on the experiment.
Fruit peel characteristics. To provide an assessment of fruit suitability for immature fly development, we assessed physical parameters of the peel from fresh fruit of the three citrus species. The thickness of the flavedo and albedo layers, and the number of oil glands in the flavedo were recorded. Flavedo and albedo thickness were measured with a Vernier calliper upon the equatorial diameter. The density of the oil glands in each citrus fruit species was determined by counting the oil glands in a 1-cm 2 portion of the peel using a stereoscopic magnifying glass. Three counts were made per fruit and the values were averaged. These recordings were performed for experiments 1 and 2.
Extraction and chemical characterization of ether extracts. Another group of 10 fruits was used to extract the compounds from the peel for its chemical characterization. One day after harvest, the fruit was washed with tap water and dried at room temperature. The flavedo was removed from the peel with a metal grater and placed in a glass Erlenmeyer flask. Peel compounds were extracted by immersion in ethyl ether. The flask was covered with a cotton plug and was shaken for 40 min. Extracts were filtered and the solvent was evaporated using a rotary evaporator at room temperature.
Chemical characterization of the extracts was performed at the Laboratory for Research and Analytical Services (LISA) of the Facultad de Bioqu ımica, Qu ımica y Farmacia, Universidad Nacional de Tucum an (FBQF, UNT, Tucum an, Argentina). The ether extracts were analysed by gas chromatography (GC) using an Ultra Trace gas chromatograph with DB-1 column-MS 25 9 0.25 mm i.d., temperature ramp of 60 to 300°C (3°C per min), and an injection temperature of 270°C. The mass spectrometer (MS) used was a Polaris Q, EI (+) 70 eV (ThermoElectron, Austin, TX, USA),) with an ion trap analyzer as detector. Individual peaks were identified by the retention time and retention rates. Two or three injections were performed for each extract. The results were processed to obtain the percentage of the area in the spectrogram occupied by each compound and this value was averaged in each extract. Identification of the components was performed by comparison of their retention index (RI) with reference to a homologous series of n-alkanes (C9-C25), by comparing their mass spectra with those reported in literature, and by computer matching with the Adams (2001) library.
Experiments
All experiments were performed in the laboratory at 25 AE 5°C, 65 AE 5% r.h, and L12:D12 photoperiod. Gravid females were at their peak of the oviposition period. Experimental cages consisted of 15-l transparent plastic cages which were provided with the standard adult diet containing sugar, hydrolysed yeast (MP Biomedicals, Santa Ana, CA, USA), hydrolysed maize (Gluten Meal; ARCOR, Tucum an, Argentina), and vitamin E (Parapharm, Buenos Aires, Argentina) (Jaldo et al., 2001). Before being placed in the cages, each fruit was washed with tap water. For experiments 1 and 2, fruits were used 24 h after harvest; for experiment 3, various time intervals after harvest were evaluated. In all cases, fruit was removed from the cages 24 h after the beginning of the exposure to the females. Experiment 1. The effect of citrus host (lemon, sweet orange, or grapefruit) on oviposition behaviour and immature development was determined in a no-choice experiment. Six fruits of a given species and 120 females were placed in each experimental cage and six cages (replicates) were set up for each fruit species. On the following day, the fruits were removed from the cages. Fruit coming from the six replicates for each citrus species were grouped and randomly assigned to one of two groups.
In the first group, fruits were placed into a plastic tray and covered with a voile fabric and stored in a chamber at 26°C and 60% r.h. for 5-7 days to allow embryonic development. After this period, fruit was dissected with a scalpel and the flavedo was removed from the peel. With the aid of a stereomicroscope, the number of successful oviposition events (clutch) per fruit, the number of eggs per clutch (clutch size), the number of egg shells or chorions (embryo completed development and the larvae initiated its way to the pulp), and the number of turgid eggs that failed to hatch (non-fertilized eggs or with dead embryos) were registered. Because the chorion of A. fraterculus is translucent, it was not possible to assess egg hatchability accurately in the albedo region. Some fruit were in poor conditions, with fungal infection, and were not evaluated.
In the second group, fruits were weighed and placed individually in plastic containers with sterilized sand as pupation substrate. Each container was covered with a voile fabric and incubated for 21 days. The sand was sieved and the number of pupae recovered was recorded every 7 days. Experiment 2. Oviposition preference for lemon and grapefruit and the location of the eggs within the citrus peel were assessed in choice and no-choice experiments. In each experimental cage (as described above), two fruits were placed in opposite corners. In the choice experiment, one lemon and one grapefruit were placed in the cage; in the no-choice experiment, two fruits belonging to the same citrus species were placed. In both cases, 10 females were released in each cage. Exposure time was 48 h. Ten experimental cages (independent replicates) of each situation (choice and no-choice for each fruit species) were set up. After exposure, the fruits were removed from the cages and assigned to one of three groups. The first group was used to assess oviposition preference and involved the choice cages. To prevent development and allow easy identification of the eggs, fruits were maintained at 2-5°C. On the following days, the number and location of the successful ovipositions within the peel (inside the essential oil glands or in the space between glands for the flavedo or in the albedo), as well as clutch size were registered using a stereomicroscope. This procedure was carried out in three randomly selected squares of the peel (3 9 3 cm). Data obtained from the three areas were summed to obtain the variables to be analysed. The second group of fruits, obtained from the no-choice experiments, was used to assess hatching. Fruits were stored in a chamber at 25 AE 2°C and 70% r.h. to allow embryonic development. After 7 days of incubation, the number of chorions and turgid eggs was determined until 10 eggs were counted for each of the three peel layers. Hatch percentage was estimated by dividing the number of chorions on the total number of eggs. The third group, also from the no-choice experiments, was placed on individual sandboxes as described in experiment 1 to allow larval development. After incubation, the number of pupae per fruit was recorded.
Experiment 3. The effect of harvest season and postharvest storage time in lemon cv. Eureka on oviposition and immature development was determined in a nochoice experiment. Methodology was similar as used in experiment 1. Two harvest periods (summer and winter) and five post-harvest storage times (1 day, 2, 4, 6, and 10 weeks) were evaluated. The experiments involved two fruit seasons within each harvest time (two replicates). After 7 days of incubation, fruits were dissected and the same variables as in experiment 1 were recorded. When a given fruit had less than 10 eggs, it was not included in the analysis of egg hatch percentage.
