# Identifying the Genes Responsible for Iron-Limited Condition inRiemerella anatipestifer CH-1 through RNA-Seq-Based Analysis

Authors: MaFeng Liu; Mi Huang; DeKang Zhu; MingShu Wang; RenYong Jia; Shun Chen; KunFeng Sun; Qiao Yang; Ying Wu; Francis Biville; AnChun Cheng
Journal: BioMed Research International
 (2017)

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## Abstract

One of the important elements for most bacterial growth is iron, the bioavailability of which is limited in hosts.Riemerella anatipestifer(R. anatipestifer, RA), an important duck pathogen, requires iron to live. However, the genes involved in iron metabolism and the mechanisms of iron transport are largely unknown. Here, we investigated the transcriptomic effects of iron limitation condition onR. anatipestiferCH-1 using the RNA-Seq and RNA-Seq-based analysis. Data analysis revealed genes encoding functions related to iron homeostasis, including a number of putative TonB-dependent receptor systems, a HmuY-like protein-dependent hemin (an iron-containing porphyrin) uptake system, a Feo system, a gene cluster related to starch utilization, and genes encoding hypothetical proteins that were significantly upregulated in response to iron limitation. Compared to the number of upregulated genes, more genes were significantly downregulated in response to iron limitation. The downregulated genes mainly encoded a number of outer membrane receptors, DNA-binding proteins, phage-related proteins, and many hypothetical proteins. This information suggested that RNA-Seq-based analysis in iron-limited medium is an effective and fast method for identifying genes involved in iron uptake inR. anatipestiferCH-1.


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## Body

## 1. Introduction

Riemerella anatipestifer (R. anatipestifer, RA) is a Gram-negative bacterium that belongs to the family Flavobacteriaceae in the rRNA superfamily V [1].R. anatipestifer infection causes disease in ducks, geese, chickens, turkeys, and other waterfowl and birds [2]. The disease presents as an acute or chronic septicemia characterized by meningitis, fibrinous pericarditis, perihepatitis, and other symptoms [3]. The disease causes increased mortality and decreased weight and is estimated to result in huge economic losses to the duck industry each year worldwide. At present, at least 21 serotypes ofR. anatipestifer have been identified in the world [2, 4].Iron is one of the most important elements for bacterial growth, as it is an essential cofactor in many important enzymes involved in energy metabolism and nucleotide synthesis [5]. Iron is the second most abundant metal on earth, but it exists primarily in the insoluble ferric oxide form under aerobic conditions, which is not available for bacterial growth [5]. Inside the host, most iron is bound to iron-binding proteins, such as ferritin, transferrin, and lactoferrin. Iron could also be included in the heme of hemoproteins (the terminology “heme” was used when talking about hemoproteins) [6]. Bacteria employ various mechanisms to capture iron from the outside [7]. One of these mechanisms is the secretion of a small molecular compound, a siderophore, which sequesters iron from the outside environment by high-affinity interactions [8]. Then, iron-bound siderophores are taken up by the bacteria through specific siderophore receptors and transport systems [9]. Alternatively, some pathogens have specific cell surface receptors that bind hemin (the terminology “hemin” was used when talking about iron and protoporphyrin ring source) or hemoprotein and transport hemin to the cell or secreted hemophores that capture hemin from host hemoproteins and then deliver hemin to bacterial surface receptors [10]. Therefore, iron-limited conditions are able to prompt most bacteria to upregulate the expression of genes related to iron/hemin uptake, such as iron/hemin transporters and siderophore biosynthetic enzymes [11–13].R. anatipestiferrequires iron and hemin to survive [14]. Genome analysis has shown thatR. anatipestifer codes for a large number of TonB-dependent receptors, a TonB family protein, two sets of TonB complexes, and an FeoAB system [15]. In a previous study, we demonstrated that TonB1 and TonB2 are involved in hemin uptake byR. anatipestifer ATCC11845 [14]. Moreover some hemin binding proteins were detected inR. anatipestifer CH-1 [16]. However, other genes involved in iron/hemin uptake byR. anatipestifer are largely unknown. In this study, we analyzed the global transcriptomic changes inR. anatipestifer CH-1 under iron-limited conditions. Here, we observed wide-ranging effects on the transcripts of iron-related genes ofR. anatipestifer CH-1 and identified some new genes involved in iron/hemin uptake.


## 2. Materials and Methods

### 2.1. Bacterial Strains and Growth Conditions

For transcriptome analyses,R. anatipestiferCH-1 was grown in tryptone soy broth (TSB) medium (Sigma, China) as the iron-replete condition, while the iron-limited condition was TSB supplemented with 100 μM iron chelator 2,2′-dipyridyl (Dip). The bacteria were cultured at 37°C with shaking at 180 rpm/min. Then, they were harvested at OD600 = 0.6 for iron-limited cultures and OD600 = 1.1 for iron-replete cultures (Figure 1).Figure 1
Growth curves ofR. anatipestifer CH-1 in iron-limited and iron-replete media. Optical densities at a wavelength of 600 nm were taken from the 2nd to the 18th hours at intervals of 2 hours. Measurements were performed on triplicate samples.


### 2.2. RNA-Seq

Total RNA extraction was performed using the RNeasy Protect Bacteria Mini Kit (QIAGEN, Cat. number 74524) using the protocol described by Liu et al. [17]. A total amount of 3 μg RNA per sample was used for the RNA sample preparations. RNA quantification, library preparation, and sequencing were performed at Beijing Novogene as described elsewhere. Then the clean data were obtained by removing reads containing adapter, reads containing ploy-N, and low-quality reads from raw data [18]. The high-quality reads obtained for each library were shown in Table 1. Then theR. anatipestiferCH-1 genome (CP003787.1) and gene model annotation files were downloaded from genome website (https://www.ncbi.nlm.nih.gov/nuccore/CP003787.1) directly, using Bowtie2-2.2.3 to build index and align clean reads of theR. anatipestifer CH-1 genome [19].Table 1
Summary of Illumina RNA-Seq data.
Sample
Total reads
Total mapped
Cleandata∗ (Gb)
Percentage of sequence reads mapped
CH_1TSB
17948156
17106745
2.24
95.31%
CH_1TSBD
21489778
21099289
2.68
98.18%
C
l
e
a
n
∗ data were obtained from raw data by removing reads containing adapter and poly-N and low-quality reads.


