&

July 2018

Microbes Environ. Vol. 31, No. 1, 33-40, 2016

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME15171

MOST VALUABLE PAPER OF THE YEAR 2016

FLDS: A Comprehensive dsRNA Sequencing Method for Intracellular RNA
Virus Surveillance
Syun-iChi urayama1*, yoShihiro taKaKi1,2, and taKuro nunoura1
1Research and Development Center for Marine Biosciences, Japan Agency for Marine-Earth Science and Technology (JAMSTEC),

2–15 Natsushima-cho, Yokosuka, Kanagawa 237–0061, Japan; and 2Department of Subsurface Geobiological Analysis andResearch, JAMSTEC, 2–15 Natsushima-cho, Yokosuka, Kanagawa 237–0061, Japan(Received October 21, 2015—Accepted December 1, 2015—Published online February 13, 2016)

Knowledge of the distribution and diversity of RNA viruses is still limited in spite of their possible environmental andepidemiological impacts because RNA virus-specific metagenomic methods have not yet been developed. We herein constructed
an effective metagenomic method for RNA viruses by targeting long double-stranded (ds)RNA in cellular organisms, which isa hallmark of infection, or the replication of dsRNA and single-stranded (ss)RNA viruses, except for retroviruses. This novel
dsRNA targeting metagenomic method is characterized by an extremely high recovery rate of viral RNA sequences, theretrieval of terminal sequences, and uniform read coverage, which has not previously been reported in other metagenomic
methods targeting RNA viruses. This method revealed a previously unidentified viral RNA diversity of more than 20 complete
RNA viral genomes including dsRNA and ssRNA viruses associated with an environmental diatom colony. Our approach will
be a powerful tool for cataloging RNA viruses associated with organisms of interest.
Key words: RNA virus, viral metagenome, dsRNA

to increase the viral read ratio; however, a relatively low
abundance of viral reads is still observed in most studies (39).
These techniques are only applicable to specific RNA viruses
because not all RNA viruses form viral particles (21). In
addition, difficulties are associated with capturing terminal
RNA sequences in an efficient and effective manner (32) andobtaining uniform coverage using the RNA-seq method.
Sample preparation methods for effective viral RNA-seq are
still inadequate and the sequence information generated isbiased and incomplete.
In an attempt to resolve these issues, an environmental
viral metagenomic approach targeting intracellular long doublestranded RNA (dsRNA) has recently been examined (2, 6, 9,37). Intracellular dsRNA consists of the genomes of dsRNA
viruses and replicative intermediates of single-stranded RNA(ssRNA) viruses, and, thus, long dsRNA is known as an RNA
virus-specific molecule and molecular marker for RNA virus
infection and replication (28). Therefore, a metagenomic
analysis targeting intracellular long dsRNA theoretically
retrieves dsRNA and ssRNA viruses, except for ssRNA retroviruses, which do not form dsRNA in the replicative stage. In
addition, it is possible to eliminate non-viral nucleic acids
such as mRNA and rRNA, which dominate RNA-seq reads,
by DNase I, S1 nuclease, RNase, or column chromatography(44). However, previous studies have reported technical issues
with the purification of dsRNA and library construction.
Random priming for the reverse transcription of dsRNA does
not enable the terminal sequences of the dsRNA molecule tobe determined or eliminate significant contamination by
non-viral sequences. The heterogeneous sequencing depth incertain viral genome segments is also an issue associated withthis method (2, 6, 9, 37). Although the full-length cDNAs ofdsRNA viruses may be obtained using loop primers that are
ligated to the dsRNA terminal ends for reverse transcription

Viruses are the universal genetic elements associated withall three domains of life (22), and virus-host interactions
impact on the status of life and surrounding ecosystems (41).
Historically, viruses are most often recognized as pathogens(38), and, thus, have been studied in the field of medical andcrop science. Recent advances in high-throughput sequencing
technologies have enabled us to identify not only viruses
associated with diseases, but also those present in naturalenvironments including oceans (41) and soil (12). Althoughthese sequencing technologies have opened a new era in virus
identification (24), a limited number of methods have been
established for virus enrichment and library construction. The
diversity and distribution of viruses in non-viral nucleic
acid-dominant environments, such as the intracellular environments in which viruses actually replicate, still remain
unclear due to technical difficulties (16). The development of
a new procedure for effective virus enrichment and library
construction is required in order to understand the full spectrum of diverse viruses.
RNA sequencing (RNA-seq) is a popular method in RNA
virus metagenomics and is widely used for RNA virus identification (35). Purification and library construction methods
have been established for RNA viruses at the extracellular
stage (7, 10, 40). However, the viral read ratio of intracellular
RNA viruses (RNA viruses at the intracellular stage) in the
RNA-seq library is typically < 1% because mRNA and rRNA
are dominant in the total RNA fraction extracted from biological samples (25). Therefore, the enrichment of viral RNA isessential for maximizing sensitivity in the identification ofnovel viruses. The physical enrichment of viral particles andnuclease digestion of non-viral nucleotides has been employed* Corresponding author. E-mail: urayamas@jamstec.go.jp;
Tel: +81–46–867–9660; Fax: +81–46–867–9715.

1

Urayama et al.

34(8), this method is only useful for short dsRNA viruses.
Therefore, to the best of our knowledge, this method has not
yet been applied to a viral metagenomic analysis.
We herein established a novel strategy to obtain full-length
RNA virus sequences with extremely high efficiency byapplying a short dsRNA full-length cloning method (8) for
physically fragmented dsRNAs. The improved method,
named FLDS (fragmented and loop primer ligated dsRNA
sequencing), was applied to a diatom colony in a tide pooland revealed previously unidentified RNA viruses. Our
results indicate that the diversity of environmental RNA
viruses has been underestimated due to the technical limitations in identifying entire RNA viromes in cellular organisms,
and this technique will be a powerful tool for cataloging RNA
viruses associated with organisms of interest.

hybrid RNAs were removed (34), cDNA was desalted and concentrated using the MinElute PCR cleanup kit (Qiagen). Primary cDNA
strands were re-annealed by lowering the temperature from 95 to
50°C, as described previously (30). Second strand DNA polymerization was performed using KOD-plus Neo (Toyobo, Osaka, Japan)
with a primer complementary to the partial sequence of the PC3-T7
loop primer, PC2 (5′-CCG AAT TCC CGG GAT CC-3′) (34). After
heat activation of KOD-plus Neo in the reaction mixture provided at
96°C for 2 min, template cDNA was added and incubated at 68°C
for 5 min. After the reaction, cDNA was amplified under thefollowing conditions: 96°C for 2 min, 25 (for MoCV1-A) or 18 (fordiatom colony) cycles of 98°C for 10 s, and 68°C for 2 min. Small
cDNA and primer dimers were removed using the 1.25 × SPRIselectreagent kit (Beckman Coulter, Brea, CA, USA) according to the LeftSide Size Selection procedure in the manufacturer’s protocol.
Total RNA extraction, cDNA synthesis, and library construction
from an environmental sample
Total RNA was isolated from a diatom colony using the TRIzol
Plus RNA Purification Kit (Invitrogen) according to the manufacturer’s
protocol. The RNA fraction was treated with DNase I (Takara, Otsu,
Japan). Double-stranded cDNA was synthesized from 2 μg of total
RNA with random primers (9-mers) using a PrimeScript Double
Strand cDNA Synthesis Kit (Takara). The resultant cDNA wasquantified using a Qubit dsDNA HS Kit.

Materials and Methods
Model and environmental samples
Mycelial plugs of Magnaporthe oryzae strain S-0412-II 1a,naturally infected with Magnaporthe oryzae chrysovirus 1 strain A(MoCV1-A) (45) were incubated in 0.5% yeast extract and 2%
glucose liquid broth (YG broth) with reciprocal shaking (60 rpm) at
25°C for 2 weeks in the laboratory of Prof. Teraoka (Tokyo
University of Agriculture and Technology). Colonies of a diatom on
tidal rocks in Tokyo Bay (35.3405° N, 139.6396° E) were sampled
in April 2014. After washing with distilled water, the colonies werestored at –80°C.

Illumina sequencing
Ultrasound was used to fragment cDNA in Snap-Cap microTUBEs at 4°C using a Covaris S220 (Woburn, MA, USA). The
fragmentation conditions were as follows; run time 55 s, peak power
175.0 W, duty factor 5.0% and 200 cycles/burst. The Illumina
library was constructed with KAPA Hyper Prep Kit Illumina platforms (Kapa Biosystems, Woburn, MA, USA). The quantity of thelibrary was evaluated using the KAPA library quantification kit(Kapa Biosystems). Each 300 bp of the paired-end sequences ofeach fragment were determined with the Illumina MiSeq platform(San Diego, CA, USA).

Purification and fragmentation of dsRNA
DsRNA was purified as described by Okada et al. with a few
modifications (31, 46). Briefly, the microbial sample was disrupted
in liquid nitrogen in a mortar and total nucleic acids were manually
extracted. DsRNA was purified twice through a micro-spin column(empty Bio-spin column; Bio-Rad Laboratories, Inc., Hercules, CA,
USA) containing cellulose powder (Cellulose D; ADVANTEC,Tokyo, Japan) to obtain pure dsRNA. The dsRNA eluted from cellulose powder in MQ water was treated with DNaseI (amplification
grade, Invitrogen, Carlsbad, CA, USA) and S1 nuclease (Invitrogen)in nuclease buffer (57 mM CH3COONa, 9.5 mM MgCl2, 1.9 mM
ZnSO4, and 189 mM NaCl) and was then incubated at 37°C for 2 h.
The final concentrations of CH3COONa, MgCl2, ZnSO4, and NaCl
were adjusted to 90 mM, 15 mM, 3 mM, and 300 mM, respectively.
DsRNA was purified using an RNeasy Mini Kit (Qiagen, Valencia,
CA). A one-tenth volume of 10 × ShortCut buffer and 10 × MnClprovided with ShortCut RNase III (NEB Japan, Tokyo, Japan) was
added to the dsRNA solution and fragmented by ultrasound at 4°C
in Snap-Cap microTUBEs using a Covaris S220 (Woburn, MA,
USA). The fragmentation conditions were as follows; run time 35 s,
peak power 140.0 W, duty factor 2.0%, and 200 cycles/burst.
Fragmented dsRNA was divided into two equal volumes, and maintained at 37°C with or without ShortCut RNase III (NEB). DsRNAs
were then purified using a ZymoClean Gel RNA Recovery Kit(ZymoResearch, Orange, CA). Note that dsRNA purification fromM. oryzae was carried out in the laboratory of Prof. Teraoka.

Data assembly and processing
Raw sequence reads were processed with the CLC Genomics
Workbench (CLC Bio, Aarhus, Denmark). Adaptor and primer
sequences were trimmed, and low quality sequence regions were
removed with default parameters. PhiX sequences derived fromcontrol libraries and experimentally contaminated sequences (< 0.05%
of total reads) were also removed using a mapping tool. The consensus sequences of viral contigs were obtained de novo exclusively
with the CLC Genomics Workbench (CLC Bio), and assemblies
were manually examined and extended using the Tablet viewer (27).
Using the mapping tool, each contig was confirmed to be constructed with at least 3 × sequence coverage, 10 × average coverage,
and 1,000 bp in length. In cases of dominant reads (more than 10
reads) that stopped in the same position around the ends of contigs,
the position was recognized as a terminal end. The predicted terminal ends of the viral genome segments were also confirmed by thepresence of adjacent PCR primer sequences next to the predicted
terminal sequence, except for cases of contigs with a poly(A) tail.
Contigs with 70–90% nucleotide identity with other contigs wereclassified as the genome types of the same species. Contigs with
> 90% nucleotide identity were assigned as the same genome typeand only major contigs were used in further analyses. Sequenceswere compared against the NCBI non-redundant nucleotide andamino acid (aa) databases using BLASTN-plus and BLASTX-plus,
respectively (5), and then classified by MEGAN 5.7.1. (18). A sequence
analysis was performed using Genetyx-MAC software version
17.0.0 (Genetyx Corp., Tokyo, Japan) and Genetyx software version
9.1.0 (Genetyx). Most full-length small subunit rRNA sequences inthe diatom colony were reconstructed from RNA-seq reads with
EMIRGE (26).

cDNA synthesis and amplification for dsRNA
The PC3-T7 loop primer (5′-p-GGA TCC CGG GAA TTC GGTAAT ACG ACT CAC TAT ATT TTT ATA GTG AGT CGT ATT
A-OH-3′) was ligated to fragmented dsRNA as described by Potgieter
et al. (34), and dsRNA was then purified using the MinElute Gel
Extraction Kit (Qiagen). After the addition of DMSO at a final concentration of 15% (v/v), dsRNA was denatured at 95°C for 3 min
and snap-frozen in ice-water slurry. RNA was reverse transcribed
into cDNA from the ligated loop primer region using the Superscript
III First-Strand Synthesis System (Invitrogen). After excess and2

Library preparation for dsRNA metagenomics

35

dsRNA molecules. Reverse transcription was initiated fromthe ligated loop primer on both ends of the dsRNA fragment.
cDNA was then thermally denatured to allow annealing of
single-stranded cDNA with the complementary sequence inthe 3′ terminal region. The single-stranded regions of annealed
cDNA were filled in with DNA polymerase. The doublestranded cDNA derived from dsRNA was amplified by PCR
with a single primer (PC2) in order to obtain sufficient cDNA
to construct a sequencing library.
Mycelial MoCV1-A was used to test the feasibility of thismethod. Since PCR amplicons were not observed in thedsRNA-specific RNaseIII-treated sample prior to reverse
transcription, most of the amplicons (cDNA) were likely tohave been derived from dsRNA (Fig. S1). The results of thesequencing analysis indicated that 99.1% of total reads were
derived from the MoCV1-A genome (Table S1). Five contigs
obtained by de novo assembly were identical to the entire
region of the MoCV1-A genome segments attained using a
conventional cloning and sequencing method (44, 45) with> 99.9% identity (Table S2). Read mapping on MoCV1-A
genomes (Fig. S2) showed that the sequence coverage ofterminal regions was generally higher than that of the central
regions of each segment with few exceptions. No obvious
relationship was observed between read coverage and GC
content (Fig. S2). These results indicated that FLDS effectively enriched dsRNA reads, thereby allowing the retrievalof complete genome sequences including terminal regions
without the requirement for the additional rapid amplificationof cDNA ends (RACE).

Phylogenetic analysis
Multiple alignments based on the deduced aa sequences of putative RNA-dependent RNA polymerase (RdRp) genes in dsRNA
contigs were obtained using ClustalX 2.0 (23) and MEGA5 software(42). Phylogenetic analyses were conducted using MrBayes 3.2.3(36) with the model of aa substitution, RtREV+I+G+F, selected by
ProtTest2.4 (1), as judged by the Akaike information criterion (33).
Bayesian analyses with the covarion parameter were run with one
run and four chains for 1,000,000 generations.
Data accession
The data sets supporting the results of this study are available in
the GenBank database repository (accession nos. DDBJ: AP014890–
AP014920) and Short Read Archive database (accession no. DDBJ:
DRA003723 and DRA003724).

Results
Application of FLDS to a segmented dsRNA virus
The novel dsRNA purification and library construction
method, named FLDS, consists of cellulose column chromatography, the physical fragmentation of dsRNA, cDNA synthesis using a loop primer, and the PCR amplification of
cDNA (Fig. 1). The purification of dsRNA was achieved by
the repeated affinity purification of dsRNA using cellulose
powder and the enzymatic removal of ssRNA and DNA.
Purified dsRNAs were fragmented using ultrasound to retrieve
all types of dsRNA viruses in order to apply the previously
reported full-length dsRNA cloning method using a loop
primer (8). The full-length dsRNA cloning method requires
overlapped cDNAs synthesized from both terminal ends forfurther cDNA amplification, and was only applicable to short

FLDS analysis in an environmental diatom colony
Gel electrophoresis showed that the total long dsRNA
fraction from the diatom colony contained at least ten dsRNA
segments, whereas genomic DNA and rRNA were the predominant in total nucleic acids (Fig. 2). Total dsRNA extracted
from 1 g of the diatom colony was analyzed using the FLDS
method. PCR amplicons were not observed in the dsRNAspecific RNaseIII-treated sample prior to reverse transcription (Fig. S3). As a result of de novo assembly and manual
extension, we obtained 42 composite viral contigs (Table 1
and Table S3). More than 98.2% of reads were mapped tothese 42 contigs (Table 2) as in the case of the model experiment described above. Both terminal ends of 31 of the viralcontigs were identified and recognized as full-length viralgenome segments. The terminal sequences of the full-length
segments were used to identify segment compositions forsome of the viral species because terminal sequences arehighly conserved between segments in some dsRNA viralgenomes for viral RNA replication and/or encapsidation (19).
Based on aa sequence similarities (E-value ≥ 1 × 10–5) inthe predicted protein-encoding sequences (CDSs), the numberof genome segments in related viruses, and terminal conserved
sequences in each segment of a single virus, we identified 22
viral putative composite genomes out of 31 full-length viralsegments. Sequence similarities between the 22 putative viralcomposite genomes were used to classify them into 19 putative
viral species, and each of the two genome types was identified
in three species (Table 1). Seventeen dsRNA and two ssRNAviral species were identified and named Diatom ColonyAssociated dsRNA virus 1–17 (DCADSRV-1–17) and Diatom

Fig. 1. Schematic work flow of FLDS. 1. Fragmentation of dsRNA by
ultrasound. 2. Ligation of a loop primer on 3′-terminal ends and reverse
transcription. 3. Selective duplex formation of cDNA from dsRNA, and
PCR amplification. Details of the FLDS method are described in the
Materials and Methods section.

3

Urayama et al.

36

tages in uniform read coverage and efficiency for retrieving
terminal sequences (Fig. 4). Sequence reads for ssRNA
viruses in FLDS were also more abundant than when RNAseq was used for four out of five ssRNA contigs. In addition,
by de novo assembly, only six partial viral contigs wereobtained using RNA-seq, and no viral contigs specific for
total RNA-seq were found. Accordingly, we concluded that
FLDS is more efficient than total RNA-seq for the detection
and identification of RNA viruses, with the exception of retroviruses, which theoretically cannot be identified using FLDS.
Phylogenetic analysis and characterization of viral RNA
genomesA phylogenetic analysis of viral RNA replicases (RNAdependent RNA polymerase; RdRp) presented the phylogenetic relationship between viral genomes from a diatom
colony and known RNA viruses (Fig. S4). Viruses belonging
to the family Totiviridae harbor non-segmented dsRNA
genomes and form isometric virions that infect either fungi or
protozoa (21). Thirteen composite genomes of Totiviridaerelated viruses were identified and classified into four clades
distinct from the five characterized genera of Totiviridae(clades a–d in Fig. S4A). Clade c was the sister clade of the
proposed genus “Trichomonasvirus” and clade d included
Ustilaginoidea virens RNA virus 1 (UvRV1). In general, –1
ribosomal frameshift signals [the XXXYYYZ motif (4), in
which XXX may be any three identical nucleotides, YYY
may be either AAA or UUU, and Z may be A, U, or C] or+1 ribosomal frameshift signals [CCCUUUU (14) or
UCCUUUCGU (47)] were located in the upstream region of
the 2nd CDS, and were used in the expression of overlapping
viral genes such as the pol (RdRp) of Totivirus andLeishmaniavirus. These regions were examined in an attempt
to better classify the identified viruses. However, as in thecase of UvRV1, –1 or +1 ribosomal frameshift signals were
not found in any of the Totiviridae genomes obtained in thisstudy. CDSs in the predicted Totiviridae virus-like segments
DCAVLRS-3 and DCAVLRS-4 showed significant similarities with the gag (coat protein; CP) and pol (RdRp) of known
totiviruses, respectively. Totiviridae genomes consist of asingle genome segment that encodes the two essential CDSs,
whereas DCAVLRS-3 and -4 lacked pol and gag, respectively.
These two segments harbored nine identical 5′-terminal
nucleotide sequences, which were distinguishable from theother identified terminal viral sequences. Genomic features
implied that DCAVLRS-3 and -4 may be parts of a bisegmented viral genome. RdRp in DCADSRV-1 segment 2
showed significant homology with that in fox Picobirnavirus,
a member of the Picobirnaviridae, although DCADSRV-1
was phylogenetically distinct from the known Picobirnaviridae
viruses (Fig. S4B). Picobirnaviruses are small, non-enveloped,
bisegmented dsRNA viruses that infect animals and humans(21). The genome structure of DCADSRV-1 was similar tothat of the known Picobirnaviridae (21). DCADSRV-14 wasclassified into the genus Deltapartitivirus of the family
Partitiviridae based on the predicted RdRp sequence (Fig.
S4C) (29). To date, all of the alphacryptoviruses have been
identified from plants including the angiosperm, gymnosperm, and chlorophytes (29). rRNA sequences belonging to
the Streptophyta, including land plants, have not yet beenFig. 2. Agarose gel electrophoresis of purified nucleic acids from adiatom colony. Nucleic acids were stained with ethidium bromide. Lane
M, 300 ng of HindIII-digested λ DNA; lane 1, total nucleic acids extracted
from 5 mg (wet weight) of the diatom colony; lane 2, purified dsRNA
extracted from 1 g (wet weight) of the diatom colony.

Colony-Associated ssRNA virus 1–2 (DCASSRV-1–2)(Table 1). Since ssRNA viruses form an RNA duplex as anintermediate in genome replication, these contigs were most
likely derived from replicating ssRNA viruses (11) and notfrom contaminant ssRNA. An additional seven full-lengthviral segments with predicted CDSs were also identified;
however, we were unable to determine the combination of
their segments or reconstruct viral genomes based on information from previously reported viruses. Thus, these viralsegments were assigned as Diatom Colony-Associated VirusLike RNA Segments (DCAVLRS-1–7).
Comparison between FLDS and total RNA-seq
Total RNA from the diatom colony was also investigatedusing shotgun RNA-seq in order to determine the active
organisms of the colony and the abundance of viral RNA
genomes in total RNA. Sequence reads derived from rRNA
were identified using EMIRGE (26). The results of theanalysis revealed that 56% of all trimmed reads were rRNA
sequences, while 37.2% of all reads showed more than 99%
identity to 18S and 23S rRNA from the diatom Achnanthes
brevipes. In addition, 4.1 and 6.2% of reads belonged to theother diatom genus Cylindrotheca and chlorophyte genus
Cladophora, respectively. The relative abundance of therRNA reads was shown in Table S4.
Only 0.3% of reads from total RNA-seq was mapped on
the major viral contigs obtained using FLDS with a read
mapping algorithm in the CLC workbench (Table 2).
Comparisons of the relative read frequencies of each major
viral contig between total RNA-seq and FLDS revealed that
FLDS achieved 0.8–4372.3-fold enrichment for each viralcontig (653.2 mean) (Fig. 3). FLDS also had apparent advan4

Library preparation for dsRNA metagenomics

37

Table 1. List of complete composite genomes of RNA viruses and full-length virus-like RNAs obtained from a diatom colony obtained using FLDS.
Accession

Description

Size (nt)

DCADSRV-1a) AP014890
AP014891

segment 1
segment 2

1,734
1,562

Num. of Average
mapped coverage
reads
1,301,278 191,942
1,717,396 279,580

RNA virus
species

DCADSRV-2

AP014892

4,026

1,337,570

DCADSRV-3

AP014893

4,911

14,544DCADSRV-4

AP014894 Genome type A

4,982

12,325DCADSRV-4

AP014895 Genome type B

4,979

1,074

DCADSRV-5

AP014896

5,252

7,863

DCADSRV-6

AP014897

4,939

2,720

DCADSRV-7

AP014898

5,327

1,957

DCADSRV-8

AP014899

4,660

1,163

DCADSRV-9

AP014900 Genome type A

4,844

1,198

DCADSRV-9

AP014901 Genome type B

4,845

364

DCADSRV-10 AP014902

5,082

1,244

DCADSRV-11 AP014903

5,160

1,173

DCADSRV-12 AP014904

5,941

1,219

DCADSRV-13 AP014905

4,671

820

DCADSRV-14a) AP014906

segment 1

1,576

438

AP014907
DCADSRV-15 AP014908

segment 2

1,490
12,172

274
1,482

DCASSRV-1

AP014912

11,413

1,011

DCASSRV-2

AP014913

4,586

4,153

DCADSRV-16 AP014909

6,635

8,735

DCADSRV-17 AP014910 Genome type A

5,907

5,325

DCADSRV-17 AP014911 Genome type B

5,909

1,564

DCAVLRS-1

AP014914 Interrupted RdRp

4,567

57,802

DCAVLRS-2

AP014915 Interrupted RdRp

4,786

41,181DCAVLRS-3

AP014916

CP only

3,458

13,140DCAVLRS-4

AP014917

RdRp only

3,190

3,995

DCAVLRS-5

AP014918

CP only

3,262

1,331

DCAVLRS-6

AP014919

RdRp only

3,325

891

DCAVLRS-7

AP014920 Interrupted RdRp

1,986

164

BlastX analysis
Top Hit for each CDS, Virus family

E-value

Protein———Fox Picobirnavirus 1 × 10–33
RdRp
Picobirnaviridae
RdRp
83,876 Ustilaginoidea virens nonsegmented virus 1 5 × 10–15
Not assigned
RdRp
703
Ustilaginoidea virens RNA virus 1 2 × 10–63
Totiviridae
RdRp
591
Aspergillus mycovirus 178 4 × 10–69
Totiviridae
52
Ustilaginoidea virens RNA virus 1 5 × 10–69
RdRp
Totiviridae
RdRp
359
Aspergillus foetidus slow virus 1 3 × 10–74
Totiviridae
RdRp
131
Aspergillus mycovirus 178 2 × 10–66
Totiviridae
RdRp
87
Gremmeniella abietina RNA virus L1 3 × 10–123
Totiviridae
Ustilaginoidea virens RNA virus 3 2 × 10–56
CPTotiviridae
RdRp
60
Aspergillus foetidus slow virus 1 8 × 10–57
Totiviridae
RdRp
60
Magnaporthe oryzae virus 2 1 × 10–65
Totiviridae
18
Aspergillus foetidus slow virus 1 2 × 10–66
RdRp
Totiviridae
RdRp
59
Rosellinia necatrix victorivirus 1 2 × 10–108
Totiviridae
Ustilaginoidea virens RNA virus 1 6 × 10–50
CPTotiviridae
RdRp
55
Ustilaginoidea virens RNA virus 1 4 × 10–128
Totiviridae
Ustilaginoidea virens RNA virus 1 8 × 10–64
CPTotiviridae
RdRp
49
Beauveria bassiana RNA virus 1 1 × 10–40
Totiviridae
RdRp
42
Aspergillus foetidus slow virus 1 4 × 10–58
Totiviridae
67
Persimmon cryptic virus 3 × 10–97
RdRp
Partitiviridae
43
—
—
—
29
Chalara endornavirus CeEV1 1 × 10–115 Polyprotein
Endornaviridae
21
Border disease virus—BD31 4 × 10–15 Polyprotein
Flaviviridae
RdRp
224
Tuber excavatum mitovirus 5 × 10–20
Narnaviridae
RdRp
310
Rhizoctonia fumigata mycovirus 4 × 10–10
Not assigned
RdRp
218
dsRNA virus environmental sample 7 × 10–14
Not assigned
63
Botrytis porri RNA virus 1 1 × 10–13
RdRp
Not assigned
RdRp
3,039 Ustilaginoidea virens nonsegmented virus 1 3 × 10–11
Not assigned
RdRp
2,100 Ustilaginoidea virens nonsegmented virus 1 2 × 10–11
Not assigned
CP
876
Ustilaginoidea virens RNA virus 1 2 × 10–41
Totiviridae
RdRp
294
Magnaporthe oryzae virus 2 2 × 10–123
Totiviridae
CP96
Phomopsis vexans RNA virus 5 × 10–47
Totiviridae
RdRp
65
Ustilaginoidea virens RNA virus 3 6 × 10–102
Totiviridae
RdRp
20
Flammulina velutipes browning virus 4 × 10–63
Partitiviridaea) The classification was based on the shared 5′ terminal sequences in paired segments, whereas CDSs in the segments that did not show significant
similarities with genes in databases.

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Urayama et al.

38
Table 2.

Classification of next-generation sequencing reads obtained by FLDS and total RNA-seq.
FLDS

total RNA-seq

Num. of reads

rate (%)

Num. of reads

rate (%)

4,631,738
4,549,629
82,109

100.0
98.2
1.7

6,979,561
24,036
6,955,525

100.0
0.3
99.6

TrimmedMajor viral reads
Unmapped reads (include minor viral reads)

Fig. 3. Comparison of mapped read frequencies for each viral contig
between FLDS and total RNA-seq. Plots indicate each viral contig. The
rhombus and triangle plots show dsRNA and ssRNA viral contigs,
respectively. 100–10–7 represent the frequencies of reads in each library.
Dotted lines with 1×, 10×, 100×, or 1000× show a higher viral read frequency
than that with an RNA-seq analysis. Reads mapped with nine contigs
found in FLDS were not found in total RNA-seq.