Data analysis
Experiments 1 and 3. Statistical analysis was performed using ANOVA. Depending on the experiment, the fixed factors were, citrus species (lemon, orange, or grapefruit), harvest season (summer or winter), or post-harvest storage time (1 day, 2, 4, 6, or 10 weeks). The dependent variables were number of successful oviposition events per fruit, number of eggs per clutch, egg hatch percentage, and number of pupae per kg of fruit. In all cases, the assumptions of normality and homoscedasticity were verified. Means were separated by multiple comparisons Tukey tests (a = 0.05).
Experiment 2. To evaluate the oviposition preference for lemon or grapefruit, we used ANOVA with two fixed factors: citrus species (lemon or grapefruit) and test condition (choice or no-choice). Response variables were the number of successful oviposition events (clutches) and clutch size. To assess the impact of citrus species on egg location, we also applied ANOVA with fruit species and peel region as fixed factors and number of clutches and clutch size as response variables. To assess the impact of clutch location on egg hatchability, we followed the same procedure: ANOVA with citrus species and clutch position (in this case, in the essential oil's gland or between the glands) as fixed factors. The response variable was egg hatchability. Data for choice and no-choice experiments were pooled. In all cases, the assumptions of normality and homoscedasticity were verified.
When fruit peel attributes were recorded, we compared the different variables by means of an ANOVA (experiment 1) or Student's t test (experiment 2) using fruit species as fixed factor and the thickness of the flavedo and the albedo as well as the number of essential oil glands per cm 2 as response variables. In experiment 1, means were separated by multiple comparisons Tukey tests (a = 0.05). All analyses were performed with InfoStat statistical software (Di Rienzo et al., 2012).
Experiment 1. Effect of citrus species on oviposition behaviour and immature development
Fruit peel characteristics. The three citrus species presented particular physical and chemical attributes in their peels (Table 1). Whereas the thickness of the flavedo was similar for the three citrus species (F 2,22 = 1.54, P = 0.24), the thickness of the albedo differed among species (F 2,22 = 39.94, P<0.001); grapefruit had the thickest albedo, whereas that of sweet orange and lemon were similar to each other. Also the number of glands per cm 2 was different among species (F 2,22 = 63.65, P<0.0001); the highest value occurred in sweet orange, whereas lemon and grapefruit presented similar values.
Oviposition behaviour and immature development. The number of successful oviposition events (clutches) was not affected by citrus species (F 2,37 = 0.88, P = 0.42). Clutch size was marginally affected by citrus species (F 2,37 = 3.22, P = 0.051). As a trend, lemon showed higher values than grapefruit (Table 3). Egg hatch rate was affected by citrus species (F 2,37 = 4.11, P = 0.025); this value was higher for grapefruit than for lemon, and for sweet orange it was intermediate ( Figure 1). In lemon and orange, all larvae were found dead 5 days after incubation. In grapefruit, after 5 days of incubation, we visualized the galleries made by the larvae on their way to the pulp. Pupae were recovered only from grapefruit with an average of 62.9 AE 12.1 pupae kg À1 of fruit (Table 4).
Experiment 2. Effect of fruit species on oviposition preference and effect of fruit peel characteristics on the location of eggs and immature development Fruit peel characteristics. Flavedo thickness was not different between lemon and grapefruit (T = 0.38, P = 0.72). The albedo from grapefruit was significantly thicker than that from lemon (T = 9.29, P<0.001). The number of glands per cm 2 was also significantly higher in grapefruit than in lemon (T = 4.67, P = 0.0016).
Chemical characterization of ether extracts from lemon and grapefruit. Thirty-two compounds were detected by GC and GC-MS in the lemon extract, and only 22 in the grapefruit extract (Table 5). The main chemical groups present in both extracts were monoterpene hydrocarbons (85.6 and 90.8% in lemon and grapefruit extracts, respectively), sesquiterpenes (4.0 and 1.6%), alcohols (2.2 and 0.24%), aldehydes (3.4 and 0.35%), and coumarins (0.28 and 0.10%). Among hydrocarbon monoterpenes, Means within a column followed by different letters differ significantly (one-way ANOVA followed by Tukey's test: P<0.05). limonene was the main component in both extracts (88.5% in grapefruit, 64.3% in lemon). Other main components were c-terpinene (11.0 and 0.23%) and bpinene (5.9 and 0.34%). Lemon extract showed 1.1% of neral and 1.7% of geranial, whereas these compounds were traces in the extract from grapefruit.
Location of the clutch at different depths of citrus peel. The number of clutches per sample unit was affected by citrus species (F 1,54 = 7.8, P = 0.0072) as well as its location in the citrus peel (F 2,54 = 6.36, P = 0.0033). The interaction between these factors was not significant (F 1,20 = 0.13, P = 0.88). Most clutches were recorded in the flavedo area of grapefruit, first in the space between the oil glands and then in the oil glands. The lowest value was recorded in the albedo of lemon (Table 7). The number of eggs per clutch was influenced by its location in the citrus peel (F 2,43 = 8.4, P = 0.0008), whereas citrus species did not affect this variable (F 1,43 = 0.229, P = 0.64), and the interaction of these factors was not significant (F 1,43 = 0.13, P = 0.89). Means within a column followed by different letters differ significantly (one-way ANOVA followed by Tukey's test: P<0.05). n, number of fruit tested. Anastrepha fraterculus females laid more eggs per clutch in the albedo than in the flavedo (Table 7).
Immatures development. Egg hatchability was affected by citrus species (F 1,10 = 31.36) and clutch location (F 1,10 = 56.03, both P<0.001) (Figure 2). In lemon, the percentage of egg hatch was significantly lower when the eggs were laid in the glands than when they were laid between the glands. In grapefruit, hatch rates were similar in and between the glands. At the time of recording this variable, all larvae were dead in lemon. In grapefruit, we observed the galleries made by the larvae on their way to the pulp. Pupae were recovered only in grapefruit (93.8 AE 19.7 pupae kg À1 of fruit).
Experiment 3. Effect of harvest season and post-harvest storage time on oviposition behaviour and immature development in lemon
Chemical characterization of ether extracts from the peel. The GC-MS analysis indicated differences in the relative amounts of the compounds present in the extracts of the lemon peel between the seasons in which fruit was harvested and the time it was stored after harvest (Table 8). In all cases, the main compound was limonene; for each harvest season, its percentage did not show significant variation as post-harvest storage time passed. The percentage of monoterpene hydrocarbons was not different between the harvest seasons and post-harvest storage times. In lemons harvested during winter, the percentage of hydrocarbons, sesquiterpenes, and oxygenated compounds decreased to half of their initial values after 10 weeks of post-harvest storage time (from 3.1 to 1.6%, and from 5.1 to 2.6%, respectively). For lemons harvested during summer, the percentage of sesquiterpenes doubled after 10 weeks (from 1.8 to 3.6%), whereas the percentage of oxygenates remained constant. The percentage of coumarins was affected for post-harvest storage time, decreasing from 0.25 to 0.09% in winter lemons (Table 8).
