Skip to main content
Download PDF

High-quality draft genome sequence of Flavobacterium suncheonense GH29-5T (DSM 17707T) isolated from greenhouse soil in South Korea, and emended description of Flavobacterium suncheonense GH29-5T

Standards in Genomic Sciences volume 11, Article number: 42 (2016) Cite this article

Abstract

Flavobacterium suncheonense is a member of the family Flavobacteriaceae in the phylum Bacteroidetes. Strain GH29-5T (DSM 17707T) was isolated from greenhouse soil in Suncheon, South Korea. F. suncheonense GH29-5T is part of the G enomic E ncyclopedia of B acteria and A rchaea project. The 2,880,663 bp long draft genome consists of 54 scaffolds with 2739 protein-coding genes and 82 RNA genes. The genome of strain GH29-5T has 117 genes encoding peptidases but a small number of genes encoding carbohydrate active enzymes (51 CAZymes). Metallo and serine peptidases were found most frequently. Among CAZymes, eight glycoside hydrolase families, nine glycosyl transferase families, two carbohydrate binding module families and four carbohydrate esterase families were identified. Suprisingly, polysaccharides utilization loci (PULs) were not found in strain GH29-5T. Based on the coherent physiological and genomic characteristics we suggest that F. suncheonense GH29-5T feeds rather on proteins than saccharides and lipids.

Introduction

Flavobacteria / Cytophagia have been frequently observed in aquatic and soil habitats [1–3] and play a major role in polysaccharide decomposition [2, 4, 5]. Type strains of the genus Flavobacterium have been isolated from many different habitats such as fresh water, sea ice and soil, and some Flavobacterium strains are pathogenic to humans and animals [2, 6]. Strain GH29-5T (= DSM 17707T = CIP 109901T = KACC 11423T ) is the type strain of Flavobacterium suncheonense [2, 7], which belongs to Flavobacteriaceae [8]. F. suncheonense GH29-5T was isolated from greenhouse soil in Korea [10]. Flavobacterium johnsoniae UW101T, a well studied model organism, was as well isolated from soil [11, 12] and harbors a considerable number of CAZymes and PULs [13]. Thus, an investigation of the genome of strain GH29-5T will give further insights into the variety of CAZymes and the polysaccharide decomposition potential of this microrganism.

Here we present the set of carbohydrate active enzymes, polysaccharide utilization loci and peptidases of F. suncheonense GH29-5T, together with a set of phenotypic features and the description and annotation of the high-quality draft genome sequence from a culture of DSM 17707T .

Organism information

Classification and features

The sequence of the single 16S rRNA gene copy in the genome is identical with the previously published 16S rRNA gene sequence (DQ222428). Figure 1 shows the phylogenetic neighborhood of F. suncheonense GH29-5T inferred from a tree of 16S rRNA gene sequence, as previously described [14]. The next related type species are F. cauense R2A-7T (EU521691), F. enshiense DK69T (JN790956), F. limnosediminis JC2902T (JQ928688) and F. saliperosum S13T (DQ021903) with less than 95.9 % 16S rRNA gene identity. The 16S rRNA gene sequence of strain GH29-5T has an identity of only 93.9 % with F. aquatile DSM 1132T (AM230485).

Fig. 1
figure 1

Phylogenetic tree of the genus Flavobacterium and its most closely related genus Capnocytophaga. Modified from Hahnke et al. [68]. In short: the tree was inferred from 1254 aligned characters of the 16S rRNA gene sequence under the maximum likelihood (ML) criterion. The branches are scaled in terms of the expected number of substitutions per site. Numbers adjacent to the branches are support values from 1000 ML bootstrap replicates (left) and from 1000 maximum-parsimony bootstrap replicates (right) if larger than 60 %

Full size image

The 16S rRNA gene sequence of F. suncheonense GH29-5T was compared with the Greengenes database [15]. Considering the best 100 hits, 99 sequences belonged to Flavobacterium and one sequence to Cytophaga sp. (X85210). Among the most frequent keywords within the labels of environmental samples were 40.4 % marine habitats (such as marine sediment, deep sea, seawater, whale fall, diatom/phytoplankton bloom, Sargasso Sea, sponge, sea urchin, bacterioplankton), 12.3 % soil habitats (such as rhizosphere, grassland, compost), 11.6 % freshwater habitats (such as lake, riverine sediment, groundwater), 8.9 % cold environments (such as Antarctic/Artic seawater, lake ice or sediment), but also 2.7 % wastewater habitats. Interestingly, environmental 16S rRNA gene sequences with 99 % sequence identity with F. suncheonense GH29-5T were clones from wetland of France (KC432449) [16] and an enrichment culture of heterotrophic soil bacteria from the Netherlands (JQ855723), and with 98 % sequence identity to a soil isolate from Taiwan (DQ239767).