Fig. 4. Comparison of coverage uniformity between FLDS and RNAseq. DsRNA segments with an average depth of > 200 in RNA-seq wereused for the analysis. (A) Coefficient of variation (the ratio of the standard
deviation to the mean coverage). Values were plotted on viral dsRNA
segments of DCADSRV-1 segment 1 (square), DCADSRV-1 segment 2(triangle), and DCADSRV-2 (circle), and were plotted on the Y axis.
(B–D) Genomic coverage of each viral segment from the FLDS (uppergraph) and RNA-seq (lower graph) analysis.

detected by an RNA-seq analysis, whereas Cladophora sp. of
the Chlorophyta, a sister division of Streptophyta, weredetected (Table S4). The CDSs of DCADSRV-15 and a few
viral contigs showed significant homology with viruses
belonging to the Endornaviridae (dsRNA), Naranviridae(ssRNA), or Hypoviridae (ssRNA), whose virion formation
has not yet been observed.
In the ssRNA viral population, RdRp in DCASSRV-1
presented a close relationship with Border disease virus—
BD31 (E-value = 4 × 10–15), a member of the genus Pestivirusof the family Flaviviridae, which consists of the arthropodborne pathogens of humans and other animals. The genome
size and CDS structure of DCASSRV-1 (11.4 kb) were similar
to those of Flaviviridae (9.6–12.3 kb) (21), and the phylogenetic tree of RdRp indicated that DCASSRV-1 was not classified into the three known Flaviviridae genera (Fig. S4D). A
phylogenetic analysis of RdRp in DCASSRV-2 suggested
that the RNA virus was classified into the genus Mitovirus,
which has a non-segmented ssRNA genome, infects the
mitochondria of fungi, and lacks viral particles (Fig. S4E).
The presence of multiple UGA codons suggested that theputative coding strand of DCASSRV-2 was likely to betranslated in mitochondria. The genome size of DCASSRV-2(4.5 kb) was larger than those of the known mitoviruses(2.3–3.6 kb) (17).

Discussion
This study revealed the presence of novel RNA viruses
associated with a diatom colony and inferred the unexpected
evolutionary relationship between environmental viruses andpathogenic animal viruses. Among the RNA viral genomes
obtained in this study, some dominant populations showed
greater similarities to fungal viruses than to known diatom
viruses; however, several ssDNA and ssRNA viruses havealready been identified from marine diatoms (20, 43). We
cannot exclude the possibility that these viral genomes were
derived from fungi associated with a diatom colony, but it ismore likely that they came from the major components of a
diatom colony because of their high abundance in the RNA
viral metagenomic library. Since extracellular viral particles
have been a major target of virus surveillance and isolation,
information on intracellular viruses in microorganisms isvery limited (13, 37). Therefore, the accumulation of knowledge on intracellular RNA viruses infecting diverse hostorganisms is essential for understanding the evolution anddistribution of RNA viruses.
6Library preparation for dsRNA metagenomics

39

FLDS revealed 22 full-length and some partial composite
viral RNA genomes associated with a diatom colony by denovo assembly. These were classified into five dsRNA(Totiviridae, Endornaviridae, Picobirnaviridae, Cystoviridae,
and Partitiviridae) and four ssRNA (Flaviviridae, Narnaviridae,
Virgaviridae, and Hypoviridae) virus families. To the best of
our knowledge, this is the largest number of full-length
genome sequences of novel RNA viruses identified in one
metagenomic library. The viral RNA community successfully detected in this study consisted of dsRNA viruses withor without virion formation and ssRNA viruses detected as
replicative intermediates. Our results suggest that FLDS
has the potential to detect a wide range of RNA viruses,
excluding retroviruses.
Several studies have been performed using metagenomic
analyses targeting dsRNA with Next-Generation Sequencing
technology. In these studies, viral read abundance reached amaximum of 52.7% (2). In contrast, FLDS provided extremely
high viral read abundance. The improvement in viral read
rates with FLDS was likely derived from [1] a combination of
repeating cellulose powder column chromatography andsubsequent enzymatic treatment, [2] the fragmentation andefficient thermal denaturation of dsRNA prior to cDNA synthesis,and [3] the selective duplex formation of dsRNA-derived
cDNA prior to PCR amplification. Furthermore, FLDS alsopresented advantages in reconstructing complete genome
sequences including terminal regions, which are difficult toobtain using RNA-seq and random priming methods (3). The
complete sequences of viral RNA segments are beneficial forthe identification of RNA virus segments, particularly incases in which coding CDSs did not show significant similarities with viral CDSs in databases. The application of a fulllength dsRNA cloning method using a PC3-T7 loop primer(8) to fragmented dsRNA enabled us to determine the terminal regions of long dsRNA genomes. Since T4 RNA ligase
requires a 5′ phosphoryl-terminated nucleic acid donor (PC3T7 loop primer) and 3′ hydroxyl-terminated nucleic acidacceptor for ligation activity, dsRNA fragments with 3′ terminal phosphate were not used as substrates. The terminal
structures of dsRNA fragmented by ultrasound have not beenreported. However, in the case of dsDNA fragmented byultrasound, double-strand breaks occur preferentially in5′-CpG-3′ dinucleotides, and the phosphate group is at the 5′side of G in the products (15). In this study, fragmented
dsRNAs were successfully converted into cDNA and amplified. Taking this into consideration, dsRNA fragmentation using
ultrasound with Covaris S220 also produced 3′ hydroxylterminated fragments. Furthermore, the lack of any modifications to the 3′ hydroxyl-terminal of viral RNA genomes (21)also allowed us to retrieve the terminal regions of the RNA
viral genome.
Total RNA-seq is considered to be a less-biased method
for identifying RNA viruses despite the very low abundanceof viral reads in general. In the present study, FLDS enrichedthe viral RNA reads by > 300-fold that with total RNA-seq(Table 2). Notably, FLDS produced significantly more
ssRNA viral reads than total RNA-seq; however, FLDS only
has the ability to detect ssRNA viruses at the replicative
stage. Moreover, FLDS showed more uniform read coveragethan RNA-seq. These results indicate that FLDS is more

effective than total RNA-seq for revealing all RNA viruses incellular organisms.
Acknowledgements
This research was supported in part by a Grant-in-Aid for
Scientific Research (26892031) from the Ministry of Education,
Culture, Sports, Science and Technology of Japan. We would like tothank Hiromitsu Moriyama, Shinsuke Kawagucci, Yukari YoshidaTakashima, and Mitsuhiro Yoshida for their fruitful discussions andvaluable suggestions. We also thank Tohru Teraoka at Tokyo
University of Agriculture and Technology allowing us the use of
equipment.
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Microbes Environ. Vol. 32, No. 2, 180-183, 2017https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME16179

MOST VALUABLE PAPER OF THE YEAR 2017

Short Communication
Predominant but Previously-overlooked Prokaryotic Drivers of Reductive
Nitrogen Transformation in Paddy Soils, Revealed by Metatranscriptomics
YoKo Masuda1†, hideoMi itoh2*†, YutaKa shiratori3, Kazuo isoBe1, shigeto otsuKa1, and Keishi senoo1
1Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1–1–1

Yayoi, Bunkyo-ku, Tokyo 113–8657, Japan; 2Bioproduction Research Institute, National Institute of Advanced Industrial Scienceand Technology (AIST), Hokkaido Center, 2–17–2–1 Tsukisamu-higashi, Toyohira, Sapporo 062–8517, Japan; and3Niigata Agricultural Research Institute, 857 Nagakuramachi, Nagaoka, Niigata 940–0826, Japan(Received November 21, 2016—Accepted January 16, 2017—Published online April 22, 2017)

Waterlogged paddy soils possess anoxic zones in which microbes actively induce reductive nitrogen transformation (RNT).
In the present study, a shotgun RNA sequencing analysis (metatranscriptomics) of paddy soil samples revealed that most RNTgene transcripts in paddy soils were derived from Deltaproteobacteria, particularly the genera Anaeromyxobacter andGeobacter. Despite the frequent detection of the rRNA of these microbes in paddy soils, their RNT-associated genes haverarely been identified in previous PCR-based studies. This metatranscriptomic analysis provides novel insights into the diversity
of RNT microbes present in paddy soils and the ecological function of Deltaproteobacteria predominating in these soils.
Key words: paddy soils, metatranscriptomics, denitrification, dissimilatory nitrate reduction to ammonium, nitrogen fixation

Paddy soils are characterized by temporal anaerobic conditions caused by waterlogging, and the active occurrence ofanaerobic biogeochemical processes (9). Among these active
processes, biological reductive nitrogen transformation (RNT),
i.e., denitrification (NO3–→NO2–→NO→N2O→N2), dissimilatory nitrate reduction to ammonium (DNRA; NO3–→NO2–→NH4+), and nitrogen fixation (N2→NH4+) contribute to lessleaching of nitrogen pollutants (NO3–, NO2–, and N2O) into
the environment and the greater retention of nitrogen-based
nutrients (NH4+) for rice plants in waterlogged paddy soils
than in upland soils (8, 22). Therefore, the identification of microbial drivers of RNT in paddy soils is important for successful
rice production with minimal environmental nitrogen burden.
However, a comprehensive understanding of the RNT
microbial community has not yet been achieved. In order toinvestigate RNT microbes in paddy soils, genes encoding the
enzymes that catalyze each reaction have been assessed via
PCR-based culture-independent methods, as represented by aclone library analysis (13, 24). Recent studies based on bacterial
genomics reported that the diversity of microbes harboring
RNT genes is greater than previously considered; PCR-based
methods have underrepresented this diversity because of
mismatches in the sequences of the primers used (5, 10, 21),indicating the need for alternative methods without a PCR
bias. Furthermore, simultaneous assessments of microbes
involved in denitrification, DNRA, and nitrogen fixation in asingle paddy field have not yet been performed. Moreover,limited information is available on the transcriptional profiles
in situ of RNT microbes in paddy soils because of the small
number of field studies conducted based on soil RNA, which
directly implicates RNT microbial activity. In the present
study, we investigated RNT-associated microbial diversity inpaddy soils via a shotgun RNA sequencing analysis without
any prior PCR preparation (metatranscriptomics).
In order to obtain a more complete understanding of paddy
soils with various biogeochemical properties spatially andseasonally (9, 12), soil RNA extracted from paddy soils inshallow (S1, S3) and deep (S2, S4) layers under waterlogged(S1, S2) and drained (S3, S4) conditions (Fig. S1) were subjected
to a metatranscriptomic analysis using an Illumina MiSeq
sequencer (Illumina, San Diego, CA, USA). The sequencesof RNT genes were retrieved from the metatranscriptomic
libraries obtained and taxonomically annotated through atandem similarity search with the blat and blast programs(full methods in Supplementary information).
Four reactions crucial to denitrification are catalyzed by
the following enzymes: NO3– reductase (Nar), NO2– reductase (Nir), NO reductase (Nor), and N2O reductase (Nos). The
nar transcripts detected in all soil samples using metatranscriptomics were related to those of Deltaproteobacteria,
Betaproteobacteria, Alphaproteobacteria, Gammaproteobacteria,and Acidobacteria (Fig. 1A), suggesting that these bacterialgroups are involved in the reduction of NO3– to NO2–. The nirtranscripts were mostly derived from Betaproteobacteria,
Gammaproteobacteria, and Alphaproteobacteria (Fig. 1A),
the members of which include common denitrifiers (5); thesewere also frequently detected in the same paddy soils in ourprevious PCR-based survey (24). Furthermore, nor and nos
transcripts were predominantly detected in Deltaproteobacteria(Fig. 1A), the transcripts of which were rarely detected via previous PCR assays (2, 24). Successive denitrification steps wereconsidered to be associated with common denitrifiers, such as
Betaproteobacteria, Gammaproteobacteria, Alphaproteobacteria,and Actinobacteria, which harbor nir, nor, and/or nos (18).
However, the metatranscriptomic data obtained in the present
study suggested that the reduction of NO2– into NO was
driven by these denitrifiers, and that the reduction of NO andN2O was mainly progressed by non-denitrifiers such as* Corresponding author. E-mail: hideomi-itou@aist.go.jp,
Tel: +81–11–857–8979; Fax: +81–11–857–8915.
† These authors contributed equally to this work.

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181

Fig. 1. Microbial diversity of RNT gene transcripts and rRNA. Taxonomic distribution of nar, nir, nor, nos, nrf, and nif transcripts, and rRNA at
the phylum and proteobacterial class level (A), and deltaproteobacterial genus level (B). Sample IDs indicate data derived from paddy soils in shallow(S1, S3) and deep (S2, S4) layers under waterlogged (S1, S2) and drained (S3, S4) conditions. Data represent the mean of triplicates.

Deltaproteobacteria, Bacteroidetes, Acidobacteria, andVerrucomicrobia, which harbor nor and/or nos, but not nir(5). Thus, paddy soil denitrification appears to be a cooperative process by each nitrogen oxide reducer, i.e., NO2– reducers(denitrifiers) and NO/N2O reducers (non-denitrifiers), similar
to nitrification (NH4+→NO2–→NO3–) orchestrated by NH4+oxidizing bacteria/archaea and NO2–-oxidizing bacteria (6).
These inferences in the denitrification process may be verified
using co-culture experiments on denitrifiers and non-denitrifiers.
DNRA, another NO3– reduction process, is catalyzed by
Nar and NH4+-forming NO2– reductase (Nrf). Most of the nrf
transcripts belong to Deltaproteobacteria, while some belong
to Verrucomicrobia (Fig. 1A). Together with the frequent
detection of nar transcripts derived from Deltaproteobacteria
as described above, Deltaproteobacteria appear to mainly
contribute to DNRA dynamics in paddy soils. Although
DNRA has been geochemically detected in paddy soils (1,23), limited information is available on DNRA microbial
diversity. To the best of our knowledge, the present study isthe first to attempt to identify the key player groups in DNRA
in paddy soils.
Diazotrophs harboring nitrogenase (Nif) drive nitrogen
fixation. The taxonomic composition of nif transcripts was
dominated by Deltaproteobacteria (Fig. 1A), indicating that
Deltaproteobacteria represents a key player group in nitrogen
fixation. Rhizospheric Alphaproteobacteria, Betaproteobacteria,
and Gammaproteobacteria and phototrophic Cyanobacteria

were considered to be key diazotrophs in paddy soils (13, 18).
However, we detected more nif transcripts in Deltaproteobacteria
than in these well-known diazotrophs; our results were consistent with a recent metatranscriptomic analysis based on a
microcosm study on Italian paddy soils (11).
The abundance of RNT genes derived from Deltaproteobacteria,
as described above, was also demonstrated in a shotgun DNA
sequencing analysis (metagenomics) (Fig. S2A). Additionally,
the microbial community structure based on rRNA gene/transcript sequences showed that Deltaproteobacteria is amajor group in paddy soil microbes (Fig. 1A, S2A). These
results support Deltaproteobacteria being a key player groupdriving RNT in paddy soils.
Further analyses on Deltaproteobacteria at the genus level
revealed the consistent detection of RNT gene transcripts
in metatranscriptomic data derived from the genera
Anaeromyxobacter and Geobacter (Fig. 1B), as well as their
RNT genes in metagenomic data (Fig. S2B). These genera
represent obligate anaerobes and metal reducers predominatingin paddy soils (7, 20) and exhibit some RNT activities in vitro(summarized in Table S1). Although the nitrogen fixation
activity of Anaeromyxobacter has yet to be characterized, thegenomes of some Anaeromyxobacter spp. conserve a similar
nif cluster to that of Geobacter spp. exhibiting nitrogen fixation activity (Fig. S3). Together with the detection of the niftranscripts of Anaeromyxobacter in this study, it is plausiblethat Anaeromyxobacter spp. perform nitrogen fixation.
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182

However, in contrast to Anaeromyxobacter and Geobacter
rRNA genes, their RNT genes have rarely been detected inpaddy soil samples using PCR-based techniques (4, 24).
Thus, the putative role of these genera in the RNT process hasreceived little attention despite their predominance in paddy
soils. The limited coverage of RNT gene-specific PCR primers
used in previous studies may have led to the oversight ofthese genera (10, 17); additionally, the GC content may be
implicated because the nor/nos/nrf/nif of Anaeromyxobacter
spp. showed markedly higher GC contents than the rRNA
genes and nor/nos/nrf/nif of other bacteria (Table S2). Even
improved nos universal primers, which have enabled lower
rates of sequence mismatches, were unable to amplify
Anaeromyxobacter nos (10). Therefore, a metatranscriptomic
analysis represents a more effective approach to examine thediversity of functional microbes, without any PCR bias
arising from the high GC content of target genes as well as
primer limitations.
Anaeromyxobacter and Geobacter, which have frequently
been detected in Japanese, Chinese, and Italian paddy soils(4, 11, rRNA data in Fig. 1B), predominate more in paddy
soils than in upland soils, as confirmed by the present study(Fig. 2A, B; Table S3). Their universal distribution andpredominance in paddy soils support Anaeromyxobacter andGeobacter being the key RNT players in paddy soils.
Furthermore, the predominance of these genera was found inriver sediments (Fig. 2A, B; Table S3); the RNT genes ofAnaeromyxobacter were frequently and globally detected inupland soil environments in recent shotgun metagenomics
studies (14, 15), indicating the contribution of these bacteria
to RNT not only in paddy soils, but also in other environments. The further application of metatranscriptomics acrossdifferent environments will expand our knowledge on thediversity of RNT microbes in nature as well as the ecological
function of Deltaproteobacteria in soil environments.
Previous studies on paddy soils identified the predominanceof Deltaproteobacteria and their ecological roles in dissimilatory metal reduction, sulfur/sulfate reduction, and hydrogenproduction (7, 9, 19). Although genomic studies showed theubiquitous possession of the RNT genes of Deltaproteobacteria,
the association of RNT with Deltaproteobacteria has notbeen considered because of the rare detection of their RNT

Fig. 2. Distribution of Anaeromyxobacter and Geobacter in various
soil environments. Proportions of Anaeromyxobacter (A) and Geobacter(B) against all bacteria estimated by a quantitative PCR method. The
mean±SD is shown (n=3). The paddy soil sample P3 was collected fromthe same paddy field used for the metatranscriptomic analysis in thisstudy. Asterisks indicate significant differences (Mann-Whitney U test;*, p<0.01; **, p<0.001); NS, not significant. Details of soil samples andqPCR data are summarized in Table S3.

genes in soil environments through PCR-based analyses. The
present study revealed the novel ecological functions ofAnaeromyxobacter and Geobacter within Deltaproteobacteria
dominating in paddy soils, namely, RNT, denitrification support,
and NH4+ production via DNRA and nitrogen fixation (Fig. 3).
Acknowledgements
We thank the technical staff of Niigata Agricultural ResearchInstitute for their assistance with field management, and T. ShinanoFig. 3. Ecological functions of Anaeromyxobacter and Geobacter, belonging to Deltaproteobacteria, predominant in paddy soils, expanded bymetatranscriptomics in this study. Anaeromyxobacter and Geobacter, ubiquitously predominant in paddy soils, are key player groups in the reductionof iron and manganese, which actively progresses in paddy soils soon after waterlogging (3, 4, 7, 9, 11, 20, Fig. 1B, S2B). Metatranscriptomics inthis study suggested that these genera also associate with reductive nitrogen transformation, i.e., denitrification, DNRA, and nitrogen fixation.
Sketches of Anaeromyxobacter and Geobacter are based on electron microscope photographs published elsewhere (3, 16). †, NO2– reduction to NO
is driven by common denitrifiers within Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria (5), not by Anaeromyxobacter andGeobacter within Deltaproteobacteria; ‡, Anaeromyxobacter reduce N2O to N2, whereas Geobacter do not (Table S1).

11

Metatranscriptomics of paddy soils

183(Hokkaido Agricultural Research Center, NARO), T. Hasegawa, H.
Akiyama (Institute for Agro-Environmental Science, NARO), S.
Asakawa (Nagoya University), S. Obata (Emeritus Professor of Mie
University), and Y. Ono (Fukushima Agricultural Technology
Center) for collecting and providing soil samples. This study was
supported by JSPS KAKENHI Grant Numbers JP22248038,
JP25252013, JP15KT0014, and JP15K14675, and the Science andTechnology Research Promotion Program for Agriculture, Forestry,
Fisheries and Food Industry (27004C), Japan.

12. Kögel-Knabner, I., W. Amelung, Z. Cao, S. Fiedler, P. Frenzel, R.
Jahn, K. Kalbitz, A. Kölbel, and M. Schloter. 2010. Biogeochemistryof paddy soils. Geoderma 157:1–14.
13. Mårtensson, L., B. Díez, I. Wartiainen, W. Zheng, R. El-Shehawy, andU. Rasmussen. 2009. Diazotrophic diversity, nifH gene expression
and nitrogenase activity in a rice paddy field in Fujian, China. Plant
and Soil 325:207–218.
14. Nelson, M.B., A.C. Martiny, and J.B. Martiny. 2016. Global biogeography of microbial nitrogen-cycling traits in soil. Proc. Natl. Acad.
Sci. U.S.A. 113:8033–8040.
15. Orellana, L.H., L.M. Rodriguez-R, S. Higgins, J.C. Chee-Sanford,
R.A. Sanford, K.M. Ritalahti, F.E. Löffler, and K.T. Konstantinidis. 2014.
Detecting nitrous oxide reductase (nosZ) genes in soil metagenomes:
method development and implications for the nitrogen cycle. MBio.
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Microbiol. 68:893–900.
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Proc. Natl. Acad. Sci. U.S.A. 109:19709–19714.
18. Shapleigh, J.P. 2006. The denitrifying prokaryotes, p. 769–792. In M.
Dworkin, S. Falkow, E. Rosenberg, K.H. Schleifer, and E. Stackebrandt(ed.), The Prokaryotes. Springer, New York.
19. Shrestha, P.M., M. Kube, R. Reinhardt, and W. Liesack. 2009.
Transcriptional activity of paddy soil bacterial communities. Environ.
Microbiol. 11:960–970.
20. Weber, K.A., L.A. Achenbach, and J.D. Coates. 2006. Microorganisms
pumping iron: anaerobic microbial iron oxidation and reduction. Nat.
Rev. Microbiol. 4:752–764.
21. Wei, W., K. Isobe, T. Nishizawa, L. Zhu, Y. Shiratori, N. Ohte, K.
Koba, S. Otsuka, and K. Senoo. 2015. Higher diversity and abundanceof denitrifying microorganisms in environments than considered previously. ISME J. 9:1954–1965.
22. Xiong, Z.Q., T.Q. Huang, Y.C. Ma, G.X. Xing, and Z.L. Zhu. 2010.
Nitrate and ammonium leaching in variable- and permanent-charge
paddy soils. Pedosphere 20:209–216.
23. Yin, S.X., D. Chen, L.M. Chen, and R. Edis. 2002. Dissimilatory
nitrate reduction to ammonium and responsible microorganisms in
two Chinese and Australian paddy soils. Soil Biol. Biochem.
34(8):1131–1137.
24. Yoshida, M., S. Ishii, D. Fujii, S. Otsuka, and K. Senoo. 2012. Identificationof active denitrifiers in rice paddy soil by DNA- and RNA-based
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nitrogen fertilization of paddy soil shifts iron-reducing microbialcommunity revealed by RNA-13C-acetate probing coupled withpyrosequencing. ISME J. 9:721–734.
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K. Senoo. 2013. Seasonal transition of active bacterial and archaeal
communities in relation to water management in paddy soils. Microbes
Environ. 28:370–380.
10. Jones, C.M., D.R. Graf, D. Bru, L. Philippot, and S. Hallin. 2013. The
unaccounted yet abundant nitrous oxide-reducing microbial community:
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12

Microbes Environ. Vol. 30, No. 1, 99-107, 2015

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME14123

MOST CITED ORIGINAL PAPER IN THIS
THREE YEARS [2015-2017] (16 citations)

Bacterial Community Analysis of Drinking Water Biofilms in Southern Sweden
KatHarina lüHrig1,2, BJörn canBäcK3, catHerine J. paul1,4, tomas JoHansson3, KennetH m. persson2,4,
and peter rådström1*
1Applied Microbiology, Department of Chemistry, Lund University, P.O. Box 124, SE-221 00 Lund, Sweden; 2Sydvatten AB, Hyllie

Stationstorg 21, SE-215 32 Malmö, Sweden; 3Microbial Ecology Group, Department of Biology, Lund University, Sölvegatan 37,
SE-223 62 Lund, Sweden; and 4Water Resources Engineering, Department of Building and Environmental Technology, Lund
University, P.O. Box 118, SE-221 00 Lund, Sweden(Received August 28, 2014—Accepted January 10, 2015—Published online February 21, 2015)

Next-generation sequencing of the V1-V2 and V3 variable regions of the 16S rRNA gene generated a total of 674,116 reads
that described six distinct bacterial biofilm communities from both water meters and pipes. A high degree of reproducibility
was demonstrated for the experimental and analytical work-flow by analyzing the communities present in parallel water
meters, the rare occurrence of biological replicates within a working drinking water distribution system. The communities
observed in water meters from households that did not complain about their drinking water were defined by sequences representing
Proteobacteria (82–87%), with 22–40% of all sequences being classified as Sphingomonadaceae. However, a water meterbiofilm community from a household with consumer reports of red water and flowing water containing elevated levels of ironand manganese had fewer sequences representing Proteobacteria (44%); only 0.6% of all sequences were classified as
Sphingomonadaceae; and, in contrast to the other water meter communities, markedly more sequences represented Nitrospiraand Pedomicrobium. The biofilm communities in pipes were distinct from those in water meters, and contained sequences thatwere identified as Mycobacterium, Nocardia, Desulfovibrio, and Sulfuricurvum. The approach employed in the present study
resolved the bacterial diversity present in these biofilm communities as well as the differences that occurred in biofilms within
a single distribution system, and suggests that next-generation sequencing of 16S rRNA amplicons can show changes in bacterial
biofilm communities associated with different water qualities.
Key words: drinking water, biofilm, next-generation sequencing, bacterial communities, 16S rRNA pyrosequencing

Biofilms are populations of microorganisms that are typicallyconcentrated at a solid-liquid interface and surrounded by an
extracellular polymeric substance matrix (13). The presenceof extracellular polymeric substances within the biofilm protects bacteria by making them more resistant to chemicals
such as disinfectants (10). The environment within a drinking
water distribution system (DWDS) is oligotrophic and cancontain disinfectants, with more than 95% of the bacterial
biomass occurring as biofilms on the inner surface of the
DWDS and less than 5% existing in the planktonic form (9).
Biofilms in the distribution system constitute an ecosystemthat can influence the esthetic quality of drinking water byaltering taste, color, and odor, and also microbial water quality through the detachment of biomass into the bulk water(22). Bacterial biofilms have also been associated with technical problems within the DWDS such as corrosion (41).
Although biofilms are known to have these impacts on drinking
water, little is known about the mechanisms involved; therefore, a deeper understanding of the mechanisms by which themicrobes in this human-built ecosystem participate in thedelivery of drinking water to consumers need to be elucidated
in more detail.
Less than 1% of bacteria in fresh and drinking water are
currently culturable and bacteria in drinking water biofilms
can also be present in a viable but non-culturable (VBNC)
state (1, 20, 37, 40). Therefore, culture-independent methods
are preferable for providing a more complete picture of the

microbial community; however, this type of analysis may not
distinguish between dead or living cells (30). While methods
using clone libraries, DGGE, and other DNA-based methods
have contributed descriptions of the microbes present in drinking
water biofilms (8, 33, 42), next-generation sequencing (NGS)
is considered to provide the most detailed, high throughput,
culture-independent method for the characterization of
microbial communities. Previous studies that have examinedbacterial communities present in water or biofilms of the
DWDS have used the NGS of amplicons from water meterbiofilms (16), clear well biofilms (44), faucet biofilms (27),and biofilms in a pilot-scale microfiltration plant that treats
drinking water (21). NGS has also been used to examine theimpact of changing hydraulic regimes on the bacterial biofilm
community structure in an experimental distribution system(5) as well as the influence of chloramination and chlorination on planktonic bacterial communities in water samples(19). However, the reproducibility of amplicon NGS for real
DWDS biofilms, the diversity present across biofilms from asingle distribution system, and the feasibility of using water
meters to investigate changes associated with the consumer
perception of water quality have not yet been investigated.
We herein examined bacterial communities in DWDS
biofilms using a deep 16S rRNA amplicon NGS analysis. To
obtain a representative drinking water biofilm, samples fromwater meters were analyzed from a single existing distribution network in southern Sweden. The reproducibility of thisapproach was demonstrated by comparing biofilms fromwater meters installed in parallel and, thus, experiencing
nearly identical hydrological environments. In addition, we* Corresponding author. E-mail: peter.radstrom@tmb.lth.se;
Tel: +46–46–222–34–12; Fax: +46−46−222−4203.

13

Lührig et al.

100
Table 1.

Samples analyzed in this study. Samples were taken in the city of Landskrona, Sweden, in which surface water is used to produce
drinking water. All water meters had a rated flow of Qn 2.5 m3 h−1. A photo showing the parallel water meters (WM1 and WM 2) is
included as Supplemental Fig. S3.

Sample Type
WM 1
WM 2

Diameter Age

Material DNA extraction

PCR reactions Sampling date Description

and Two cotton swabs
2007 brass
plastic
and Two cotton swabs
2001 brass
plastic

2

March 2011

Water meters installed in parallelin an apartment building

WM 3

water n/ameter
water n/ameter

3

March 2011

Water meter from a family house

WM 4

water n/ameter

and Two cotton swabs
2004 brass
plastic

2

March 2011

P1

pipe

50 cm

3

April 2011

P2

pipe

15 cm

1966 cast iron Two extractions from 200 µL of
resuspended biofilm material
1908 cast iron Two extractions from 200 µL of
resuspended biofilm material

3

June 2011

Table 2.

Water meter from a family house,
in which problems with red water
have been reported
Pipe situated in the same street as
WM 1 and WM 2
Pipe situated in the Landskrona
DWDS

Water Quality Parameters. Water was obtained from households in which different water
meter sampling was conducted and submitted for a routine analysis. Representative water
quality data for the city of Landskrona (Sweden) are included for comparisons. The water of
WM 4 had a brown color during sampling.

pH
Conductivity [mS m−1]
Hardness [°dH]
Calcium Ca [mg L−1]
Magnesium Mg [mg L−1]
Sulfate SO42− [mg L−1]
Turbidity [FNU]
Iron Fe [mg L−1]
Manganese Mn [mg L−1]
Total chlorine [mg L−1 Cl2]

Landskrona

WM 1 + 2

WM 3

WM 4

8.1
40.2
9.5
63
3.1
—
0.21
<0.05
<0.02
—

8.1
40.2
11
70
3.4
83
0.24
<0.05
<0.02
0.13

8
38.4
8.7
58
2.9
80
<0.1
<0.05
<0.02
0.14

8.1
39.7
8.9
59
2.9
85
12
1.5
0.04
0.05

showed that differences in the biofilm community composition in water meters and pipes as well as perceived water
qualities within a single DWDS were resolvable.