Harvest season and post-harvest storage time. The number of clutches per fruit was affected by harvest season (F 1,132 = 7.29, P = 0.0078) and by post-harvest storage time (F 4,132 = 3.84, P = 0.0055). The interaction of these two factors was not significant (F 4,132 = 0.91, P>0.05). Lemons harvested in summer had more clutches than lemons harvested in winter (Table 9). Lemons stored for 4 weeks before being exposed to the females had more clutches than lemons stored for 6 weeks. Clutch size was not affected, neither by harvest season (F 1,132 = 0.89, Means within a column followed by different letters differ significantly (two-way ANOVA followed by Tukey's test: P<0.05). (Table 9). Egg hatchability was neither affected by harvest season (F 1,102 = 0.38, P = 0.54), nor by post-harvest storage time (F 4,102 = 0.91, P = 0.46). The interaction between the two factors was significant (F 4,102 = 3.42, P = 0.011). Lemon harvested in winter and stored for 6 weeks had the highest egg hatch percentage (Figure 3).
Discussion
We explored the behavioural and developmental effects of exposure to three citrus species on A. frater- Table 8 Chemical composition and mean (AE SE) relative percentages (area) of the components in ether extracts of lemon cv. Eureka harvested in winter (W) or summer (S), and tested in the forced infestation trials, 1 day (W0, S0), 6 weeks (W6, S6), and 10 weeks (W10, S10) after sample harvest ( culus. We found evidence that citrus species conditions oviposition behaviour and affects survival of immature stages. Although females laid eggs in lemon, sweet orange, and grapefruit, the way in which this was done differed and development was not always completed. In orange and lemon, larvae were found dead close to the oviposition areas. When given a choice, females preferred grapefruit over lemon. Most eggs were laid in the flavedo but in the albedo the clutch size was higher. Lemon resistance was not affected by harvest season, nor by fruit storage time. Anastrepha fraterculus laid eggs in lemon, orange, and grapefruit. The number of clutches per fruit was equal among species, but clutch size was higher in lemon and orange than in grapefruit. Egg hatchability was higher in grapefruit and pupae were obtained only in this fruit species. This indicates that even when oviposition occurs, development is not possible in all citrus species. D ıaz-Fleischer & found that clutch size in A. ludens varied with host firmness and degree of ripeness, and they considered this a strategy to compensate for the high mortality of larvae in a bad host. Similar results were found by da Silva-Branco et al. (2000) in C. capitata: larval survival in citrus increased as clutch size increased. The high number of dead larvae found in lemon and orange suggested that toxic properties kill the larvae before they reach the pulp (Greany, 1989;Leyva et al., 1991;Birke et al., 2006). Differences in fruit species suitability are also reflected in infestation patterns in the field. In Argentina, there are records of recovery of A. fraterculus pupae from mandarin, Citrus reticulata Blanco, bitter orange, Citrus aurantium L. (Rootstock), grapefruit, and sweet orange (Ovruski et al., 2003;Schliserman & Ovruski, 2004;Segura et al., 2006;Oroño et al., 2008); unfortunately, not all records indicate the variety of fruit species analysed. Regarding lemon, there are no records of naturally occurring infestations .
When given a choice, A. fraterculus females preferred grapefruit over lemon. This was reflected by the higher number of clutches per unit area in grapefruit compared to lemon. However, this did not occur under no-choice conditions. Studies in Mexican populations of A. fraterculus demonstrated that this morphotype chooses between hosts of different quality, based on the number of visits made to a particular fruit species and the number of oviposition attempts . When grapefruit cv. Ruby Red and orange cv. Valencia were offered, females laid eggs at a very low frequency, only in the laboratory, under no-choice conditions. Field studies conducted in Argentina also showed that oviposition behaviour is affected by fruit species (Oroño, 2010). In spite of this, the number of eggs per clutch was equal regardless of the host and the trial situation. This is contrary to what was found in our first experiment and previous studies in which females modulate the number of eggs per clutch depending on the quality (da Silva-Branco et al., 2000;Aluja et al., 2003;D ıaz-Fleischer & Aluja, 2003) and the variety of the host .
We found that females placed their egg clutches differentially within the layers of the peel. Most eggs were located in the flavedo (almost 90% in grapefruit, 85% in lemon), and within this region, the space between the oil glands was preferred; the other eggs were located in the albedo. Similar results were presented by . These authors evaluated the host status of sweet orange (three varieties), bitter orange, and lemon for C. capitata and found that the percentage of eggs laid in the flavedo and albedo depended on citrus variety. Aluja & Mangan (2008) suggested that size, colour, penetrability, and phenological stage of the fruit and the presence of host-marking pheromones determine the oviposition behaviour in females. The differences found in the number of clutches and their location, indicate that A. fraterculus females can modulate oviposition behaviour once the fruit has been accepted as substrate. Interestingly, within a given fruit, the largest clutch sizes were registered in the albedo, the most favourable region for embryo development. The presence of eggs in the albedo was recorded for C. capitata in sweet orange, bitter orange, and lemon ), for A. ludens in grapefruit (Birke et al., 2006) and lemon (Mangan & Moreno, 2012), for Anastrepha obliqua (Macquart) in grapefruit (Mangan et al., 2011a), and for Anastrepha serpentina (Wiedemann) in grapefruit and sweet orange (Mangan et al., 2011b). The capacity of females to reach this area of the peel has been linked to the length of the ovipositor (Birke et al., 2006). Anastrepha fraterculus has an intermediate ovipositor length of 1.65-2.1 mm (Stone, 1942), in between that of C. capitata (0.9-1.3 mm; Delrio & Cocco, 2012) and A. ludens (3.4-4.7 mm; Stone, 1942).
Egg hatchability was affected by the location of the eggs in lemon but not in grapefruit. Eggs laid inside the glands hatched <15% in lemon and >80% in grapefruit. The results for lemon are in agreement with those of Greany et al. (1983), who found that egg hatchability of A. suspensa was significantly higher between glands than within, in lemon cvs Lisbon and Eureka, white and pink grapefruit, and Temple orange. The high egg hatchability found in grapefruit in our study was unexpected but may be explained by the high number of eggs laid in this species (29 more than in lemon, as inferred from the differences in the number of clutches). D ıaz-Fleischer & proposed that the metabolic heat produced by a large number of larvae can create a microenvironment that favours the growth of bacteria and these could metabolize the toxic compounds present in oil glands. However, this needs confirmation.