As described for Flavobacterium [17], F. suncheonense GH29-5T stains are Gram-negative (Table 1). The colonies are convex, round and yellow, but flexirubin-type pigments are absent and gliding motility was not observed [10]. The strain is positive for the catalase and oxidase tests [10], as are most members of the genus Flavobacterium [6]. Cells divide by binary fission, possess appandages and occur either as single rod shaped cells, with 0.3 μm in width and 1.5–2.5 μm in length, or as filaments (Fig. 2).

Table 1 Classification and general features of F. suncheonense GH29-5T in accordance with the MIGS recommendations [59], as developed by [60], List of Prokaryotic names with Standing in Nomenclature [61] and the Names for Life database [62]
Full size table
Fig. 2
figure 2

Scanning-electron micrograph of F. suncheonense GH29-5T (DSM 17707T) showing appendages 50–80 nm in diameter and 0.5–8 μm in length (arrows)

Full size image

F. suncheonense GH29-5T grows between 15 °C and 37 °C, pH 6 and 8 and in media with up to 1 % NaCl [10], with optimal growth at pH 7.0 and without NaCl [7]. Strain GH29-5T decomposes gelatin and casein, but not starch, carboxymethyl cellulose, agar, alginate, pectin, chitin, aesculin and DNA [10]. Strain GH29-5T produces H2S and neither reduces nitrate nor produces indole or ferments glucose [10]. Moreover, strain GH29-5T does not utilize arabinose, mannose, N-acetyl-D-glucosamine, maltose, gluconate, caprate, adipate, malate, citrate and phenylacetate [19]. Strain GH29-5T possesses alkaline phosphatase, esterase C4, esterase lipase C8, leucine arylamidase, valine arylamidase, acid phosphatase, naphthol-AS-BI-phosphohydrolase and N-acetyl-β-glucosaminidase, but has no lipase C14, cystine arylamidase, trypsin, α-chymotrypsin, α-galactosidase, β-galactosidase, β-glucuronidase, α-glucosidase, β-glucosidase, α-mannosidase, α-fucosidase and urease activity [10].

Chemotaxonomic data

The major cellular fatty acids are iso-C15 : 0 (29.9 %), iso-C17 : 0 3-OH (17.7 %), iso-C15 : 1 G (12.0 %) and iso-C15 : 0 3-OH (11.1 %) and MK-6 is the sole quinone [10], as common in Flavobacterium [6]. Besides phosphatidylethanol-amine, several unidentified lipids, aminolipids and aminophospholipids were observed in strain GH29-5T [7]. The DNA G + C content was reported to be 39.0 mol % [10].

Genome sequencing information

Genome project history

This strain was selected for sequencing on the basis of its phylogenetic position [20, 21], and is part of Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes (KMG) project [22], a follow-up of the Genomic Encyclopedia of Bacteria and Archaea (GEBA) pilot project [23], which aims at sequencing key reference microbial genomes and generating a large genomic basis for the discovery of genes encoding novel enzymes [24]. KMG-I is the part of the “Genomic Encyclopedia of Bacteria and Archaea: sequencing a myriad of type strains initiative” [25] and a Genomic Standards Consortium project [26]. The genome project is deposited in the Genomes OnLine Database [27] and the permanent draft genome sequence is deposited in GenBank. Sequencing, finishing and annotation were performed by the DOE-JGI using state-of-the-art sequencing technology [28]. A summary of the project information is shown in Table 2.

Table 2 Project information
Full size table

Growth conditions and genomic DNA preparation

A culture of GH29-5T (DSM 17707) was grown aerobically in DSMZ medium 830 (R2A Medium) [29] at 28 °C. Genomic DNA was isolated using a Jetflex Genomic DNA Purification Kit (GENOMED 600100) following the standard protocol provided by the manufacturer. DNA is available from the DSMZ through the DNA Bank Network [30].

Genome sequencing and assembly

The draft genome of strain GH29-5T was generated using the Illumina technology [31]. An Illumina Std. shotgun library was constructed and sequenced using the Illumina HiSeq 2000 platform which generated 9,392,462 reads totaling 1408.9 Mbp (Table 3). All general aspects of library construction and sequencing performed at the DOE-JGI can be found at [32]. All raw sequence data were passed through DUK, a filtering program developed at DOE-JGI, which removes known Illumina sequencing and library preparation artifacts (Mingkun L, Copeland A, Han J: DUK. unpublished 2011). The following steps were performed for assembly: (1) filtered reads were assembled using Velvet [33], (2) 1–3 Kbp simulated paired-end reads were created from Velvet contigs using wgsim [34], (3) Sequence reads were assembled with simulated read pairs using Allpaths–LG [35]. Parameters for assembly steps were: 1) Velvet (“velveth 63 -shortPaired” and “velvetg -very_clean yes -exportFiltered yes -min_contig_lgth 500 -scaffolding no -cov_cutoff 10”), (2) wgsim (“wgsim -e 0–1 100–2 100 -r 0 -R 0 -X 0”) (3) Allpaths–LG (“PrepareAllpathsInputs: PHRED_64 = 1 PLOIDY = 1 FRAG_COVERAGE = 125 JUMP_COVERAGE = 25 LONG_JUMP_COV = 50” and “RunAllpathsLG THREADS = 8 RUN = std shredpairs TARGETS = standard VAPI_WARN_ONLY = True OVERWRITE = True”). The final draft assembly contained 57 contigs in 54 scaffolds. The total size of the genome is 2.9 Mbp and the final assembly is based on 331.3 Mbp of data, which provides a 114.2x average coverage of the genome.