### 2.3. Real-Time PCR Validation of RNA-Seq

The differential expression of selected genes was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) using the SYBR green-based detection system on a CFX Connect® Real-Time PCR Detection System (Bio-Rad Laboratories, Hercules, CA) using the KAPA SYBR® FAST qPCR kit (KAPABIOSYSTEMS, Boston, USA). cDNA was synthesized from each RNA sample (1μg) using the HiScript™ Q RT SuperMix for qPCR (+gDNA wiper) (R123-01; Vazyme, Nanjing, China). Real-time PCR assays were conducted with the primers for real-time PCR listed in Table S1 in Supplementary Material, available online at https://doi.org/10.1155/2017/8682057. Quantitative PCR was performed on samples deposited in triplicate using the standard curve mode protocol in which the calibration curve was generated using serial fivefold dilutions of 100 ng of total RNA. The RNA quantity was normalized using a probe specific for 16S rRNA.


### 2.4. RNA-Seq Analysis

To quantify the expression level of genes, HTSeq v0.6.1 was used to count the read numbers mapped to each gene [20]. Then, the FPKM (expected number of Fragments Per Kilobase of transcript sequence per Million base pairs sequenced) of each gene was calculated based on the length of the gene and the read counts mapped to this gene. Prior to differential gene expression analysis, for each sequenced library, the read counts were adjusted by edgeR program package through one scaling normalized factor [21]. In this study, we used the DEGSeq R package (1.20.0) to execute the differential expression analysis of two conditions [22]. Corrected P value of 0.005 and log2 (fold change) of 1 were set as the threshold for significantly differential expression. To analyze the gene structure ofR. anatipestiferCH-1, Rockhopper was used to identify operons and transcription start sites. This program can be used for efficient and accurate analysis of bacterial RNA-Seq data and can aid in the elucidation of bacterial transcriptomes [23]. Moreover we used the aligned paired-end reads to infer the operonic structure ofR. anatipestifer CH-1 transcripts. If genes obtained >20 reads aligning on both genes in a sequencing sample, they would be selected as potential in an operonic structure. Sequential genes that are present in operonic structure were merged together to form potential operonic transcripts (Table S2).


## 2.1. Bacterial Strains and Growth Conditions

For transcriptome analyses,R. anatipestiferCH-1 was grown in tryptone soy broth (TSB) medium (Sigma, China) as the iron-replete condition, while the iron-limited condition was TSB supplemented with 100 μM iron chelator 2,2′-dipyridyl (Dip). The bacteria were cultured at 37°C with shaking at 180 rpm/min. Then, they were harvested at OD600 = 0.6 for iron-limited cultures and OD600 = 1.1 for iron-replete cultures (Figure 1).Figure 1
Growth curves ofR. anatipestifer CH-1 in iron-limited and iron-replete media. Optical densities at a wavelength of 600 nm were taken from the 2nd to the 18th hours at intervals of 2 hours. Measurements were performed on triplicate samples.


## 2.2. RNA-Seq

Total RNA extraction was performed using the RNeasy Protect Bacteria Mini Kit (QIAGEN, Cat. number 74524) using the protocol described by Liu et al. [17]. A total amount of 3 μg RNA per sample was used for the RNA sample preparations. RNA quantification, library preparation, and sequencing were performed at Beijing Novogene as described elsewhere. Then the clean data were obtained by removing reads containing adapter, reads containing ploy-N, and low-quality reads from raw data [18]. The high-quality reads obtained for each library were shown in Table 1. Then theR. anatipestiferCH-1 genome (CP003787.1) and gene model annotation files were downloaded from genome website (https://www.ncbi.nlm.nih.gov/nuccore/CP003787.1) directly, using Bowtie2-2.2.3 to build index and align clean reads of theR. anatipestifer CH-1 genome [19].Table 1
Summary of Illumina RNA-Seq data.
Sample
Total reads
Total mapped
Cleandata∗ (Gb)
Percentage of sequence reads mapped
CH_1TSB
17948156
17106745
2.24
95.31%
CH_1TSBD
21489778
21099289
2.68
98.18%
C
l
e
a
n
∗ data were obtained from raw data by removing reads containing adapter and poly-N and low-quality reads.


## 2.3. Real-Time PCR Validation of RNA-Seq

The differential expression of selected genes was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) using the SYBR green-based detection system on a CFX Connect® Real-Time PCR Detection System (Bio-Rad Laboratories, Hercules, CA) using the KAPA SYBR® FAST qPCR kit (KAPABIOSYSTEMS, Boston, USA). cDNA was synthesized from each RNA sample (1μg) using the HiScript™ Q RT SuperMix for qPCR (+gDNA wiper) (R123-01; Vazyme, Nanjing, China). Real-time PCR assays were conducted with the primers for real-time PCR listed in Table S1 in Supplementary Material, available online at https://doi.org/10.1155/2017/8682057. Quantitative PCR was performed on samples deposited in triplicate using the standard curve mode protocol in which the calibration curve was generated using serial fivefold dilutions of 100 ng of total RNA. The RNA quantity was normalized using a probe specific for 16S rRNA.


## 2.4. RNA-Seq Analysis

To quantify the expression level of genes, HTSeq v0.6.1 was used to count the read numbers mapped to each gene [20]. Then, the FPKM (expected number of Fragments Per Kilobase of transcript sequence per Million base pairs sequenced) of each gene was calculated based on the length of the gene and the read counts mapped to this gene. Prior to differential gene expression analysis, for each sequenced library, the read counts were adjusted by edgeR program package through one scaling normalized factor [21]. In this study, we used the DEGSeq R package (1.20.0) to execute the differential expression analysis of two conditions [22]. Corrected P value of 0.005 and log2 (fold change) of 1 were set as the threshold for significantly differential expression. To analyze the gene structure ofR. anatipestiferCH-1, Rockhopper was used to identify operons and transcription start sites. This program can be used for efficient and accurate analysis of bacterial RNA-Seq data and can aid in the elucidation of bacterial transcriptomes [23]. Moreover we used the aligned paired-end reads to infer the operonic structure ofR. anatipestifer CH-1 transcripts. If genes obtained >20 reads aligning on both genes in a sequencing sample, they would be selected as potential in an operonic structure. Sequential genes that are present in operonic structure were merged together to form potential operonic transcripts (Table S2).


## 3. Results and Discussion

### 3.1. Growth ofR. anatipestifer CH-1 in TSB and TSB with Dip

To evaluate the effect of iron restriction on the growth ofR. anatipestifer CH-1, we grewR. anatipestifer CH-1 in TSB and TSB with 100 μM Dip, which restricts most iron. Figure 1 showed that the growth ofR. anatipestifer CH-1 was seriously hindered when iron was restricted, indicating that iron is an essential element forR. anatipestifer. Thus, this condition was suitable for performing RNA-Seq.