The equal number of clutches on lemon and grapefruit in no-choice trials suggests that, under certain conditions, A. fraterculus females laid their eggs on a poor host or even in a non-host plant. Many phytophagous insects lay their eggs on plants on which the larvae do not reach the adult stage (Krainacker et al., 1987). Internal physiologi-cal changes due to shortage of the preferred host have been proposed as one of the main reasons. When an optimal host is hard to find, it becomes important to have some 'flexibility' to use a sub-optimal host. Laying eggs in poor host plants may also have advantages (Craig et al., 1989), for example, when competition for food is minimized and/or when the energetic cost of searching for the optimal host is high (Mayhew, 1997;Papaj, 2000). In extreme cases, when the female lays its eggs in an atypical plant, it exposes dozens or hundreds of them to a new host, increasing the possibility of exploring a new feeding environment. This phenomenon has been postulated as one possible basis for the population divergence observed within this species (Rull et al., 2013).
Unsuitability of lemon as a medium to complete development was neither affected by the harvest season nor by storage duration of the fruit after harvest. Although citrus fruits stop the ripening process once harvested, significant changes occur in the chemical composition of essential oils of the peel as well as its hardness (Bodenheimer, 1951). This may have an impact on the oviposition behaviour and development of some fruit fly species. Our third experiment indicated differences in the number of A. fraterculus clutches; more clutches were recorded for lemons harvested in summer, though complete development was not achieved.
The physical and chemical characteristics of the citrus peel differed among species and these differences may have affected the levels of resistance to infestation by A. fraterculus. Thickness of the flavedo did not differ among the citrus species evaluated, but the albedo was thicker in grapefruit. Albedo thickness may be directly correlated with the ability of development of eggs and larvae, as grapefruit was the only species from which pupae were obtained. Interestingly, clutch size was higher in albedo than in flavedo. For other species of the genus Anastrepha, there are records of high mortality in the albedo, caused by some chemical compounds present in this region. In A. obliqua mortality occurs both in the flavedo and albedo, whereas in A. ludens it occurs mostly in the albedo (Mangan et al., 2011b). Regarding the chemical attributes, the spectrogram area represented by the hydrocarbon monoterpenes was (above) 85% in grapefruit, 90% in lemon, and 98% in orange. In addition, grapefruit had a large variety of coumarins. Essential oils perform an important function as attractants, repellents, and toxins. Although attraction for oviposition could have been elicited by the large number of coumarins present in grapefruit, toxicity could have been generated by monoterpenes and aldehydes as shown in other fruit flies (Salvatore et al., 2004;) and recently in A. fraterculus (Ruiz et al., 2014). The differences between grapefruit and lemon in the areas occupied by monoterpene hydrocarbons may explain the different egg hatchability in lemon and grapefruit. We also found differences in oil composition of these species. The content of secondary metabolites in plants varies between locations and years, and is influenced by factors such as temperature, humidity, and soil composition (Isman et al., 2007). For example, the concentration of 1,8-cineole and a-pinene ranged from 7 to 55% and from 11 to 30%, respectively, in rosemary plants from different locations in Italia (Flamini et al., 2002). There are similar examples in basil (Pascual-Villalobos & Ballesta-Acosta, 2003) and myrtle (Flamini et al., 2004). During storage of lemon, the amounts of some compounds that are reported as highly toxic to other fruit fly species decreased, such as geranial, b-bisabolene, and citroptene (Salvatore et al., 2004;. However, but this did not improve the status of this fruit as a host much, because even under the most favourable conditions, development was not completed. Our results suggest that A. fraterculus females recognize the citrus species, modulate the number of clutches accordingly, and locate their clutches in the layers of the peel where embryonic development is favoured. All this proposes that female behaviour evolved to maximize reproductive success. Yet, females still lay eggs in nonfavoured hosts suggesting some flexibility due to host availability. Such findings have implications for the study of insect-plant interactions and, more particularly, in determining the host status of lemon cv. Eureka. The inability to obtain pupae in lemon, even when oviposition and embryonic development occurred, supports the nonhost status of this fruit. These results were obtained under laboratory conditions, which are expected to favour complete development. The lack of development in fruit that was stored for several weeks gives additional quarantine security, as it indicates that lemon does not become susceptible to infestation after harvest. Sweet orange was already reported as a non-host of the Mexican morphotype of A. fraterculus. Given that the Mexican and the Brazilian 1 morphotypes (Argentinean populations belong to Brazilian 1 morphotype) have the same ovipositor length (Hern andez-Ortiz et al., 2004), we propose more comprehensive studies to define a more accurate host status of sweet orange for Argentine A. fraterculus. The complete larval mortality close to the egg shells in lemon and orange suggest that chemical resistance acts at the early stages of development and compounds present in the flavedo of the peel are the most likely responsible for this toxicity (Ruiz, 2013;Ruiz et al., 2014). We trust this information is of practical importance at the time of bilateral negotiations between fruit-producing areas and pest-free importing countries. | v3-fos |
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} | s2 | Agronomic Management Strategies to Reduce the Yield Loss Associated with Spring Harvested Corn in Ontario
Some growers in northern corn (Zea mays L.) producing regions forgo the typical autumn harvest for various reasons, but not without the risk of significant yield loss. Therefore, strategies are needed for managing the risks to yield when harvesting corn in spring. Field experiments, with various management strategies, were initiated in Ontario, Canada near Belmont and Ridgetown in 2009 and near Belmont, Ridgetown, and Lucan in 2010. Management strategies investigated the use of hybrids with a range in maturity, the use of standard and reduced plant populations, and the use of a foliar fungicide applied around tasseling. The parameters examined were stay-green in autumn, lodging in spring, and grain yield, moisture, and test weight of corn harvested in autumn and spring. Standard corn production practices consist of using a full-season hybrid planted at 80,000 plants∙ha−1 with no late-season fungicide application; however, if over-wintered at Belmont, corn managed using these practices resulted in a 23.1% yield loss (12.1 vs 9.3 Mg∙ha−1) averaged across years when the crop was harvested in the spring. An overwintering management strategy for corn was identified, which consisted of planting at a reduced plant population (60,000 plants∙ha−1) and spraying the crop with QUILT® (azoxystrobin + propiconazole at 200 g a.i. ha−1) at the VT to R1 growth stage. Averaged across all hybrids, this strategy minimized yield losses through improvements on corn standability with only a 3.5% yield loss at Ridgetown and a 13.2% yield loss at Belmont. Furthermore, grain test weights for corn with the overwintering strategy were similar to or greater than corn overwintered with the standard production practice. However, weather conditions have the potential to overwhelm any management strategy. In spite of the favorable data indicating reduced risks with a spring harvest, lodging was still higher than expected and yield losses would likely be unacceptable for most growers to make a spring corn harvest a widely accepted practice, unless autumn grain moistures are extremely high, drying charges Corresponding author. K. J. Mahoney et al. 373 are high, and if stalk strength going into the winter was exceptional.