Sampling
Six biofilm samples were collected from the DWDS of the city ofLandskrona (Sweden) in March, April, and June, 2011 (Table 1).
Water meter biofilms were sampled using sterile cotton transportswabs. Biofilm samples from the walls of the pipes were taken witha sterile cell spatula (TPP, Trasadingen, Switzerland) and the collectedmaterial was resuspended in approximately 5 mL of water from thesampling site. All samples were transported to the laboratory in acooling box within 8 h after sampling and then stored at −20°C until
further analyses. Water samples for water quality testing were takenfrom households during the sampling of water meter biofilms andthe results obtained were reported together with general water quality data representative for drinking water in the city of Landskrona(Sweden) (Table 2). Water quality testing was performed by
ALcontrol AB, Malmö, Sweden using standard methods (pH:SS028122-2; conductivity: SS-EN 27888-1; hardness: calculated
from magnesium and calcium concentrations; calcium: SS-EN ISO
11885-1; magnesium: SS-EN ISO 11885-1; sulfate: SS-EN ISO
10304-1:2009; turbidity: SS-EN ISO 7027 utg 3, iron: SS-EN ISO
11885-1, manganese: SS-EN ISO 11885-1). Total chlorine wasmeasured with a portable colorimeter (Hach).

before PCR amplification. DNA was also extracted from empty
cotton swabs and MilliQ water as negative controls for PCR. PCR
amplification of a specific bacterial 16S rRNA region was performed
using the primers 27F (5' GS FLX Titanium adapter A - TCAG MID - AGAGTTTGATCCTGGCTCAG 3') and 534R (5' GS FLX
Titanium adapter B - TCAG - MID - ATTACCGCGGCTGCTGGC
3') (16) with adapter A representing the forward 454 sequencing
primer, adapter B representing the 454 reverse primer, and a 10-bp
long sample-specific barcode (MID). Barcodes recommended by
Roche were used with the following sequences: ACGAGTGCGT(MID1 for P1), ACGCTCGACA (MID2 for P2), AGACGCACTC(MID3 for WM 4), AGCACTGTAG (MID4 for WM 3),
ATCAGACACG (MID5 for WM 1), and ATATCGCGAG (MID6for WM 2). PCR reactions were carried out in a C1000 thermal
cycler (Bio-Rad) and contained: 1 × PicoMaxx Reaction buffer, 2 mM
MgCl2, 0.2 mM of each dNTP, 0.8 µM of each forward and reverse
primer, 1.5 U PicoMaxx polymerase, and 5 µL of template DNA(diluted 10-fold) in a total volume of 30 µL. The cycling parameters
were: 5 min at 95°C, followed by 30 cycles of 95°C for 1 min, 55°C
for 1 min, 72°C for 1 min, and a final 72°C held for 5 min. Two to
three PCR reactions were carried out for each biofilm sample, andpooled together for amplicon purification. The FAST DNA Spin Kit
for Soil has been proposed as the method of choice for DWDS DNA
extraction, generating representative community information andreproducibility, while PicoMaxx polymerase efficiently amplifies
low amounts of DNA in the presence of PCR inhibitors (15, 18). A
high concentration of primers was used to outcompete partiallyextended primers and reduce the formation of chimeras (36).

Generation of amplicons
DNA was extracted from cotton swabs or 200 µL resuspended
biofilm material using the Fast DNA Spin Kit for Soil (MPBiomedicals) and a bead beater. DNA from two cotton swabs was
extracted for each sample, pooled together, and diluted 10-fold

Amplicon library preparation
Pooled amplicons were purified using the E.Z.N.A® Cycle Pure
Kit (OMEGA, Bio-tek) and Cycle-Pure Spin Protocol according to
the manufacturer’s instructions. Sequencing was conducted at the
Lund University Sequencing Facility, Sweden. Pooled amplicons

Materials and Methods

14Communities in Drinking Water Biofilms
Table 3.

101

Overview of NGS Results. F represents the forward sequencing direction covering the V1-V2 region of thebacterial 16S rRNA gene and R represents the reverse sequencing direction covering the V3 region.
chimerascleanedsequencessubsampled

OTUs

singletons

doubletons

OTUsa

WM 1 - F
WM 2 - F
WM 3 - F
WM 4 - F
P1 - FP2 - F

218
212
160
247
189
495

35,66230,34645,433
26,46630,701
26,695

26,466
26,466
26,466
26,466
26,466
26,466

824
669
923
818
282
622

289
260
376
218
93
198

159
108
171
123
45
106

185
177
129
227
126
184

WM 1 - R
WM 2 - R
WM 3 - R
WM 4 - R
P1 - RP2 - R

638
510
271
590
205
1,611

51,55342,89366,70042,17453,02342,307

26,466
26,466
26,466
26,466
26,466
26,466

622
537
709
543
216
458

239
209
275
162
82
152

105
106
128
82
30
66

154
151
133
165
105
144

a OTUs in which at least one of the six samples contained 20 sequences.

construction of the phylogenetic tree (see Supplemental Fig. S2).
Venn diagrams were constructed using information from theOTU tables and plotted with the Venn Diagram Plotter (http://omics.
pnl.gov/software/VennDiagramPlotter.php). A heatmap of the 50 mostabundant OTUs was constructed using the pheatmap package in R
(http://cran.r-project.org/web/packages/pheatmap/pheatmap.pdf).

were reduced for short fragments by using Agencourt AMPure XP(Beckman Coulter) and inspected using a DNA 1000 kit on a 2100
Bioanalyzer (Agilent). Amplicons were quantified using the Quant-iT
dsDNA assay kit (Invitrogen) and Quantifluor fluorometer (Promega),
and pools were diluted to obtain a total of 1×107 copies µL−1.
Titration and library production (aiming at 10–15% enrichment)
were performed using emulsion PCR and the Lib-A kit (Roche).
DNA-positive beads were enriched, counted on an Innovatis CASY
particle counter (Roche), processed using the XLR70 sequencing kit(Roche), and loaded onto a picotiter plate for pyrosequencing on
a 454 Life Sciences Genome Sequencer FLX machine (Roche).
DNA sequences were archived at NCBI SRA under the accession
number SRP039011.

Results
16S rRNA gene amplicon NGS of DWDS biofilms
Six biofilm samples from a single DWDS were selected fora detailed community analysis using NGS of the 16S rRNA
gene. The aim was to permit comparisons of both dominant
and rare members of the communities to determine whether
the community changed with location as well as the number ofsequences required to resolve these differences between samples.
Sequences obtained from the forward reads encompassed
the V1-V2 region of the 16S rRNA gene while reverse reads
corresponded to the V3 region. A total of 674,116 reads
describing the six bacterial biofilm communities were initiallyobtained; 174,817 of these reads did not meet the quality
requirements and were removed, and random subsampling
selected 52,932 sequences (26,466 for each read direction) to
represent each biofilm community (Table 3). Sequences used
for analyses ranged in length from 200–332 bp, with anaverage length of 312 bp after trimming and cleaning.
Sequences describing either the V1-V2 region or V3 region
were classified using the RDP classifier at a confidence levelof 80%. Classification of the V1-V2 and V3 regions showed
highly similar trends with respect to the community composition for each biofilm sample at the phylum (Fig. 1) and class(Fig. 2) level.
Sequences were clustered into OTUs (phylotypes), applyinga threshold corresponding to 97% identity. OTUs relevant forcomparisons of the distinct biofilm bacterial communities
were restricted to those containing 20 or more sequencesfrom any one of the six biofilm samples in order to avoid
including sequences containing errors introduced during
sequencing or PCR amplification (17). The removal of rare
sequences reduced the number of OTUs from 2,383 to 308.
The number of OTUs representing each of the six biofilm
communities ranged from 126 to 227 (Table 3, V1-V2 region)
with 57 of these 308 OTUs being present in all the biofilm

Data analysis
Amplicons were sequenced from both directions, with reads fromforward (V1-V2 region) and reverse (V3 region) directions being
treated separately during data analysis following the cleaning step
(Supplemental Fig. S1). Reads were sorted by a barcode using sfffile(SFF Tools, Roche). The barcode and TCAG-tags were also
removed using sfffile. Reads were quality filtered using PrinSeq lite
(v 0.19.3) (34) and custom Perl scripts and discarded if they wereshorter than 220 bp, longer than 650 bp, contained ambiguous basepairs, or had a mean quality score below 25. Reads were trimmed
after 350 bp or if the mean quality score within a 50 bp sliding
window with a step size of 1 was less than 35. Reads with a perfectmatch to the primer in the 5' region (27F or 534R) were kept and thesequence information corresponding to the primer region wasremoved. Reads from the reverse direction were converted to theirreverse complement using custom Perl scripts. Chimera checking
was done using Uchime (7) in the de novo mode after de-replication
as implemented in Usearch (v 5.2.32) (6). Reads detected as chimeras were removed from the dataset. In order to avoid bias, sequenceswere randomly subsampled without replacement to the smallest
sample size using the Perl script daisychopper.pl (http://www.
genomics.ceh.ac.uk/GeneSwytch/Tools.html v0.6) (11). The subsampled sequences were classified using the command line version of
the RDP classifier (v. 2.5) (43) and clustered using CROP (v133)
with the option -s corresponding to a 97% sequence identity (14).
The parameters were 3176 for -b and 480 for -z for both forward andreverse reads. CROP was run on the Lunarc supercomputer at Lund
University. Only clusters with at least 20 sequences in one of the six
samples were kept to construct a phylogenetic tree. Metaxa (v 1.1)
was applied to detect sequences of chloroplasts, mitochondria,
archaea, and eukaryotes (2). Sequences were aligned using Greengenes(4) (greengenes.lbl.gov), and a phylogenetic tree was constructed using
RAxML (38) and displayed in iTOL (24). OTUs detected by Metaxa
as being chloroplasts or having an uncertain origin, or OTUs that did
not align to the Greengenes reference dataset were removed before
15

Lührig et al.

102

Fig. 1. Relative abundance of bacterial phyla from water meters andpipes. F represents the forward sequencing direction covering theV1-V2 region of the bacterial 16S rRNA gene and R represents thereverse sequencing direction covering the V3 region of the bacterial 16S
rRNA gene.

Fig. 3. Comparison of OTUs and sequences for selected sample
combinations. Venn diagrams are shown comparing the presence andabsence of OTUs and shared sequences for the V1-V2 region for
selected combinations of samples. The left circle represents the first of
the two samples listed in the first column. Only OTUs with at least 20
sequences in one of the six samples were considered in the presence/
absence comparison (left panel). The number of OTUs in each sample
can be found in Table 3. All OTUs and sequences were considered in thesequence-based comparison (right panel). Each sample contained
26,466 sequences. The number of shared sequences between samples
was determined for each OTU and then summed to give the total numberof all shared sequences for the samples being compared.

in parallel within the DWDS were physically present on
distinct surfaces of two water meters (WM 1 and WM 2), andhad developed for four years within an apartment buildingthat had experienced identical temperatures, seasons, water
flow, and source water (Supplemental Fig. S3). The analysisof these two communities was used to examine the reproducibility of the established high resolution sequencing work-flow
for determining community compositions, OTU frequencies,
and phylotypes.
WM 1 and WM 2 were dominated at the phylum level byProteobacteria (82% for WM 1; 87% for WM 2), and unclassified Bacteria (11% for WM 1; 8% for WM 2, Fig. 1). A totalof 185 OTUs were identified in WM 1 and 177 OTUs in WM
2, with the two communities sharing 163 OTUs and 75% of
the sequences (Fig. 3). A heatmap illustrating the 50 mostabundant OTUs showed highly similar profiles of OTU frequencies for both water meters (Fig. 4).
The phylotype-based analysis showed that the most abundant
OTU was classified to the family level as Sphingomonadaceae
in both WM 1 (22%) and WM 2 (36%). Other abundant OTUs
were Hyphomicrobium (WM 1: 5% and WM 2: 6%) andunclassified Proteobacteria (WM 1: 6% and WM 2: 5%).
To determine whether the bacterial biofilm communitychanged within a single DWDS or if the water meter biofilms
were similar throughout the same DWDS, biofilms were
sampled from a third water meter (WM 3) connected to thesame distribution system a few kilometers away from theWM 1 and 2 sampling site.

Fig. 2. Relative abundance of Proteobacteria from water meters andpipes. 100% corresponds to all sequences classified as Proteobacteria. F
represents the forward sequencing direction covering the V1-V2 regionof the bacterial 16S rRNA gene and R represents the reverse sequencing
direction covering the V3 region of the bacterial 16S rRNA gene.

communities examined. Since comparisons of information
obtained from the V1-V2 and V3 regions by both RDPclassification (Fig. 1 and Fig. 2) and OTU frequencies (Fig. 3,
4, Table 4 and 5) gave similar results, the V1-V2 region
was chosen to facilitate comparisons between the different
biofilm communities.
Assessment of reproducibility using biofilm communities
from parallel water meters
Bacterial biofilm communities in water meters (WM) installed
16

Communities in Drinking Water Biofilms
Table 4.

103

Classification of the 20 most abundant OTUs for the V1-V2 region. OTUs are from the bacterial 16S rRNA gene found in the six drinking
water biofilm samples from water meters and pipes. Sequences for the OTUs are found in Supplemental Table S1.

PhylumClass

Actinobacteria
Actinobacteria
Actinobacteria
Gemmatimonadetes
NitrospiraProteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria

Actinobacteria
Acidimicrobiales
Actinobacteria
Actinomycetales
Actinobacteria
Actinomycetales
Gemmatimonadetes
Gemmatimonadales
Nitrospira
Nitrospirales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Sphingomonadales
Alphaproteobacteria Sphingomonadales
Alphaproteobacteria
Betaproteobacteria
Betaproteobacteria
Burkholderiales
Deltaproteobacteria Desulfovibrionales
Epsilonproteobacteria Campylobacterales
Gammaproteobacteria

Order

FamilyGenus

Mycobacteriaceae
Nocardiaceae
Gemmatimonadaceae
Nitrospiraceae
Hyphomicrobiaceae
Hyphomicrobiaceae
Hyphomicrobiaceae

Mycobacterium
Nocardia
Gemmatimonas
Nitrospira
Hyphomicrobium
Pedomicrobium

Sphingomonadaceae
Sphingomonadaceae
Burkholderiales_incertae_sedis Methylibium
Desulfovibrionaceae
Desulfovibrio
Helicobacteraceae
Sulfuricurvum
Percentage of total
sequences

Table 5.

WM 1 - F WM 2 - F WM 3 - F WM 4 - F

P1 - FP2 - F

0
118
2
523
196
1,401
488
1,144
3,723
378
570
5,952
935
1,084
753
85
1
1
0
1,542

0
69
3
318
146
1,715
363
2,332
2,263
336
312
9,578
617
807
579
27
1
0
0
1,258

0
81
2
6
117
580
8
5,171
59
55
89
10,689
17
12
10
7
0
0
2
3,490

0
4
3
7
2,852
751
1,949
102
44
109
76
149
48
715
334
33
0
0
0
56

1,875
3,369
5,050
87
2
1,701
78
543
321
146
99
581
160
265
98
24
1
0
8,621
106

0
859
2
141
137
664
553
380
423
205
71
604
369
623
1,466
1,434
2,470
1,476
0
13

71%

78%

77%

27%

87%

45%

Classification of the 20 most abundant OTUs for the V3 region. OTUs are from the bacterial 16S rRNA gene found in the six drinking
water biofilm samples from water meters and pipes. Sequences for the OTUs are found in Supplemental Table S1.

PhylumClass

Actinobacteria
Actinobacteria
NitrospiraProteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria

Actinobacteria
Acidimicrobiales
Actinobacteria
Actinomycetales
Nitrospira
Nitrospirales
Alphaproteobacteria Caulobacterales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Rhizobiales
Alphaproteobacteria Sphingomonadales
Alphaproteobacteria
Alphaproteobacteria
Betaproteobacteria
Burkholderiales
Betaproteobacteria
Burkholderiales
Betaproteobacteria
Burkholderiales
Betaproteobacteria
Rhodocyclales
Betaproteobacteria
Deltaproteobacteria Desulfovibrionales
Epsilonproteobacteria Campylobacterales
Gammaproteobacteria

Order

FamilyGenus

Nitrospiraceae
Caulobacteraceae
Hyphomicrobiaceae

Nitrospira

Sphingomonadaceae
Comamonadaceae
Oxalobacteraceae

Herminiimonas

Rhodocyclaceae
Desulfovibrionaceae
Helicobacteraceae

Desulfovibrio
Sulfuricurvum

Percentage of total
sequences

WM 3 was also dominated by Proteobacteria and gave asimilar overall picture at the phylum and class levels as WM
1 and WM 2 (Fig. 1 and Fig. 2). Sequences from WM 3 wereclassified into the 20 most abundant OTUs in largely the same
proportions as those classified for WM 1 and WM 2 (Table4). These included OTUs of Sphingomonadaceae (40%),
Hyphomicrobiaceae (20%), and unclassified Proteobacteria(13%). The diversity of WM 3 was represented by slightly
fewer OTUs (a total of 129) than WM 1 and WM 2 (185 and177, respectively) (Table 3). WM 3 shared 114 OTUs and
42% of the sequences with WM 1, and 113 OTUs and 60% of
the sequences with WM 2 (Fig. 3).

WM 1 - R WM 2 - R WM 3 - R WM 4 - R

P1 - RP2 - R

0
146
168
998
7,398
365
6,913
257
253
619
562
131
259
840
2
4
0
1,588
439
0

3
106
157
667
6,937
251
10,667
217
206
331
420
30
170
639
0
2
2
1,225
298
0

0
103
119
6
5,832
10
10,808
75
53
53
21
16
52
10
0
0
12
3,596
21
0

2
101
2,800
677
4,007
145
254
1,175
1,204
46
38
62
245
369
0
0
0
38
905
1,820

1,630
8,445
5
193
2,645
247
614
55
104
53
375
49
102
92
0
0
9,805
65
87
0

1
919
94
523
2,530
432
1,166
400
235
1,015
409
1,800
629
1,599
2,779
1,854
0
2
141
0

79%

84%

79%

52%

93%

62%

A bacterial biofilm from an area with unacceptable water quality
A biofilm from a fourth water meter within the same
DWDS was sampled from a location in which problems withwater quality had been reported by the consumer in order todetermine whether changes within the bacterial biofilm community associated with changes in water quality could be
resolved.
Differences were observed at the phylum level between
WM 4 and WM 1-3. Proteobacteria were less abundant
than in the other water meters (44% in WM 4 and 82–87% in
WM 1-3). However, the composition of classes within theProteobacteria remained the same across all WMs with
17

Lührig et al.

104

Fig. 4. Heatmap of the 50 most abundant OTUs for the V1-V2 region. High similarity was observed in the number of sequences for the selected
OTUs for WM1 and WM2, while other samples were distinguished by the presence or absence of specific OTUs. The legend shows the number ofsequences corresponding to the different colors of the heatmap.

Alphaproteobacteria as the most abundant class (Fig. 2).
Planctomycetes (4%), Acidobacteria (7%), and Nitrospira(11%) were present in WM 4 and virtually absent in any of
the other samples. The amount of unclassified bacteria in
WM 4 was the highest at 30%, while these amounts were only
2–13% in the other five samples.
Within the 20 most abundant OTUs, only 1% of the WM
4 sequences belonged to the OTU classified as family
Sphingomonadaceae.
Certain OTUs contained a large number of sequences from
WM 4, but were not represented in other WMs, including
sequences classified as genus Nitrospira (11%) and genus
Pedomicrobium (7%) for WM 4.
WM 4 contained 227 OTUs, the highest number of OTUs
found in any of the six biofilm samples. WM 4 and WM 3
shared 102 OTUs, similar to the amount of shared OTUs
observed between other samples (Fig. 3); however, only 8%of the sequences were shared. Differences in the abundanceof the sequences with the OTUs obtained from WM 4 differentiated this bacterial biofilm community from those of WM
1-3: the heatmap profile of OTU frequency (Fig. 4) showedthat the distribution of sequences across OTUs was distinct
for WM 4.

An analysis at the phylum level (Fig. 1) showed that P1 wasdominated by Proteobacteria (58%) and Actinobacteria (39%),
with other phyla accounted for less than 3% of the sequences.
The classification identified specific OTUs containing
large numbers of sequences that were mainly found in P1.
These included class Gammaproteobacteria (33%); order
Acidomicrobiales (7%); and within order Actinomycetales,
Mycobacterium (13%) and Nocardia (19%). P1 contained
fewer sequences belonging to the family Sphingomonadaceae(2%) than those describing WM 1-3.
P1 contained 126 OTUs, the fewest OTUs found in any of
the samples examined, sharing 110 OTUs with WM 1 and
106 OTUs with WM 2 (Fig. 3). As observed with WM 4,
despite the number of shared OTUs between samples, P1
shared fewer sequences with WM 1 (21%) and WM 2 (23%).
At the phylum level, sequences obtained from P2 consistedof 86% Proteobacteria and 5% unclassified Bacteria withother phyla accounting for less than 3%, as observed for P1.
Within Proteobacteria, both pipes consisted of sequencesmore widely distributed across the different classes, and were
not predominated by Alphaproteobacteria as observed for
WM 1-3 and WM 4 (Fig. 2). A small overlap in the community
structure was observed between P1 and P2. OTU frequencies
gave a heatmap profile of P2 that was distinct from all othersamples, with the highest OTU frequencies appearing in OTUs
that were not predominant in any other sample examined; forexample Desulfovibrio (9%), and Sulfuricurvum (6%) (Fig. 4),
and, although a number of the OTUs themselves were shared,
only 21% of the sequences were shared between P1 and P2(Fig. 3).

Bacterial community composition in DWDS pipes
A biofilm was sampled from a pipe (P1) to compare thepipe bacterial biofilm community adjacent to the biofilm
communities established on water meters. A second pipe (P2)
was selected as a biofilm community from the same DWDS,
but with a number of distinct characteristics such as the age ofthe biofilm (Table 1).
18

Communities in Drinking Water Biofilms

105in the geographical location of WM 3 and/or water consumption associated with this biofilm community relative to WM 1
and WM 2. The biofilms in WM 1 and WM 2 were obtained
from a building with high water consumption (436 and 527 m3
over six months, respectively), whereas that in WM 3 was
obtained from a water meter within a family house that had alower water consumption of 49 m3 over six months. The
communities in WM 4, and P1 and P2 pipe biofilms, may
have diverged from those of WM 1–3 to the degree that thesurrounding environment of the biofilm differed. Since theenvironment of WM 4 was the most similar to that of WM 3
(Table 1), differences in this community may be explained byits unique location within the DWDS, and/or the distinct
water quality profile associated with this sample. The composition of biofilms was different in pipe biofilm communities
and those in water meters, while similar OTUs were present
in both types of samples, but only a low percentage of sequenceswere shared (Fig. 3). The hydrological characteristics (i.e. pipe
diameter), geographical location (including temperature),
sampling season, microbial corrosion, and age of the biofilm
differed between P1 and P2, which made it difficult to define
any relationship between community composition and any
DWDS or sampling parameters.
In addition, sampling of pipe biofilms within a working
DWDS is often determined by the water company’s activities, which further limits study design. The location of thewater meter biofilm at the boundary between the drinking
water provider and consumer often represents a change in
responsibility for water quality and, together with the resultspresented here, support and strengthen the application ofsampling water meters for biofilm communities in contact
with drinking water. In contrast, water meters contain structures and surfaces for the establishment of biofilms that are
the same at each sampling location; therefore, the possibility
exists for biological replicates within a DWDS if parallelwater meters have been installed in some buildings, andinstallation and removal is simple and monitored so thelength of time for the biofilm to have become established is
known. Hong et al. (16) also proposed that biofilms obtained
from water meters were suitable for studying the microbial
ecology of DWDS due to the ease of sampling. With uniform
physical structures and the possibility for more standardized
sampling, comparisons of WM communities can more
directly be related to variables such as water quality and/or
water usage.
Large numbers of sequences that clustered into OTUs
described as Sphingomonadaceae were found in the water
meter samples WM 1–3, with a reduced number of sequences
being detected for this group in WM 4. Sphingomonadaceae
have previously been detected in drinking water systems (16,44) and have been related to drinking water quality because
they may be responsible for initial biofilm formation (3) andare very resistant to chlorine (39). These phenotypes may
promote bacterial growth in the distribution system and, thus,
influence drinking water quality. The WM 4 community had
a reduced number of sequences that were classified as
Sphingomonadaceae, and a community composition distinct
from the other water meters in this study. This was also
observed at phylum level, with Proteobacteria, the mostabundant phylum in the drinking water biofilms analyzed in

Discussion
The bacterial communities present in six samples from asingle DWDS system in Sweden were analyzed using amplicon NGS of the V1-V2 and V3 regions of the 16S rRNA
gene. Sampling sites were chosen to test the resolution andlimits of the experimental and analytical protocols, and to
determine whether the described work-flow was capable ofresolving community changes associated with small variations in a DWDS ecosystem.
Although the most relevant analysis of drinking water
biofilms is an examination of those within established drinking
water delivery networks, one difficulty associated with working
in these systems is obtaining biological replicates to validate
the experimental approach. In this study, bacterial biofilm
communities of parallel installed water meters (WM 1, WM 2)
allowed an approach to be developed and tested for a highresolution community analysis through NGS that included
controls for both the experimental approach, by comparing
results between WM 1 and WM 2, as well as the influence ofchanges in the DWDS on the community, by comparing
additional drinking water biofilms.
Biofilms from virtually identical locations and sampling
regimes associated with WM 1 and WM 2 showed highly
similar communities when described by any of the NGS
analyses in this study. This degree of similarity between two
descriptions of communities has not been reported in previous studies that used NGS to examine the bacterial communities of drinking water biofilms, and may reflect the difficultyin obtaining true biological replicates in working DWDSs.
Even small variations in the ecology of the drinking water
biofilm can affect the community composition. Hong et al.
(16) observed numerous differences in communities associated with two water meters that had experienced stable turbidity, pH, and chlorine levels, but differed in the origin of
the water meter (two separate households) and the time ofyear they were sampled (October and December). Douterelo
et al. (5) examined biofilm communities within a model
DWDS, including NGS of material assumed to be biologicalreplicates; however, even samples retrieved from this highly
homogenous model system produced biofilm communities
that showed a high variability in biological diversities acrossthree biological replicates. The diversity was suggested to havebeen linked to the short time (28 d) over which the biofilms
were grown, and Martiny et al. (29) showed that biofilms in amodel drinking water system followed a successional formation that only culminated in a stable population after three
years. Thus, the high similarity between WM 1 and WM 2 isa reflection of the nearly identical physical and temporalparameters that nurtured the ecology of these two biofilms.
This result strongly suggests that the differences observed in
the other WM communities arose from ecological changes
and not from experimental or analytical artefacts and, in
addition to physical parameters defining the ecosystem, thetime over which this biofilm developed also contributed tothe consistency of the observed community composition.
The results obtained for WM 1 and WM 2 suggest thatdifferences in the WM 3 composition were related to changes
in the environment of WM3; small differences in the community, OTU, and phylotype comparisons may be due to changes
19Lührig et al.