### 3.2. General Assessment of Iron Limitation Transcriptomic Datasets

Over 95% of all clean reads aligned to coding regions of theR. anatipestifer CH-1 genome (Table 1). Since only one sample in the different iron condition was used to perform RNA-Seq, qRT-PCR validation was performed on the transcriptome data using a subset of 20 differentially regulated genes (Table S1). The transcriptome data generally corresponded well with the qRT-PCR data, with a Pearson correlation coefficient of 0.806 (Figure 2), illustrating that our RNA-Seq data were of suitable quality for transcriptome analysis.Figure 2
Validation of RNA-Seq data. Correlation analysis oflog2-based fold changes between RNA-Seq data and qRT-PCR data for 20 genes ofR. anatipestifer CH-1. The chart depicts a plot of RNA-Seq log2-based fold changes versus qRT-PCR log2-based fold changes for transcripts of genes in cultures ofR. anatipestiferCH-1 grown in TSB+Dip medium versus TSB medium. A Pearson correlation coefficient of 0.806 was noted.Upon comparing cultures grown in TSB and TSB with Dip, overall differences in gene expression were observed (Figure3). To examine these differences further, DEGs (differentially expressed genes) were identified using the DEseq package [22]. A total of 463 DEGs were identified, including 80 upregulated (Table 2) and 383 downregulated genes (Table S3). These genes represent 23% of the genome (2038 genes) [15]. The large number of DEGs suggests that iron-limited environments have global effects onR. anatipestifer CH-1. Since samples of different OD were used to perform RNA-Seq, this study can not exclude the fact that cell density might influence gene expression.Table 2
Genes upregulated inRiemerella anatipestifer CH-1 in iron-depleted conditions.
Gene ID
Gene name
log2.Fold_change.
P value
Description
13715178
B739_0074
1.289
0.00021641
Hypothetical protein
13715197
B739_0093
2.8509
2.72
E
-
108
Hypothetical protein
13715198
B739_0094
1.2615
8.08
E
-
28
Outer membrane receptor for Fe3+FecA
13715199
B739_0095
1.5902
5.31
E
-
23
Type I deoxyribonuclease HsdR
13715200
B739_0096
3.3265
4.50
E
-
246
Hypothetical protein
13715201
B739_0097
3.1172
1.67
E
-
115
Carbohydrate-binding protein
13715202
B739_0098
3.3417
0
Hypothetical protein
13715203
B739_0099
3.5712
5.25
E
-
128
Hypothetical protein
13715204
B739_0100
3.5135
5.06
E
-
149
Hypothetical protein
13715205
B739_0101
3.0646
1.23
E
-
132
Substrate import-associated zinc metallohydrolase
13715206
B739_0102
3.4075
0
Glycan metabolism protein RagB
13715207
B739_0103
3.8099
0
TonB-linked outer membrane protein, SusC/RagA family
13715231
B739_0127
1.275
1.56
E
-
06
DNA-binding protein
13715277
B739_0173
3.3109
2.55
E
-
195
TonB-dependent receptor CirA, mostly Fe transport
13715278
B739_0174
3.6434
5.92
E
-
216
Hypothetical protein
13715279
B739_0175
2.413
5.96
E
-
53
Ankyrin
13715280
B739_0176
3.0584
1.11
E
-
20
Predicted periplasmic protein
13715281
B739_0177
1.0467
3.85
E
-
06
Nitric oxide synthase
13715373
B739_2137
1.1196
6.02
E
-
07
Camphor resistance protein CrcB; integral membrane protein possibly involved in chromosome condensation [cell division and chromosome partitioning]
13715432
B739_0891
1.0093
1.05
E
-
06
Hypothetical protein
13715452
B739_0912
1.0968
6.65
E
-
11
Ribonuclease III
13715453
B739_0913
1.0147
0.0019348
Hypothetical protein
13715513
B739_0973
1.0814
1.74
E
-
42
50S ribosomal protein L16/L10E
13715515
B739_0975
1.0712
4.92
E
-
15
30S ribosomal protein S17
13715522
B739_0982
1.1625
3.94
E
-
41
50S ribosomal protein L18
13715525
B739_0985
1.2524
1.07
E
-
63
50S ribosomal protein L15
13715526
B739_0986
1.0086
2.96
E
-
104
Preprotein translocase subunit SecY
13715542
−//−
1.4285
1.38
E
-
29
tRNA-Glu
13715606
B739_1068
3.8593
0
FecA
13715627
B739_1089
1.3526
1.76
E
-
65
Hypothetical protein
13715649
B739_1112
1.0673
5.05
E
-
41
50S ribosomal protein L31
13715783
B739_1246
1.0718
1.24
E
-
91
30S ribosomal protein S16
13715836
B739_1299
1.2361
5.75
E
-
09
Hypothetical protein
13715897
B739_1360
1.3576
0.0002407
Hypothetical protein
13715932
B739_1395
1.4655
1.89
E
-
17
2-Amino-4-hydroxy-6-hydroxymethyldihydropteridine pyrophosphokinase
13715934
B739_1397
1.08
1.36
E
-
93
Outer membrane protein-related peptidoglycan-associated (lipo)protein
13715952
B739_1415
4.7103
0
Hypothetical protein
13715953
B739_1416
3.7691
0
FepA
13715954
B739_1417
4.5479
5.15
E
-
244
HmuY
13715956
B739_1419
1.2458
2.43
E
-
15
Restriction endonuclease S subunits, Hsds
13716000
B739_1467
1.605
7.16
E
-
26
Hypothetical protein
13716023
B739_1491
1.2534
2.55
E
-
67
Hypothetical protein
13716028
B739_1496
1.0255
0.00022217
Hypothetical protein
13716038
B739_1506
1.2051
1.41
E
-
13
Phosphate transport regulator
13716056
B739_1525
1.0126
2.76
E
-
16
OmpA
13716068
B739_1537
1.1923
2.42
E
-
35
Thioredoxin
13716179
B739_1648
1.1687
1.56
E
-
06
Hypothetical protein
13716365
B739_1842
1.4584
1.63
E
-
10
Hypothetical protein
13716406
B739_1883
1.1398
2.85
E
-
14
Preprotein translocase subunit SecG
13716420
B739_1898
1.1221
8.61
E
-
20
3-Oxoacyl-(acyl-carrier-protein) synthase III
13716438
B739_1916
1.1349
1.80
E
-
07
Hypothetical protein
13716459
B739_1938
1.0469
7.76
E
-
115
Hypothetical protein
13716524
B739_2003
1.1565
1.21
E
-
26
Polyisoprenoid-binding protein; YceI-like domain
13716533
B739_2012
1.3031
0.0098864
Prevent-host-death protein; Antitoxin Phd_YefM, type II toxin-antitoxin system
13716610
B739_2089
1.0236
0.00048509
Porin
13716613
B739_2092
1.0406
3.79
E
-
32
Starch binding outer membrane protein SusD
13716712
B739_0221
1.0457
3.80
E
-
21
Gliding motility protein GldL
13716745
B739_0254
1.1712
1.78
E
-
48
Hypothetical protein
13716748
B739_0257
1.0548
1.69
E
-
11
Hypothetical protein
13716800
B739_0310
1.1729
4.55
E
-
21
Carbohydrate-binding protein SusD
13716803
B739_0313
1.0601
2.33
E
-
59
Ribonuclease G
13716804
B739_0314
1.3277
1.60
E
-
56
Bacterial nucleoid DNA-binding protein
13716824
B739_0335
1.2846
9.72
E
-
16
Hypothetical protein
13716825
B739_0336
1.0435
1.66
E
-
07
Hypothetical protein
13716826
B739_0337
1.0406
3.10
E
-
06
Ras_like_GTPase
13716848
B739_0360
1.2725
1.12
E
-
137
50S ribosomal protein L11
13716849
B739_0361
1.0413
1.23
E
-
42
Transcription antiterminator
13716885
B739_0397
1.0567
6.51
E
-
19
IMP dehydrogenase/GMP reductase
13716908
B739_0420
1.0126
2.35
E
-
05
Sec-independent protein secretion pathway component
13716924
B739_0436
1.019
0.00033736
Predicted glycosyltransferases
13716964
B739_0476
1.2682
6.15
E
-
21
Hypothetical protein
13716978
B739_0490
2.3711
4.94
E
-
95
Ferritin-like domain
13717035
B739_0547
1.2256
9.53
E
-
39
RNA polymerase Rpb6
13717082
B739_0594
1.082
1.16
E
-
21
Iron transporter FeoB
13717083
B739_0595
2.259
5.94
E
-
27
Iron transporter FeoA
13717096
B739_0608
1.6768
3.57
E
-
11
Oxidoreductase; siderophore-interacting protein [inorganic ion transport and metabolism]ViuB
13717113
B739_0625
1.7097
2.66
E
-
21
RNA polymerase sigma factor
13717239
B739_0753
1.1957
3.41
E
-
12
Transthyretin-like protein
13717245
B739_0759
1.1112
2.64
E
-
14
Iron-sulfur binding proteinFigure 3
Differential gene transcription in cells grown in iron-limited TSB medium compared to TSB medium. Thex-axis of the chart shows log2-based fold changes of transcripts in cells grown in iron-limited medium or TSB medium. The y-axis of the chart shows the statistical significance. Each dot in the chart represents one annotated gene. Red dots: upregulated, green dots: downregulated, and blue dots: no significant change.