Introduction
Growers in the northern corn (Zea mays L.) producing regions of North America can encounter various management challenges. While selecting full-season or later maturing corn hybrids can maximize yield [1]- [3], later maturity hybrids can have high grain moisture content at harvest (more than 30% to 35%), contributing to increased drying costs [4] and low grain test weights. Increased autumn precipitation, a trend observed in eastern Canada and the northeastern United States [5] [6], can also delay harvest and could contribute to high grain moisture content. As a result, growers have devised hybrid selection and grain drying strategies in an attempt to maximize economic returns with an acceptable level of risk. However, if soil moisture conditions make a timely harvest unfeasible [7] [8] or if volatility in the corn market and/or energy prices makes drying high-moisture corn cost prohibitive, growers may need an alternative strategy to minimize risk. A practice used by some growers is to forgo the typical autumn harvest, allow the corn to dry down in the field over winter, and harvest the crop in spring when the harvested grain does not incur drying costs. While alleviating the added expense of drying high-moisture corn and storing dry corn over winter, there can be increased risk of lodging over winter, impacting crop harvestability and grain yield [9].
Management practices currently exist which can improve corn standabilty (i.e., stalk or root lodging). For example, growers can manage lodging by selecting hybrids rated for superior stalk strength and by selecting later maturing hybrids. In an Ohio study, standability improved with a later maturing hybrid with an above average stalk strength rating during delayed autumn harvests compared to an earlier maturity hybrid with a similar stalk strength rating [7]. In the absence of concerns with the high grain moisture content associated with later maturing hybrids, the selection of a full-season or later maturing hybrid could be a management strategy to capitalize on improved standability that would accompany a decision to forgo the typical autumn harvest. Furthermore, growers can also alter seeding rates to manage lodging since the relationship between increased plant densities and increased lodging is well documented [10]- [15]. Due to concerns with lodging from overwintering corn, a reduction in plant density could improve standability for a spring harvest. For example, stalk lodging during a harvest delayed until early to mid-December [7] or late March [8] was considerably reduced when using a low plant density (i.e., 59,000 plants•ha −1 ) compared to using higher plant densities. Lastly, foliar fungicides applied around tasseling (e.g., VT to R2 growth stage) have been shown to delay leaf senescence and improve stalk health [16] [17], which could contribute to improved standability.
Very limited research has been performed on managing corn with the intent of overwintering for a spring harvest. Wisconsin data from 2000 and 2001 indicated that yield losses during a spring harvest can vary widely with 38% to 65% yield loss during a winter with heavy snow cover and only 7% to 10% yield loss in a winter with little snow cover [9]. However, since that data were reported, newer hybrid trait technologies, which have become adopted extensively [18]- [20], could have the potential to also improve corn standability over the winter. For example, Bt (Bacillus thuringiensis) traits for various insect pest resistance, which have been shown to reduce stalk and root lodging [11] [21]- [24], are commonly stacked in hybrids to include herbicide resistance. Use of these highly resistant hybrids [18] may reduce or eliminate the use of herbicides with more injurious modes of action (e.g., phenoxy or synthetic auxin herbicides) that may weaken stalks and increase lodging [25] and reduce corn yield [26]. When coupled with genetics for improved stalk strength, the adoption of hybrids with stacked resistance traits might improve the likelihood of successfully overwintering corn for a spring harvest. Unfortunately, management recommendations developed from research trials do not exist for minimizing the risks associated with harvesting corn in spring. However, management strategies for spring harvesting corn could be developed using technological innovations that are currently available to corn growers. Therefore, the objectives of this study were to: 1) determine the effects of hybrid maturity, plant population, foliar fungicide application, and harvest timing on grain yield and standability, and 2) identify potential management opportunities for overwintering corn.
Study Establishment
Field experiments were initiated in 2009 and 2010 on five separate locations in southern Ontario, Canada. Experiments were installed on two farm fields near Belmont (42˚87'N, 81˚07'W) and Ridgetown, ON (42˚46'N, 81˚87'W) in 2009, and on three other farm fields near Belmont (42˚87'N, 81˚08'W), Ridgetown (42˚46'N 81˚89'W), and Lucan, ON (43˚20'N, 81˚40'W) in 2010. These locations were selected to not only represent major corn growing areas of the province, but to test treatments in contrasting winter environments. For example, winters at Ridgetown tend to be less harsh (e.g., moderate temperatures with less snow) than at Belmont. Compared to Belmont and Ridgetown, Lucan usually receives more snow because it is situated in the "snowbelt" region of southwest Ontario, which is leeward of Lake Huron. At each location, the treatments were arranged in a split-plot design with three splits and replicated four times. The main plot factor was harvest timing (autumn or spring), the first split was plant population (60,000 or 80,000 plants•ha −1 ), the second split was QUILT ® (azoxystrobin + propiconazole) foliar fungicide (0 or 200 g a.i. ha −1 ) applied at the VT to R1 growth stage, and the third split included three corn hybrids with different maturities. The hybrids that were selected for each location covered a range of maturity: early, full-season, and late (approximately 100 Crop Heat Units [27] later than the full-season). All hybrids exhibited good yield potential, standability, and stacked resistance traits ( Table 1). The corn was seeded into rows spaced 0.75-m apart to create experimental units 4 rows wide by 35-m long. A buffer strip of 4 rows was used between each foliar fungicide split to minimize interference from the sprayer at tasseling. The experiments were designed to mimic farm field-scale environments by reducing field-edge effects from wind and snow. For example, an unharvested border of at least 12 rows was maintained around the experimental area at each field location, and an additional 4 rows of border were left unharvested around the overwintered corn. Within the unharvested border rows, 6 rows were harvested for trapping blowing snow during the winter.