106

this study and others (16, 25, 33, 44), being markedly reduced
in WM 4. A decrease in bacterial biofilm diversity has been
associated with a loss of multifunctionality (31) and thelarger number of OTUs observed at WM 4 may reflect a morediverse substrate or more active biofilm using the wider
spectrum of nutrients present in less-than-ideal drinking water.
Since water consumption was similar between WM 3 and
4 (49 m3 in six months for WM 3 and 53 m3 in 6 months for
WM 4), other factors may account for the differences
observed between these biofilm communities.
Sequences related to Nitrospira were more abundant in
WM 4 than in WM 1–3. Ling and Liu (26) observed a community shift to Nitrospirae in unchloraminated biofilms,
suggesting the sensitivity of Nitrospirae to the disinfection
treatment, and Nitrospira was previously detected in a model
DWDS using unchlorinated groundwater (29). Even thoughchlorination has been used for disinfection in the DWDS
examined in this study, water samples characterizing flowing
water moving past the WM 4 biofilm had a lower total chlorine concentration (0.05 mg L−1 Cl2) than those for the other
WM communities (WM 1, WM 2: 0.13 mg L−1 Cl2; WM 3:
0.14 mg L−1 Cl2). Lower chlorine levels may be related to thereport of red water for WM 4, as an increase in biofilm activity(due to reduced exposure to a disinfectant) has been associated with an increase in the deposition of iron and manganese
into biofilms (12). Cell death within the biofilms or disruption
due to hydraulic changes may release deposited iron andmanganese, resulting in red water and the elevated levels ofiron and manganese previously observed during discoloredwater events (35). Li et al. (25) reported changes in the bacterial community associated with the occurrence of red waterand observed a higher percentage of the iron-oxidizing bacteria Gallionella together with the extensive precipitation ofiron oxides in water samples. Although Gallionella was notdetected in the present study, Pedomicrobium was identified
in WM 4, the only community that was exposed to flowing
water containing detectable iron and manganese concentrations (1.5 mg L−1 Fe and 0.04 mg L−1 Mn). The presence of
these metals within the water may support the growth ofPedomicrobium, which deposits oxidized metals on its cellsurface, resulting in the accumulation of metal oxides in biofilms (23, 32).

information regarding bacterial community compositions forhigh throughput analyses and comparisons. Lundin et al. (28)suggested that 5,000 sequences allowed trends in alpha diversity to be estimated; hence, using fewer sequences from asingle 16S region and biofilm from easily accessible water
meters will facilitate the analysis of many bacterial biofilm
communities associated with differing water qualities. The
results of the present study support this experimental andanalytical approach as a strategy for compiling an accurate
and complete knowledge of the ecology of DWDS biofilms
and their role in drinking water delivery.
Acknowledgements
This study was financially supported by the Swedish Water andWastewater Association Development Fund (SVU), Nordvästra
Skånes Vatten och Avlopp AB (NSVA), Sydvatten AB and VA
SYD. The funding providers did not participate in the study design.
The authors wish to thank the employees of NSVA for their extensive assistance with the sampling of biofilms, especially S. Vegehalland L. Ödemark; and the selected homeowners for allowing accessto samples. Computational resources were provided by the Swedish
National Infrastructure for Computing (SNIC) through Lunarc, theCenter for Scientific and Technical Computing at Lund University.
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Microbes Environ. Vol. 30, No. 2, 126-132, 2015

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME14176

MOST CITED REVIEW PAPERS IN THIS
THREE YEARS [2015-2017] (28 citations)

Minireview
Effect of Probiotics/Prebiotics on Cattle Health and Productivity
Yutaka uYeno1*, Suguru Shigemori2,3, and takeShi ShimoSato1,2
1Faculty of Agriculture, Shinshu University, Minamiminowa, Nagano 399–4598, Japan; 2Interdisciplinary Graduate School of

Science and Technology, Shinshu University, 8304 Minamiminowa, Kamiina, Nagano 399–4598, Japan; and 3Research Fellow of
the Japan Society for the Promotion of Science (JSPS)(Received December 26, 2014—Accepted April 5, 2015—Published online May 23, 2015)

Probiotics/prebiotics have the ability to modulate the balance and activities of the gastrointestinal (GI) microbiota, and are,thus, considered beneficial to the host animal and have been used as functional foods. Numerous factors, such as dietary andmanagement constraints, have been shown to markedly affect the structure and activities of gut microbial communities inlivestock animals. Previous studies reported the potential of probiotics and prebiotics in animal nutrition; however, their efficacies
often vary and are inconsistent, possibly, in part, because the dynamics of the GI community have not been taken into consideration. Under stressed conditions, direct-fed microbials may be used to reduce the risk or severity of scours caused by disruption of the normal intestinal environment. The observable benefits of prebiotics may also be minimal in generally healthy
calves, in which the microbial community is relatively stable. However, probiotic yeast strains have been administered withthe aim of improving rumen fermentation efficiency by modulating microbial fermentation pathways. This review mainly
focused on the benefits of probiotics/prebiotics on the GI microbial ecosystem in ruminants, which is deeply involved innutrition and health for the animal.
Key words: rumen, gastrointestinal tract, yeast, oligosaccharide

teria has been cultivated (18), further research is required touncover a larger proportion of the unknown microorganisms
abundantly present in the GI microbiota.
The term “probiotics” has been amended by the FAO/
WHO to “Live microorganisms, which, when administered inadequate amounts, confer a health benefit on the host” (24).
Several lactic acid bacteria (LAB) strains, species belonging
to the genera Lactobacillus, Bifidobacterium, and Enterococcus,
are considered beneficial to the host and have, thus, been usedas probiotics and included in several functional foods.
Probiotics have the ability to enhance intestinal health bystimulating the development of a healthy microbiota (predominated by beneficial bacteria), preventing enteric pathogens from colonizing the intestine, increasing digestive
capacity, lowering the pH, and improving mucosal immunity.
It is important for the introduced microbes not to disturb theindigenous population, which has already been adapted to theenvironment of the GI tract to work both for and with thehost. Additionally, there are a number of requirements forallochthonous probiotic strains to adapt to the intestinal
environment of an animal species, e.g., bile acid tolerance
and affinity to the intestinal mucosa and glycoproteins. The
situation in the rumen is similar; ingested microbes have tofind out a suitable niche to inhabit, such as the rumen epithelium, rumen fluid, or fibrous feed, and exert effects on thehealth of the host, such as the removal of toxic molecules anddigestion of polymeric carbohydrates.
Prebiotics are non-digestible food ingredients that, when
consumed in sufficient amounts, selectively stimulate thegrowth and/or activity of one or a limited number of microbes
in the gut. Impacts of orally administered probiotics (in thiscase, referred to as symbiotics) and intrinsic beneficial bacteria of the GI tract can be enhanced by the use of prebiotics(28). The most commonly used prebiotics to yield health

Overview
The gastrointestinal (GI) microbial community, which
consists of at least one thousand different microbial species
in human gut (14, 84), has an impact on energy efficiency inthe host, including energy intake, transport, conversion, andstorage. In ruminants, a large amount of energy recovery
from dietary polysaccharides that cannot be digested by thehost has been attributed to the function of the microbialcommunity in the rumen; however, this process also depends
on the structure of the microbiota inhabiting this organ.
Environmental and stochastic factors, such as diet composition, feeding practices, and farm management, have beenshown to strongly affect the composition and functions of the
microbiota in livestock animals (83).
Most of the GI bacterial community of mammals is affiliated with two phyla, Bacteroidetes and Firmicutes (1, 39,
77). On the other hand, other phyla have niches in each
community, depending on the animal species. Therefore, theGI tract community is unique among species, which require
owning different systems to efficiently convert their diet into
their energy. The main GI bacterial groups in cattle have been
identified as defined groups (mainly genera) for up to 90% of
the total community (78, 79). However, a certain proportionof the gut bacterial community has yet to be identified due toan incomplete understanding of the bacterial community
structure in GI ecosystems because many of the 16S rRNA
gene sequences recovered from fecal samples are derived
from unknown (i.e., not previously identified in the intestinal
microbiota) species (21). While GI tract ecosystems (especially in humans) are known that a higher proportion of bac* Corresponding author. E-mail: ytkuyeno@shinshu-u.ac.jp;
Tel: +81–265–77–1650; Fax: +81–265–77–1650.

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127

which leads to an increase in the susceptibility of young
animals to pathogen colonization and subsequent diarrhea
and respiratory disease.
GI microbial communities are involved in the digestion
and fermentation of plant polymers, which is of particularimportance in mature herbivorous animals. Ruminant animals harbor a complex microbial community consisting of adiverse array of anaerobic microbes in the rumen, whichforms a different community structure from aerobic consortia
for fiber digestion (20). These microorganisms interact with
one another and take part in the systematic digestion offibrous plant material, which they anaerobically ferment intoend products that are, in turn, used as energy sources by thehost (66). Microbial characteristics, functions, and current
concerns regarding dysfunctions in the two respective sites(i.e., the rumen and lower intestine) in cattle are summarizedin Table 1. Even though the major functionalities differ fromeach other, ruminal community may affect that of large
intestine.
Numerous factors, such as dietary and management constraints, can strongly affect the structure and activities ofthese microbial communities, sometimes leading to impaired
health and performance in livestock animals (16). For example, sub-acute ruminal acidosis (SARA) is a well-recognizeddigestive dysfunction that is increasingly becoming a healthproblem. Microbial community changes associated with
SARA of lactating dairy cattle have been monitored using
terminal-restriction fragment length polymorphisms (T-RFLP)
of 16S rRNA genes and real-time PCR (40). Different rumen
microbial population structures between grain- and forageinduced SARA were observed even though rumen fermentation conditions were similar. The findings of a T-RFLP analysis indicated that the most predominant shift during SARA
was a decline in Gram-negative Bacteroidetes. Since inflammatory responses may be attributed, in part, to lipopolysaccharides released by the dead cells of Gram-negative bacteria(44, 58), the change observed in the number of Bacteroidetes
in response to SARA appears to be reasonable. The potential
microbial and physiological factors that increase the incidence of SARA by enhancing the epithelial permeability oflipopolysaccharides have not yet been identified. Furthermore,
the overconditioning (excess body fat deposition) of dairy
cows is a major risk factor for metabolic, infectious, diges-

benefits are carbohydrate substrates, such as oligosaccharides
or dietary fiber with low digestibility.
Research on probiotics and prebiotics has developed as acollaborative study domain between the fields of food andfeed with medicine and pharmaceutics. There are also a
number of application studies for cattle; however, few havebeen discussed in association with the dynamics of the inherent microorganisms. This review explored the better usage ofprobiotics and prebiotics to improve ruminant performanceby discussing the possible impacts of the applications ofprobiotics and prebiotics on the ruminant-specific GI microbial community.
Gastrointestinal microbial structure of cattle
Neonatal ruminants are unique in that, at birth, they arephysically and functionally two different types of animal withrespect to their GI system (34). The intestine of a newly born
calf is sterile, and colonization of the GI tract begins immediately after birth. Thereafter, a complex and dynamic microbial ecosystem with high densities of living bacteria is established in the large intestine as animals grow to maturity (72).
Molecular-based monitoring of the intestinal bacterial communities of calves revealed that the community undergoes
dynamic changes during the first 12 weeks of life (78). For
example, the main groups detected at a very young age(less than 3 weeks old) were found as major populations in
the human fecal bacterial community (i.e., BacteroidesPrevotella, the Clostridium coccoides-Eubacterium rectale
group, Faecalibacterium, and Atopobium) (30, 70, 77).
Bacteroides-Prevotella and the C. coccoides-E. rectale group
comprised a major fraction of the microbiota (ca. 50%–70%of the total) throughout the first 12-week period after birth,whereas the numbers of Atopobium, Faecalibacterium, andsome probiotic bacteria (such as those of the genera
Lactobacillus and Bifidobacterium) decreased as the animal
aged. Instead, an uncultivated rumen bacterial group as wellas Ruminococcus flavefaciens and Fibrobacter emerged at
detectable levels (1%–2%) in feces sampled after weaning.
Changes in the GI microbiota of young calves are in accordance with the metabolic and physiological development of
the GI tract (15). As discussed later, this immature and fluctuating gut microbiota has to face an abrupt change in diet,
Table 1.

Cattle GI microbial characteristics and relationships with host health and performance

Rumen

Large intestine

Major groups in microflora

Bacteroidetes
Firmicutes
Fibrobacter
Archaea
Protozoan species

Major microbial functions

Involved in host nutrition (digestion of fibrous plant material andanaerobic fermentation to short chain fatty acids, which can be used
as an energy source by the host; microbial protein synthesis)
Overgrowth of lactate-producing bacteria, leading to a decrease inrumen pH and subsequent rumen acidosis
Decrease in microbial activity by unbalanced nutrition, leading adecrease in feed protein efficacy

in preweaned calves:
Bacteroidetes
Firmicutes
Atopobium
Bifidobacteria
in weaned calves or older cattle:
Bacteroidetes
Firmicutes (including uncultured groups)
Fibrobacter
Immunological responses
Digestion of polymers

Microbial dysfunctions

23

Pathogenesis by harmful bacteria, such as
E. coli and Salmonella.

Uyeno et al.

128

numbers have been shown to decrease in the community inthe early stages of life in cattle (78). Optimizing the entericflora is considered effective for healthy calf rearing because it
increases the numbers of such beneficial microorganisms.
The supply of microorganisms together with feed from birth
in a preventive manner allows the incorporation and establishment of these probiotic strains together with the microbiota of calves. In addition, early colonization by LAB in theintestinal ecosystem may decrease the adherence of pathogens to the intestinal mucosa (37). A stable microbial load of
Lactobacillus species has been shown to improve weight gain
and immunocompetence in young calves (3); however, previous findings regarding the use of probiotics in calf feeding
have generally been equivocal, as shown in Table 2. The
efficacy of probiotic strains may vary depending on whether
calves are raised under healthy conditions because, in previous studies, the effects of probiotics were often significant
when control (untreated) calves were less healthy, as determined from fecal scores or rectal temperatures (5, 76). Understressed conditions, direct-fed microbials may be used toreduce the risk or severity of scours caused by disruption of
the normal intestinal environment. A better understanding of
how the selected lactobacilli and bifidobacteria strains overcome the effects of pathogens, by antagonizing the pathogenicity, and/or modulating the immune responses to infections
is needed (3, 69).

tive, and reproductive disorders (68). However, the efficient
fermentation system in the rumen of dairy cows is primarily
responsible for the conversion and accumulation of energy,
while the colonial microbiota is majorly contributed toenergy harvesting and metabolism in human (14, 38, 45).
This implies the importance of controlling rumen microbial
fermentation, although rumen function is not directly related
to body fat deposition.
Current applications of probiotics in calves
In young pre-ruminants, probiotics such as LAB or
Bacillus species generally target the lower intestine and represent an interesting means to stabilize the gut microbiota anddecrease the risk of pathogen colonization. LAB are wellknown probiotic supplement for young calves, and are
regarded as applicable to regular feeding practices. Previous
findings support the beneficial effects of these products inbalancing the GI tract microbiota as well as in animal nutrition and health (Table 2). Diarrhea is the main cause of morbidity and mortality in calves during their early life (13, 36);
therefore, its prevention is important to promote the growthof calves (69, 76). Antibiotic therapy has been applied tomaintain the performance of calves and reduce scours.
However, due to increasing safety concerns regarding therisks of antibiotic resistance due to the release of antibiotics
into the environment and persistence of chemical residues inanimal products (49, 82), probiotic additives have beendeveloped as alternatives to improve animal health and productivity (4, 8). Although the administration of probiotics toanimals has been linked with efficacy on specific groups(pathogens) in the gut microbiota (25, 69, 76), how theyinteract with the whole gut community currently remains
unclear. As discussed above, lactobacilli and bifidobacteria
Table 2.
Targets and materials applieda

Current applications of prebiotics in calves
Several types of oligosaccharides have been suggested tohave specific functionalities in calves. Mannan oligosaccharides (MOS) are complex mannose sugars that are believed toblock colonization of pathogens in the digestive tract. A previous study demonstrated that deeding fructooligosaccharides

Recent probiotic/prebiotic trials applied for young cattle

Positive effects in respect toRemarks

Reference

Weight gain Feed efficiency

HealthNot assessed
No

Yes
No

No
Yes

(42)
(53)

Yes
Yes

No
Yes

No
Yes

(43)
(76)

MSPB

Yes

No

Lactobacillus casei ssp. casei
MSPBb
MSPBb
Prebiotics (for calves):
FOS
FOS (short chain)
MOS
MOS
MOS
Cellooligosaccharide
A commercial productc
A commercial productc

Yes
Yes
No

No
No
No

No
No
No
No
Yes
Yes
No
No

No
Yes
No
No
Yes
No
No
No

Probiotics (for heifers):
Yeast culture
Yeast culture
Probiotics (for calves):
Yeast culture
MSPB or CSPB

Effects were determined when the results of four
experiments were pooled.
Not assessed Two mixtures were tested, a commercial probiotic andlaboratory-produced probiotic that was made underlaboratory conditions.
Yes
Synbiotic trial
Yes
No
Yes
Not assessed
Yes
No
Yes
Used crossbred calves
Yes
Synbiotic trial
No
No
The lactobacilli count in feces was higher and that ofbifidobacteria was slightly higher in the prebiotic group.

a MSPB, multi-species probiotic; CSPB, calve-specific probiotic; MOS, mannan-oligosaccharides.

b A mixture of Lactobacillus casei subsp. casei, Lactobacillus salivarius, and Pediococcus acidilactici.
c Derived from a cell-free culture of a Propionibacterium freudenreichii strain.

24

(5)
(32)
(22)
(23)
(62)
(29)
(33)
(74)
(27)
(32)
(35)
(60)

Probiotics and Prebiotics for Cattle

129

administered to ruminants are consumed by ruminal microbes
and fail to reach the lower intestine unless protected fromruminal digestion. The administration of oligosaccharides toweaned calves still appears to be advantageous because theformation of a desirable intestinal (rumen and/or lower intestine) community in calves through prebiotic supplementation
may contribute to further improvements in growth performance at an older age.

(FOS) in combination with spray-dried bovine serum tocalves reduced the incidence and severity of enteric disease(62). It has been suggested that this sugar prevents theadhesion of Enterobacteriaceae, most notably Escherichia
coli and Salmonella, to the intestinal epithelium (7, 31).
Galactosyl-lactose (GL) is a trisaccharide (galactose plus
lactose) that is produced by the enzymatic treatment of wheywith beta-galactosidase. The addition of GL to milk replacer(MR) was previously found to have beneficial effects on thegrowth and health of dairy calves (61). Supplementation with
MOS, FOS, and GL may improve the growth performance of
calves in either the pre- or postweaning stage; however,modifications to the activities of microbial fermentation by
these sugars have not yet been examined in detail. In addition,
similar to the case of probiotics, the observable benefits ofprebiotics are likely to be minimal when calves are generally
healthy (35). As shown in Table 2, most prebiotics may nothave any apparent beneficial effects (body weight gain, feed
efficiency, or health measures) over probiotics.
We previously evaluated the effects of feeding cellooligosaccharide (CE), which is a commercially available oligosaccharide that consists of glucose with beta-1-4 linkages, on
performance and intestinal ecology in Holstein calves fed
MR or whole milk (80). No significant differences wereobserved in fecal bacterial community compositions ororganic acid profiles in the MR group. However, this supplementation appeared to effectively modulate the intestinalbacterial community of calves when administered with whole
milk because the proportion of the C. coccoides–E. rectale
group was higher in the prebiotic group in the wholemilk-feeding trial. From these results, type of liquid feed
(MR or whole milk) to preweaned calves may be responsible
for the different responces to feeding CE. Overall, CE supplementation had no effect on the maintenance of Lactobacillus
and Bifidobacterium species levels in the large intestine ofpreweaning calves. CE is considered to be utilized by specificmicrobes inhabiting the calf intestine, resulting in increases in
the number of butyric acid-producing bacteria belonging to
C. coccoides–E. rectale (19, 47). Fecal butyrate concentrations were also higher at that time. Along with its value as anenergy source, butyrate is also involved in the growth anddifferentiation of intestinal cells in the large intestine, thereby
improving its epithelial structure (59) and enhancing digestion and absorption efficiencies, which may also contribute toa superior ability for nutrition capture (54). CE fed withliquid feed (milk or reconstituted MR) may reach the lower
digestive tract vis the esophageal groove reflex (34), andexert prebiotic effects using a similar mechanism to that ofmonogastric animals.
An in vivo study indicated that CE feeding improved daily
gain and feed efficiency in calves during the postweaning
period, but not the pre-weaning period (32). This may havebeen mainly due to the enhancement in ruminal fermentation
as propionate and total short chain fatty acid (SCFA) levels
were increased, which suggests that CE affected the fermentation pattern by providing carbon and energy sources (46).
After weaning, solid feeds directly reach the rumen and arethen microbially processed. Ruminal CE may eventually be asource of nutrition for various types of indigenous microbes.
With the exception of very young ruminants, prebiotics orally

Effects of supplementation with probiotics/prebiotics on theperformance of heifers, lactating cows, and beef cattle
Probiotics for adult ruminants have mainly been selected to
improve fiber digestion by rumen microorganisms. Suchprobiotics have positive effects on various digestive processes,
especially cellulolysis and the synthesis of microbial proteins.
The main form of probiotic commonly used in dairy cows isvarious strains of yeast (mostly Saccharomyces cerevisiae).
Regarding bacterial probiotics for adult ruminants, lactateproducing bacteria (Enterococcus, Lactobacillus), which sustain
lactic acids are a more constant level than Streptococcus
bovis, may represent a possible means of limiting acidosis in
high-concentrate-fed animals (55, 56), especially feedlot
cattle. Megasphaella elsdenii or Propionibacterium species,
which utilize lactate, have also been administered as directfed microbials to avoid the accumulation of ruminal lactate(26, 41, 71).
The most consistent effects following the addition of yeast
cultures to the diet include improved productivity in bothlactating and growing animals. The mode of action of yeast
products has not yet been elucidated in detail, but is generally
considered to involve changes in rumen fermentation rates
and patterns. Certain strains of active dry yeast are particularly effective at raising and stabilizing ruminal pH by stimulating certain populations of ciliate protozoa, which rapidly
engulf starch and, thus, effectively compete with amylolytic
lactate-producing bacteria (2, 9, 41, 56, 73, 75). A less acidic
ruminal environment has been shown to benefit the growthand fiber-degrading activities of cellulolytic microorganisms(6, 10, 12, 52). Yeast also has the potential to alter the fermentation process in the rumen in a manner that reduces theformation of methane (CH4) gas (12). In a previous study,commercial yeast product slightly decreased CH4 in growing
beef cattle, while neither the SCFA amount nor the profiles
changed (51). The cells of S. cerevisiae provide growth factors for rumen microbes, including organic acids and oligosaccharides, B vitamins, and amino acids, which stimulate
microbial growth in the rumen, thereby indirectly stabilizing
ruminal pH (50). Another function of yeast in the rumen is the
scavenging of oxygen, which creates the more anaerobic
environment required by ruminal microorganisms (16). In
this context, yeast itself functions not only as a probiotic, butalso helps other rumen community members grow, and, thus,
acts as a type of prebiotic. The effects of active dry yeast on
the rumen microbial community structure was recently determined by 16S rRNA gene-based clustering using a pyrosequencing technique (57). An evaluation of the effects of yeast
on the microbiota revealed that some bacterial groups weremore affected than others. The relative abundance of lactateutilizing bacteria such as Megasphaera and Selenomonas as25

Uyeno et al.

130

well as fibrolytic groups (Fibrobacter and Ruminococcus)
increased with yeast supplementation, confirming improvements
in cellulolytic activity as a supposed mode of action of yeast.
Intervention studies on the application of commercial yeast
cultures to young cattle (heifers and calves) are summarizedin Table 2. A large number of studies that evaluated theeffects of yeast on dairy production (milking and body mass
deposition) were summarized in two studies published concurrently several years ago, one of which was a meta-analysis
and the other was a review (17, 63). Desnoyers et al. evaluated the effects of yeast supplementation on intake, milk
production, and rumen fermentation characteristics using aquantitative meta-analysis. The positive effects of yeast supplementation were an increase in rumen pH and a decrease inlactic acid with the increases in concentrate in the diet andwith the intake level. Controversially, the positive effects ofyeast supplementation on organic matter digestibility increased
with the percentage of fiber in the diet, suggesting an improvement in rumen fermentation by yeast supplementation.
In beef cattle, the stabilization of ruminal pH may also be
effective when they are fed a high readily fermentable dietthat increases the risk of acidosis. Growth parameters (average daily gain, final weight, intake, and feed to gain ratio)
were previously reported to be improved by continuous live
yeast supplementation (11), whereas no or little effect on
performance was observed in other studies (6, 81). This difference in result may be attributed to a primal difference inthe rumen microbial composition, in which respective members have different pH tolerances. For example, fibrolytic
bacteria are generally less pH tolerant than saccharolytic
bacteria (65).
Although previous findings have supported the efficacy ofyeast supplementation, conclusive evidence has not yet beenobtained to show that supplementation is beneficial at all
times (11). It should be noted that this potential varies markedly with products (51). Increases in profitability are generally variable, especially when taking the rise in feeding costs
for these products into account. Some of these differences
may be attributed to the type and strain of yeast used as wellas whether the cells are alive or dead (48). Furthermore, insome commercial products, the data available have been
generated under in vitro conditions and in monogastric animals or small ruminants, which do not necessarily correspondto actual dairy and beef production.

that work either or both on the rumen and on the lower intestine.
Although controlled studies demonstrated that probiotics
and prebiotics achieved a positive balance in the GI microbiota of cattle, the dynamics and functions of the rumen community need to be examined in more detail. Further studies on
the structure and activities of the gut microbiota, functional
interactions between gut microbes, and relationships between
microbes and host cells are warranted to determine thefundamental aspects of future probiotic/prebiotic research.
“Meta-omic” approaches (metagenomic, metatranscriptomic,
metaproteomic, and meta-metabolomic analyses) are powerful tools for analyzing the relationships between the GI
microbial community and host metabolism (64, 67, 84).
Future meta-omic-based studies together with the knowledge
obtained to date will provide deeper insights into the effects of“health-improving” diet for animals by better characterizing
and understanding the functionalities of probiotics on thebalance of the GI microbiota.
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Concluding remarks
The cattle GI microbial composition was shown to bealtered by various factors, including diet, age, and stress, as
an adaptive response of the community to the environment(66). Therefore, GI health may be defined as the ability tomaintain a balance of GI ecosystem. Desirable community
shift may be attributed to the effect of probiotics and prebiotics, rather than autonomic change. Probiotics and prebiotics
both have great potential in livestock productivity as well as
human health. Cellooligosaccharide is one example because
many rumen bacteria may be able to use it, but, when administered to preweaned calves, the proportion of the C. coccoides–
E. rectale group specifically increases in the lower intestine.
Like CE, it may become possible to use powerful materials
26

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36. Hill, T.M., J.M. Aldrich, and R.L. Schlotterbeck. 2005. Nutrient
sources for solid feed and factors affecting thier intake by calves, p.
113–134. In P.C. Garnsworthy (ed.), Calf and Heifer Rearing.
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Microbes Environ. Vol. 30, No. 1, 1-11, 2015

https://www.jstage.jst.go.jp/browse/jsme2 doi:10.1264/jsme2.ME14144

MOST CITED REVIEW PAPERS IN THIS
THREE YEARS [2015-2017] (28 citations)

Minireview
Recent Trends in Control Methods for Bacterial Wilt Diseases Caused by
Ralstonia solanacearum
Yuliar1,2, Yanetri asi nion2,3, and KoKi toYota2*
1Research Center for Biology, Indonesian Institute of Sciences (LIPI), Jl. Raya Jakarta-Bogor, Km 46, Cibinong Science Center

16911, Indonesia; 2Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Technology,
2–24–16 Nakacho, Koganei, Tokyo, 184–8588, Japan; and 3Palangka Raya University Jl. Yos Sudarso, Center of Kalimantan,
Palangka Raya, Indonesia(Received October 9, 2014—Accepted December 23, 2014—Published online February 26, 2015)

Previous studies have described the development of control methods against bacterial wilt diseases caused by Ralstonia
solanacearum. This review focused on recent advances in control measures, such as biological, physical, chemical, cultural,and integral measures, as well as biocontrol efficacy and suppression mechanisms. Biological control agents (BCAs) have been
dominated by bacteria (90%) and fungi (10%). Avirulent strains of R. solanacearum, Pseudomonas spp., Bacillus spp., andStreptomyces spp. are well-known BCAs. New or uncommon BCAs have also been identified such as Acinetobacter sp.,
Burkholderia sp., and Paenibacillus sp. Inoculation methods for BCAs affect biocontrol efficacy, such as pouring or drenchingsoil, dipping of roots, and seed coatings. The amendment of different organic matter, such as plant residue, animal waste, andsimple organic compounds, have frequently been reported to suppress bacterial wilt diseases. The combined application of
BCAs and their substrates was shown to more effectively suppress bacterial wilt in the tomato. Suppression mechanisms are
typically attributed to the antibacterial metabolites produced by BCAs or those present in natural products; however, thenumber of studies related to host resistance to the pathogen is increasing. Enhanced/modified soil microbial communities arealso indirectly involved in disease suppression. New promising types of control measures include biological soil disinfection
using substrates that release volatile compounds. This review described recent advances in different control measures. We
focused on the importance of integrated pest management (IPM) for bacterial wilt diseases.
Key words: antibiosis, biological control agent, competition, induced systemic resistance, organic amendment

The world’s population is increasing every year. In order tomeet the demands of an ever expanding human population,
global crop production needs to double by 2050; however,current estimates are far below what is needed (104). Plant
diseases, insects, and weeds decrease the production of crops
worldwide by 36%, and diseases alone have been shown to
reduce crop yields by 14% (5). Thus, the control of plantdiseases contributes to increased crop production. Amongplant diseases, soil-borne diseases are considered to be more
limiting than seed-borne or air-borne diseases in the production of many crops and account for 10–20% of yield losses
annually (120).
The top ten bacterial species have been listed based on
their scientific and economic importance in plant diseases: i)Pseudomonas syringae pathovars, ii) Ralstonia solanacearum,iii) Agrobacterium tumifaciens, iv) Xanthomonas oryzae
pv. oryzae, v) X. campestris pathovars, vi) X. axonopodis
pathovars, vii) Erwinia amylovora, viii) Xylella fastidiosa,ix) Dickeya (former Erwinia) (dadantanii and solani), andx) Pectobacterium (former Erwinia) carotovorum (andPectobacterium atrosepticum) (79).
R. solanacearum (Smith) Yabuuchi et al. (132) (syn.
Pseudomonas solanacearum [Smith] Smith, Burkholderia
solanacearum [Smith]) causes a vascular wilt disease and has
been ranked as the second most important bacterial pathogen.

It is one of the most destructive pathogens identified to datebecause it induces rapid and fatal wilting symptoms in hostplants. The host range is extensively wide, over 200 species,
and the pathogen is distributed worldwide and induces a
destructive economic impact (57). Direct yield losses by R.
solanacearum vary widely according to the host, cultivar,
climate, soil type, cropping pattern, and strain. For example,
yield losses vary from 0 to 91% in the tomato, 33 to 90% in
the potato, 10 to 30% in tobacco, 80 to 100% in the banana,and up to 20% in the groundnut (28). Difficulties are associated with controlling this pathogen due to its abilities to growendophytically, survive in soil, especially in the deeper layers, travel along water, and its relationship with weeds (122).
The management of bacterial wilt with physical, chemical,
biological, and cultural methods has been investigated for
decades. Elphinstone (28) extensively reviewed bacterial wilt
in 2005, and many studies have since been conducted on this
topic. We herein reviewed the same topic, but mainly basedon findings published between 2005 and 2014.
Elphinstone (28) reported that over 450 studies had been
published on R. solanacearum since the second International
Bacterial Wilt Symposium was held in Guadaloupe in 1997.
A broad classification on these studies showed that 24% wereconcerned with breeding and selection for resistance, while
the remainder investigated the diversity, distribution, andhost range of the pathogen (22%), disease management andcontrol (18%), pathogenicity and host-pathogen interactions(17%), biological control (10%), detection and diagnosis of* Corresponding author. E-mail: kokit@cc.tuat.ac.jp;
Tel: +81–42–388–7915; Fax: +81–42–388–7915.