Table 3 Genome statistics
Full size table

Genome annotation

Genes were identified using Prodigal [36] as part of the DOE-JGI genome annotation pipeline [37], followed by manual curation using the DOE-JGI GenePRIMP pipeline [38]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information non-redundant database, UniProt, TIGR-Fam, Pfam, PRIAM, KEGG, COG, and InterPro database. These data sources were combined to assert a product description for each predicted protein. Additional gene prediction analysis and functional annotation was performed within the IMG-ER platform [39].

Genome properties

The assembly of the draft genome sequence consists of 54 scaffolds amounting to 2,880,663 bp. The G + C content is 40.5 % (Table 3) which is 1.5 % higher than previously reported by Kim et al. [10] and thus shows a difference that surpasses the maximal range among strains belonging to the same species [40]. Of the 2821 genes predicted, 2739 were protein-coding genes, and 82 RNAs. The majority of the protein-coding genes (69.2 %) were assigned a putative function while the remaining ones were annotated as hypothetical proteins. The distribution of genes into COG functional categories is presented in Table 4.

Table 4 Number of genes associated with the general COG functional categories
Full size table

Insights from the genome sequence

Comparative genomics

We conducted a comparative genomics analysis of F. suncheonense (AUCZ00000000) with a selection of closely related (according to 16S rRNA gene sequence similarities) Flavobacterium type strains, i.e., F. enshiense (AVCS00000000), F. cauense (AVBI00000000), F. saliperosum (AVFO00000000) and F. columnare (CP003222) and the type species F. aquatile (JRHH00000000). The genome sizes of the five type strains were 3.1 Mbp on average with the biggest difference of 0.5 Mbp between the genomes of F. suncheonense and F. saliperosum , on the one hand, and F. enshiense , on the other hand. Genome sizes were 3.1 Mbp ( F. cauense ), 3.2 Mbp ( F. columnare ), 3.4 Mbp ( F. enshiense ), 2.9 Mbp ( F. suncheonense ) and 2.9 Mbp ( F. saliperosum ). However, since these genomes have not yet been sequenced completely, their sizes might slightly change in the future.

An estimate of the overall similarity between F. suncheonense and the five reference strains was conducted using the Genome-to-Genome Distance Calculator (GGDC 2.0) [41, 42]. It reports model-based DDH estimates (digital DDH or dDDH) along with their confidence intervals [42], which allow for genome-basted species delineation and genome-based subspecies delineation. The recommended distance formula 2 is robust against the use of incomplete genome sequences and is thus especially suited for this dataset.

The result of this comparison is shown in Table 5 and yields dDDH of below 22 % throughout, which confirms the expected status of distinct species. Furthermore, the G + C content was calculated from the genome sequences of the above strains and their pairwise differences were assessed with respect to F. suncheonense . Differences were 2.4 % ( F. cauense ), 2.8 % ( F. enshiense ), 1 % ( F. saliperosum ), 9.1 % ( F. columnare ) and 8.3 % ( F. aquatile ). These differences confirm the status of distinct species, because, if computed from genome sequences, these differences can only vary up to 1 % within species [40].

Table 5 Pairwise comparison using the GGDC (Genome-to-Genome Distance Calculator) of F. suncheonense with a selection of currently available Flavobacterium genomes, F. enshiense (AVCS00000000), F. cauense (AVBI00000000), F. saliperosum (AVFO00000000) and F. columnare (CP003222), plus the type species F. aquatile (JRHH00000000)
Full size table

Gliding motility

McBride and Zhu [43] described the diversity of genes involved in gliding motility among members of phylum Bacteroidetes . The machinery for gliding motility is composed of adhesin-like proteins, the type IX secretion system, and additional proteins [43]. Even though strain GH29-5T was never observed to glide [10], all necessary genes for gliding motility were identified in its genome (Table 6).

Table 6 Gliding motility-related genes in strain GH29-5T compared to genes in Flavobacterium strains studied by McBride and Zhu [43]
Full size table

Carbohydrate active enzymes and peptidases

Cottrell and Kirchman [44] showed that members of the Cytophaga-Flavobacteria group preferentially consume polysaccharides and proteins rather than amino acids. This phenotypic feature was attributed by Fernández-Gómez et al. [4] to higher numbers of peptidases and additionally higher numbers of glycoside hydrolases and carbohydrate-binding modules in the genomes of Bacteroidetes compared to other bacteria. F. suncheonense GH29-5T was isolated from greenhouse soil, hydrolyzes casein and gelatin, but did not utilize any of the tested saccharides [10, 19]. Therefore, we compared the predicted CDS against the CAZyme [45, 46] and dbCAN [47] database. The CAZyme annotation (Additional file 1, Table S1) was a combination of RAPSearch2 search [48, 49] and HMMER scanning [50] as described in Hahnke et al. [14]. The genome of strain GH29-5T comprised a small number of carbohydrate active enzymes (49) including 36 glycosyl transferases, nine glycoside hydrolases, four carbohydrate binding modules and six carbohydrate esterases (Table 7). Furthermore, sulfatases were suggested as important enzymes for the metabolic potential of Bacteroidetes to degrade sulfated algae polysaccharides such as carrageenan, agarans and fucans. Only, three sulfatases were identified in the genome of strain GH29-5T (Additional file 1, Table S2).