Fields at all locations were planted at an optimal timing in early May of each year. Both fields near Belmont followed winter wheat underseeded to red clover; these fields were moldboard plowed in the autumn and cultivated twice in the spring for seedbed preparation. The previous crop for the fields near Ridgetown was soybean and the seedbed was prepared by cultivating twice in the spring. At the Lucan site, the previous crop was wheat and the field was moldboard plowed in the previous fall and received two passes with a cultivator in the spring. Soil tests were in the "medium" range for both phosphorus and potassium with a pH around 7 at each field location. A liquid starter pop-up fertilizer (6-24-6) was applied in-furrow at 56 L•ha −1 during both years at Belmont and 8-32-16 was applied at 150 kg•ha −1 in a band 5 cm to the side and 5 cm below the seed at Ridgetown during both years and at Lucan. Nitrogen was applied preplant or sidedress as 28-0-0 to achieve approximately 150 kg N ha −1 total in all fields. Weeds were controlled using recommended preplant incorporated and post emergence herbicide applications [28]. The fungicide treatment was applied when the latest hybrid reached VT growth
Data Collection and Analysis
Stay-green was estimated visually as the percentage of the total leaf area remaining green in all plots in late September. In the spring, the lodging percentage was calculated by recording the number of stalks lodged by more than 45˚ or broken below the ear found within three, 5-m lengths of the two center rows of all overwintered plots. Regardless of the harvest timing, corn was harvested from the middle two rows of each four-rowplot. Grain yields, grain moistures, and test weights were measured on small-plot combines equipped with Harvest Master Grain Gage Classic grain measurement systems (Juniper Systems, Inc., Logan, UT). All data were analyzed using PROC MIXED (SAS Ver. 9.2, SAS Institute Inc., Cary, NC). Treatment effects were similar across years within each of the Belmont and Ridgetown locations (P > 0.25), but the treatment responses were different between Belmont and Ridgetown; therefore, years within each location were combined and the locations were analyzed separately in the final analysis. In this analysis, the fixed effects included harvest timing, plant population, fungicide, hybrid, and all of their interactions. The random effects included replication × harvest timing within year, replication × harvest timing × population within year, and replication × harvest timing × population × fungicide within year. Significance of fixed effects was tested using an F-test and random effects were tested using a Z-test of the variance estimate. PROC UNIVARIATE in SAS was used to test data for normality and homogeneity of variance. For grain yield, residual variances were different across harvest timing and year at Belmont and Ridgetown, which violated an assumption of ANOVA. Thus, these heterogeneous variances were modeled in PROC MIXED using the repeated statement with group = year × harvest timing. Satterthwaite's approximation was used to estimate degrees of freedom. Residuals for grain moisture and test weight data were normalized using a transformation [(n + 0.1) 0.5 ] before analysis; means were backtransformed for presentation purposes. No transformations were necessary for other parameters. The sums of squares for interactions were partitioned across harvest timing using the SLICE option in PROC MIXED [29]. Means were separated within each slice using Fisher's Protected LSD at P = 0.05.
Results and Discussion
Four out of the five field locations (Belmont and Ridgetown, initiated in 2009 and 2010) were harvested in the following spring. Data from the Lucan location were discarded because nearly 100% of the corn plants left to overwinter were pulled to the ground due to excessive snow accumulation. The Lucan experiment site was located approximately 20 km north of the London, ON weather station ( Table 2) and typically receives twice as much snow from November to January due to enhanced lake-effect precipitation from Lake Huron. In comparison, the overwintering conditions in the fields near Belmont (approximately 15 km south of London) were less severe than at Lucan, but more severe than what occurred near Ridgetown. Ridgetown is approximately 80 km southwest from London and typically receives half as much snow as London ( Table 2). In the current study, the main effects of harvest timing, plant population, fungicide application, and hybrid selection on grain yield tended to be highly significant (P < 0.001, Table 3) for the data collected at the Belmont and Ridgetown locations; the exceptions to this were harvest timing effects on grain yield at the Ridgetown locations (P = 0.616) and plant population effects on grain yield at the Belmont locations (P = 0.326). Significant harvest timing × management strategy interactions were also detected; accordingly, those and other interactions of interest [29] were explored.
Harvest Timing and Hybrid Maturity Effects
Full-and long-maturity hybrid yields were generally greater than the early-maturity hybrids (increases ranging from 2.6% to 10.8%), regardless of harvest timing ( Table 4). These results from the autumn harvests were consistent with the previous research [1]- [3]; however, for autumn harvests at the Belmont locations, the greatest yield was recorded from the full-maturity hybrid (12.2 Mg•ha −1 ) and there were no differences in yield between [29] partitioned interactions across harvest timing treatments and P-values indicate significance (Fisher's Protected LSD at P = 0.05) within the slice. c Data were pooled across autumn and spring harvest timing treatments within a location. d P-values for stay-green and lodging main effects are reported in Table 3.
the early-and long-maturity hybrids, 11.7 and 11.8 Mg•ha −1 respectively ( Table 4). The lowered yield potential of the long-maturity hybrid was likely due to the growing conditions in 2009. That year at Belmont, hail destroyed approximately 50% of the leaf area at the VT growth stage; in addition, the long-maturity hybrid may not have had sufficient time to reach physiological maturity before a killing frost (data not shown). The autumn yield responses of the long-maturity hybrid at the Belmont locations likely contributed to a harvest timing × hybrid interaction (P = 0.001, Table 3). When the hybrids were overwintered at the Belmont locations, spring harvest losses increased from 13.4% to 21.7% as maturity ratings of the hybrids decreased from long-to early-maturity (Table 4). Conversely, at the Ridgetown locations no harvest timing × hybrid interaction was detected (P = 0.168, Table 3), indicating that yield losses were minimal (1.0% to 2.4%) regardless of maturity when corn was harvested in spring ( Table 4).
While long-maturity hybrids tended to have increased yields, long-maturity hybrids also had the highest grain moistures in autumn and lowest test weights in autumn and spring. Grain moisture in autumn for the long-maturity hybrid was greater than both the early-and full-maturity hybrids with 22.0% and 22.4% at the Belmont and Ridgetown locations, respectively ( Table 4). Compared to the grain harvested in autumn, grain moistures of overwintered corn were quite low, ranging from 12.1% to 13.7% in spring, regardless of hybrid maturity or location (Table 4), consistent with a comparable study [9]. Corn grain with higher moisture is often associated with lower test weight at harvest [9]. In the current study, early-and full-maturity hybrids consistently produced grain with greater test weights than long-maturity hybrids regardless of harvest timing. For example, at the Belmont locations, grain from long-maturity hybrids had test weights of 69.6 and 68.1 kg•hL −1 for the harvests in autumn and spring, respectively ( Table 4). In a Wisconsin study, similarly low test weights were reported for overwintered corn [9]. However, contrary to that study, grain test weights in spring increased as maturity decreased, especially for the full-maturity hybrid at the Ridgetown locations ( Table 4), indicating that grain quality was preserved.