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2

the pathogen (4%), and epidemiology and ecology (3%).
Based on our reference search from books and journals
between 1984 and 2014 using the Web of Science, LINK
(Springer), InterScience (Wiley), SD-Science Direct (Elsevier),
and Synergy (Blackwell), studies on methods regarding thebiological control of bacterial wilt (54%) were the mostcommon, followed by those on cultural practices (21%),chemical methods (8%), and physical methods (6%). Somestudies also focused on integrated pest management (11%).
This finding suggested that many researchers were interested
in biological control.
We herein discussed the following points, (i) methods used
to control bacterial wilt and their limitations, and (ii) how
these methods are useful for improving crop production
through the suppression of bacterial wilt.

tance was associated with increases in the amount of microorganisms in the soil as well as soil enzyme activity (urease andacid phosphatase). The soaking of seeds in a low sodium
chloride solution was previously found to increase seedlingvigor and tolerance to R. solanacearum in the tomato (86).
The mechanism of action of non-pesticide chemicals thatsuppress bacterial wilt is considered to involve either induced
systemic resistance or antibacterial activity. Some new
methods have been reported to suppress bacterial wilt. Livemicrobial cells of the pathogen were captured with 10 g kg−1
of coated sawdust with 1% of an equimolar polymer ofN-benzyl-4-vinylpyridinium chloride with styrene (PBVPco-ST) (55) or coagulated in the soil with 10 mg kg−1 ofa co-polymer of methyl methacrylate with N-benzyl-4vinylpyridinium chloride at a molar ratio 3:1 (PMMA-coBVP) (56). Infection by the bacterial wilt pathogen was prevented through bacteriostatic actions with a phosphoric acidsolution (89).
Various non-pesticide chemicals have the potential to be
applied in the field in order to control bacterial wilt diseasebecause they have less damaging effects on the environment;
however, economic considerations often influence the chemicals selected. Expensive chemicals and repeated applications
are only possible for valuable crops that may incur substantial
economic losses in the absence of treatments. Since crop
yield and quality are not damaged when disease severity is
low or in the absence of pathogens, a diagnosis based on
economic thresholds is essential for determining whether
chemical treatments are needed.
Biological method. 1) Biological control agents (BCAs)
Interest in biological control has increased due to concerns
over the general use of chemicals (126). The benefits of
BCAs are 1) potentially self-sustaining, 2) spread on theirown after initial establishment, 3) reduced input of nonrenewable resources, and 4) long-term disease suppression in
an environmentally friendly manner (102, 127).
The mechanisms employed by BCAs are sustained byvarious interactions such as competition for nutrients andspace, antibiosis, parasitism, and induced systemic resistance(5, 22). Our reference survey revealed that BCAs have been
dominated by bacteria (90%) and fungi (10%). Montesinos(84) found that most patented BCAs are made of bacteria.
Topics regarding biocontrol agents for bacterial wilt havebeen separated into the following categories: isolation,screening and identification of BCAs, application methods of
BCAs, improved BCAs, suppression mechanisms of BCAs,
and effects of BCAs on the environment.
Previous studies showed the potential value of some promising BCAs, which are dominantly avirulent strains of R.
solanacearum and Pseudomonas spp., followed by Bacillus
spp., Streptomyces spp., and other species, in controlling
bacterial wilt. A total of 109 strains of endophytic or rhizobacteria were recently screened for their antibacterial activities against R. solanacearum, and effective isolates (a total of22) consisted of Pseudomonas spp. (18 isolates) and Bacillus
sp. (2 isolates) (103). Kurabachew et al. (64) screened 13 outof 150 isolates of rhizobacteria based on in vitro antibiosis,
and they were Pseudomonas spp., Serratia marcescens, andBacillus cereus. Among Bacillus spp., the number of studies
being conducted on B. amyloliquefaciens is increasing (21,Methods used for crop protection
Chemical methods (pesticides and non-pesticides). World
pesticide use exceeded 5.0 billion pounds in 2000 and 2001
(59). Herbicides account for the largest portion of the total use,followed by insecticides and fungicides. Plant disease control
has been largely dependent on the use of pesticides (127).
Schreinemachers et al. (107) reported that pesticide use perhectare, especially herbicides and fungicides/bactericides,
had generally increased more than porportionally with crop
output per hectare, and revealed that a 1% increase in crop
output per hectare was associated with 1.8% increase in pesticide use per hectare.
Pesticides such as algicide (3-[3-indolyl] butanoic acid),
fumigants (metam sodium, 1,3-dichloropropene, and chloropicrin), and plant activators generating systemic resistance on
the tomato (validamycin A and validoxylamine) have beenused to control bacterial wilt. The combination of methyl
bromide, 1,3-dichloropropene, or metam sodium with chloropicrin significantly reduced bacterial wilt in the field from
72% to 100% and increased the yield of tobacco and thetomato. The yield of the pesticide-treated tomato was 1.7- to
2.5-fold higher than that of the untreated control (32, 105).
Edwards-Jones (27) reported that pesticides offered greater
net benefits than other control methods, but this has notalways been the case. For example, if farmers use pesticides
carelessly or without proper knowledge, a percentage of thepesticide may remain in the environment for many years (34),
become a contaminant in soil and/or groundwater (2), and bepoisonous to farmers (25).
Bactericides (triazolothiadiazine [0.5 to 12 mM, in solution] (58), streptomycin sulfate [400 mg kg−1 of soil] (72)),
other chemicals such as bleaching powders (application rate
to the field, 30 kg ha−1) as sterilizers (108), or weak acidic
electrolyzed water (40 ppm of available chlorine, in pH 5.6
solution) (137) have also been shown to effectively destroy
microorganisms.
Acibenzolar-S-methyl (ASM) has been proposed to induce
systemic resistance (38, 100). The combination of ASM andthymol significantly reduced the incidence of disease andincreased the yield of the tomato, whereas ASM or thymol
alone did not (43). Silicon (24, 65, 129) or Si and chitosan(61) reduced the incidence of bacterial wilt through induced
resistance. Wang et al. (123) reported that Si-mediated resis30

Control Methods for Bacterial Wilt Diseases

3(115), and Xenorhabdus nematophila (52). The possible
suppression mechanisms of these species are competition,induced systemic resistance, antibiosis, and the production of
enzymes that degrade the cell wall and siderophores.
Successful trials using BCA in the field are introduced inTable 1. Hyakumachi et al. (47) recently revealed that B.
thuringiensis, a famous bioinsecticide-producing bacterium,
induced defense-related genes, such as PR-1, acidic chitinase,and beta-1,3-glucanase and showed resistance against a direct
inoculation with R. solanacearum. The expression of several
salicylic acid-responsive defense-related genes was confirmed to be specifically induced (114), and also that suppression by B. thuringiensis may differ from the induced systemic
resistance (ISR) elicited by many plant growth-promoting
rhizobacteria (PGPR), in which jasmonic acid and ethylenedependent signaling pathways mediate plant resistance topathogens (47).
Some fungal BCAs have been reported to control bacterial
wilt. In pot cultures, populations of R. solanacearum in therhizosphere, on root surfaces, and in the xylem of tomato
plants decreased by 26.7, 79.3, and 81.7%, respectively, following the inoculation of Glomus versiforme. The coloniza-

26, 44, 116, 124, 143). Plant growth-promoting rhizobacteria
are commonly isolated from the rhizosphere of healthy plants
and an interesting strategy has been reported. Huang et al.
(45) revealed that isolates from the rhizosphere of diseased
plants performed better in reducing disease incidence thatthose of healthy plants. In their study, the biocontrol efficacies of the antagonists were related to root colonizing capacities, but not with antibiosis in vitro, suggesting that root colonizing capacity may play a key role in disease suppression.
Several new or uncommon BCAs have been reported tocontrol bacterial wilt such as Acinetobacter sp. (130),
Burkholderia nodosa, B. sacchari, B. tericola, B. pyrrocinia(88), bacteriophages (10, 133), Bacillus thuringiensis (146),
Chryseobacterium daecheongense (45), Chryseobacterium
indologenes (42), Chryseomonas luteola (42), Clostridium
sp. (82), Delftia acidovorans (45), Enterobacter sp. (130),
Flavobacterium johnsoniae (45), Myroides odoratimimus(138), Paenibacillus marcerans (70), P. polymyxa (69, 74),
Pseudomonas brassicacearum (145), Ralstonia pickettii(125), Serratia sp. (37, 131), Sphingomonas paucimobilis(42), Staphylococcus auricularis (42), Stenotrophomonas
maltophilia (81), Streptomyces rochei (76), S. virginiae

Table 1. Various biocontrol agents that have been tested in the field to control bacterial wilt diseases caused by Ralstonia solanacearum (2005–2014)
Microorganisms

Inoculation method and application rate

Mechanisms

BE (%)

Yield*Ref

1. Bacillus amyloliquefaciens
SQR-7 and SQR-101 and B.
methylotrophicus SQR-29
2. Ralstonia pickettii QL-A6

Pouring, 6.8×1010 cfu plant−1 (SQR-7),

Production of indole
acetic acid andsiderophores
Competition

18–60% intobacco25–38%

143

73% in theNAtomato54%
3. Pseudomonas monteilii (A) + Stem cuttings were dipped in A (9.1×108 mL−1), Increased plant nutrient 56–75% in herbs
uptake (N, P, K) and(ColeusB (53 infective propagules) was added to each
Glomus fasciculatum (B)reduced the pathogen forskohli)
cutting, and A was then poured again
population
Decreased root
30–95% in
87–100%4. Brevibacillus brevis L-25 + Mixed with soil at a density of 7.3×107 (L-25)
and 5.0×105 (L-9) cfu g−1 of soilcolonization by the
tobaccoStreptomyces roche L-9 +pathogenorganic fertilizer
64–65%
5. Bacillus amyloliquefaciens + Mixed with soil at a density of 5.5×106 (BIO23) Plant growth promotion 58–66% in the
potatobio-organic fertilizer (BIO23) and 7.0×106 (BIO36) cfu g−1 of soil
B. subtilis + bio-organic
fertilizer (BIO36)
81% in the
60–90%
6. Bacillus sp. (RCh6)
3×108 cfu g−1 (talc formulation). Seedlings were Production of
inhibitory compounds eggplant
Pseudomonas mallei (RBG4)
dipped in antagonist suspension (25 g talc
and siderophores
formulation L−1). Leftover suspension waspoured around the root zone of the seedling(50 mL plant−1)
Competition for
7–43% in herbs 159–227%
7. Trichoderma viride (A), B.
D (53 infective propagules) was added to eachnutrient uptake (NPK) (Coleus
subtilis (B), Azotobacter
stem cutting that was dipped inforskohlii)chroococcum (C), Glomus
A (1.2×106 CFU mL−1), B (1.8×108 CFU mL−1), and reduced R.
solanacearum
fasciculatum (D), P. fluorescens C (2.3×107 CFU mL−1), and8−1
E (2.5×10 CFU mL ). A total of 5 mL of A, B, population(E)C, and E was then poured into 200 g soil.
17–87% in theNA
8. B. amyloliquefaciens QL-5, Mixed with soil at a density of 1×107 (QL-5) or Decreased root
1×107 (QL-18) cfu g−1 of soilcolonization by thetomatoQL-18 + organic fertilizer
pathogen
Production of
60–80% inNA
9. B. amyloliquefaciens Bg-C31 Poured 10 mL of bacterial suspension plant−1
antimicrobial proteins Capsicum(potato dextrose broth culture).
Rhizocompetence and 57–67% in the
32–41%
10. Acinetobacter sp. Xa6,
Poured 20 mL of the bacterial suspension
tomatoEnterobacter sp. Xy3(1×109 cells mL−1) plant−1 or seedling roots were root colonization
soaked in the bacterial suspension.
17%
11. B. vallismortis ExTN-1
Bacterial suspension was mixed into an organic Induction of systemic 48–49% in theresistance
tomatofertilizer (106 cfu mL−1) and poured onto soil.
25% in the16%
12. Glomus mossease
A total of 30 g of the inoculum (650–700 spores Competition for
nutrients and decreased tomato
of G. mossease 100 g−1 soil) was added to aplanting hole.
pathogen population

125

7.5×1010 cfu plant−1 (SQR-101),
8.2×1010 cfu plant−1 (SQR-7)
Stem injection, 10 µL of 107 CFU mL−1

BE: biological control efficacy, NA: not applicable, Yield*: increase in yield

31

111

76
26

103

110

124
44
130
119
113

Yuliar et al.

4tion of plants by both R. solanacearum and G. versiforme
increased the contents of soluble phenols and cell-wall boundphenols in the root tissue, which may be related to ISR by thefungus (147). Another fungus, Pythium oligandrum, has thepotential to control bacterial wilt disease, in which cell wall
proteins may play an important role in the induction of resistance to R. solanacearum, accompanied by activation of theethylene-dependent signaling pathway (41). Shiitake mycelia
leachate was found to contain an antibiotic ingredient thatsuppressed the growth of R. solanacearum in vitro (93). In
addition, three endomycorrhizal fungi (Gigaspora margarita,
Glomus mosseae, and Scutellospora sp.) (112) and the lichen
Parmotrema tinctorum (35) have been identified as BCAs
against R. solanacearum.
In the inoculation methods of BCAs, pouring or drenchingsoil was more prevalent than other methods, whereas thebiocontrol efficacy range appeared to be lower than that of thedipping of roots or seed coating method.
There are some disadvantages to BCAs. The biggest obstacle is their poor performance due to inconsistent colonization.
Suppression by BCAs has been observed in a narrow range ofhost plants or restricted to a single pathogen or disease (127).
The degree of suppression is sometimes too low to becommercially acceptable or requires uneconomically highrates of inoculums to be applied (127). Difficulties have also
been associated with producing, storing, and subsequently
applying BCAs. An option to overcome the storage problem
is to select spore formers as BCAs (e.g. 21, 47, 74, 116,
124, 146).
2) Organic matter
Organic amendments to soil have direct impacts on plant
health and crop productivity. They are advantageous because
they improve the physical, chemical, and biological properties
of soil, which can have positive effects on plant growth (14).
The degradation of organic matter in soil can directly
affect the viability and survival of a pathogen by restricting
available nutrients and releasing natural chemical substanceswith varying inhibitory properties (14). Carbon released
during the degradation of organic matter contributes toincreasing soil microbial activity and thereby enhances thelikelihood of competition effects in the soil (14). Organic
amendments to soil have been shown to stimulate the activities of microorganisms that are antagonistic to pathogens (6).
In addition, organic amendments often contain biologically-active molecules such as vitamins, growth regulators, andtoxins, which can affect soil microorganisms. Youssef andTartoura (139) recently reported that plant resistance against
the bacteial wilt pathogen was enhanced through the augmented activities of ascorbate peroxidase, monodehydroascorbate reductase, dehydroascorbate reductase, and glutathione reductase following the application of compost.
Organic matter originates from recently living organisms
and decays or is the product of decay. It is categorized intoplant or animal origins, and simple organic carbons. In theprevious references to an R. solanacearum study, different
organic matter, such as plant residue (80%), animal waste(10%), and simple organic matter (10%), were shown tocontrol bacterial wilt disease. Larkin (67) found that biological amendments were generally effective for delivering
microorganisms to natural soil, resulting in a wide variety ofeffects on soil microbial communities depending on the particular types, numbers, and formulations of organisms added.
A new approach is the suppression of bacterial wilt in an
organic hydroponic system through a rhizosphere biofilm that
only forms on roots in the organic system (33).
2a) Plant residue controlling bacterial wilt
Several previous studies reported that bacterial wilt was
suppressed by plant residues derived from, e.g. chili(Capsicum annum) (117), Chinese gall (Rhus chinensis)(142), clove (Szygyum aromaticum) (11), cole (Brassica sp.)
(13, 90, 97), eggplant (Solanum melongena), (9), eucalyptus(Eucalyptus globules) (94, 95), geranium (Geranium
carolinianum) (91), guava (Psidium guajava and P. quineense)(3), hinoki (Chamaecyparis obtusa) (141), Japanese cedar(Cryptomeria japonica) (46, 80), lemongrass (Cimbopogon
citratus) (94, 95), marigold (Tagetes patula) (118), neem
(Azadirachta indica) (96), palmarosa (Cimbopogon martint)(94, 95), pigeon pea (Cajanus cajan), sunn hemp (Crotalaria
juncea) (20), tamarillo (Cyphomandra betacea) (92), thyme(Thymus spp.) (53, 99), wood wax tree (Toxicodendron
xylvestre) (142), and worm killer (Aristolochia bracteata)(109). The possible mechanisms of action of the plant
residues are mainly considered to be antimicrobial activities,
followed by the indirect suppression of the pathogen throughimproved physical, chemical, and biological soil properties(20). For example, the antimicrobial compounds fromTagetes patula that suppressed R. solanacearum in an in vitro
experiment were identified as 5-(3-buten-1-ynyl)-2,2'-bithienyl(BBT) and 5-(4-acetoxy-1-butynyl)-2,2'-bithienyl (BBTOAc)(118). Other plants such as Cryptomeria japonica produced
sandaracopimarinol and ferruginol (80) while Cyphomandra
betacea contained a glycosidase inhibitory protein thatsuppressed R. solanacearum in an in vitro experiment (92).
Lansiumamide B isolated from the seeds of Clausena lansium
suppressed tobacco bacterial wilt more than an antibiotic
streptomycin when applied at a density of 100 mg kg−1 (71).
Previous experiments demonstrated the successful application of organic matter against bacterial wilt in greenhouses
and in the field. For example, in a greenhouse experiment,
when the freshly cut aerial parts of pigeon pea (Cajanus
cajan) and crotalaria (Crotalaria juncea) were incorporated
at concentrations of 20–30% and incubated for 30 d, they
completely suppressed tomato bacterial wilt 45 d after the
inoculation (20); however, the application rate of this organic
matter was high and, thus, not feasible for farmers. Thymol
oil derived from a thyme plant reduced bacterial wilt by 65%
in the fall 2002 tomato cultivation and by 82% in fall 2003
tomato cultivation at an application rate of 0.72% in the field(53). Alfano et al. (8) reported that the disease suppressive
effects of olive waste compost appeared to be due to the
combined effects of suppression phenomena caused by thepresence of microorganisms competing for both nutrientsand space as well as by the activity of specific antagonistic
microorganisms.
2b) Animal waste controlling bacterial wilt
Although many studies have already reported that animal
waste controls plant disease, few have shown that animal
waste suppresses bacterial wilt disease. For example, theapplication of pig slurry decreased the population of R.
solanacearum in the soil (36). The mechanisms underlying
32

Control Methods for Bacterial Wilt Diseases

5

the enhanced decline of the population of this pathogen anddisease suppression remains unclear; however, shifts in bacterial community profiles have been proposed. Another study
suggested that the suppression of bacterial wilt by poultry andfarmyard manure were related to higher microbial activity
and higher numbers of cultural bacteria and fungi (50). In thatstudy, a lower disease index was related to the poor survivalof the pathogen. However, limitations are associated with thewide use of organic waste. Janvier et al. (51) demonstrated
that the major key-points for the efficiency of organic
matter in suppressing plant pathogens depended on: i) theplant-pathogen combination, ii) the rate of application, iii) thenature/type of amendment, and iv) the degree of maturity ofthe decomposition stage of crop residues.
2c) Simple organic compounds controlling bacterial wilt
The efficacy of simple organic compounds, including
amino acids, sugars, and organic acids, on bacterial wilt in thetomato was evaluated in pot experiments. The application oflysine to a pumice culture medium (0.25 mg g−1) and soil (2.5mg g−1) reduced bacterial wilt in the tomato by 85–100% (48,87) and by 58–100% (97), respectively. The suppression
mechanism was not attributed to the induction of systemic
resistance, but to shifts in the soil microbial community
structure that led to the more rapid death of the pathogen (98).
In contrast, riboflavin induced a series of defense responses
and secondary metabolism in cell suspensions and, thus,
protected tobacco against R. solanacearum (75). DL,-3aminobutyric acid (BABA) also increased polyphenol oxidase activity and decreased that of catalase in tomato plants,suggesting the induction of resistance to bacterial wilt in thetomato (40). Another study showed that methyl gallate exhibited strong bactericidal effects on R. solanacearum (30).
Physical methods, including biofumigation. A numberof physical control methods, e.g. solarization and hot water
treatments, have proved to be effective against R. solanacearum.
Vinh et al. (121) found that soil solarization using transparent
plastic mulches for 60 d prior to the planting of tomatoes
reduced the incidence of bacterial wilt. Another study
reported that rhizome solarization on ginger seeds for 2 to 4 h
reduced bacterial wilt by 90–100% 120 d after planting, andthat ginger seeds sterilized with discontinuous microwaving(10-s pulses) at 45°C reduced the incidence of wilt by 100%
(63). Baptista et al. (16, 17) studied the mechanisms of soil
solarization that reduced bacterial wilt in the tomato. Soilsolarization reduced soil pH, potassium (K), sodium (Na),boron (B), and zinc contents, microbial biomass, and microbial respiration in soil, but did not significantly affect othersoil chemical properties. A heat treatment at either 45°C for
2 d or a minimum temperature of 60°C for 2 h of the infectedsoil prior to tomato planting reduced the total bacterial population by 60–97%, that of Ralstonia sp. from 2 to 7×108 cfu g−1
to 0 to 115 cfu g−1, and the incidence of bacterial wilt by
50–75% (62). Several parameters need to be carefully considered before the application of soil solarization can be expanded:
controlling temperature or the release of volatile compounds
and economical and/or practical feasibility in field.
In addition to heat treatments, cold temperatures are also
sometimes effective. Bacterial wilt rarely occurs in tobacco
crops planted in May or June (winter crop) in north
Queensland because of cool weather conditions, whereas thedisease developed when crops were planted in spring(September to November), particularly when bacterial wilt
had previously occurred and crop rotation was not practiced(7). Lower moisture conditions (20–30% maximum water
holding capacity) and pre-incubation at lower temperatures(4°C) reduced bacterial wilt and had a negative impact on thesurvival of R. solanacearum (50). Scherf et al. (106) foundthat R. solanacearum survived for 6 months in an infected
geranium at a constant temperature, but declined rapidly inrepeated winter temperature cycles of 2 d at 5°C followed by
2 d at −10°C. The mechanism of action responsible for the
suppression of bacterial wilt by physical methods generally
involves killing pathogens with high or low temperatures.
Biofumigation, which refers to the agronomic practice ofusing volatile chemicals released from plant residues to suppress soil-borne plant pathogens, has recently been attracting
attention (61). Biofumigation is called biological soil disinfection (BSD) and the production of organic acids or heavy
metal ions is involved in the suppression of pathogens (83).
Another approach is control with a high voltage electrostatic field and radio frequency electromagnetic field, inwhich ISR is involved in the suppression mechanism (128).
Silver-coated non-woven cloth filter and a visible light source(15) or electrostatic spore precipitator ozone-saturated water(144) was developed as a sterilization device and inactivatedthe pathogen.
Cultural practices. 1) Cultivar resistant
The growth of cultivars that are resistant to bacterial wilt is
considered to be the most economical, environmentallyfriendly, and effective method of disease control. Breeding
for resistance to bacterial wilt has been concentrated on cropsof wide economic importance such as the tomato, potato,
tobacco, eggplant, pepper, and peanut, and has commonly
been influenced by factors such as the availability ofresistance sources, their diversity, genetic linkage between
resistance, and other agronomic traits, differentiation andvariability in pathogenic strains, the mechanism of plantpathogen interactions, and breeding or selection methodology(19, 28, 39). For example, the Arabidopsis NPR1 (nonexpresser of PR genes) gene was introduced into a tomato
cultivar, and enhanced resistance to bacterial wilt andreduced the incidence of wilt by approximately 70% 28 dafter the inoculation (73). Potato genotype BP9, which is asomatic hybrid between Solanum tuberosum and S. phureja,
successfully reduced bacterial wilt by 90–100% (31).
Somatic hybrids between S. melongena cv. Dourga and twogroups of S. aethiopicum were produced by the electricalfusion of mesophyll protoplasts and were found to be tolerant
to R. solanacearum. Public acceptance in Japan is needed prior
to the commercial use of such genetically modified crops.
Prior et al. (101) showed that resistant plants were heavily
invaded by R. solanacearum without displaying wilt symptoms. Nakaho et al. (2004) revealed that bacterial multiplication in the stems of resistant tomato plants was suppressed
due to limited pathogen movement from the protoxylem or
primary xylem to other xylem tissues (85). A proteomic
approach was used to elucidate molecular interactions in thecell walls of resistant and sensitive plants inoculated with R.
solanacearum (23). Resistance to bacterial wilt in many crops
has generally been negatively correlated with yield and33

Yuliar et al.

6quality. Thus, the release of resistant cultivars may be poor
because of other agronomic traits and are not widely acceptedby farmers or consumers. The breeding of a good resistantcultivar is expected in the future through stronger efforts in
the genetic enhancement of bacterial wilt resistance throughbiotechnology approaches in order to improve yield crop.
2) Crop rotation, multi-cropping
The benefits of crop rotation are maintenance of the soil
structure and organic matter, and a reduction in soil erosionthat is often associated with continuous row crops (51). Whilecontinuous cropping with the same susceptible host plant willlead to the establishment of specific plant pathogenic populations, crop rotation avoids this detrimental effect and is often
associated with a reduction in plant diseases caused by soilborne pathogens (51, 66). For example, the onset of bacterial
wilt was delayed by 1 or 3 weeks and wilt severity was
reduced by 20–26% when a susceptible tomato variety wasgrown after corn, lady’s fingers, cowpea, or resistant tomato(4). Potato cultivation rotated with wheat, sweet potato,maize, millet, carrots, sorghum, or phaseolus beans reduced
the incidence of wilt by 64 to 94% while the yield of potatoes
was 1- to 3-fold higher than that of monocultured potatoes(54). In an example of multi-cropping, Yu et al. (140)reported the suppression mechanisms of Chinese chive(Allium tuberosum), which reduced the incidence of bacterial
wilt in the tomato (approximately 60%) because the root
exudates of Chinese chive may prevent R. solanacearum
from infecting tomato plants.
3) Soil amendment
Previous studies revealed that the application of fertilizers
reduced the incidence of bacterial wilt. Calcium (Ca) is themost well-known fertilizer to suppress disease. Increased Ca
concentrations in plants reduced the severity of bacterial
wilt as well as the population of R. solanacearum in the stemsof the tomato (134, 136). Furthermore, an increase in Ca
uptake by tomato shoots correlated with lower levels of
disease severity (135, 136). Lemaga et al. (68) reported thatthe application of nitrogen (N) + phosphorus (P) + K and
N + P (application rate of each fertilizer = 100 kg ha−1)
reduced bacterial wilt by 29% and 50%, respectively, andincreased the yield of potatoes to 18.8 t ha−1 and 16.6 t ha−1,
respectively, which was higher than that in untreated controls (11.2 t ha−1). Hacisalihoglu et al. (38) reported that bacterial wilt induced changes in the distribution of nutrients,
especially Ca, B, and P in tomato leaves. Li and Dong (70)showed that the combined amendment of rock dust andcommercial organic fertilizer reduced the incidence of bacterial
wilt in the tomato. A single amendment with rock dust also
effectively reduced the incidence of bacterial wilt in thetomato and higher soil pH and Ca content were key factors in
the control of bacterial wilt by the rock dust amendment.
Many elements in the cell walls influence the susceptibilityor resistance of plants to infections by pathogens and silicon
is considered to be a beneficial element for plants and higher
animals (29). Kiirika et al. (60) reported that the combined
application of silicon and chitosan reduced the incidence ofbacterial wilt in the tomato by inducing resistance. Si andchitosan exhibited synergistic effects against the disease.
Integrated Pest Management (IPM)
According to Agrios (5), the main goals of an integrated

plant disease control program, regarded as integrated pest
management (IPM), are to (i) eliminate or reduce the initial
inoculums, (ii) reduce the effectiveness of initial inocula, (iii)increase the resistance of the host, (iv) delay the onset of
disease, and (v) slow secondary cycles.
IPM reduced bacterial wilt disease by 20–100% in the fieldor under laboratory conditions, and typically combines two or
three methods among cultural practices and chemical andbiological methods. For example, the incidence of bacterial
wilt in the tomato was monitored in soil infested with R.
solanacearum and the addition of an organic mixture consisting of agricultural and industrial waste such as bagasse, ricehusks, oyster shell powder, urea, potassium nitrate, calcium
superphosphate, and mineral ash or Actigard (active
ingredient: acibenzolar-S-methyl [ASM]). The addition of theorganic mixture decreased the incidence of bacterial wilt inthe tomato by 32%, while that of Actigard decreased it by
5%. In contrast, the addition of the organic mixture andActigard decreased the incidence of bacterial wilt by 53%(12). We previously demonstrated that suppressive effects
against bacterial wilt in the tomato were enhanced by combinations of BCAs and their substrates, such as lysine, sucrose,and anaerobically digested slurry, in which the addition ofsubstrates improved the colonization of tomato roots by
BCAs (87, 88).
The relative importance of factors accounting for production losses need to be assessed in order to develop IPM.
Combinations in cultural practice methods, such as the combination of crop rotation with a resistant cultivar or a soil
amendment, or the combination of organic matter with a
non-pesticide chemical such as formaldehyde or bleachingpowder appear to have effectively reduced the incidence ofbacterial wilt and increased crop yield (4, 68, 108, 121). The
combined application of ASM and P. fluorescens Pf2 resulted
in the greatest reduction in the incidence of bacterial wilt inthe tomato, while the application of ASM or P. fluorescens
Pf2 was also effective (1). A previous study reported that the
combination of endophytic bacteria (Bacillus sp. and Serratia
marcescens, both of which had no antibiosis) with resistantcultivars of the tomato reduced the incidence of bacterial
wilt (18).
Grafting is an important strategy in integrated pest management for soil-borne pathogens. Disease management by
grafting has been reported for fungal pathogens (such as
Verticillium, Fusarium, Pyrenochaeta, and Monosporascus),
oomycete pathogens (Phytophthora), bacterial pathogens(particularly Ralstonia), root knot nematodes, and several
soil-borne viruses (78).
We need to select methods that are easy, practical, profitable, and also environmentally healthy to control diseases andimprove yields.
Cautions for disease control measures. 1) Keep the environment healthy
Preventive methods are essential for maintaining fields thatare free of bacterial wilt. R. solanacearum is a soil-borne
bacterium and may survive for prolonged periods in soil,
water, and plant materials (77). Thus, to keep environment
free of this pathogen, it is important to clean seeds, soil,
water, and tools in order to improve crop production by preventing this disease. The use of healthy seeds that are free of34