Table 7 Carbohydrate active enzymes (CAZy) in the genome of strain GH29-5T
Full size table

Polysaccharide utilization loci

CAZymes of Flavobacteria that are suggested to be involved in polysaccharide decomposition are frequently observed to be organized in gene clusters. Such polysaccharides-utilization loci (PULs) consist of a TonB-dependent receptor, a SusD-like protein and carbohydrate active enzymes [51, 52]. In strain GH29-5T five TonB-dependent transporters were identified of which G498_00119, G498_01595, G498_02575 were associated to siderophores and G498_00706, G498_00915 were associated with a SusD-like protein. The gene cluster up-stream of the TonB-dependent transporter G498_00706 comprised five hypothetical proteins.

Peptidases

The MEROPS annotation was carried out by searching the sequences against the MEROPS 9.10 database [53] (access date: 2014.10.16, version: pepunit.lib) as described in Hahnke et al. [14]. The genome of strain GH29-5T comprised 117 identified peptidase genes (or homologues), mostly serine peptidases (S, 50), metallo peptidases (M, 50) and cysteine peptidases (C, 14) (Table 8, Additional file 1: Tables S3 and S4). Hence, the low number of carbohydrate active enzymes and the high number of peptidases in the genome of strain GH29-5T reflects its currently known substrate range being proteins rather than saccharides.

Table 8 Peptidases and simple peptidase inhibitors in the genome of strain GH29-5T
Full size table

Conclusions

The genome of F. suncheonense GH29-5T contains a relaltively low number of carbohydrate active enzymes in contrast to genomes of other Flavobacteriaceae such as Flavobacterium branchiophilum [54], Flavobacterium rivuli [14], Formosa agariphila [55], Polaribacter [4, 56], ‘ Gramella forsetii ’ [57] and Zobellia galactanivorans [17]. This is surpising, since greenhouse soil might be a rich source of plant litter. McBride et al. [13] described the genome features of Flavobacterium johnsoniae UW101T, a bacterium that was as well isolated from soil [11, 58]. Both the genomes of F. johnsoniae UW101T and F. suncheonense GH29-5T have an almost equal number of 31 and 39 peptidases per Mbp, respectively. The genomes, however, differ remarkably in the number of CAZymes, with 47 genes per Mbp in the genome of F. johnsoniae UW101T and only 18 genes per Mbp in the genome of F. suncheonense GH29-5T. Thus, this small set of CAZymes contributes only little to a pool of enzymes, which might be essential for a Flavobacterium to feed on soil components.

A systematic collection of genome sequences, such as GEBA [23] and KMG-1 [22], will provide the scientific community with the possibility for a systematic discovery of genes encoding for novel enzymes [24] and support microbial taxonomy. In addition, genome sequences also provide further taxonomically useful information such as the G + C content [40], which, as seen in this report might significantly differ from the values determined with traditional methods.

Based on the observed large difference in the DNA G + C content and the additional information on cell morphology obtained in this study, an emended description of F. suncheonense is proposed.

Emended description of F. suncheonense GH29-5T Kim et al. 2006 emend. Dong et al. 2013

The description of Flavobacterium suncheonense is as given by Kim et al. [10] and Dong et al. [7], with the following modifications: the DNA G + C content is 40.5 mol%, and amendments: possesses appendages of 50–80 nm in diameter and 0.5–8 μm in length.

Abbreviations

DOE:

Department of Energy

EMBL:

European molecular biology laboratory

GEBA:

Genomic encyclopedia of Bacteria and Archaea

JGI:

Joint Genome Institute

IMG-ER:

Integrated microbial genomes – expert review

KMG:

One thousand microbial genomes project

RDP:

Ribosomal database project (East Lansing, MI, USA)

References

  1. 1.

    Bodenhausen N, Horton MW, Bergelson J. Bacterial communities associated with the leaves and the roots of Arabidopsis thaliana. PLoS One. 2013;8:2.

    Article  Google Scholar 

  2. 2.

    Kirchman DL. The ecology of Cytophaga-Flavobacteria in aquatic environments. FEMS Microbiol Ecol. 2002;39:91–100.

    CAS  PubMed  Google Scholar 

  3. 3.