### 3.3. Genome-Wide Identification ofR. anatipestifer CH-1 Genes in Operonic Structures

In addition to identifying gene boundaries, we drew on paired-end sequencing information to identify theR. anatipestifer CH-1 global operonic structure. In total, 377 genes were determined to be in operonic structures using this analysis, thus constituting 230 operons (Table S2). These genes represent 18% of the genome (2038 genes) [15].


### 3.4. Gene Ontology (GO) Annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Mapping of DEGs

The DEGs were assigned to 26 functional groups by enrichment analysis of Gene Ontology (GO) assignments [18]. In the three main GO categories of biological process, cellular component, and molecular function, genes in the role categories of “localization, transport, and establishment of localization” in biological process, “membrane” in cellular component or “receptor activity and transporter activity” in molecular function were notably up- or downregulated (Figure 4).Figure 4
Role categories of genes from the transcriptome data. The numbers of genes that are up- and downregulated inR. anatipestifer CH-1 grown in iron-limited TSB medium versus TSB medium are categorized according to role categories. Some genes are listed in more than one category and so may be counted more than once.The biological functions associated with the DEGs were further analyzed in terms of enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [24], and a total of 20 pathways were predicted (Figure 5). Among these pathways, “microbial metabolism in diverse environments,” “ribosome,” and “thiamine metabolism” were the most highly represented categories (Figure 5).Figure 5
KEGG pathway enrichment analysis of differentially expressed genes between TSB and TSB with Dip. They-axis of the chart shows the pathway name. The x-axis of the chart shows the Richness factor. The size of each point shows the number of genes in the pathway. The color of each point shows theQvalue range.


### 3.5. Iron Limitation Increased the Transcription of Putative Iron Acquisition Systems

Genome sequence analysis indicated thatR. anatipestiferCH-1 encodes Fe2+ and Fe3+ acquisition systems [15]. Once in the periplasm, Fe2+ is taken across the inner membrane via a divalent metal uptake system, such as the Feo system ofE. coli [25] and the Yfe system ofYersinia pestis [26]. In this study, the predicted genesfeoB (B739_0594) andfeoA (B739_0595), which encode an Fe2+ transporter, were highly upregulated in the iron-limited condition, suggesting a role in the uptake of ferrous iron (Table 2). Sequence comparison revealed that all of the sequencedR. anatipestifergenomes have homologues of FeoA and FeoB ofR. anatipestifer CH-1, with similarities of 100% for FeoA and between 88% and 100% for FeoB. In turn, theseR. anatipestifer CH-1 genes have 33.45% and 32.89% identities to the FeoA and FeoB products ofE. coli, respectively. InE. coli,this operon is regulated by Fur and is induced in acidic conditions [27]. The functions of FeoA and FeoB and their regulation inR. anatipestiferare underinvestigated.In aerobic conditions, many bacteria produce siderophores to solubilize Fe3+. Then, siderophore-bound Fe3+ is taken up by TonB-dependent receptors [5]. Genome analysis revealed that there are at least 33 predicted TonB-dependent receptors inR. anatipestiferCH-1, some of which are predicted transporters for ferric-siderophore complexes or heme. In this study, 5 TonB-dependent receptors were upregulated (B739_0094, B739_0103, B739_0173, B739_1068, and B739_1416) in the presence of iron depletion. The expression levels of seven other putative TonB-dependent transporters (B739_0115, B739_0876, B739_1045, B739_1343, B739_0216, B739_0329, and B739_0389) (Table S3) were downregulated in the presence of iron depletion. Upregulated TonB-dependent receptors would be predicted to be involved in iron or hemin uptake, while the functions of all downregulated TonB-dependent receptors are presently unknown. Similar results have been obtained in other bacteria, such asPseudomonas fluorescens[28].TonB-dependent receptors rely on the accessory proteins ExbB, ExbD, and TonB for energy transduction. One TonB family protein and two sets of ExbB-ExbD-TonB were found and identified inR. anatipestifer[14]. In other bacteria, such asE. coli[29] andPseudomonas fluorescens[28], thetonB gene is negatively regulated by iron. However, the transcription oftonBgenes inR. anatipestiferCH-1 was not significantly changed in the iron-limited condition. To ensure the validity of the result, we also used qRT-PCR to measuretonB gene transcription in iron-limited conditions. The result was coincident with that of RNA-Seq. These results suggested that, in contrast to many bacteria, thetonB systems ofR. anatipestiferCH-1 are not regulated by iron.Once siderophore-bound Fe3+ is transported into the cytoplasm, the iron must be released from the siderophore. The first mechanism is that siderophore-bound Fe(III) is reduced to siderophore-bound Fe(II) followed by its spontaneous release due to the low affinity of iron Fe(II) with the siderophore. Another mechanism is that siderophore-bound Fe(III) is hydrolyzed by specialized enzymes, leading to a dramatic loss of complex stability and facilitating the subsequent removal of the iron [30] in a reduction process. In this study, a gene coding for a siderophore-interacting protein (B739_0608) was upregulated significantly in the presence of iron depletion. This siderophore-interacting protein is involved in iron acquisition and virulence inR. anatipestifer strain CH-3 [31]. Surprisingly, among the upregulated genes, we did not find any homologue gene related to siderophore synthesis.