Control Methods for Bacterial Wilt Diseases

7

pathogens is the most economical, environmentally friendly,and effective method for disease control. Cultural practices
involving soil amendments, including organic matter, crop
rotation, and multi-cropping, can be used to maintain soil
health. These agricultural practices influence the chemical,
biological, and physical properties of soil, which, in turn,influence the viability and distribution of pathogens as well as
the availability of nutrients for pathogens in the soil.
Researchers are becoming more interested in investigating
the effects of such practices on microbial communities, or inassessing their potential to control soil-borne pathogens. Soil
health indicators may be very useful for risk prevision andtechnical advice (53).
The early detection of R. solanacearum in irrigation wateror soil is essential for preventing its introduction into newareas. A sensitive quantitative assay was recently developed
to detect Ralstonia solanacearum in soil by the most probable
number (MPN) analysis based on PCR results, in which a
pre-culture was performed in a buffer containing antibiotics,
but no other carbon source in order to allow the pathogen togrow and to suppress the growth of other soil microorganisms(49). This assay enabled pathogens to be detected at levels as
low as 9.3 cfu g−1 soil.
2) Abiotic and biotic factors to be considered
Plant diseases caused by soil-borne pathogens such as R.
solanacearum result from the multiple and complex interactions, including both biotic and abiotic factors, they have withplants. Abiotic factors such as nutrient (organic matter andminerals) conditions, soil type, pH, anaerobic conditions,temperature, and moisture content influence the developmentof R. solanacearum in soil, as described above.
Biotic factors are related to microorganisms, flora, faunain the soil, and plants that can affect R. solanacearum.
Previous studies investigated the biotic factors controlling R.
solanacearum such as the microbial community in soil,
introduction of BCAs, cultivar resistance, and rotation, as
described above. Various suppression mechanisms are considered to be biotic factors for the pathogen, such as enhanced
microbial activity, which can suppress R. solanacearum, therelease of antibiotics, enhanced competition, decrease in colonization, the induction of systemic resistance, and protection
against or avoidance of pathogen contact with the host crop.
3) Economic analysis
Many researchers have managed bacterial wilt with biological, physical, and chemical methods and/or with cultural
practices; however, few studies have examined the efficiencyof these methods to improve crop yield, especially economic
analyses. Based on our reference survey, only 10% of themethods reported improved crop yield. In integrated disease
management, soil amendments with 300 kg N and 1,500 kg
CaO, together with soil solarization using transparent plastic
mulches, reduced the incidence of wilt in the tomato by 20%
and increased grower profits, equivalent to 369 to 998 US$
per ha (121). Our primary goal is to contribute to safe, sustainable, and high agricultural production. Attention tocost-benefit analyses is indispensable in the short, middle,
and long term.
4) Future of fumigants
The use of a fumigant type of agrochemical in Japan has
enabled the establishment of a pathogen-free environment

and, thus, intensive agriculture, leading to high quality crop
production. However, some of these indiscriminating fumigants are prohibited in European countries, e.g. chloropicrin
has been banned since 2011 due to the risks posed to pesticide
operators and aquatic organisms, birds, and bees (EU No
1381/2011). Due to public concerns and environmental
impact, it is not advisable to rely only on single controlling
methods, such as fumigants, for high yield and quality crop
production. Proper control methods need to be adopted basedon the density of and crop resistance to pests.
Concluding remarks
The research discussed in this review shows how manydifferent diverse options have been reported on control methods against diseases caused by R. solanacearum. This unequivocally indicates the importance of these diseases worldwide.
The avoidance of crop losses due to pathogens significantly
contributes to increased crop production worldwide. We
will be able to identify solutions by integrating a biologicalcontrol agent and organic matter including simple organic
compounds, compost, or plant residue.
Acknowledgements
Yuliar gratefully acknowledges the financial support of Japan
Society for the Promotion of Science (JSPS) RONPAKU
Dissertation PhD Program. Yanetri Asi Nion would like to express
gratitude to the Ministry Education, Science, Sports and Culture ofJapan for financial support during her stay in Japan. We express
sincere thanks to Dr. Marylene Posas for her advice on the structure
and careful checking of this manuscript.
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39

MOST CITED ORIGINAL PAPER IN THISTEN YEARS [2008-2017] (57 citations)

Microbes Environ. Vol. 26, No. 1, 15–22, 2011

http://wwwsoc.nii.ac.jp/jsme2/

doi:10.1264/jsme2.ME10131

Seasonal Dynamics of Anammox Bacteria in Estuarial Sediment of the Mai
Po Nature Reserve Revealed by Analyzing the 16S rRNA and Hydrazine
Oxidoreductase (hzo) Genes
MENG LI1, HUILUO CAO1, YI-GUO HONG1,2, and JI-DONG GU1,3*
1School of Biological Sciences, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, P.R. China; 2Key
Laboratory of Tropical Marine Environment Dynamics (LED), South China Sea Institute of Oceanography, Chinese
Academy of Sciences, 164 Xingang Road West, Guangzhou 510301, P.R. China; and 3The Swire Institute of Marine
Science, The University of Hong Kong, Shek O, Cape d’Aguilar, Hong Kong SAR, P.R. China(Received May 14, 2010—Accepted September 25, 2010—Published online December 4, 2010)

The community and population dynamics of anammox bacteria in summer (wet) and winter (dry) seasons in estuarial mudflat sediment of the Mai Po Nature Reserve were investigated by 16S rRNA and hydrazine oxidoreductase(hzo) genes. 16S rRNA phylogenetic diversity showed that sequences related to ‘Kuenenia’ anammox bacteria were
presented in summer but not winter while ‘Scalindua’ anammox bacteria occurred in both seasons and could be
divided into six different clusters. Compared to the 16S rRNA genes, the hzo genes revealed a relatively uniform
seasonal diversity, with sequences relating to ‘Scalindua’, ‘Anammoxoglobus’, and planctomycete KSU-1 found inboth seasons. The seasonal specific bacterial groups and diversity based on the 16S rRNA and hzo genes indicatedstrong seasonal community structures in estuary sediment of this site. Furthermore, the higher abundance of hzo genes
in summer than winter indicates clear seasonal population dynamics. Combining the physicochemical characteristics ofestuary sediment in the two seasons and their correlations with anammox bacteria community structure, we proposed
the strong seasonal dynamics in estuary sediment of Mai Po to be due to the anthropogenic and terrestrial inputs,
especially in summer, which brings in freshwater anammox bacteria, such as ‘Kuenenia’, interacting with the coastal
marine anammox bacteria ‘Scalindua’.
Key words: anammox bacteria, seasonal dynamics, 16S rRNA, hzo, estuary, Mai Po Nature Reserve

Anammox, the conversion of ammonium to dinitrogengas (N2) by nitrite under anoxic conditions, has been proposed to play a key role in the global nitrogen cycle (9),which might be responsible for more than half of all oceanic
N2 production (7). The anammox process has been demonstrated in marine ecosystems (15, 19, 20, 31, 43, 45, 47) andfreshwater terrestrial ecosystems (29, 41), low-temperaturepolar regions (32, 33) and high-temperature hot spring anddeep sea hydrothermal vents (3, 13), and oil reservoirs (22),even on the surface of marine sponges (12, 26). Certain
Planctomycetes are monophyletic members linked to this process, and five genera, ‘Candidatus Brocadia’, ‘Candidatus
Kuenenia’, ‘Candidatus Anammoxoglobus’, ‘Candidatus
Scalindua’ and ‘Candidatus Jettenia’, have been described(16–18, 30, 37). Interestingly, anammox bacterial diversityand distribution differ among various ecosystems, showing
niche specificity (6). The genera ‘Brocadia’ and ‘Kuenenia’are usually found in engineered systems such as wastewater
treatment plants though a few reports indicated their presence in freshwater and marine ecosystems (1, 27, 50),
while ‘Scalindua’ genus dominates in natural ecosystems,
especially in marine environments (39, 49).
Cape Fear River estuary sediment showed a strong
temporal and spatial distribution of anammox bacteria andseasonal variations of anammox bacteria detected by theisotope method and 16S rRNA gene, which extend ourunderstanding of the seasonal distribution of anammox
bacteria in estuary ecosystems (6). Hietanen et al. suggested
that anammox accounted for 10% and 15% of total N2
production during spring and autumn at a coastal station on
the Gulf of Finland in the Baltic Sea (11), but gave no information about the seasonal variation in anammox bacteria
community structure. These results indicated anammox
bacteria have clear seasonal variations in their activity,
as well as community structure, diversity and abundance.
However, most information about anammox bacterial diversity and distribution in natural ecosystems is based on 16SrRNA genes. Functional biomarkers that respond to theanammox process are needed to describe anammox bacterial
ecology more comprehensively. Hydrazine oxidoreductase(HZO) dehydrogenated the unique anammox intermediate,
hydrazine, to form dinitrogen gas, and has been proposed
as a functional biomarker for anammox bacteria, especiallythe two copies of the HZO-encoding gene (hzo) within
hzo-cluster 1 (34, 40), and recent studies also successfully
used hzo to evaluate the diversity and distribution of
anammox bacteria in different natural ecosystems, including
marine sediment (23), a wastewater treatment plant (24) andhigh-temperature petroleum reservoirs (22). On the other
hand, knowledge about the temporal community structureof anammox bacteria in natural ecosystems is still limited,
especially in natural ecosystems with anthropogenic influences. Thus, elucidating the seasonal variation in bacterial* Corresponding author. E-mail: jdgu@hkucc.hku.hk;
Tel: 852–2299–0605; Fax: 852–2559–9114.

40

16

LI et al.
of sediment samples, after centrifugation, were measured with anautoanalyzer (QuickChem, Milwaukee, USA) according to standard
methods of the American Public Health Association (2). Totalammoniacal nitrogen (T-NH4+), total Kjeldahl nitrogen, total nitrogen, total phosphorus and total sulphide concentrations of sediment
samples were measured according to the standard methods ASTM
D3590-89B, ASTM D51588B and ASTM E200 60–61; while levelsof arsenic, cadmium, copper, mercury and lead were determined by
USEPA method 6020 (48).

community structures and checking whether different generaor species have specific niches or seasonal requirements are
obviously important for understanding anammox microbial
ecology.
To extend our understanding of the seasonal variation of
anammox bacterial communities in natural ecosystems, weinvestigated the anammox bacterial dynamics in estuarial
sediment of the Mai Po Nature Reserve, where rivers bringin wastewater during the wet season in summer. The resultsof 16S rRNA and hzo genes based analyses showed obvious
and strong seasonal dynamics of anammox bacteria, controlled by seasonal anthropogenic or terrestrial inputs andregular coastal tides.

DNA extraction, PCR amplification and clone library construction
Total genomic DNA of each sediment sample was extractedusing the SoilMaster DNA Extraction kit (Epicentre Biotechnologies, Madison, USA) according to the manufacturer’s
instructions, and the DNA concentration of each sample wasmeasured by a Biophotometer (Eppendoff, Hamburg, Germany).
PCR amplification of the 16S rRNA gene was carried out using
two primer sets: Brod541F (5'-GAGCACGTAGGTGGGTTTGT-3')(29)-Amx820R (5'-AAAACCCCTCTACTTAGTGCCC-3') (36); andAMX368F (5'-TTCGCAATGCCCGAAAGG-3')-Amx820R (5'-AA
AACCCCTCTACTTAGTGCCC-3') (36). For amplification of thehzo gene, the primer set HZOF1 (5'-GTGCATGGTCAATTGA
AAG-3)-HZOR1 (5'-CAACCTCTTCWGCAGGTGCATG-3') wasused (23). The reaction conditions were described elsewhere (23).
PCR products were checked by electrophoresis on 1% agarosegels and subsequent staining with ethidium bromide (0.5 µg mL−1),
purified using the Gel Advance-Gel Extraction System (Viogeme,
Taipei, Taiwan), and used to construct the 16S rRNA and hzo clone
libraries with the pMD-18 T-vector (Takara, Otsu, Japan).

Materials and Methods
Site description, sampling and chemical analyses
The Mai Po Nature Reserve of Hong Kong (22°29'N to 22°31'N
and 113°59'E to 114°03'E), an intertidal estuary of the Pearl River
Delta, China, consists of intertidal mudflats, mangroves, traditionally operated shrimp ponds, fishponds, reedbeds and drainage
channels (28). In the Nature Reserve, the Shenzhen River andinland San Pui River especially the former, bring large quantities ofdomestic sewage and industrial wastewater from adjacent areas
where manufacturing activities and residential development haveintensified in recent years (21, 28). Furthermore, the Reserve isdriven by two seasonal monsoons; the northeast monsoon prevails
in winter and the southwest monsoon in summer (4, 42). According
to a long-term ecological monitoring project, the Mai Po Nature
Reserve varies greatly in physicochemical characteristics between
summer and winter, and slightly spring and autumn (unpublisheddata, Ecological Monitoring Programme for the Mai Po and Inner
Deep Bay Ramsar Site from 2003 to 2008). Thus, five samplingsites were selected (Fig. 1) and triplicate sediment samples werecollected during summer (May) and winter (November) in 2008.
Each sample was labeled according to site (A to E) and season (5 or11). The temperature, redox potential and pH of the sediment
samples were measured in situ using an IQ180G Bluetooth MultiParameter System (Hach Company, Loveland, USA). The salinityof pore water was measured using a YSI 556 Multiprobe System(YSI, Yellow Springs, USA). The total organic carbon of sedimentand concentration of NH4+-N, NO3−-N, and NO2−-N in pore water

Fig. 1.

Sequencing and phylogenetic analysis
Clones with the correctly inserted DNA fragment in each librarywere checked by PCR with M13 primers, and randomly selected forsequencing. Sequencing was performed with the Big Dye Terminate kit (Applied Biosystems, Foster City, USA) and an ABI Prism
3730 DNA analyzer. DNA sequences were examined and editedusing MEGA 4.0 software (44) and then checked for chimera using
the Check Chimera program of the Ribosomal Database Project(5) or manually. For the 16S rRNA gene, DNA sequences weremanually compiled and aligned using Clustal W (46). For the hzo
gene, nucleic acid sequences were translated into amino acids andthe resulting amino acids sequences were aligned using Clustal
W. Phylogenetic trees were constructed by MEGA 4.0 with theneighbor-joining method, and bootstrap re-sampling with 1,000

A map showing the sampling sites at Mai Po Nature Reserve of Hong Kong.

41

Seasonal Variation of Anammox Bacteria

17

replicates was performed to estimate the confidence values of thetree nodes.

nity structures and environmental variables were determined using
the Microsoft Excel program.

Quantitative PCR
The copy numbers of the hzo gene in all samples were determined in triplicate using an ABI 7000 Sequence detection system(Applied Biosystems). The quantification was based on the fluorescent dye SYBR-Green I. Each reaction was performed in a 25 µL
volume containing 1 µL of DNA template (30–50 ng µL−1), 0.5 µL
BSA (0.1%), 0.5 µL of each primer (20 µM, HZOF1 and HZOR1)
and 12.5 µL of Power SYBR Green PCR Master Mix (Applied
Biosystems). The PCR profile was 2 min at 50°C and 10 min at
95°C, followed by a total of 45 cycles of 1 min at 95°C, 1 min at
53°C, and 1.5 min at 72°C. A standard plasmid carrying hzo was
generated by amplifying the gene from extracted DNA of site A andcloning into the pMD 18 T-Vector (Takara). The plasmid DNA
concentration was determined and the copy number of hzo was
calculated directly from the concentration of the extracted plasmidDNA. Ten-fold serial dilutions of a known copy number of the plasmid DNA were subjected to a quantitative PCR assay in triplicate to
generate an external standard curve. The amplification efficiency
ranged from 0.90 to 0.95 and the correlation coefficient (R2) of thestandard curve was 0.991.

Nucleotide sequence accession numbers
The GenBank accession numbers for the 16S rRNA genesequences reported here are GQ427230 to GQ427485 andHM209472 to HM209609. The accession numbers for the hzo genesequences are GQ427486 to GQ427673 and HM209610 toHM209725.

Results
Seasonal variation in environmental variables
Table 1 shows the main physicochemical attributes ofthe sediment samples and pore water. Many environmental
parameters showed strong seasonal variation, for example,
pH, the pore water NH4+ concentration, salinity and TOC
were higher in winter while temperature, and total NH4+,
total Kjeldahl nitrogen (TKN), Cu and Hg concentrations
were lower in winter. However, within the same season,
five sampling sites did not show strong spatial variation
although some environmental parameters exhibited significant differences among the five sites (Table 1).

Statistical analysis
Operational taxonomic units (OTUs) for the community analysis
were defined by a 3% cut-off in the 16S rRNA gene nucleotide
sequences and a 5% cut-off in the hzo genes deduced amino acidsequences, as determined using the furthest neighbor algorithm inthe DOTUR program (35). DOTUR was also used to analyze
diversity including Shannon and Simpson indices for each clone
library. To examine the seasonal and geographic distribution of
anammox bacteria in estuary sediments of the Mai Po Nature
Reserve, 16S rRNA and hzo gene sequences were analyzed withthe online software UniFrac (http://bmf2.colorado.edu/unifrac/index.
psp) using the principal coordinates analysis (PCoA) as suggested
previously (25). Pearson moment correlations for bacterial commuTable 1.
Sampling Season
site
A
B
C
D
E

May
Nov.
May
Nov.
May
Nov.
May
Nov.
May
Nov.

pH

Community structures of anammox bacteria within two
seasons
From the 16S rRNA gene clone libraries, 1 to 7 OTUs
were obtained from each sediment sample, with site E in
May (E5) showed the highest number. The Shannon index(0.00–1.19) and Chaol index (1.0–8.5), calculated by the
DOTUR program, also showed similar variation (Table 2).
However, 343 hzo sequences from 10 libraries yielded
52 unique OTUs, with the highest diversity again at E5

Environmental characteristic of research sediment samples and pore water

T-N
T-P
As
Cd
Cu
Hg
Pb
TOC
T Redox NH4+* NOX* Salinity* T-NH4+ TKNS2−(°C) (mV) (µM) (µM) (‰) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1) (mg kg−1)

6.24 28.9 −59.2 342.5
7.36 22.8 −96.3 345.2
7.13 30.1 −160.4 20.0
7.41 22.2 −90.0 603.9
6.74 29.5 −89.6 43.6
7.55 22.4 −126.0 117.1
7.16 29.3 −116.0 71.0
7.52 22.6 −59.0 683.3
7.18 31.2 −154.0 101.6
7.49 22.6 −189.0 460.4

2.4
1.1
1.1
0.5
1.5
0.9
2.1
2.7
9.3
0.6

5.2
13.8
6.9
15.5
7.0
25.7
3.5
20.4
6.0
26.3

170.1 1160.3 1170.0 1128.0 53.0
25.1 997.0 1006.0 956.0 552.0
172.0 575.9 583.0 1151.0 336.0
37.1 649.0 857.0 1360.0 400.0
148.7 917.8 927.0 1193.0 350.0
19.6 592.0 600.0 653.0 341.0
162.5 872.9 881.0 1608.0 365.0
31.7 605.0 614.0 836.0 771.0
154.2 847.2 864.0 1657.0 101.0
13.3 711.0 718.0 399.0 132.0

13.7
17.9
10.7
13.5
10.8
13.8
11.7
13.6
9.2
10.0

27.0
17.5
21.0
18.8
16.0
13.9
31.0
18.2
16.0
17.0

0.45
0.60
0.53
0.35
0.23
0.33
0.45
0.55
0.25
0.20

103.7
98.3
100.3
84.0
61.8
55.7
124.7
104.7
103.7
44.7

0.22
0.20
0.23
0.15
0.12
0.09
0.24
0.17
0.21
0.15

72.5
66.0
85.1
75.0
49.8
40.0
70.2
67.3
72.0
43.7

* The concentrations of pore water for each sediment sample.

Table 2.
Sampling
Season
site
A
B
C
D
E

May
Nov.
May
Nov.
May
Nov.
May
Nov.
May
Nov.

Diversity of anammox bacteria in sediment samples

Clone Number

OTUs

ShannonChaol

Coverage

16S rRNAhzo

16S rRNAhzo

16S rRNAhzo

16S rRNAhzo

16S rRNA

hzo

45
33
31
41
34
32
59
34
38
47

40
28
57
26
52
20
30
23
37
30

4
3
4
3
4
1
5
3
7
4

8
6
3
3
5
4
4
5
8
6

0.73
0.50
1.12
0.97
1.04
0.00
1.19
0.69
1.14
0.85

1.37
1.40
0.43
0.78
1.38
1.19
0.77
1.12
1.00
1.47

5
3
4
3
5
1
5
3
8.5
4

14
6
3
3
5
4
4
8
23
6

0.96
0.97
0.97
1.00
0.97
1.00
1.00
0.97
0.92
1.00

0.90
0.96
0.96
1.00
0.98
0.95
0.97
0.87
0.84
0.97

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Fig. 2. Neighbor-joining phylogenetic tree of anammox bacterial 16S
rRNA gene sequences. Numbers in parentheses refer to how manyclones retrieved were assigned to an OTU. The numbers at the nodes
are percentages indicating the level of bootstrap support based on 1,000
resampled data sets (only values greater than 50% are shown). Branch
lengths correspond to sequence differences as indicated by the scalebar.

Fig. 3. Neighbor-joining phylogenetic tree of hzo gene sequences.
Numbers in parentheses refer to how many hzo gene clones retrieved
were assigned to an OTU. The numbers at the nodes are percentages
indicating the levels of bootstrap support based on 1,000 resampled data
sets (only values greater than 50% are shown). Branch lengths correspond to sequence differences as indicated by the scale bar.

(Table 2). The coverage ranged from 0.92 to 1.0 (16S
rRNA) and 0.84 to 1.0 (hzo), indicating that all clone
libraries covered the majority of the natural diversity of the
16S rRNA and hzo genes targeted by the selected primer
sets, as confirmed with the asymptotic rarefaction curves(Fig. S1). Interestingly, diversity among both the 16S rRNA
and hzo genes was higher in the samples collected in summer
than winter though exceptions occurred for hzo at sites B
and D, indicating a strong seasonal variation of anammox
bacteria diversity.
The phylogeny indicated that 394 of the 16S rRNA genesequences grouped into six clusters, affiliated with the
Kuenenia and Scalindua genera of anammox bacteria (Fig.
2). The ‘Kuenenia’ cluster consisting of sequences fromsites B, D and E in May (B5, D5 and E5) was affiliatedwith sequences retrieved from Cape Fear River estuary sediment and ‘Candidatus K. stuttgartiensis’. However, the otherfive clusters were distributed in the ‘Scalindua’ genus. The“Scalindua wagneri cluster”, closely related to ‘Candidatus
S. wagneri’ and sequences recovered from an intertidal sandbank, Cape Fear River estuary sediment and Ago Bay
sediment, was supported by sequences recovered from all
samples except A5, C5 and E5. The “Scalindua southchina(zhenghea) I cluster” containing a single sequence retrieved
from A5 was affiliated with sequences from sediment ofSouth China Sea and Ryukyu Trench. The “Scalindua sp.
cluster” was closely related to ‘Candidatus Scalindua’enrichment and sequences recovered from Namibian OMZand Xinyi River sediment. The “Scalindua arabica cluster”
containing sequences recovered from A5 and C5 wasaffiliated with the newly described anammox bacterial
species ‘Candidatus S. arabica’ (49), while the “Scalindua
brodae/sorokinii cluster” was composed of sequences
recovered from all samples except A5, B5, C11 and D11.
C5 further yielded a sequence which did not affiliate withthe phylogenetic clusters, but is close to the ‘Scalindua’than other genera of anammox bacteria (Fig. 2).
For the phylogeny of the hzo gene, sequences distributed
into two major groups, Cluster 1a and Cluster 1c (Fig. 3).
Within each group, 4 and 3 sub-clusters were evident,
namely Cluster 1a-1 to Cluster 1a-4, and Cluster 1c-1 to
Cluster 1c-3, respectively. One sequence in Cluster 1a-1
recovered from E5 was closely related to the ‘Candidatus
43

Seasonal Variation of Anammox Bacteria

19

Anammoxoglobus’ enrichment culture CAQ57911, grouping
with sequences of the HZO proteins BAF36963 andBAF36964 from planctomycete KSU-1, and ABX90016,
ABX90017, ABX90018, ACF5874, ACF5875 and ACF5876
from ‘Candidatus J. asiatica’ enrichment reactors (Fig. 3);
while sequences in cluster 1a-2, cluster 1a-3 and cluster 1a-4
constituted novel sister clades with the sequences of cluster
1a-1, representing niche specific groups in estuary sedimentof the Mai Po Nature Reserve. More interestingly, cluster 1a3 only consisted of sequences from C11 and D11, indicatinga seasonal specific group for hzo genes (Fig. 3). Withincluster 1c, sequences in cluster 1c-1 were affiliated withthose of the HZO proteins CAQ57913 and CAQ57914 of
uncultured planctomycetes and CAQ57909 from a ‘Candidatus Scalindua’ enrichment culture, and cluster 1c-2 and cluster 1c-3 also constituted novel sister clades with cluster 1c-1,
again indicating the site-specificity of HZO sequences in Mai
Po. Meanwhile, a branch in cluster 1c-3 further showed aseasonal distribution, being composed of sequences fromsites D and E in November only (Fig. 3).

to ‘Anammoxoglobus’, ‘Jettenia’ and planctomycetes KSU1, was the dominant hzo group in most sediment samples,
representing 28.6% to 100%; while cluster 1-c, affiliatedwith ‘Scalindua’, was the second group except at site A in
winter. The abundance of anammox bacteria was estimatedthrough a quantitative analysis of the hzo genes. Results
showed that abundance ranged from (10.2±1.9)×104 (A5) to(39.8±9.1)×104 (E5) copies per gram of sediment for samples
collected in May, and from (2.9±0.6)×104 (A11) to(18.9±2.5)×104 (E11) in November (Fig. 4). The resultclearly showed a higher abundance of the hzo gene in May
than November, indicating strong seasonal population
dynamics in mudflat sediment of the Mai Po Nature Reserve.
Classification of anammox bacteria
To better understand the seasonal and spatial distributionof anammox bacteria in sediment in the Mai Po Nature
Reserve, PCoA was carried out by Unifrac. Results showedthat the 16S rRNA genes had strong seasonal variation,with all the samples collected in winter grouped together,sharing similar community structures. For summer samples,A5 and C5 showed a similar 16S rRNA gene structure while
B5, D5 and E5 shared a similar community structure (Fig.
5a). However, the hzo genes did not show a strong seasonal
distribution though sites A and D in summer had a similar
hzo gene composition to the winter samples (Fig. 5b).

Seasonal dynamics of the community composition andpopulation of anammox bacteria
According to the phylogeny of anammox bacterial 16S
rRNA genes, two different genera were confirmed. The proportions of the two genera showed that ‘Scalindua’ was the
only group detected in most clone libraries, except in sediment collected from B, D and E during the summer, where‘Kuenenia’ represent 77.4% (B5), 57.6% (D5), and 7.9%
(E5), respectively (Fig. 4). However, hzo cluster 1-a, related

Correlations of anammox bacteria with environmental
factors
The diversity of the 16S rRNA gene was significantly
correlated with temperature, the concentration of NOx (NO2−+NO3−) in pore water, and total NH4+ and total phosphorus
concentrations, and negatively correlated with salinity. However, hzo diversity was significant correlated with the concentration of NOx (NO2−+NO3−) in pore water, and TKN and
Pb levels. In addition, hzo gene abundance was correlated
positively with temperature and the concentration of NOx(NO2−+NO3−) in pore water and negatively with sediment
TOC (Table 3).
Discussion
Occurrence and seasonal variability of anammox bacteria
In the present study, we investigated the dynamics of the
anammox bacterial community based on the 16S rRNA andhzo genes. Both genes had higher OUT numbers in summer
than winter with some exceptions for hzo. The environmental
classification also supported that the 16S rRNA and hzo
genes shared a similar community composition in sediment
samples collected in winter. Furthermore, using 16S rRNA
and hzo as biomarkers provided some unexpected results
regarding the variation in anammox bacteria in the Mai
Po Nature Reserve within different seasons. From the 16S
rRNA gene phylogeny, two major groups of anammox
bacteria were found, with ‘Scalindua’-like anammox bacteria
detected in all samples collected in summer and winter,making them the dominant groups as in previous reports(39, 49), ‘Kuenenia’-like 16S rRNA gene sequences weredetected in summer not winter, representing season-specificanammox bacteria. However, two major hzo gene cladesFig. 4. The summer to winter community composition and population dynamics of anammox bacteria in estuarial mudflat sediment. Error
bars represent standard deviations of triplicate experiments.

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LI et al.

Fig. 5.
data.

PCoA based on the UniFrac metric of 16S rRNA (a) and hzo (b) sequence diversity of anammox bacteria, including sequence abundance

Table 3.