Full-and long-maturity hybrids maintained greater green leaf area percentages (stay-green) in September and generally had lower lodging percentages in spring. As would be expected, at both the Belmont and Ridgetown locations, stay-green increased with increasing maturity, with as much as 19% of the leaf area remaining green for the long-maturity hybrid in September at Ridgetown ( Table 4). While stay-green responded similarly to hybrid maturity, the overall lodging percentages differed between the Belmont and Ridgetown locations and among the hybrids within locations. For example, spring lodging percentages ranged from 50.5% to 62.9% at the Belmont locations and 25.1% to 32.4% at the Ridgetown locations ( Table 4), consistent with a study that showed that hybrids can exhibit a lower level of lodging (39%) at one location and a higher level (60% to 65%) at another during a delayed harvest [7]. Within locations, lodging tended to be greater for the early-maturity hybrid and the full-and long-maturity hybrid had the lowest lodging percentage at the Ridgetown and Belmont locations, respectively ( Table 4).
Harvest Timing and Plant Population Effects
When plant populations were reduced from 80,000 down to 60,000 plants•ha −1 , there was a 6% to 6.5% reduction in yield for the autumn harvests at the Belmont and Ridgetown locations and for the spring harvest at the Ridgetown locations; however, at the Belmont locations, grain yields in the spring increased 5% as plant population decreased ( Table 5). An overall yield reduction in response to a reduced plant population was consistent with the literature [ [31]. Yet in this study, a significant harvest timing × plant population interaction was detected at the Belmont locations (P = 0.001, Table 3) primarily because corn yield increased from 9.5 Mg•ha −1 at the 80,000 plants•ha −1 population to 10.0 Mg•ha −1 at the 60,000 plants•ha −1 population ( Table 5). This meant that the use of a lowered plant population reduced yield losses from overwintering corn; compared to the autumn harvests, yield losses for corn grown at 80,000 plants•ha −1 was 22.8% when harvested in the spring and 13% for corn at 60,000 plants•ha −1 ( Table 5). Conversely, there was no harvest timing × plant population interaction at Ridgetown (P = 0.821, Table 3) as less than 2% of the yield was lost from overwintering corn, regardless of plant population ( Table 5). Consequently, when using standard production practices (plant population of 80,000 plants•ha −1 and an autumn harvest) compared to managing the crop to harvest in spring, there was only a 7.7% yield loss at Ridgetown (11.7 vs. 10.8 Mg•ha −1 , Table 5), consistent with other research [9].
At both locations, grain moisture in autumn and grain test weight in spring tended to increase as plant populations decreased. At the Ridgetown locations, grain moisture in autumn increased negligibly (from 20.6% to 21.3%) as plant population decreased ( Table 5), similar to other research [31]. Grain moisture in autumn responded similarly at the Belmont locations, but there was no statistical difference (P = 0.074, Table 5). For grain test weight, contrary to one study [31] but consistent with another [32], this parameter tended to increase as plant population decreased ( Table 5). However, the test weight responses to a reduced plant population were only detected when corn was harvested in spring, unlike other studies using an autumn harvest [31] [32], which could indicate that the use of the 60,000 plants•ha −1 plant population preserved grain quality.
Corn grown at 60,000 plants•ha −1 generally had lower stay-green in autumn and substantially less lodging in spring after overwintering than corn grown at 80,000 plants•ha −1 . At the Ridgetown locations, 10.1% of the leaf area remained green in September compared to 12.2% for corn grown at 60,000 and 80,000 plants•ha −1 populations, respectively (Table 5). Whereas, at the Belmont locations, stay-green was not affected by plant population (P = 0.285, Table 3). For lodging ratings in spring, the proportion of corn lodged after overwintering at the 80,000 plants•ha −1 population was 42.3% to 67.4% and lodging was reduced to 16.7% to 49.7% at the 60,000 plants•ha −1 population for the Ridgetown and Belmont locations, respectively ( Table 5). The overall reduction in [29] partitioned interactions across harvest timing treatments and P-values indicate significance (Fisher's Protected LSD at P = 0.05) within the slice. c Data were pooled across autumn and spring harvest timing treatments within a location. d P-values for stay-green and lodging main effects are reported in Table 3.
lodging with the use of a lowered plant population was consistent with reports on a study where the harvest was delayed until early to mid-December [7] or late March [8].
Harvest Timing and Fungicide Application Effects
Compared to untreated plants, corn that received 200 g a.i. ha −1 of QUILT ® fungicide (azoxystrobin + propiconazole) at the VT to R1 growth stage had increased yields regardless of harvest timing. Depending on location, the fungicide application contributed to a 3.3% to 3.5% and 4.4% to 6.9% yield increase for the autumn and spring harvest, respectively ( Table 6). In the literature, strobilurin (e.g., azoxystrobin) fungicide application has been associated with increased yields [33], but generally not in corn when disease severity is low [16] [34]- [37]. In this study, foliar disease severity was relatively low across in all location-years, with severity visually rated at less than 5% coverage of leaf tissue in September (data not shown). The yield response to a fungicide application depended on harvest timing; thus, a significant harvest timing × fungicide application interaction was detected at the Belmont locations (P = 0.041), but not at the Ridgetown locations (P = 0.512, Table 3). For example, less than 2% of the yield was lost from overwintering corn at Ridgetown, regardless of fun- a Means followed by the same letter within a row are not significantly different according to Fisher's Protected LSD (P = 0.05). b The SLICE option in PROC MIXED [29] partitioned interactions across harvest timing treatments and P-values indicate significance (Fisher's Protected LSD at P = 0.05) within the slice. c Data were pooled across autumn and spring harvest timing treatments within a location. d P-values for stay-green and lodging main effects are reported in Table 3.
gicide application. Whereas at Belmont, spring yield losses for corn that did not receive an application of fungicide was 19.7% (11.7 vs. 9.4 Mg•ha −1 ) compared to 16.5% (12.1 vs. 10.1 Mg•ha −1 ) for corn treated with fungicide ( Table 6). Therefore, when comparing standard management practices (no unwarranted fungicide application and an autumn harvest) compared to managing the crop to harvest in spring, fungicide use reduced yield losses to an average of 13.7% (11.7 vs. 10.1 Mg•ha −1 ) across locations at Belmont, and appeared to increase yields at the Ridgetown locations by an average of 2.6% (11.1 vs. 11.4 Mg•ha −1 , Table 6).