### 3.6. A Putative Polysaccharide Utilization Locus ofR. anatipestiferCH-1 Was Upregulated in Iron-Limited Conditions

InCapnocytophaga canimorsus, a member of the Bacteroidetes, a polysaccharide utilization system uses serotransferrin as an iron source [32]. Each polypeptide encoded by this locus is required for this iron uptake activity [32]. This type of system was named the iron capture system (ICS), and it contains seven genes:icsA, icsC, icsD, icsE, icsF, icsG,andicsH[32]. In this study, we identified a gene cluster (B739_0094, B739_0095, B739_0096, B739_0097, B739_0098, B739_0099, B739_0100, B739_0101, B739_0102, and B739_0103) (Table 2) involved in polysaccharide utilization, the expression of which was upregulated in the presence of iron depletion. Sequence comparison showed that the homologues oficsC, icsD, icsE, icsF, icsG,andicsH fromCapnocytophaga canimorsus are B739_0103, B739_0102, B739_0101, B739_0100, B739_0099, and B739_0098, respectively, in theR. anatipestiferCH-1 genome. The homologue oficsA,B739_1068, was not cotranscribed with the others. Interestingly, some genes that were upregulated in the gene cluster, such as B739_0094, B739_0095, B739_0096, and B739_0097, were not predicted to contribute to the ICS system. Additionally, theR. anatipestiferCH-1 genome contains at least 6 polysaccharide utilization systems. In iron-limited conditions, three of the genes (locus B739_0094–B739_0103, locus B739_2091–B739_2093, and locus B739_0310–B739_0312) were upregulated (Table 2), while three other genes (locus B739_0115–B739_0118, locus B739_0875-B739_0876, and locus B739_1044-B739_1045) were downregulated (Table S3). Why some loci were upregulated and some loci were downregulated in the iron-limited condition is not currently understood.


### 3.7. Iron Limitation Increased Transcription of Putative Hemin Acquisition Systems

In the host, heme-containing proteins, such as hemoglobin, can be used as the main iron source by pathogenic bacteria [33]. Hemin uptake systems are regulated by iron in other bacteria [34, 35]. Here, putative genes involved in hemin uptake were more highly expressed in iron-limited cultures ofR. anatipestiferCH-1 than in iron-replete cultures. Within the upregulated genes, the most highly expressed gene cluster wasFepA-hmuY (B739_1416, B739_1417), which encodes a putative outer membrane ferrienterochelin, a colicin receptor and an HmuY-like hemophore protein. InPorphyromonas gingivalis, HmuY is a heme-binding lipoprotein associated with the outer membrane or secreted to the outside environment [36, 37]. Gene (B739_1415) adjacent to theFepA-hmuYoperon was also upregulated in iron-limited medium. The functions of B739_1415, B739_1416, and B739_1417 in hemin utilization are underinvestigated in our group.


### 3.8. Transcription of Respiratory Chain Genes

In aerobic metabolism, the respiratory chain typically uses proteins that require iron as a cofactor [38]. WhenR. anatipestiferCH-1 was grown in iron-limited medium, the expression of genes coding for cytochrome biogenesis protein (B739_0948), periplasmic cytochrome c552 subunit (B739_0946), and cytochrome C (B739_0186) were downregulated (Table S3). It indicated that iron restriction hinderedR. anatipestifer aerobic metabolism. Similarly, in other bacteria, such asPseudomonas fluorescens Pf-5, the transcription levels of genes encoding cytochrome c-type biogenesis proteins (PFL_1684-88) and subunits of cbb3-type cytochrome c oxidases (PFL_1922-25, PFL_2834) are downregulated in iron-limited versus iron-replete medium [28].


### 3.9. Transcription of Genes Related to Natural Competence

Natural transformation refers to the process by which bacteria can actively take up and integrate exogenous DNA. Natural transformation is a major mechanism of horizontal gene transfer (HGT) and plays a prominent role in bacterial evolution [39]. The process ofVibrio cholerae natural transformation involves four steps: DNA-binding via type IV pili, DNA pulling via ComEA, DNA translocation via ComEC, and DNA recombination by the single-strand DNA-binding proteins DprA and RecA [40]. Previously, we found thatR. anatipestiferCH-1 is naturally competent [41]. InR. anatipestiferCH-1, no putative type IV pilus locus is evident in the genome. InR. anatipestiferCH-1, two proteins that are predicted to be involved in the DNA uptake process, a ComEC homologue (B739_1095) and a gene encoding a single-strand DNA-binding protein (B739_1757), were downregulated in iron-limited conditions. One possibility for this phenomenon is that these proteins require iron for activity, as well as iron being predicted to be involved in the natural transformation process. This relationship between natural transformation and iron availability has not yet been described.


## 3.1. Growth ofR. anatipestifer CH-1 in TSB and TSB with Dip

To evaluate the effect of iron restriction on the growth ofR. anatipestifer CH-1, we grewR. anatipestifer CH-1 in TSB and TSB with 100 μM Dip, which restricts most iron. Figure 1 showed that the growth ofR. anatipestifer CH-1 was seriously hindered when iron was restricted, indicating that iron is an essential element forR. anatipestifer. Thus, this condition was suitable for performing RNA-Seq.