Correlation analyses of environmental parameters and anammox bacteria diversity and abundancePearson moment correlation*

Parameter

pH
Temp.
Redox
NH4+
NOX
NH4+/NOx
Salinity
NH4+
TKN
T-N
T-P
S2−
TOC
As
Cd
Cu
Hg
Pb

OTUs
16S rRNA
−0.33
0.75
−0.30
−0.31
0.76
−0.29
−0.66
0.65
0.35
0.31
0.66
−0.47
−0.62
0.30
−0.25
0.44
0.62
0.42

Shannon Index
hzo
−0.45
0.27
0.06
0.04
0.61
−0.25
−0.19
0.19
0.69
0.58
0.04
−0.49
−0.05
0.00
−0.18
0.09
0.24
−0.06

16S rRNA
−0.30
0.66
−0.20
−0.20
0.33
−0.04
−0.67
0.65
0.12
0.17
0.66
−0.23
−0.62
0.42
−0.15
0.40
0.57
0.56

hzo
−0.16
−0.33
0.20
0.25
−0.08
0.06
0.37
−0.38
0.49
0.40
−0.53
−0.12
0.27
−0.32
−0.29
−0.50
−0.43
−0.69

Chao index
16S rRNA
−0.45
0.78
−0.21
−0.34
0.82
−0.35
−0.68
0.69
0.44
0.40
0.65
−0.53
−0.61
0.21
−0.33
0.37
0.53
0.35

Abundance
hzo
−0.33
0.45
−0.02
−0.07
0.91
−0.31
−0.32
0.34
0.42
0.36
0.36
−0.47
−0.28
−0.05
−0.22
0.28
0.32
0.19

hzo
−0.22
0.64
−0.39
−0.56
0.68
−0.26
−0.42
0.51
−0.10
−0.05
0.61
−0.49
−0.64
−0.21
−0.51
0.04
0.05
0.20

* Pearson moment correlation (r) was determined using the following equation:n(ΣXY) – (ΣX)(ΣY)---------------------------------------------------------------------------------r= [ n Σ X 2 – ( Σ X ) 2 ] [ n Σ Y 2 – ( Σ Y ) 2 ] . Boldface denotes a P value of <0.05, which is typically regarded as significant, as determined by Excel
function TDIST from the t value given by the following equation:n–2
t=× ----------------2 . The number of samples is given by n.
(1 – r )were also detected, one related to the ‘Scalindua’ genus
and the other affiliated with hzo genes recovered from a‘Candidatus Anammoxoglobus’ enrichment culture, planctomycetes KSU-1, and a ‘Candidatus J. asiatica’ enrichment
culture. Although sequences in the two major hzo geneclades could be found in summer and winter sediment sam-ples, season-specific clusters could still be observed (cluster
1a-3 and branch in cluster 1c-3). In addition, the quantitative
analysis of the hzo gene copy number within the two seasonsalso clearly indicated that anammox bacteria have strong
seasonal variation in not only diversity but also abundance.
45

Seasonal Variation of Anammox Bacteria

21

abundance and the total organic carbon (TOC) concentration
might also indicate the un-favorable effect of organic matteron the growth of anammox bacteria though organic mattercannot be excluded as either a carbon or energy source foranammox bacteria in marine environments (10).
In conclusion, anammox bacterial community structure
and abundance in estuary sediment of the Mai Po Nature
Reserve showed strong seasonal dynamics, which might beaffected by anthropogenic and terrestrial inputs withindifferent seasons, and also by mangrove coverage and otherenvironmental factors.

Environmental factors influence the seasonal dynamics ofanammox bacteria
To further understand the seasonal variation in the bacterial community structure, the influences of sampling locationand environmental factors should be considered. According
to the physicochemical data from sediment samples, May
samples had higher values for temperature, NOx in porewater, total NH4+, TKN, TN, TP and several metals in
sediment, but lower values for redox potential, reduced
sulfide (S2−) and total organic carbon (TOC) compared toNovember samples, indicating strong anthropogenic andterrestrial input during the summer season. The quite low
salinity in May also provides evidence of a large quantity
freshwater during the summer, which is consistent withprevious study in the area (28). The strong anthropogenic
and terrestrial inputs, mainly through the Shenzhen River,
would certainly bring a lot of freshwater anammox bacteria,such as ‘Kuenenia’, into the Mai Po Nature Reserve. This
speculation is reflected by the variation in bacterial community structure with numerous ‘Kuenenia’ anammox bacteria
detected from May except at sites A and C. On the other
hand, the northeast monsoon prevails and the South China
Coastal Current dominates the coastal water of the Nature
Reserve during winter (4, 42), and thus marine anammox
bacteria, usually ‘Scalindua’ (39, 49), become the dominantgroup in this area. Recently, reports also found ‘Brocadia’and ‘Kuenenia’ to be present in marine ecosystems (1, 6,27); however, these ecosystems are strongly affected byanthropogenic or terrestrial influences, such as estuaries andinternal bays. Furthermore, the highest hzo abundance of site
E in summer further indicates the Shenzhen River to be thesource of ‘Candidatus K. stuttgartiensis’. So, the ‘Kuenenia’
anammox bacteria in summer but not winter in estuary
sediment of the Mai Po Reserve may be possibly fromthe strong anthropogenic or terrestrial inputs, which mostly
come from the Shenzhen River. These freshwater or terrestrial bacteria together with anammox bacteria increase thediversity of anammox bacteria in summer, with strong
positive correlations among the diversity and abundance ofanammox bacteria and the concentration of NOx (NO2−+NO3−) in pore water, total NH4+ content and total phosphorus level of sediment, and strong negative correlations withsalinity. The absence of ‘Kuenenia’ anammox bacteria at siteA, close to the Shenzhen River, might be due to mangrove
plants that have a strong influence on the distribution of
anammox bacteria through interaction for available nitrogen.
In addition, its significant positive relationship with bacterial
community and abundance further indicates that temperature
is an important environmental factor influencing the seasonalvariation of anammox bacteria in Mai Po. Previous studies
have found that ‘Scalindua’ anammox bacteria are distributed in low-temperature environments in sea water columns,
surface and subsurface of ocean sediment (8, 14, 49),
while quite different in high-temperature environments,
such as hydrothermal vents (3) and oil reservoirs (22),indicating ‘Scalindua’ species prefer low-temperature environments. Our results are consistent with these findings, with
‘Scalindua’ bacteria dominating in winter. Last but notleast, the significantly negative correlation between hzo geneAcknowledgements
This research was supported in part by grants from the Agriculture, Fisheries and Conservation Department of The Hong Kong
SAR Government (J-DG), a PhD studentship (ML) and the National
Natural Science Foundation of China (3080032), Guangdong Province Natural Science Foundation 450 (84510301001692) (Y-GH).
We would like to thank Jessie Lai and Dr. Zhen-Ye Zhao forlaboratory assistance, technical support and chemical analyses
during this investigation at The University of Hong Kong.
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32. Rysgaard, S., and R.N. Glud. 2004. Anaerobic N-2 production in
Arctic sea ice. Limnol. Oceanogr. 49:86–94.

47

MOST CITED REVIEW PAPER IN
THIS TEN YEARS [2008-2017] (106 citations)

Microbes Environ. Vol. 24, No. 3, 205–216, 2009http://wwwsoc.nii.ac.jp/jsme2/ doi:10.1264/jsme2.ME09151S

Minireview
Cultivation of Uncultured Chloroflexi Subphyla: Significance andEcophysiology of Formerly Uncultured Chloroflexi ‘Subphylum I’
with Natural and Biotechnological Relevance
TAKESHI YAMADA1, and YUJI SEKIGUCHI2*
1Department of Ecological Engineering, Toyohashi University of Technology, 1–1 Hibarigaoka, Tempaku, Toyohashi

441–8580, Japan; and 2Institute for Biological Resources and Functions, National Institute of Advanced Industrial
Science and Technology (AIST), 1–1–1 Higashi, Tsukuba 305–8566, Japan（Received May 31, 2009—Accepted July 30, 2009—Published online August 20, 2009）

Cultivation-independent molecular surveys have shown members of the bacterial phylum Chloroflexi to be ubiquitous in various natural and artificial ecosystems. Among the subphylum-level taxa of the Chloroflexi known to date,
the formerly uncultured ‘subphylum I’ had well been recognized as a typical group that contains a number of environmental gene clones with no culture representatives. In order to reveal their ecophysiology, attempts were made over the
past decade to domesticate them into laboratory cultures, and significant advances have been made in cultivatingstrains belonging to the group. The microorganisms characterized so far include seven species in six genera, i.e.,
Anaerolinea, Levilinea, Leptolinea, Bellilinea, Longilinea, and Caldilinea, and were proposed to represent two classes,
Anaerolineae and Caldilineae, providing solid insights into the phenotypic and genetic properties common to thegroup. Another subphylum-level uncultured group of the Chloroflexi, i.e., the class Ktedonobacteria, has also been
represented recently by a cultured strain. In addition to the results from these tangible cultures, data obtained fromfunctional analyses of uncultured Chloroflexi populations by assessing substrate uptake patterns are accumulating at anencouraging rate. In this review, recent findings on the ecological significance and possible ecophysiological roles of‘Chloroflexi subphylum I’ are discussed based on findings from both the characteristics of the cultured Chloroflexi andmolecular-based analyses.
Key words: Chloroflexi, Anaerolineae, Caldilineae, uncultured microorganism

such microbial groups have recently been cultured and characterized.
The phylum Chloroflexi, formerly known as ‘Green nonsulfur bacteria’, has been recognized as a typical ubiquitousbacterial taxon containing a number of diverse environmental 16S rRNA gene clones with a limited number of cultured
representatives (33, 63). Formerly, the phylum had been
divided into four major subphylum (class)-level taxa on thebasis of 16S rRNA/rRNA gene sequences, i.e. ‘subphyla I,
II, III, and IV (Fig. 1) (33), but the class Thermomicrobia has
been reclassified into the phylum as an additional subphylum(34). The phylogenetic depth of the phylum is comparablewith that of the phylum Proteobacteria (20). In addition to
the major five subphyla, other uncultured lineages at thesubphylum level were also identified (14, 63). Among thesubphyla, ‘subphylum III’, known as the class Chloroflexi,
has been best represented by cultured organisms belonging
to the genera Chloroflexus, Oscillochloris, Chloronema,
Heliothrix, Herpetosiphon, and Roseiflexus. These organisms
mostly possess filamentous morphotypes, and show photoheterotrophic and/or chemolithoheterotrophic growth undermesophilic or moderately thermophilic conditions. The class
Thermomicrobia also involves cultured organisms belonging

Introduction
Cultivation-independent molecular methods have provided new tools to study the microbial world, enabling us tounderstand the actual microbial diversity that traditional cultivation-based methods have never unveiled (32). With theapplication of these techniques, it has become evident thatthe majority of microorganisms in the environment areuncultured, and that the ecophysiology of these organisms
remains largely unknown. The finding of yet-to-be cultured
microorganisms have driven renewed efforts in the cultivation and isolation of such microbes, because the domestication (cultivation) of microorganisms into laboratory cultures
is still the best means to gain solid insights into metabolic
ability and detailed genomic traits of individual microbes. In
the past few years, new microorganisms have been successfully isolated that belong to uncultured taxa with environmental and biotechnological relevance, and the informationof their physiology in conjugation with phylogeny has been
updated (63). Chloroflexi subphyla are also examples where* Corresponding author. E-mail: y.sekiguchi@aist.go.jp; Tel: +81–
29–861–7866; Fax: +81–29–861–6400.

48

SpecialIssue

Special issue: Significance of culturing microbes in the omics era

YAMADA and SEKIGUCHISpecial

Issue

206

Fig. 1. Evolutionary distance dendrogram of the bacterial phylum Chloroflexi derived from a comparative analyses of 16S rRNA gene sequences,
showing the phylogenetic relationship of the subphyla (class)-level taxa of the phylum. The sequences were aligned, and the phylogenetic tree wasconstructed by the neighbor-joining (NJ) method with the ARB software package (52). The fidelity of the topology of the NJ tree was also confirmed by bootstrap resampling (based on 1,000 replicates) with the neighbor-joining (PAUP* 4.0 program package) and maximum likelihood(TREEFINDER program package) methods. Nodes highly supported with bootstrap values higher than 85% by both analyses are marked as circles(filled circles, >95%; open circles, 95–85%). Nodes without symbols were not highly resolved (<85%) as specific groups in either analysis. The bar
represents 10 nucleotide substitutions per 100 nucleotides.

been isolated and characterized that belongs to anotheruncultured lineage at the subphylum level in the Chloroflexi
phylum, representing a new class, Ktedonobacteria.
In this review, recent findings on the ecological significance and possible ecophysiological roles of the formerly
uncultured Chloroflexi subphyla are discussed based on findings from rRNA-based community analyses for the environment, as well as from the characteristics of recently cultured
Chloroflexi. In addition, recent studies on the ecophysiologyof these organisms in engineered systems through theevaluation of their substrate uptake pattern are described.
Special emphasis is placed on the ecology and function of
Chloroflexi ‘subphylum I’ members with natural and biotechnological relevance, particularly those found in waste/
wastewater treatment systems.

to the genera Thermomicrobium and Sphaerobacter (34),which are rod-shaped, moderately thermophilic or hyperthermophilic, chemoheterotrophic aerobes. In addition, Themobaculum terrenum, a moderately thermophilic chemolithoheterotrophic aerobe, represents a distinct lineage in thephylum, forming a new class-level taxon (9). The other threemajor subphyla (I, II, and IV) had been comprised solely of avariety of environmental clones except for purified, coccoidshaped organisms, ‘Dehalococcoides ethenogenes’ andrelated strains (e.g., (1, 53)) able to reductively dechlorinate
chlorinated compounds, being classified into ‘subphylum II’(class ‘Dehalococcoidetes’) (31, 33). ‘Subphylum I’ contains
the most diverse environmental clones among the four subphyla of the Chloroflexi; in the current 16S rRNA Ribosome
Database Project (RDP) database (release 10.11), ‘subphylum I’ phylotypes are most frequently represented
among the subphyla known to date and make up approximately >70% (>5,000 entries) of all the deposited sequences
relative to the Chloroflexi phylum. Although the past two
decades have seen a number of papers reporting the detectionof ‘Chloroflexi subphylum I’ in various ecosystems (seebelow), there had long been no description of cultivablemicrobes. However, in recent years, aerobic and anaerobic
strains have successfully been cultivated and characterizedthat belong to ‘subphylum I’. The microorganisms characterized so far are seven species in six genera in total, andwere proposed to represent two distinct classes Anaerolineae
and Caldilineae. In addition, an aerobic strain has recently

Ecological significance of Chloroflexi subphyla
In 1998, Hugenholtz et al. analyzed 16S rRNA genesequences of 5,224 cultured bacteria and 2,918 environmental gene clones retrieved from a wide range of natural andartificial ecosystems, revealing ubiquitous bacterial groups
to be those of the phyla Proteobacteria, Actinobacteria,
Firmicutes, Bacteroidetes, Planctomycetes, Acidobacteria,
Verrucomicrobia, and Chloroflexi, and the candidate phylum
OP11 (33). In the past decade, a flood of papers reporting themolecular detection of Chloroflexi phylotypes in a variety ofenvironments have been published, further supporting their49

Microorganisms Affiliated with the Classes Anaerolineae and Caldilineae

Relative abundance of Chloroflexi phylotypes in natural and artificial ecosystems as determined by 16S rRNA gene-based clone library
analyses

SubphylaDeepseafloor

Sea Lake○a○● ● - ●●

○

—

—

—

—

Subphylum IV

Subphylum I(Anaerolineae andCaldilineae)
Subphylum II(‘Dehalococcoidetes’)
Subphylum III(Chloroflexi)

Artificial habitats

Soil

River

Wastewater treatment

Microbial
Hot Freshwater Ocean Hypersaline
Lagoon Mine fuel cellspringlake
drainage
Agricultural Geothermal Meadow
Aerobic Anaerobic
system
●●●

○

○

○-●

○

—

○ - ●●●●○ - ●●●○●○ - ●●

●●

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

—

○-●

—

—

○ - ●●●

○

—

—

●

—

○ - ●●● —

—

—

—

—

—

—

●

○

—

—

—

—

—

—

New subphyla

○

—

—

○

—

—

●

—

—

—

—

—

—

—

References

59

54 82

46

5

78

22

48

85, 99

29

50

97

79

39, 64——42, 45, 3, 24, 58,
56
64, 90a Frequency of clones assigned to a subphylum of Chloroflexi as a percentage of the total number of bacterial sequencs analyzed:—, 0%; ○, 0.1–5%; ●, 5–15%, ●●, 15–25%, ●●●, >25%.

phylotypes found were classified into ‘subphylum I’ as wellas other formerly and currently uncultured, previously unrecognized groups at the subphylum level, including theclass Ktedonobacteria (see below). These findings suggest awide range of temperature (0 to 65°C) and salinity for thehabitats of Chloroflexi.
Soil is believed to be one of the most complex environments for microbial life (15). Concerning Chloroflexi phylotypes in soil environments, a recent review by Janssen
showed the Chloroflexi to be one of the most dominant phyla
in soils: 32 previously published clone libraries for different
soil samples were re-evaluated and the mean contribution of
the Chloroflexi phylum to soil bacterial communities wasfound to be 3% (range: 0–16%) (40). Similarly, pyrosequencing of rRNA gene clone libraries (ca. 150,000 clones
in total) for different soils further supported the significanceand genetic diversity of the Chloroflexi population (22, 65).
Concerning the Chloroflexi phylum in oceanic and freshwater bacterioplanktons, environmental clones belonging to‘subphylum IV’ (formerly known as cluster SAR202) were
found in the Sargasso sea (4% of bacterial clones) (29), andsimilar phylotypes were detected in different ocean samples(6). Freshwater bacterioplankton also often contain the
Chloroflexi phylum (average: 1%, range: 0–4%), most ofthem affiliated with ‘subphyla I and IV’ (85, 99).
Chloroflexi phylotypes have also been found in abundancein artificial and engineered ecosystems, such as lagoons (e.g.,(97)), mine drainage (e.g., (73, 79)), anaerobic sludges for
waste and wastewater treatment (e.g., (2, 12, 17, 19, 25, 30,
43, 51, 57, 58, 64, 66, 71, 74, 76, 90, 94)), activated sludge
systems (e.g., (3, 8, 13, 25, 42, 45, 47, 55, 56, 60, 62, 77, 80,98)), and microbial fuel cell systems (39, 61). Among theseecosystems, waste/wastewater treatment facilities are perhaps the best-recognized habitat where Chloroflexi phylotypes reside in abundance. For example, Rivière et al. evaluated bacterial and archaeal community structures of sevenmesophilic (29–37°C), anaerobic (methanogenic) digesters
decomposing municipal sewage sludge and found the
Chloroflexi to be the most abundant bacterial phylum (average: 32% of all the bacterial clones analyzed, range: 15–45%)

ubiquity in natural and engineered environments (Table 1).
For example, Chloroflexi phylotypes were found as the mostnumerous bacterial group (nearly 80% of all bacterial geneclones analyzed) in an organic-rich deep subseafloor biosphere (38), where these phylotypes mainly fall into ‘subphyla I, II and IV’. Similarly, Chloroflexi are often one of themost dominating bacterial phyla in various deep subseafloor
sediments (e.g., (7), see also a recent review by Fry et al.
(27)), some of which were associated with methane hydratebearing sites (38, 59). Other natural environments where
Chloroflexi phylotypes were detected in abundance are hotsprings (e.g., (4, 48)), hypersaline microbial mats (e.g., (50)),
soil (e.g., agricultural soils (5, 75), geothermal soils (78), andlow-temperature meadow soils (14)), sediment (e.g., sea andlake (river) sediment (18, 35, 46, 54, 82, 89), and hydrothermally active sediment (79, 83)), chlorinated-solvent-contaminated aquifer sites (21, 26, 88)), oceans (e.g., (6, 29, 63,87)), and freshwater (e.g., (85, 99)).
Recently, Lau et al. analyzed the bacterial communities of
microbial mats from five hot springs (temperature: 60–65°C), indicating that 10–15% of the phylotypes detected
were related with the Chloroflexi phylum (48). These
Chloroflexi phylotypes fall into ‘subphyla I and III’. Similarly, Chloroflexi phylotypes were found in a hypersaline(salinity: 8%) microbial mat as the majority of the mat constituents (21–39% of the bacterial rRNA clones analyzed
were those of the Chloroflexi phylum) (50). These Chloroflexi
phylotypes, again, fall into the ‘subphyla I and III’. In thisstudy, quantitative rRNA-targeted dot blot hybridization was
conducted with an oligonucleotide probe specific for thephylum Chloroflexi (GNSB941 probe, Fig. 2, Table 2), estimating their abundance to be 22–41% of the total rRNA. Thesemicrobial mats were fueled by sunlight, and therefore photosynthetic bacteria of the class Chloroflexi (‘subphylum III’)
were found in association with uncultured ‘subphylum I’organisms. Costello et al. determined the bacterial community of a tundra wet meadow soil, where the annual soil temperature was 0.3°C and the temperature was stable throughout the year, revealing Chloroflexi phylotypes to make up
16% of the bacterial rRNA gene clones (14). In this case, the
50

Issue

Natural habitats
Sediment

SpecialTable 1.

207

YAMADA and SEKIGUCHISpecial

Issue

208

Fig. 2. Evolutionary distance dendrogram of the class Anaerolineae derived from a comparative analyses of 16S rRNA gene sequences, showing
the phylogenetic positions of cultivated strains belonging to the class (indicated by arrow) and other related gene clones that were retrieved from avariety of environments. The sequences were aligned, and the phylogenetic tree was constructed by the NJ method with the ARB software package(52). The base tree was constructed with >1,200 nt sequences. Partial sequences of <1,200 nt (highlighted with dotted branches) were inserted
into the base tree using the parsimony insertion tool of the ARB program. 16S rRNA gene sequences of members affiliated with the phylum
Thermotogae were used as outgroups (not shown in the tree). The bar represents 10 nucleotide substitutions per 100 nucleotides. The fidelity ofthe topology of the NJ tree was also confirmed by bootstrap resampling (based on 1,000 replicates) with the neighbor-joining (PAUP* 4.0 program
package) and maximum likelihood (TREEFINDER program package) methods. Nodes highly supported with bootstrap values higher than 85% byboth analyses are marked as circles (filled circles, >95%; open circles, 95–85%). Nodes without symbols were not highly resolved (<85%) as
specific groups in either analysis. Probe specificity is shown to the right of the figure with the probe name; the bars indicate a perfect match between
the probe and target sequences.

20% of the total rRNA (12). Similarly, Narihiro et al. estimated the microbial diversity of twelve different types ofmesophilic (35–40°C), anaerobic (methanogenic) sludges
treating organic wastewaters, detecting Chloroflexi phylotypes as a predominant phylum (average: 12% of the bacterial clones analyzed, range: 0–32%) (58). The abundance of(64). All the Chloroflexi phylotypes detected were affiliatedwith ‘subphylum I’. Chouari et al. conducted quantitativerRNA-targeted dot blot hybridization with an oligonucleotide probe specific to the phylum Chloroflexi (GNSB1126
probe, Fig. 2, Table 2) for a mesophilic (33°C), anaerobic
digester for sewage sludge, estimating their abundance to be51

Microorganisms Affiliated with the Classes Anaerolineae and Caldilineae

209

Table 2. 16S rRNA-tageting oligonucleotide probes used for in situ detection of the Chloroflexi phylum and ‘subphylum I’

CFX1223
GNSB1126
CFX784
GNSB633
S-*OTU25to31-1406-a-A-18
S-*GNS-0667-a-A18
CFX197
CFX223virtually all members of the phylum
Chloroflexi
virtually all members of the phylum
Chloroflexi
members of the class Anaerolineae
members of the class Anaerolineae
Anaerolinea thermophila
uncultured phylotypes of the class
Anaerolineae
uncultured phylotypes of the class
Anaerolineae
uncultured phylotypes of the class
Anaerolineae
uncultured phylotypes of the class
Anaerolineae

Probe sequences (5'-3')Target site
(E. coli position)

LengthReferences(nt)

AAACCACACGCTCCGCT

941–957

17

28

CCATTGTAGCGTGTGTGTMG

1223–1242

20

8AACACACAGCGAGGG
ACCGGGGTCTCTAATCCCTAGCCCGCCAGTCTTGAACG

1112–1126
784–801
633–652

15
18
18

12
8
68

CCAGCTCCCATGACGTGA

1406–1423

1842

CACCCSGAATTCCACRTT

667–6841845

TCCCGGAGCGCCTGAACT

197–2141880

GGTGCTGGCTCCTCCCAG

223–24018

80Groups targeted by the probes are shown in Fig. 2.

these phylotypes varied depending on wastewater type, andall of them fell into ‘subphylum I’. Similar phylotypes (‘subphylum I’) have been frequently found in anaerobic sludgesthat had treated wastewaters containing compounds recalcitrant to biodegradation, such as phenol (11% of bacterial
clones) (24), phthalates (4–7%, (51, 90)), 4-methylbenzoate,(7%, (90)), 2,4-dinitroanisole and n-methyl-4-nitroaniline(36–42%, (3)).
Chloroflexi phylotypes are often present in activatedsludge systems; phylogenetic analysis of activated sludge
clones belonging to the Chloroflexi phylum indicated thatthey are affiliated with ‘subphyla I and III’ (8, 47). Theseclones were most abundant in submerged membrane bioreactors treating municipal wastewater (Chloroflexi phylum-specific probes, GNSB941 and CFX1223, were used for in situ
detection and the probe-reactive cells accounted for 14–26%
of the total, (56)). The phylotypes found in the systems again
fall into ‘subphyla I and III’. Nitrifying systems were also
shown to contain these Chloroflexi in abundance; Kindaichi
et al. found that phylotypes belonging to ‘subphylum I’ were
dominant (13% of bacterial clones analyzed) in nitrifying
biofilms formed in a submerged rotating disk reactor (45).
Chloroflexi cells were found in abundance in nitrifyingdenitrifying systems, in which uncultured ‘subphylum I’ cells(as detected using the probe S-*OTU25to31-1406-a-A-18,
Fig. 2) accounted for 16% of the cells (42). Another exampleof these engineered ecosystems is the microbial fuel cell.
The microbial fuel cell is a bio-electrochemical system thatgenerates electric power from organic matter, in which
Chloroflexi phylotypes are often found. For example, aphylotype affiliated with ‘subphylum I’ was one of the mostdominant (17% of bacterial clones) in a microbial fuel cellsystem fed with cellulose (39).
These molecular inventories of Chloroflexi phylotypes in awide range of natural and human-made ecosystems strongly
suggest the ecological significance and physiological breadthof these organisms, playing indispensable roles in such habitats.

Cultivation of uncultured Chloroflexi at the subphylum
level
The classes Anaerolineae and Caldilineae as ‘Chloroflexi
subphylum I’. Phylotypes affiliated with ‘subphylum I’ aredetected in a wide range of environments, and the group now
contains the most diverse rRNA gene sequences among
known subphyla with strong natural and biotechnologicalrelevance. To unveil their physiology, attempts were made tocultivate them, and the first pure culture representing thegroup, i.e., Anaerolinea thermophila, was obtained in 2001
from a thermophilic (55°C) anaerobic sludge treating organic
wastewater (71, 72). Simultaneously, the second tangible
organism of the group, Caldilinea aerophila, was obtained
from a hot spring (72). Later, a new thermophilic speciesof the genus Anaerolinea and four species of four genera,i.e., Levilinea, Leptolinea, Bellilinea, and Longilinea, weresuccessfully cultivated and characterized (92, 93). To ourknowledge, these seven species are only the cultivatedorganisms of ‘subphylum I’.
The morphology, physiology, and genetic properties ofcultivated strains of the two classes are shown in Table 3.
The strains are anaerobic or aerobic, mesophilic or moderately thermophilic, multicellular filamentous, chemolithoorganoheterotrophic organisms degrading carbohydrates andamino acids (or peptides). No growth was found in the dissimilatory reduction of nitrate and sulfate. It may not beappropriate to conclude that ‘subphylum I’ is comprised
solely of such heterotrophs, but based on the unveiled physiological traits of these microorganisms, common featuresthat make ‘subphylum I’ recalcitrant to isolation are likely tobe (1) a relatively slow growth rate compared to commonly
cultivable microbes and/or (2) the need to associate withother microbes (syntrophy) for efficient growth. In fact, theAnaerolinea-type anaerobes cultivated so far are all very
slow growers (doubling time: 45–92 hrs), and hence areeasily outcompeted by fast-growing heterotrophic anaerobes like Clostridia- and Thermoanaerobacter-type cells.
We actually found that irrelevant fast-growing microbes
immediately outcompeted Anaerolinea-type cells when we
52

Issue

GNSB941

Target group

SpecialOligonucleotide

210

YAMADA and SEKIGUCHI
Table 3.