    Kolton M, Harel YM, Pasternak Z, Graber ER, Elad Y, Cytryn E. Impact of biochar application to soil on the root-associated bacterial community structure of fully developed greenhouse pepper plants. Appl Environ Microbiol. 2011;77:4924–30.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Fernández-Gómez B, Richter M, Schüler M, Pinhassi J, Acinas SG, González JM, Pedrós-Alió C. Ecology of marine Bacteroidetes: a comparative genomics approach. ISME J. 2013;7:1026–37.

    Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Kolton M, Sela N, Elad Y, Cytryn E. Comparative genomic analysis indicates that niche adaptation of terrestrial Flavobacteria is strongly linked to plant glycan metabolism. PLoS One. 2013;8:1–11.

    Article  Google Scholar 

  6. 6.

    Bernardet JF, Bowman JP. Genus I. Flavobacterium Bergey, Harrison, Breed, Hammer and Huntoon 1923, 97AL emend. Bernardet, Segers, Vancanneyt, Berthe, Kersters and Vandamme 1996, 139. In: Bergey's Manual of Systematic Bacteriology, The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes, vol. 4. 2nd ed. New York: Springer; 2011. p. 112–54.

    Google Scholar 

  7. 7.

    Dong K, Xu B, Zhu F, Wang G. Flavobacterium hauense sp. nov., isolated from soil and emended descriptions of Flavobacterium subsaxonicum, Flavobacterium beibuense and Flavobacterium rivuli. Int J Syst Evol Microbiol. 2013;63:3237–42.

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Bernardet JF. Family I. Flavobacteriaceae Reichenbach 1992b, 327VP (effective publication: Reichenbach 1989b, 2013.) emend. Bernardet, Segers, Vancanneyt, Berthe, Kersters and Vandamme 1996, 145 emend. Bernardet, Nakagawa and Holmes 2002, 1057. In: Bergey's Manual of Systematic Bacteriology, The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes, vol. 4. 2nd ed. New York: Springer; 2011. p. 106–314.

    Google Scholar 

  9. 9.

    Reichenbach H. Order 1. Cytophagales Leadbetter 1974, 99AL. In: Staley JT, Bryant MP, Pfennig N, Holt JG, editors. Bergey’s Manual of Systematic Bacteriology, vol. 3. New York: Springer New York; 1989. p. 2011–3.

    Google Scholar 

  10. 10.

    Kim BY, Weon HY, Cousin S, Yoo SH, Kwon SW, Go SJ, Stackebrandt E: Flavobacterium daejeonense sp. nov. and Flavobacterium suncheonense sp. nov., isolated from greenhouse soils in Korea. Int J Syst Evol Microbiol. 2006;56:1645–9.

    CAS  Article  PubMed  Google Scholar 

  11. 11.

    Bernardet JF, Segers P, Vancanneyt M, Berthe F, Kersters K, Vandamme P. Cutting a gordian knot: emended classification and description of the genus Flavobacterium, emended description of the family Flavobacteriaceae, and proposal of Flavobacterium hydatis nom. nov. (basonym, Cytophaga aquatilis Strohl and Tait 1978). Int J Syst Bacteriol. 1996;46:128–48.

    Article  Google Scholar 

  12. 12.

    Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A. 1990;87:4576–9.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    McBride MJ, Xie G, Martens EC, Lapidus A, Henrissat B, Rhodes RG, Goltsman E, Wang W, Xu J, Hunnicutt DW, Staroscik AM, Hoover TR, Cheng YQ, Stein JL: Novel features of the polysaccharide-digesting gliding bacterium Flavobacterium johnsoniae as revealed by genome sequence analysis. Appl Environ Microbiol. 2009;75:6864–75.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Hahnke RL, Stackebrandt E, Meier-Kolthoff JP, Tindall BJ, Huang S, Rohde M, Lapidus A, Han J, Trong S, Haynes M, Reddy TBK, Huntemann M, Pati A, Ivanova NN, Mavromatis K, Markowitz V, Woyke T, Göker M, Kyrpides NC, Klenk H-P: High quality draft genome sequence of Flavobacterium rivuli type strain WB 3.3-2T (DSM 21788T), a valuable source of polysaccharide decomposing enzymes. Stand Genomic Sci. 2015;10:46.

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL: Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72:5069–72.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Bouali M, Zrafi I, Bakhrouf A, Chaussonnerie S, Sghir A. Bacterial structure and spatiotemporal distribution in a horizontal subsurface flow constructed wetland. Appl Microbiol Biotechnol. 2014;98:3191–203.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Thomas F, Barbeyron T, Tonon T, Génicot S, Czjzek M, Michel G. Characterization of the first alginolytic operons in a marine bacterium: From their emergence in marine Flavobacteriia to their independent transfers to marine Proteobacteria and human gut Bacteroides. Environ Microbiol. 2012;14:2379–94.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, Harris MA, Hill DP, Issel-Tarver L, Kasarskis A, Lewis S, Matese JC, Richardson JE, Ringwald M, Rubin GM, Sherlock G: Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Lee K, Park S-C, Yi H, Chun J. Flavobacterium limnosediminis sp. nov., isolated from sediment of a freshwater lake. Int J Syst Evol Microbiol. 2013;63:4784–9.