## 3.2. General Assessment of Iron Limitation Transcriptomic Datasets

Over 95% of all clean reads aligned to coding regions of theR. anatipestifer CH-1 genome (Table 1). Since only one sample in the different iron condition was used to perform RNA-Seq, qRT-PCR validation was performed on the transcriptome data using a subset of 20 differentially regulated genes (Table S1). The transcriptome data generally corresponded well with the qRT-PCR data, with a Pearson correlation coefficient of 0.806 (Figure 2), illustrating that our RNA-Seq data were of suitable quality for transcriptome analysis.Figure 2
Validation of RNA-Seq data. Correlation analysis oflog2-based fold changes between RNA-Seq data and qRT-PCR data for 20 genes ofR. anatipestifer CH-1. The chart depicts a plot of RNA-Seq log2-based fold changes versus qRT-PCR log2-based fold changes for transcripts of genes in cultures ofR. anatipestiferCH-1 grown in TSB+Dip medium versus TSB medium. A Pearson correlation coefficient of 0.806 was noted.Upon comparing cultures grown in TSB and TSB with Dip, overall differences in gene expression were observed (Figure3). To examine these differences further, DEGs (differentially expressed genes) were identified using the DEseq package [22]. A total of 463 DEGs were identified, including 80 upregulated (Table 2) and 383 downregulated genes (Table S3). These genes represent 23% of the genome (2038 genes) [15]. The large number of DEGs suggests that iron-limited environments have global effects onR. anatipestifer CH-1. Since samples of different OD were used to perform RNA-Seq, this study can not exclude the fact that cell density might influence gene expression.Table 2
Genes upregulated inRiemerella anatipestifer CH-1 in iron-depleted conditions.
Gene ID
Gene name
log2.Fold_change.
P value
Description
13715178
B739_0074
1.289
0.00021641
Hypothetical protein
13715197
B739_0093
2.8509
2.72
E
-
108
Hypothetical protein
13715198
B739_0094
1.2615
8.08
E
-
28
Outer membrane receptor for Fe3+FecA
13715199
B739_0095
1.5902
5.31
E
-
23
Type I deoxyribonuclease HsdR
13715200
B739_0096
3.3265
4.50
E
-
246
Hypothetical protein
13715201
B739_0097
3.1172
1.67
E
-
115
Carbohydrate-binding protein
13715202
B739_0098
3.3417
0
Hypothetical protein
13715203
B739_0099
3.5712
5.25
E
-
128
Hypothetical protein
13715204
B739_0100
3.5135
5.06
E
-
149
Hypothetical protein
13715205
B739_0101
3.0646
1.23
E
-
132
Substrate import-associated zinc metallohydrolase
13715206
B739_0102
3.4075
0
Glycan metabolism protein RagB
13715207
B739_0103
3.8099
0
TonB-linked outer membrane protein, SusC/RagA family
13715231
B739_0127
1.275
1.56
E
-
06
DNA-binding protein
13715277
B739_0173
3.3109
2.55
E
-
195
TonB-dependent receptor CirA, mostly Fe transport
13715278
B739_0174
3.6434
5.92
E
-
216
Hypothetical protein
13715279
B739_0175
2.413
5.96
E
-
53
Ankyrin
13715280
B739_0176
3.0584
1.11
E
-
20
Predicted periplasmic protein
13715281
B739_0177
1.0467
3.85
E
-
06
Nitric oxide synthase
13715373
B739_2137
1.1196
6.02
E
-
07
Camphor resistance protein CrcB; integral membrane protein possibly involved in chromosome condensation [cell division and chromosome partitioning]
13715432
B739_0891
1.0093
1.05
E
-
06
Hypothetical protein
13715452
B739_0912
1.0968
6.65
E
-
11
Ribonuclease III
13715453
B739_0913
1.0147
0.0019348
Hypothetical protein
13715513
B739_0973
1.0814
1.74
E
-
42
50S ribosomal protein L16/L10E
13715515
B739_0975
1.0712
4.92
E
-
15
30S ribosomal protein S17
13715522
B739_0982
1.1625
3.94
E
-
41
50S ribosomal protein L18
13715525
B739_0985
1.2524
1.07
E
-
63
50S ribosomal protein L15
13715526
B739_0986
1.0086
2.96
E
-
104
Preprotein translocase subunit SecY
13715542
−//−
1.4285
1.38
E
-
29
tRNA-Glu
13715606
B739_1068
3.8593
0
FecA
13715627
B739_1089
1.3526
1.76
E
-
65
Hypothetical protein
13715649
B739_1112
1.0673
5.05
E
-
41
50S ribosomal protein L31
13715783
B739_1246
1.0718
1.24
E
-
91
30S ribosomal protein S16
13715836
B739_1299
1.2361
5.75
E
-
09
Hypothetical protein
13715897
B739_1360
1.3576
0.0002407
Hypothetical protein
13715932
B739_1395
1.4655
1.89
E
-
17
2-Amino-4-hydroxy-6-hydroxymethyldihydropteridine pyrophosphokinase
13715934
B739_1397
1.08
1.36
E
-
93
Outer membrane protein-related peptidoglycan-associated (lipo)protein
13715952
B739_1415
4.7103
0
Hypothetical protein
13715953
B739_1416
3.7691
0
FepA
13715954
B739_1417
4.5479
5.15
E
-
244
HmuY
13715956
B739_1419
1.2458
2.43
E
-
15
Restriction endonuclease S subunits, Hsds
13716000
B739_1467
1.605
7.16
E
-
26
Hypothetical protein
13716023
B739_1491
1.2534
2.55
E
-
67
Hypothetical protein
13716028
B739_1496
1.0255
0.00022217
Hypothetical protein
13716038
B739_1506
1.2051
1.41
E
-
13
Phosphate transport regulator
13716056
B739_1525
1.0126
2.76
E
-
16
OmpA
13716068
B739_1537
1.1923
2.42
E
-
35
Thioredoxin
13716179
B739_1648
1.1687
1.56
E
-
06
Hypothetical protein
13716365
B739_1842
1.4584
1.63
E
-
10
Hypothetical protein
13716406
B739_1883
1.1398
2.85
E
-
14
Preprotein translocase subunit SecG
13716420
B739_1898
1.1221
8.61
E
-
20
3-Oxoacyl-(acyl-carrier-protein) synthase III
13716438
B739_1916
1.1349
1.80
E
-
07
Hypothetical protein
13716459
B739_1938
1.0469
7.76
E
-
115
Hypothetical protein
13716524
B739_2003
1.1565
1.21
E
-
26
Polyisoprenoid-binding protein; YceI-like domain
13716533
B739_2012
1.3031
0.0098864
Prevent-host-death protein; Antitoxin Phd_YefM, type II toxin-antitoxin system
13716610
B739_2089
1.0236
0.00048509
Porin
13716613
B739_2092
1.0406
3.79
E
-
32
Starch binding outer membrane protein SusD
13716712
B739_0221
1.0457
3.80
E
-
21
Gliding motility protein GldL
13716745
B739_0254
1.1712
1.78
E
-
48
Hypothetical protein
13716748
B739_0257
1.0548
1.69
E
-
11
Hypothetical protein
13716800
B739_0310
1.1729
4.55
E
-
21
Carbohydrate-binding protein SusD
13716803
B739_0313
1.0601
2.33
E
-
59
Ribonuclease G
13716804
B739_0314
1.3277
1.60
E
-
56
Bacterial nucleoid DNA-binding protein
13716824
B739_0335
1.2846
9.72
E
-
16
Hypothetical protein
13716825
B739_0336
1.0435
1.66
E
-
07
Hypothetical protein
13716826
B739_0337
1.0406
3.10
E
-
06
Ras_like_GTPase
13716848
B739_0360
1.2725
1.12
E
-
137
50S ribosomal protein L11
13716849
B739_0361
1.0413
1.23
E
-
42
Transcription antiterminator
13716885
B739_0397
1.0567
6.51
E
-
19
IMP dehydrogenase/GMP reductase
13716908
B739_0420
1.0126
2.35
E
-
05
Sec-independent protein secretion pathway component
13716924
B739_0436
1.019
0.00033736
Predicted glycosyltransferases
13716964
B739_0476
1.2682
6.15
E
-
21
Hypothetical protein
13716978
B739_0490
2.3711
4.94
E
-
95
Ferritin-like domain
13717035
B739_0547
1.2256
9.53
E
-
39
RNA polymerase Rpb6
13717082
B739_0594
1.082
1.16
E
-
21
Iron transporter FeoB
13717083
B739_0595
2.259
5.94
E
-
27
Iron transporter FeoA
13717096
B739_0608
1.6768
3.57
E
-
11
Oxidoreductase; siderophore-interacting protein [inorganic ion transport and metabolism]ViuB
13717113
B739_0625
1.7097
2.66
E
-
21
RNA polymerase sigma factor
13717239
B739_0753
1.1957
3.41
E
-
12
Transthyretin-like protein
13717245
B739_0759
1.1112
2.64
E
-
14
Iron-sulfur binding proteinFigure 3
Differential gene transcription in cells grown in iron-limited TSB medium compared to TSB medium. Thex-axis of the chart shows log2-based fold changes of transcripts in cells grown in iron-limited medium or TSB medium. The y-axis of the chart shows the statistical significance. Each dot in the chart represents one annotated gene. Red dots: upregulated, green dots: downregulated, and blue dots: no significant change.