Characteristics of cultivated species belonging to classes Anaerolineae and Caldilineae in the phylum Chloroflexi
Class
Caldilineae

Class Anaerolineae

SpecialIssue

Characteristic
Anaerolinea
thermophila

Anaerolinea
thermolimosa

Type strainstrain UNI-1T

strain IMO-1T strain KIBI-1T strain YMTK-2T strain GOMI-1T strain KOME-1T strain STL-6-O1T

Cell diameter (µm)
Temperature range (°C)
Optimum growthtemperature (°C)
pH range
Optimum growth pH
Doubling time (h)O2 respiration
Major cellular fatty acids

0.2–0.3
50–60
55

0.3–0.4
42–55
50

Levilinea
saccarolytica

0.4–0.5
25–50
37–40

Major quinone
DNA G+C content (mol%)

6.0–8.0
around 7.0
72 (48)*−
C16:0, C15:0,
C14:0
−
54.5

Utilization in the presenceof yeast extract of:
Tryptone
BetainPyruvate
GlucoseMannose
Galactose
Fructose
Arabinose
XyloseRibosePectinStarch

±
ND
±
+
+
+
+
±
±
±
±
+

+
−
+
+
+
+
+
+
+
+
±
±

+
±
+
+
±
±
+
−
+
+
±
−

Thermophilic
UASB sludge

Thermophilic
UASB sludge

Mesophilic
UASB sludge

71, 7293, 9493, 94Isolation source
Reference

6.5–7.5
6.0–7.2
around 7.0
around 7.0
48 (10)*56 (56)*−−ai-C17:0, i-C15:0, C14:0, i-C15:0,
C16:0
C16:0
−
−
53.3
59.5

Leptolinea
tardivitalis

Bellilinea
caldifistulae

Longilinea
arvoryzae

Caldilinea
aerophila

0.15–0.2
25–50
37

0.2–0.4
45–65
55

0.4–0.6
30–40
37

0.7–0.8
37–65
55

6.0–7.2
around 7.0
50 (50)*−Branched C17:0,
C16:0, C14:0−
48.2

6.0–8.5
around 7.0
45 (29)*−
C16:0, C14:0,
i-C15:0−54.7

5.0–7.5
around 7.0
92 (38)*−i-C15:0, ai-C15:0,
C14:0,−
54.5

7.0–9.0
around 7.5–8.0
5 (N.D)*+
C18:0, C16:0,
C17:0
MK-10
59.0

+
+
±
+
+
±
+
±
+
+
+
±

±
−
+
+
+
+
+
+
±
+
+
−

+
−
−
−
−
−
±
−
−
−
+
−

+
ND
+
+
−
ND
−
−
−
−
ND
+

Rice paddy
soil

Hot spring

92

72

Mesophilic
Thermophilic
UASB sludge anaerobic sludge
93, 9492* Doubling time in parentheses indicates that for sytrophic growth with hydrogenotrophic methanogens.
−, Negative; ±, variable; +, positive; ND, not determined. Only differences found among the strains are listed. All strains showed the following
characteristics: multicellular filamentous morphology; growth under anaerobic conditions (fermentation).

Another approach that eliminates irrelevant fast-growing
heterotrophic microbes (i.e., ‘subphylum I’ cells) is to establish primary enrichment cultures that allow the growth ofother slow growing bacteria, such as syntrophic propionateoxidizers (37). When we constructed methanogenic,
syntrophic propionate-degrading enrichment cultures, wefound that they contained GNSB941 probe-positive filamentous cells as a concomitant population (92). Therefore, theenrichment cultures were transferred to anaerobic media that
support the growth of Anaerolinea-type cells, resulting in thecultivation and isolation of two additional anaerobes of thegenera Bellilinea and Longilinea (92). In primary enrichment
cultures, they might survive on certain remnants fromthe propionate-oxidizing community. Similarly, Caldilinea
aerophila was isolated from a primary aerobic enrichment
culture to focus on the isolation of chemolithotrophic thermophiles (72). For the primary enrichment culture, thiosulfate was used as the sole energy source, and the cultured cells
were subsequently transferred to an aerobic organic medium,
resulting in the cultivation and isolation of C. aerophila.
Similar to Bellilinea and Longilinea, C. aerophila survived
on remnants from the community that formed during theattempted to isolate them (70, 71). This is probably the primary reason why many attempts to isolate ‘subphylum I’organisms have failed. Consequently, selecting appropriate
inocula, in which ‘subphylum I’-type cells are highly abundant, is one of the keys to success (71). In fact, the cultivation and isolation of Anaerolinea thermophila was possible
only when we used spine-like structures of sludge granules
as the inoculum, in which Anaerolinea cells were highly
concentrated. In the isolation, highly enriched portions ofAnaerolinea cells were found by fluorescence in situ hybridization (FISH) with the probe GNSB633 (Fig. 2, Table 2),
and were carefully washed and serially diluted in liquidmedium. In this case, the fast-growing anaerobes outgrew theAnaerolinea cells in lower dilutions, but the Anaerolinea
grew slowly in the highest dilution, in which growth was
also checked as determined by FISH with GNSB633. SuchrRNA-directed cultivation may be also important for cultivating uncultured cells. In fact, four strains of the genera
Anaerolinea, Levilinea and Leptolinea were successfully isolated by this approach, with rRNA-directed cultivation using
inocula that contain ‘subphylum I’ cells in abundance (71,
94).
53

211

SpecialIssue

Microorganisms Affiliated with the Classes Anaerolineae and Caldilineae

Fig. 3. Evolutionary distance dendrogram of the class Caldilineae derived from a comparative analysis of 16S rRNA gene sequences, showing
the phylogenetic positions of Caldilinea aerophila (indicated by arrow) and other related gene clones that were retrieved from a variety of environments. The tree was constructed and marked as described in the legend of Fig. 2. The bar represents 5 nucleotide substitutions per 100 nucleotides.

on the 16S rRNA gene sequences of these cultured organisms and environmental gene sequences, and the group was
found not to be a monophyletic taxon (93), as suggested
by Hugenholtz and Stackebrandt (34). In particular, theCaldilinea cluster did not often form a clade with othermembers of Anaerolineae (93). Thus, it was concluded that
‘subphylum I’ should be phylogenetically subdivided into
at least two class-level taxa (Fig. 1), the class Anaerolineae
representing the majority of lineages in ‘subphylum I’ (Fig.
2) and the class Caldilineae representing a deeply branchedlineage relative to the Anaerolineae (Fig. 3). Physiologically,
distinct differences, such as aerobic respiration, were foundin the cultured members of the two classes (Table 3).
Whole-genome analyses of A. thermophila and C. aerophila
are now underway to unveil detailed genetic properties ofthese organisms (http://www.bio.nite.go.jp/ngac/e/projecte.html), which may also help to further assess the evolutional
relationship among the Chloroflexi subphyla.

primary enrichment, because C. aerophila cannot utilize
thiosulfate as an energy source. In contrast, inoculating theoriginal sample (hot spring microbial mat) directly into thesame aerobic, organic medium resulted in the cultivation of
typical fast growers like Thermus-type cells (72). These
cases also demonstrated that the elimination of fast-growers
from an inoculum is indispensable to the cultivation of‘subphylum I’.
Co-cultivation is an additional strategy. In the enrichmentof Anaerolinea-type anaerobes, hydrogenotrophic methanogens were added beforehand, which stimulated the growth of‘subphylum I’ anaerobes (94). Interestingly, some ‘subphylum I’ anaerobes produced hydrogen as an end productof fermentation, and grew more rapidly when co-cultivatedwith hydrogenotrophic methanogens (Table 3), indicatingthat they are “semi-syntrophic” bacteria requiring a hydrogen-scavenging partner for efficient growth (71, 72, 92, 93).
Because microorganisms rarely live in pure cultures, thisapproach may be generally applicable to uncultured strains,
whereby in situ conditions are appropriately mimicked, using
co-cultivation for example.
These results indicated that it is still feasible to apply traditional cultivation techniques to the isolation of unseen
microbes, if they are used thoughtfully in combination withmolecular tools, and with carefully selected inocula, whichcontain sufficient amounts of targeted cells. By using a combination of these approaches, more novel microbes belonging to ‘subphylum I’ may be obtained.
Concerning the higher taxonomy of these organisms, themonophyly of ‘subphylum I’ was evaluated in detail based

Other cultured subphyla of the Chloroflexi phylum.
Recently, a novel strain was isolated from a soil and named
Ktedobacter racemifer (11). The bacterium is a Gram-positive, aerobic, chemolithoorganoheterotrophic organism that
produces branched vegetative mycelia, growing well under
microaerobic conditions; this finding further expanded themorphological diversity of the phylum. Phylogenetically, thebacterium represents a new subphylum-level clade of the
Chloroflexi phylum, to which the name Ktedonobacteria
classis nov. has been given (11, 23). The subphylum (class)level clade contains a variety of environmental gene clones(>100 sequences in public databases) retrieved mainly from54

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Based on FISH using oligonucleotide probes for
Chloroflexi members (Fig. 2 and Table 2), the Anaerolineae
in anaerobic sludge were shown to be filamentous. For
example, FISH using a probe (GNSB 633) specific for
Anaerolinea thermophila showed that all of the probereactive cells in thermophilic sludges had a thin-filamentous
morphotype (70, 71). FISH experiments using GNSB633 ora Chloroflexi-specific probe (GNSB941) for various types ofanaerobic sludge also indicated that the probe-reactive cells
were all filamentous with a wide range of thicknesses (66, 70,
71, 94). Considering that almost all the Chloroflexi-related
16S rRNA gene sequences in anaerobic sludges are classified
into the class Anaerolineae, the filamentous morphology
observed with the GNSB941 probe may be a common trait of
the Anaerolineae lineage.
Interestingly, this filamentous morphotype was found to
be important for biotechnological reasons: Anaerolineae
members are considered important for the granulation ofsludge in UASB reactors, as well as the formation of fluffy
sludge (bulking) in similar treatment systems. The granulation of sludge (formation of sludge granules with good settleability) is the major premise for the start-up and stable operation of UASB reactors (67, 69). It was reported that the
granulation of thermophilic sludges was difficult to achieve
when volatile fatty-acid mixtures were used as the sole substrate, while the addition of sucrose or glucose to the influent
wastewater resulted in the formation of a granular sludge
with good settleability (84, 86). In thermophilic UASB reactors having well-settleable sludge granules, Anaerolineatype filamentous microbes predominated on the surface ofthe granules (70, 71, 94). Considering these findings together
with the physiological properties of the cultured Anaerolineae, Anaerolinea-type filaments are indispensable organisms to the granulation of thermophilic UASB sludges, forming a web-like coating on the surface of granules (70, 71, 94).
Besides their importance in thermophilic UASB reactors,
Anaerolinea-type organisms microorganism are a potential
causative agent for the bulking of granular sludges (71).
Once these filaments outgrew in the system, the sludge
became fluffy, resulting in flotation and washout of thesludge from the system (71, 95). Similar observations weremade in mesophilic anaerobic systems (71, 91, 95, 96).
Therefore it is important to control the growth of these filamentous Anaerolineae not only to enhance the formation of
granules but also to prevent the bulking of sludge granules.

soil samples (these sequences can be browsed on the recent
version of the greengene database (http://greengenes.lbl.gov/).
In addition to the class Ktedonobacteria, Davis et al. successfully isolated a strain belonging to a formerly uncultured
Chloroflexi clade at the subphylum level, called the
Ellin7237 lineage, from a soil sample using nontraditional
aerobic media solidified with gellan (16). The lineage contains a relatively small number of environmental genesequences mainly from soil environments (these sequences
can also be seen on the greengene database (http://greengenes.lbl.gov/). Although detailed physiological propertiesof the strain have not yet been published, the bacterium will
also provide new information on the genetic and phenotypic
traits of the newly cultured subphylum. Gellan-based methods were found to be more effective than conventional agarbased techniques for culturing uncultured strains (10, 41,44), resulting in the isolation of novel bacterial lineages,
even at the phylum level, using media solidified with gellan(16, 81). This approach may also be useful for further isolating and characterizing uncultured Chloroflexi phylotypes.
Ecophysiology and function of the Chloroflexi‘subphylum I’Members of the class Anaerolineae in anaerobic sludge.
The cultured Anaerolineae (the cultured members of thegenera Anaerolinea, Levilinea, Leptolinea, Bellilinea, andLongilinea) share common physiological and morphologicaltraits, such as anaerobic (fermentative) growth on carbohydrates and/or peptides (amino acids) and a multicellularfilamentous morphology. Considering that the class Anaerolineae contains a number of rRNA gene clone sequences
mainly retrieved from anoxic environments, most of whichwere obtained from anaerobic (methanogenic) sludges (2, 12,30, 51, 57, 58, 64, 66, 71, 74, 90, 94), the common physiological traits of the cultured Anaerolineae are likely to represent
those of organisms in the Anaerolineae, at least those of theAnaerolineaceae lineage (Fig. 2). For example, a layered
microbial structure of different trophic groups of anaerobes
was often found within granular sludges in upflow anaerobic
sludge blanket (UASB) systems treating organic wastewaters(e.g., (36, 70)), with the Anaerolineae-type populations often
found in the outer most layer of such sludge granules (66, 70,
71, 94). This unique architecture of sludge granules is considered to be a result of substrate profiles formed within the
granules (68). That is, because the methanogenic conversionof organic matter is driven by a food web of different trophic
groups of anaerobes, i.e., fermentative heterotrophs, protonreducing syntrophic bacteria, and methanogenic archaea(68), fermentative heterotrophs, that mainly utilize primary
substances in wastewaters such as carbohydrates, mainly
reside in the outer layer of granules. That Anaerolineae populations were found in the outer layers of sludge granules
suggests them to be heterotrophic degraders, decomposing
carbohydrates, for example. In addition, because yeast
extract and peptides are good substrates for cultured Anaerolineae (Table 3), and some Anaerolineaceae-type filaments
were also found inside of sludge granules (94), they may beable to act as degraders of cellular materials (like aminoacids) that are present inside sludge granules.

Members of the class Anaerolineae in activated sludge
systems. Although Anaerolineae strains have not yet beencultivated and isolated from oxic environments, phylotypesof the class have been frequently found in oxic systems likeactivated sludges (Fig. 2). FISH for the detection of Anaerolineae-type cells in activated sludges revealed that all of theprobe-reactive cells were filamentous (8, 45, 55, 56, 60, 80).
For example, Björnsson et al. used a probe (CFX784) specific for part of the class Anaerolineae and a probe (CFX109)
for the class Chloroflexi (‘subphylum III’) for in situ detection of these organisms in various activated sludge systems
and found that Anaerolineae in sludge samples were generally thin (<1 µm), smooth filaments, although they were lessabundant than filamentous Chloroflexi (‘subphylum III’)55

anaerobic heterotrophs decomposing carbohydrates andamino acids, and often need to be associated with other microbes (syntrophy) for growth. They are ubiquitous in naturaland artificial environments, and likely to play indispensable
roles in ecosystems. They are often closely associated withthe process performance of biological treatment systems, suchas granule and floc formation and/or sludge bulking. Theirecophysiology and function have been well establishedbased on information from cultured representatives, as well
as from molecular-based ecological analyses, including anassessment of their substrate uptake patterns with the MARFISH technique. This synergism between traditional (or rRNAdirected) cultivation and molecular ecological analyses may
be a promising strategy for further elucidating the function ofthese yet-to-be cultured lineages.
The cultivated Anaerolineae only make up part (the family
Anaerolineaceae in Fig. 2) of the Anaerolineae lineage, andthe class still contains surprisingly diverse, yet-to-be cultured
environmental clades even at the subclass level (Fig. 2). The
phylogenetic depth of the class is the highest among the
Chloroflexi phylum (approximate rRNA gene sequence
divergence of the class is 18%), possibly suggesting thepresence of more genetically (and phenotypically) diverse
Anaerolineae organisms than the cultured Anaerolineae
strains. Similarly, the recently cultured classes, Caldilineae
and Ktedonobacteria, contain only single cultured strains.
Other uncultured subphyla of the Chloroflexi phylum remain
to be characterized (63). To further unveil the function ofthese lineages that are less represented by cultured organisms, rRNA-directed cultivation and molecular ecologicalanalyses may be useful, and should be applied to environments where targeted populations are abundant. To efficiently isolate and cultivate these organisms, it may be necessary to employ newly developed cultivation approaches for
yet-to-be cultured microbes (10). More comprehensive studies of these Chloroflexi subphyla, involving cultivation,
molecular ecological analyses, (meta-) genomics, and transcriptomics, will allow us to gain deeper insight into theirfunctions, which may answer questions such as why theseorganisms are so abundant and ubiquitous in the environment.

cells as detected with CFX109 (8).
To reveal the ecophysiology of these Anaerolineae-typeorganisms in activated sludge systems, functional analyses
were conducted using microautoradiography-fluorescent insitu hybridization (MAR-FISH) (45, 49). For example, using
the MAR-FISH method, substrate uptake patterns of uncultured Chloroflexi, particularly those of the class Anaerolineae, were studied for autotrophic nitrifying biofilms
and revealed that the microbes aerobically utilized N-acetyl
glucosamine, a major structural component of bacterial cells,
as well as amino acids, implying that they metabolize cellular materials in the biofilms (45, 60). Similarly, Miura etal. (55, 56) found using MAR-FISH that filamentous cells of
the class Anaerolineae in membrane bioreactors (MBR) were
metabolically versatile and preferentially utilized N-acetyl
glucosamine and glucose under oxic and anoxic conditions.
Zang et al. observed that Anaerolineae-related cells incorporated decayed tritium-labeled bacterial cells in activatedsludges (98). Based on these observations, it may be concluded that Anaerolineae-type organisms in activated sludge
systems are likely to utilize carbohydrates, as well as toscavenge cellular materials formed in the systems, similar tothe cultured Anaerolineae in anaerobic sludges.
The Chloroflexi filaments in activated sludge may provide
a stabilizing backbone for sludge flocs, explaining one
important role of these organisms in the systems (8). Miuraet al. indicated that Anaerolineae-type filaments were
responsible for the degradation of soluble microbial products, including carbohydrates and cellular materials from
cells, consequently reducing membrane fouling potential inmembrane bioreactors (55, 56). Anaerolineae-type filaments
were also shown to be a causative agent for the filamentous
bulking in activated sludge systems as well. Recently, Speirs
et al. reported that Anaerolineae-type filamentous cells, asdetected with the probes CFX197 and CFX223 (Table 2 andFig. 2), are causative agents for aerobic filamentous bulking,which had long been recognized as Eikelboom Type 0092
(80). These studies demonstrate the importance of Anaerolinea organisms in activated sludge systems, drawing ananalogy between their functions in oxic and anoxic (methanogenic) biological waste/wastewater treatment systems.
The class Caldilineae in natural and biotechnologicalsystems. No detailed in situ studies have been conducted forthe class Caldilinea, i.e., no specific oligonucleotide probes
have been designed and no substrate-uptake properties have
yet been elucidated. Although 16S rRNA gene sequences
have been obtained from various ecosystems (Fig. 3), including hot springs (33), anaerobic sludges (76), aerobic sludges(13, 25, 56), geothermal soil (79), marine sediment (35),hydrothermal vents (83), rice paddy soils (75) and chlorinated-solvent-contaminated aquifers (88), the ecophysiology and functions of this class remain to be clarified.

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59

MICROBES AND ENVIRONMENTSEDITORIAL BOARD (2017-2018)

Editor-in-Chief

Ken Takai, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan

Senior Editors

Koki Toyota, Tokyo University of Agriculture and Technology, Koganei, Japan
Shin Haruta, Tokyo Metropolitan University, Hachioji, Japan
Satoshi Hanada, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Hiroyuki Futamata, Shizuoka University, Hamamatsu, Japan
Hiroyuki Ogata, Kyoto University, Kyoto, Japan
Kazuhiko Narisawa, Ibaraki University, Ami, Japan
Kiwamu Minamisawa, Tohoku University, Sendai, Japan
Nobuhiko Nomura, University of Tsukuba, Tsukuba, Japan

Managing Editors

Keizo Shimada (Manuscript Reception), Tokyo Metropolitan University, Hachioji, Japan
Hiroyuki Yamamoto (Manuscript Reception), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Akira Hiraishi (Manuscript Reception), Toyohashi University of Technology, Toyohashi, Japan
Yoshihiro Takaki (Online Journal), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Satoshi Nakagawa (Online Journal), Kyoto University, Kyoto, Japan
Shigeto Otsuka (Online Journal), The University of Tokyo, Tokyo, Japan
Takuro Nunoura (Journal Management), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Hiroyuki Imachi (Journal Management), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Yuki Morono (Manuscript Edition), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Nan-goku, Japan
Michinari Sunamura (Manuscript Edition), The University of Tokyo, Tokyo, Japan
Takashi Narihiro (Manuscript Edition), National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Yoshinori Sato (Manuscript Edition), National Institutes for Cultural Heritage, Tokyo, Japan
Yasuhiro Tanaka (Manuscript Edition), University of Yamanashi, Kofu, Japan
Akihiro Saito (Manuscript Edition), Shizuoka Institute of Science and Technology, Shizuoka, Japan
Noriaki Momma (Manuscript Edition), Institute for Horticultural Plant Breeding, Matsudo, Japan
Satoko Shinozaki-Yabana (Manuscript Edition), National Institutes for Cultural Heritage, Tokyo, Japan
Nana Yoshikane (Manuscript Edition), Saga University, Saga, Japan

Associate Editors

Yoshiteru Aoi, Hiroshima University, Higashi-Hiroshima, Japan
Chih-Yu Chiu, Academia Sinica, Taipei, Taiwan
Jang-Cheon Cho, Inha University, Incheon, Korea
Peter Dunfield, University of Calgary, Calgary, Canada
Craig Everroad, NASA Ames Research Center, Moffett Field, CA, USA
Manabu Fukui, Hokkaido University, Sapporo, Japan
Natsuko Hamamura, Kyushu University, Fukuoka, Japan
Yasufumi Hikichi, Kochi University, Nangoku, Japan
Shir-Ly Huang, National Central University, Jhongli City, Taiwan
Yuichi Hongoh, Tokyo Institute of Technology, Tokyo, Japan
Hiroyuki Imachi, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Satoshi Ishii, University of Minnesota, St. Paul, MN, USA
Shun’ichi Ishii, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Kochi, Japan
Tsukasa Ito, Gunma University, Kiryu, Japan
Elena P. Ivanova, Swinburne University of Technology, Melbourne, Australia
Wataru Iwasaki, The University of Tokyo, Tokyo, Japan
Yasuhiro Kasahara, Hokkaido University, Sapporo, Japan
Takafumi Kataoka, Fukui Prefectural University, Obama, Japan
Junichi Kato, Hiroshima University, Higashi-Hiroshima, Japan
Yoshitomo Kikuchi, National Institute of Advanced Industrial Science and Technology (AIST), Sapporo, Japan
Hiroyuki Kimura, Shizuoka University, Shizuoka, Japan
Tomonori Kindaichi, Hiroshima University, Higashi-Hiroshima, Japan
Staffan Kjelleberg, The University of New South Wales, Sydney, Australia
Ken-ichi Kucho, Kagoshima University, Kagoshima, JapanKen Kurokawa, National Institute of Genetics, Mishima, Japan
Mei-Chin Lai, National Chung Hsing University, Taichung, Taiwan
Shuang-Jiang Liu, Institute of Microbiology Chinese Academy of Sciences (IMCAS), Beijing, China
Wen-Tso Liu, University of Illinois at Urbana-Champaign, Champaign, IL, USA
Fumito Maruyama, Kyoto University, Kyoto, Japan
Shawn McGlynn, Tokyo Institute of Technology, Tokyo, Japan
This journal is partly subsidized by the Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the
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Keisuke Miyauchi, Tohoku Gakuin University, Tagajo, Japan
Ryo Miyazaki, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Keizo Nagasaki, Kochi University, Kochi, Japan
Yuji Nagata, Tohoku University, Sendai, Japan
Atsushi Nakabachi, Toyohashi University of Technology, Toyohashi, Japan
Satoshi Nakagawa, Kyoto University, Kyoto, Japan
Tatsunori Nakagawa, Nihon University, Kanagawa, Japan
Shin-ichi Nakano, Kyoto University, Otsu, Japan
Naohiro Noda, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Satoko Noda, University of Yamanashi, Yamanashi, Japan
Hideaki Nojiri, The University of Tokyo, Tokyo, Japan
Takuro Nunoura, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Ryo Ohtomo, Hokkaido Agricultural Research Center (NARO), Sapporo, Hokkaido
Shigeto Otsuka, The University of Tokyo, Tokyo, Japan
Joonhong Park, Yonsei University, Seoul, Korea
Michael J. Sadowsky, University of Minnesota, St. Paul, MN, USA
Keishi Senoo, The University of Tokyo, Tokyo, Japan
Toru Shigematsu, Niigata University of Pharmacy and Applied Sciences, Niigata, Japan
Masaki Shintani, Shizuoka University, Hamamatsu, Japan
Satoru Suzuki, Ehime University, Matsuyama, Japan
Shino Suzuki, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Kochi, Japan
Mio Takeuchi, National Institute of Advanced Industrial Science and Technology (AIST), Osaka, Japan
Hideyuki Tamaki, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
Sen-Lin Tang, Academia Sinica, Taipei, Taiwan
Akinori Yabuki, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, Japan
Naoko Yoshida, Nagoya Institute of Technology, Nagoya, Japan
Takashi Yoshida, Kyoto University, Kyoto, Japan
Susumu Yoshizawa, The University of Tokyo, Tokyo, Japan
Lian-Hui Zhang, Institute of Molecular and Cell Biology, Proteos, Singapore
Kazuhiko Saeki, Nara Womenʼs University
Shusei Sato, Tohoku University, Sendai, Japan

JAPANESE SOCIETY OF MICROBIAL ECOLOGY

President (2017–2018): Yoichi KAMAGATA, National Institute of Advanced Industrial Science and Technology (AIST)
Secretary (2017–2018): Seigo AMACHI, Chiba University
Business affairs (2017–2018): Hideyuki TAMAKI, National Institute of Advanced Industrial Science and Technology (AIST)
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JAPANESE SOCIETY OF SOIL MICROBIOLOGY

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TAIWAN SOCIETY OF MICROBIAL ECOLOGY

President (2014–2018): Shir-Ly HUANG, National Central University
Vice President (2014–2018): Jyh-Yih LEU, Fu-Jen Catholic University
Secretary-General (2014–2018): Gia-Luen GUO, Institute of Nuclear Energy ResearchJAPANESE SOCIETY OF PLANT MICROBE INTERACTIONS

Chair of Society: Kiwamu MINAMISAWA, Tohoku University
Secretary-General: Shusei SATO, Tohoku University
Treasurer: Hisayuki MITSUI, Tohoku University

Microbes and Environments
Instructions for Authors
Microbes and Environments (M&E) is an international journal devoted tothe publication of original and minireview articles regarding all aspects ofresearch on microbial ecology and environmental microbiology. Articles candeal with culturable and non-culturable forms of any type of microorganism:
Bacteria, archaea, fungi, yeasts, protozoa, algae and viruses. M&E is an
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and Taiwan Society of Microbial Ecology (TSME), and Japanese Society ofPlant Microbe Interactions (JSPMI).
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1. Saito, A., S. Ikeda, H. Ezura, and K. Minamisawa. 2007. Microbialcommunity analysis of the phytosphere using culture-independent methodologies. Microbes Environ. 22:93–105.
2. Katsuyama, C., N. Kondo, Y. Suwa, T. Yamagishi, M. Itoh, N. Ohte, H.
Kimura, K. Nagaosa, and K. Kato. 11 November 2008. Denitriﬁcation activity and relevant bacteria revealed by nitrite reductase gene fragments in soilof temperate mixed forest. Microbes Environ. doi:10.1264/jsme2.ME08541.
3. Sambrook, J., and D.W. Russell. 2001. Molecular Cloning: A Laboratory
Manual, 3rd ed. Cold Spring Harbor Laboratory Press, New York.
4. Hiraishi, A. 1989. Isoprenoid quinone proﬁles for identifying and classifying microorganisms in the environment, p. 663-668. In T. Hattori, Y.
Ishida, Y. Maruyama, R. Y. Morita, and A. Uchida (ed.), Recent
Advances in Microbial Ecology. Japan Scientiﬁc Societies Press, Tokyo.
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Microbes and Environments
DIGEST 2018
CONTENTS
MOST VALUABLE PAPER OF THE YEAR 2016
FLDS: A Comprehensive dsRNA Sequencing Method for Intracellular RNA Virus Surveillance
Syun-ichi urayama, yoShihiro Takaki, and Takuro nunoura
31(1): 33–40, 2016.

1

MOST VALUABLE PAPER OF THE YEAR 2017
Predominant but Previously-overlooked Prokaryotic Drivers of Reductive Nitrogen
Transformation in Paddy Soils, Revealed by Metatranscriptomics

yoko maSuda, hidemi iToh, yuTaka ShiraTori, kazuo iSobe, ShigeTo oTSuka, and keiShi Senoo
32(2): 180–183, 2017.

9

MOST CITED ORIGINAL PAPER IN THIS THREE YEARS [2015-2017](16 citations)
Bacterial Community Analysis of Drinking Water Biofilms in Southern Sweden
Katharina Lührig, Bjӧrn CanBäCK, Catherine j PauL, tomas johansson,
Kenneth m Persson, and Peter rådstrӧm
30(1):99–107, 201513

MOST CITED REVIEW PAPERS IN THIS THREE YEARS [2015-2017](28 citations)
Effect of Probiotics/Prebiotics on Cattle Health and Productivity
yuTaka uyeno, Suguru Shigemori, and TakeShi ShimoSaTo
30(2):126–132, 2015

22

Recent Trends in Control Methods for Bacterial Wilt Diseases Caused by
Ralstonia solanacearum
yuliar, yaneTri aSi nion, and koki ToyoTa
30(1):1-11, 2015

29

MOST CITED ORIGINAL PAPER IN THIS TEN YEARS [2008-2017](57 citations)
Seasonal Dynamics of Anammox Bacteria in Estuarial Sediment of the Mai Po Nature Reserve
Revealed by Analyzing the 16S rRNA and Hydrazine Oxidoreductase (hzo) Genes
meng li, huiluo cao, yi-guo hong, and Ji-dong gu
26(1): 15–22, 201140

MOST CITED REVIEW PAPER IN THIS TEN YEARS [2008-2017](106 citations)Cultivation of Uncultured Chloroflexi Subphyla: Significance and Ecophysiology of Formerly
Uncultured Chloroflexi ‘Subphylum I’ with Natural and Biotechnological Relevance
TakeShi yamada, and yuJi Sekiguchi
24(3): 205–216, 200948