Fungicide application had no effect on grain moisture and had a minimal impact on test weight in autumn at the Ridgetown locations; but, fungicide application did have a considerable effect on stay-green (green leaf area increased in autumn) and lodging (lodging was reduced in spring). Grain moisture was not affected by fungicide application at either the Belmont (P = 0.529) or Ridgetown locations (P = 0.375, Table 3). Grain test weight negligibly increased with a fungicide application, but only at the Ridgetown locations in autumn ( Table 6). However, compared to grain moisture and test weights, more notable effects were detected for stay-green and lodging. For example, corn plants treated with fungicide had a greater percentage of green leaf area at the autumn harvests at the Belmont (7.3%) and Ridgetown locations (12.8%) compared to untreated plants, 4.8% and 9.6% respectively ( Table 6). These observations were consistent with the stay-green "physiological effect" reported in corn and other crops following an application of a strobilurin fungicide [16] [17] [33]. Furthermore, at the Belmont locations, the proportion of corn lodged in spring that did not receive an application of fungicide was 65% and lodging percentage was reduced to 52% for plants that received fungicide ( Table 6). Strobilurin fungicides have been shown to reduce stalk rot and improve corn stalk health [16] [17] [36]; but, to the best of our knowledge, this is the first documented instance of an autumn-applied fungicide that contributed to improved overwintering standability for plants harvested in spring.
Management Strategy Combination to Overwinter Corn
Across all hybrids, corn managed specifically for overwintering (plant population of 60,000 plants•ha −1 and a foliar fungicide application) had similar or greater spring yields than corn that was overwintered with the standard production practices (plant population of 80,000 plants•ha −1 with no fungicide). For example, at the Ridgetown locations across all hybrids, there was no difference in yield between corn with the overwintering strategy and corn overwintered with the standard production practices (11.1 vs. 11.3 Mg•ha −1 , Table 7). Furthermore, yield losses at the Ridgetown locations were only 3.5% (11.1 vs. 11.5 Mg•ha −1 ) across all hybrids when comparing the overwintering management strategy in a spring harvest to corn that was harvested in autumn managed using the Table 3.
standard production practices ( Table 7). At the Belmont locations, yields for corn with the overwintering strategy were 11.4% greater (10.5 vs. 9.3 Mg•ha −1 ) than corn that was overwintered using standard practices ( Table 7). This meant that, compared to harvesting the crop in autumn with the standard management practices, there was only a 13.2% yield loss in spring (12.1 vs. 10.5 Mg•ha −1 ) when the overwintering strategy was used. While comparable studies on overwintering corn are limited, the yield losses observed in this study (3.5% and 13.2% for the Ridgetown and Belmont locations, respectively) were substantially lower than the 7% to 10% yield loss reported under favorable conditions and the 38% to 65% yield loss under less favorable overwintering conditions [9]. The results of the current study were more similar to 15% yield loss when a harvest was delayed until late March [8]; however, yield losses reported in that study represented only one site-year, contrary to this study. While minimizing yield loss is an important overall goal for the development of an overwintering management strategy, the maintenance of grain quality is an important consideration as well. As such, grain test weights in spring across all hybrids tended to be lower for corn managed for overwintering than corn grown with standard production practices and harvested in autumn. However, grain test weights in spring for corn with the overwintering strategy were greater than or equal to corn overwintered with the standard practices. For example, grain test weights across all hybrids were generally lower in spring for corn with the overwintering strategy compared to harvesting in autumn using the standard production practice at the Belmont (70.4 vs. 71.3 kg•hL −1 ) and Ridgetown (74.0 vs. 74.2 kg•hL −1 ) locations (Table 7). Yet, across all hybrids at the Belmont locations, corn harvested in spring with the overwintering strategy had a greater grain test weight than corn with standard production practices, 70.4 and 69.2 kg•hL −1 respectively ( Table 7). At the Ridgetown locations, grain test weights in spring for corn with the overwintering strategy were numerically greater than corn managed with standard practices, but the differences were not statistically significant ( Table 7). Grain test weights have been shown to decrease as corn overwinters [8] [9]. In the current study, when comparing grain test weights across management strategies within the spring harvest timings, the results indicate that test weight, a grain quality trait, was conserved. However, overwintering corn can also reduce the quality and value of harvested grain because of fungal infections [38]. There was some evidence of higher mycotoxin levels present in the corn harvested in spring, but this was not a grain quality parameter considered in this study.
Conclusion
Harvesting corn in spring is often considered when fields are inaccessible for a timely harvest, when grain moistures are excessively high (>30% to 35%) in autumn, when market prices are low, and/or when drying costs are high. Thus, there is a need for developing a strategy to minimize some of the risks associated with this practice. In this research, an overwintering management strategy for corn was identified which consisted of planting at a low plant population (60,000 plants•ha −1 ) and spraying the crop with a foliar fungicide around tasseling. This strategy minimized yield losses across all hybrids by 3.5% to 13.2% at four out of five field locations, through improvements on corn standability compared to when the crop was overwintered using a standard population with no fungicide application. In southern Ontario, the standard management practices for corn production consists of planting at a relatively high plant population (80,000 plants•ha −1 ), applying a foliar fungicide only if there is justifiable disease pressure, harvesting in the autumn when grain moisture is approximately 25% or less, and drying grain down to 15.5% using on-farm grain dryers or through commercial elevators. Unfortunately, while the overwintering management strategy was an improvement over previous reports of yield losses [8] [9], lodging was still unacceptable at most locations, with yield losses as high as 50% (estimated) at the Lucan location where 100% of the corn was lodged in spring. Furthermore, regardless of the management treatment, grain moistures in this study would likely have been too low for growers to economically justify forgoing the typical autumn harvest, especially if there are relatively low breakeven drying costs [38]. Further research in this area is warranted as a comprehensive economic analysis of the yield data in this study as affected by management strategy would still be of value to growers in the northern corn producing regions. In addition, the management of grain quality as affected by rot and mold after overwintering should be addressed in future research as well. However, based on the uncertainty of winter weather and impact on lodging and yield loss, harvesting corn in spring may still be too much of a high-risk practice to be widely accepted in areas where the winters are typically harsh, regardless of the management strategy deployed. | v3-fos |
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