## 3.3. Genome-Wide Identification ofR. anatipestifer CH-1 Genes in Operonic Structures

In addition to identifying gene boundaries, we drew on paired-end sequencing information to identify theR. anatipestifer CH-1 global operonic structure. In total, 377 genes were determined to be in operonic structures using this analysis, thus constituting 230 operons (Table S2). These genes represent 18% of the genome (2038 genes) [15].


## 3.4. Gene Ontology (GO) Annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Mapping of DEGs

The DEGs were assigned to 26 functional groups by enrichment analysis of Gene Ontology (GO) assignments [18]. In the three main GO categories of biological process, cellular component, and molecular function, genes in the role categories of “localization, transport, and establishment of localization” in biological process, “membrane” in cellular component or “receptor activity and transporter activity” in molecular function were notably up- or downregulated (Figure 4).Figure 4
Role categories of genes from the transcriptome data. The numbers of genes that are up- and downregulated inR. anatipestifer CH-1 grown in iron-limited TSB medium versus TSB medium are categorized according to role categories. Some genes are listed in more than one category and so may be counted more than once.The biological functions associated with the DEGs were further analyzed in terms of enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways [24], and a total of 20 pathways were predicted (Figure 5). Among these pathways, “microbial metabolism in diverse environments,” “ribosome,” and “thiamine metabolism” were the most highly represented categories (Figure 5).Figure 5
KEGG pathway enrichment analysis of differentially expressed genes between TSB and TSB with Dip. They-axis of the chart shows the pathway name. The x-axis of the chart shows the Richness factor. The size of each point shows the number of genes in the pathway. The color of each point shows theQvalue range.


## 3.5. Iron Limitation Increased the Transcription of Putative Iron Acquisition Systems

Genome sequence analysis indicated thatR. anatipestiferCH-1 encodes Fe2+ and Fe3+ acquisition systems [15]. Once in the periplasm, Fe2+ is taken across the inner membrane via a divalent metal uptake system, such as the Feo system ofE. coli [25] and the Yfe system ofYersinia pestis [26]. In this study, the predicted genesfeoB (B739_0594) andfeoA (B739_0595), which encode an Fe2+ transporter, were highly upregulated in the iron-limited condition, suggesting a role in the uptake of ferrous iron (Table 2). Sequence comparison revealed that all of the sequencedR. anatipestifergenomes have homologues of FeoA and FeoB ofR. anatipestifer CH-1, with similarities of 100% for FeoA and between 88% and 100% for FeoB. In turn, theseR. anatipestifer CH-1 genes have 33.45% and 32.89% identities to the FeoA and FeoB products ofE. coli, respectively. InE. coli,this operon is regulated by Fur and is induced in acidic conditions [27]. The functions of FeoA and FeoB and their regulation inR. anatipestiferare underinvestigated.In aerobic conditions, many bacteria produce siderophores to solubilize Fe3+. Then, siderophore-bound Fe3+ is taken up by TonB-dependent receptors [5]. Genome analysis revealed that there are at least 33 predicted TonB-dependent receptors inR. anatipestiferCH-1, some of which are predicted transporters for ferric-siderophore complexes or heme. In this study, 5 TonB-dependent receptors were upregulated (B739_0094, B739_0103, B739_0173, B739_1068, and B739_1416) in the presence of iron depletion. The expression levels of seven other putative TonB-dependent transporters (B739_0115, B739_0876, B739_1045, B739_1343, B739_0216, B739_0329, and B739_0389) (Table S3) were downregulated in the presence of iron depletion. Upregulated TonB-dependent receptors would be predicted to be involved in iron or hemin uptake, while the functions of all downregulated TonB-dependent receptors are presently unknown. Similar results have been obtained in other bacteria, such asPseudomonas fluorescens[28].TonB-dependent receptors rely on the accessory proteins ExbB, ExbD, and TonB for energy transduction. One TonB family protein and two sets of ExbB-ExbD-TonB were found and identified inR. anatipestifer[14]. In other bacteria, such asE. coli[29] andPseudomonas fluorescens[28], thetonB gene is negatively regulated by iron. However, the transcription oftonBgenes inR. anatipestiferCH-1 was not significantly changed in the iron-limited condition. To ensure the validity of the result, we also used qRT-PCR to measuretonB gene transcription in iron-limited conditions. The result was coincident with that of RNA-Seq. These results suggested that, in contrast to many bacteria, thetonB systems ofR. anatipestiferCH-1 are not regulated by iron.Once siderophore-bound Fe3+ is transported into the cytoplasm, the iron must be released from the siderophore. The first mechanism is that siderophore-bound Fe(III) is reduced to siderophore-bound Fe(II) followed by its spontaneous release due to the low affinity of iron Fe(II) with the siderophore. Another mechanism is that siderophore-bound Fe(III) is hydrolyzed by specialized enzymes, leading to a dramatic loss of complex stability and facilitating the subsequent removal of the iron [30] in a reduction process. In this study, a gene coding for a siderophore-interacting protein (B739_0608) was upregulated significantly in the presence of iron depletion. This siderophore-interacting protein is involved in iron acquisition and virulence inR. anatipestifer strain CH-3 [31]. Surprisingly, among the upregulated genes, we did not find any homologue gene related to siderophore synthesis.