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Göker M, Klenk H-P. Phylogeny-driven target selection for large-scale genome-sequencing (and other) projects. Stand Genomic Sci. 2013;8:360–74.

    Article  PubMed  PubMed Central  Google Scholar 

  21. 21.

    Klenk HP, Göker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol. 2010;33:175–82.

    CAS  Article  PubMed  Google Scholar 

  22. 22.

    Kyrpides NC, Woyke T, Eisen JA, Garrity G, Lilburn TG, Beck BJ, et al. Genomic encyclopedia of type strains, Phase I : The one thousand microbial genomes (KMG-I) project. Stand Genomic Sci. 2014;9(3):628–634.

    Google Scholar 

  23. 23.

    Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova NN, Kunin V, Goodwin L, Wu M, Tindall BJ, Hooper SD, Pati A, Lykidis A, Spring S, Anderson IJ, D’haeseleer P, Zemla A, Singer M, Lapidus A, Nolan M, Copeland A, Han C, Chen F, Cheng J-F, Lucas S, Kerfeld C, Lang E, Gronow S, Chain P, Bruce D, et al . A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature. 2009;462:1056–60.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Piao H, Froula J, Du C, Kim TW, Hawley ER, Bauer S, Wang Z, Ivanova N, Clark DS, Klenk HP, Hess M. Identification of novel biomass-degrading enzymes from genomic dark matter: Populating genomic sequence space with functional annotation. Biotechnol Bioeng. 2014;111:1550–65.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Kyrpides NC, Hugenholtz P, Eisen J a, Woyke T, Göker M, Parker CT, Amann R, Beck BJ, Chain PSG, Chun J, Colwell RR, Danchin A, Dawyndt P, Dedeurwaerdere T, DeLong EF, Detter JC, De Vos P, Donohue TJ, Dong X-Z, Ehrlich DS, Fraser C, Gibbs R, Gilbert J, Gilna P, Glöckner FO, Jansson JK, Keasling JD, Knight R, Labeda D, Lapidus A, et al. Genomic encyclopedia of bacteria and Archaea: sequencing a myriad of type strains. PLoS Biol. 2014;12:e1001920.

    Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Field D, Amaral-Zettler L, Cochrane G, Cole JR, Dawyndt P, Garrity GM, Gilbert J, Glöckner FO, Hirschman L, Karsch-Mizrachi I, Klenk HP, Knight R, Kottmann R, Kyrpides N, Meyer F, San Gil I, Sansone SA, Schriml LM, Sterk P, Tatusova T, Ussery DW, White O, Wooley J. The Genomic Standards Consortium. PLoS Biol. 2011;9:e1001088.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Reddy TBK, Thomas AD, Stamatis D, Bertsch J, Isbandi M, Jansson J, Mallajosyula J, Pagani I, Lobos EA, Kyrpides NC: The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification. Nucleic Acids Res. 2014;43:D1099–106.

    Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Mavromatis K, Land ML, Brettin TS, Quest DJ, Copeland A, Clum A, Goodwin L, Woyke T, Lapidus A, Klenk HP, Cottingham RW, Kyrpides NC: The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation. PLoS One. 2012;7:e48837.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    List of growth media used at the DSMZ. http://www.dsmz.de/.

  30. 30.

    Gemeinholzer B, Dröge G, Zetzsche H, Haszprunar G, Klenk H-P, Güntsch A, Berendsohn WG, Wägele J-W. The DNA bank network: the start from a German initiative. Biopreserv Biobank. 2011;9:51–5.

    Article  PubMed  Google Scholar 

  31. 31.

    Bennett S. Solexa Ltd. Pharmacogenomics. 2004;5:433–8.

    Article  PubMed  Google Scholar 

  32. 32.

    DOE Joint Genome Institute, http://www.jgi.doe.gov/.

  33. 33.

    Zerbino DR, Birney E. Velvet: Algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;18:821–9.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    wgsim. [https://github.com/lh3/wgsim].

  35. 35.

    Gnerre S, Maccallum I, Przybylski D, Ribeiro FJ, Burton JN, Walker BJ, Sharpe T, Hall G, Shea TP, Sykes S, Berlin AM, Aird D, Costello M, Daza R, Williams L, Nicol R, Gnirke A, Nusbaum C, Lander ES, Jaffe DB: High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proc Natl Acad Sci U S A. 2011;108:1513–8.

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Huntemann M, Ivanova NN, Mavromatis K, Tripp HJ, Paez-Espino D, Palaniappan K, Szeto E, Pillay M, Chen IM-A, Pati A, Nielsen T, Markowitz VM, Kyrpides NC. The standard operating procedure of the DOE-JGI microbial genome annotation pipeline (MGAP v.4). Sciences. 2015;10:86.

    Google Scholar 

  38. 38.

    Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods. 2010;7:455–7.