## 3.6. A Putative Polysaccharide Utilization Locus ofR. anatipestiferCH-1 Was Upregulated in Iron-Limited Conditions

InCapnocytophaga canimorsus, a member of the Bacteroidetes, a polysaccharide utilization system uses serotransferrin as an iron source [32]. Each polypeptide encoded by this locus is required for this iron uptake activity [32]. This type of system was named the iron capture system (ICS), and it contains seven genes:icsA, icsC, icsD, icsE, icsF, icsG,andicsH[32]. In this study, we identified a gene cluster (B739_0094, B739_0095, B739_0096, B739_0097, B739_0098, B739_0099, B739_0100, B739_0101, B739_0102, and B739_0103) (Table 2) involved in polysaccharide utilization, the expression of which was upregulated in the presence of iron depletion. Sequence comparison showed that the homologues oficsC, icsD, icsE, icsF, icsG,andicsH fromCapnocytophaga canimorsus are B739_0103, B739_0102, B739_0101, B739_0100, B739_0099, and B739_0098, respectively, in theR. anatipestiferCH-1 genome. The homologue oficsA,B739_1068, was not cotranscribed with the others. Interestingly, some genes that were upregulated in the gene cluster, such as B739_0094, B739_0095, B739_0096, and B739_0097, were not predicted to contribute to the ICS system. Additionally, theR. anatipestiferCH-1 genome contains at least 6 polysaccharide utilization systems. In iron-limited conditions, three of the genes (locus B739_0094–B739_0103, locus B739_2091–B739_2093, and locus B739_0310–B739_0312) were upregulated (Table 2), while three other genes (locus B739_0115–B739_0118, locus B739_0875-B739_0876, and locus B739_1044-B739_1045) were downregulated (Table S3). Why some loci were upregulated and some loci were downregulated in the iron-limited condition is not currently understood.


## 3.7. Iron Limitation Increased Transcription of Putative Hemin Acquisition Systems

In the host, heme-containing proteins, such as hemoglobin, can be used as the main iron source by pathogenic bacteria [33]. Hemin uptake systems are regulated by iron in other bacteria [34, 35]. Here, putative genes involved in hemin uptake were more highly expressed in iron-limited cultures ofR. anatipestiferCH-1 than in iron-replete cultures. Within the upregulated genes, the most highly expressed gene cluster wasFepA-hmuY (B739_1416, B739_1417), which encodes a putative outer membrane ferrienterochelin, a colicin receptor and an HmuY-like hemophore protein. InPorphyromonas gingivalis, HmuY is a heme-binding lipoprotein associated with the outer membrane or secreted to the outside environment [36, 37]. Gene (B739_1415) adjacent to theFepA-hmuYoperon was also upregulated in iron-limited medium. The functions of B739_1415, B739_1416, and B739_1417 in hemin utilization are underinvestigated in our group.


## 3.8. Transcription of Respiratory Chain Genes

In aerobic metabolism, the respiratory chain typically uses proteins that require iron as a cofactor [38]. WhenR. anatipestiferCH-1 was grown in iron-limited medium, the expression of genes coding for cytochrome biogenesis protein (B739_0948), periplasmic cytochrome c552 subunit (B739_0946), and cytochrome C (B739_0186) were downregulated (Table S3). It indicated that iron restriction hinderedR. anatipestifer aerobic metabolism. Similarly, in other bacteria, such asPseudomonas fluorescens Pf-5, the transcription levels of genes encoding cytochrome c-type biogenesis proteins (PFL_1684-88) and subunits of cbb3-type cytochrome c oxidases (PFL_1922-25, PFL_2834) are downregulated in iron-limited versus iron-replete medium [28].


## 3.9. Transcription of Genes Related to Natural Competence

Natural transformation refers to the process by which bacteria can actively take up and integrate exogenous DNA. Natural transformation is a major mechanism of horizontal gene transfer (HGT) and plays a prominent role in bacterial evolution [39]. The process ofVibrio cholerae natural transformation involves four steps: DNA-binding via type IV pili, DNA pulling via ComEA, DNA translocation via ComEC, and DNA recombination by the single-strand DNA-binding proteins DprA and RecA [40]. Previously, we found thatR. anatipestiferCH-1 is naturally competent [41]. InR. anatipestiferCH-1, no putative type IV pilus locus is evident in the genome. InR. anatipestiferCH-1, two proteins that are predicted to be involved in the DNA uptake process, a ComEC homologue (B739_1095) and a gene encoding a single-strand DNA-binding protein (B739_1757), were downregulated in iron-limited conditions. One possibility for this phenomenon is that these proteins require iron for activity, as well as iron being predicted to be involved in the natural transformation process. This relationship between natural transformation and iron availability has not yet been described.


## 4. Conclusion

In this study, we examined the transcriptomic impact of iron limitation onR. anatipestiferCH-1 by comparing iron-limited TSB cultures with iron-replete TSB cultures. This transcriptome analysis identified numerous genes involved inR. anatipestiferCH-1 iron utilization. Under iron limitation, we observed changes in the transcription levels of genes related to iron homeostasis functions, such as the Feo system, the ICS system, and other iron uptake systems. Iron limitation also resulted in several unexpected responses, particularly the increased transcription of the ribosomal protein genes L18, L15, and L31. The data in this study were useful for identifying genes involved in iron utilization inR. anatipestiferCH-1 and for shedding light on the adaptation mechanisms ofR. anatipestiferCH-1 in iron-limited environments, such as hosts.



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*Source: 8682057-2017-04-30.xml*