    CAS  Article  PubMed  Google Scholar 

  39. 39.

    Markowitz VM, Mavromatis K, Ivanova NN, Chen IMA, Chu K, Kyrpides NC. IMG ER: A system for microbial genome annotation expert review and curation. Bioinformatics. 2009;25:2271–8.

    CAS  Article  PubMed  Google Scholar 

  40. 40.

    Meier-Kolthoff JP, Klenk H-P, Göker M. Taxonomic use of DNA G + C content and DNA-DNA hybridization in the genomic age. Int J Syst Evol Microbiol. 2014;64(Pt 2):352–6.

    CAS  Article  PubMed  Google Scholar 

  41. 41.

    Auch AF, Klenk H-P, Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci. 2010;2:142–8.

    Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Meier-Kolthoff JP, Auch AF, Klenk H-P, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics. 2013;14:60.

    Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    McBride MJ, Zhu Y. Gliding motility and Por secretion system genes are widespread among members of the phylum Bacteroidetes. J Bacteriol. 2013;195:270–8.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Cottrell MT, Kirchman DL. Natural assemblages of marine proteobacteria and members of the Cytophaga-Flavobacter cluster consuming low- and high-molecular-weight dissolved organic matter. Appl Env Microbiol. 2000;66:1692–7.

    CAS  Article  Google Scholar 

  45. 45.

    Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B. The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res. 2009;37:D233–8.

    CAS  Article  PubMed  Google Scholar 

  46. 46.

    Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42:D490–5.

    CAS  Article  PubMed  Google Scholar 

  47. 47.

    Yin Y, Mao X, Yang J, Chen X, Mao F, Xu Y. dbCAN: A web resource for automated carbohydrate-active enzyme annotation. Nucleic Acids Res. 2012;40:W445–51.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Ye Y, Choi J-H, Tang H. RAPSearch: a fast protein similarity search tool for short reads. BMC Bioinformatics. 2011;12:159.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Zhao Y, Tang H, Ye Y. RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data. Bioinformatics. 2012;28:125–6.

    CAS  Article  PubMed  Google Scholar 

  50. 50.

    Finn RD, Bateman A, Clements J, Coggill P, Eberhardt RY, Eddy SR, Heger A, Hetherington K, Holm L, Mistry J, Sonnhammer ELL, Tate J, Punta M: Pfam: the protein families database. Nucleic Acids Res. 2014;42:D222–30.

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    Bjursell MK, Martens EC, Gordon JI. Functional genomic and metabolic studies of the adaptations of a prominent adult human gut symbiont, Bacteroides thetaiotaomicron, to the suckling period. J Biol Chem. 2006;281:36269–79.

    CAS  Article  PubMed  Google Scholar 

  52. 52.

    Sonnenburg ED, Zheng H, Joglekar P, Higginbottom SK, Firbank SJ, Bolam DN, Sonnenburg JL. Specificity of polysaccharide use in intestinal bacteroides species determines diet-induced microbiota alterations. Cell. 2010;141:1241–52.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Rawlings ND, Waller M, Barrett AJ, Bateman A. MEROPS: the database of proteolytic enzymes, their substrates and inhibitors. Nucleic Acids Res. 2014;42(Database issue):D503–9.

    CAS  Article  PubMed  Google Scholar 

  54. 54.

    Touchon M, Barbier P, Bernardet J-F, Loux V, Vacherie B, Barbe V, Rocha EPC, Duchaud E: Complete genome sequence of the fish pathogen Flavobacterium branchiophilum. Appl Environ Microbiol. 2011;77:7656–62.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Mann AJ, Hahnke RL, Huang S, Werner J, Xing P, Barbeyron T, Huettel B, Stüber K, Reinhardt R, Harder J, Glöckner FO, Amann RI, Teeling H The genome of the alga-associated marine flavobacterium Formosa agariphila KMM 3901T reveals a broad potential for degradation of algal polysaccharides. Appl Environ Microbiol. 2013;79:6813–22.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Xing P, Hahnke RL, Unfried F, Markert S, Huang S, Fuchs BM, Barbeyron T, Harder J, Schweder T, Glöckner FO, Amann RI, Teeling H. Niche separation of two Polaribacter strains isolated from the German Bight of the North Sea during a spring diatom bloom. ISME J. 2014;9:1410–22.

    Article  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Kabisch A, Otto A, König S, Becher D, Albrecht D, Schüler M, Teeling H, Amann RI, Schweder T. Functional characterization of polysaccharide utilization loci in the marine Bacteroidetes “Gramella forsetii” KT0803. ISME J. 2014;8:1492–502.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Stanier RY. Studies on nonfruiting myxobacteria I. Cytophaga johnsonae, n. sp., a chitin-decomposing myxobacterium. J Bacteriol. 1947;53:297–315.

    CAS  PubMed Central  Google Scholar 

  59. 59.

    Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli S V, Ashburner M, Axelrod N, Baldauf S, Ballard S, Boore J, Cochrane G, Cole J, Dawyndt P, De Vos P, DePamphilis C, Edwards R, Faruque N, Feldman R, Gilbert J, Gilna P, Glöckner FO, Goldstein P, Guralnick R, Haft D, Hancock D, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol. 2008;26:541–7.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Field D, Amaral-Zettler L, Cochrane G, Cole JR, Dawyndt P, Garrity GM, Gilbert J, Glöckner FO, Hirschman L, Karsch-Mizrachi I, Klenk HP, Knight R, Kottmann R, Kyrpides N, Meyer F, Gil IS, Sansone SA, Schriml LM, Sterk P, Tatusova T, Ussery DW, White O, Wooley J: The Genomic Standards Consortium. PLoS Biol. 2011;9:8–10.

    Article  Google Scholar 

  61. 61.

    Euzéby JP. List of bacterial names with standing in nomenclature: a folder available on the internet. Int J Syst Bacteriol. 1997;47:590–2.

    Article  PubMed  Google Scholar 

  62. 62.

    Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today. 2010;37:9.

    Google Scholar 

  63. 63.

    Krieg NR, Ludwig W, Euzéby J, Whitman WB. Phylum XIV. Bacteroidetes phyl. nov. In: Krieg NR, Staley JT, Brown DR, editors. Bergey’s Manual of Systematic Bacteriology, The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes, vol. 4. 2nd ed. New York: Springer; 2010. p. 25–469.

    Google Scholar 

  64. 64.

    Euzéby J. Validation List N° 143. Int J Syst Evol Microbiol. 2012;62:1–4.

    Article  Google Scholar 

  65. 65.

    Bernardet J-F. Class II. Flavobacteriia class. nov. In: Krieg NR, Staley JT, Brown DR, Hedlund BP, Paster BJ, Ward NL, Ludwig WWWB, editors. Bergey's Manual Of Systematic Bacteriology, The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes, vol. 4. 2nd ed. New York: Springer; 2010. p. 106–314.

    Google Scholar 

  66. 66.

    Euzéby J. Validation List N° 145. Int J Syst Evol Microbiol. 2012;62:1017–1019.

    Article  Google Scholar 

  67. 67.

    Bernardet JF. Order I. Flavobacteriales ord. nov. In: Krieg NR, Staley JT, Brown DR, Hedlund BP, Paster BJ, Ward NL, Ludwig W, Whitman WB, editors. Bergey's Manual of Systematic Bacteriology, The Bacteroidetes, Spirochaetes, Tenericutes (Mollicutes), Acidobacteria, Fibrobacteres, Fusobacteria, Dictyoglomi, Gemmatimonadetes, Lentisphaerae, Verrucomicrobia, Chlamydiae, and Planctomycetes, vol. 4. 2nd ed. New York: Springer; 2011. p. 105–329.

    Google Scholar 

  68. 68.

    Holmes B, Owen RJ. Proposal that Flavobacterium breve be substituted as the type species of the genus in place of Flavobacterium aquatile and emended description of the genus Flavobacterium: status of the named species of Flavobacterium, Request for an Opinion. Int J Syst Bacteriol. 1979;29:416–26.

    Article  Google Scholar 

  69. 69.

    BAuA 2010 – 2012 update, Classification of bacteria and archaea in risk groups. http://www.baua.de TRBA 466:19.

Download references

Acknowledgments

The authors gratefully acknowledge the help of Andrea Schütze for growing cells of GH29-5T and of Evelyne-Marie Brambilla (both at DSMZ), for DNA extraction and quality control. This work was performed under the auspices of the US Department of Energy's Office of Science, Biological and Environmental Research Program, and by the University of California, Lawrence Berkeley National Laboratory under contract No. DE-AC02-05CH11231. AL was supported by the St. Petersburg State University grant (No 1.38.253.2015). R.L.H. was supported by the Bundesministerium für Ernährung und Landwirtschaft No. 22016812 (PI Brian J. Tindall). We would also like to thank the Center of Nanotechnology at King Abdulaziz University for their support.

Authors’ contributions

HPK and NCK initiated the study. RLH, SS, NT, MF, NCK and HPK designed research and project outline. SS, NT, MF, RLH, JPMK, MG, BJT, HPK and NCK drafted the manuscript. AL, JH, MP, TBKR, MH, AP, NNI, VM, TW and NCK sequenced, assembled and annotated the genome. MNB and NAB provided financial support. SH performed CAZy and MEROPS analysis. RLH investigated the CAZymes and PUL. JPMK conducted comparative genomics. JPMK and RLA performed 16S rRNA based phylogeny. MR performed electron microscopy. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Author information

Affiliations

  1. Department of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia

    Nisreen Tashkandy, Sari Sabban, Mohammad Fakieh, Mohammed N. Baeshen, Nabih A. Baeshen & Nikos C. Kyrpides

  2. Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany

    Jan P. Meier-Kolthoff, Sixing Huang, Brian J. Tindall, Markus Göker & Richard L. Hahnke

  3. HZI – Helmholtz Centre for Infection Research, Braunschweig, Germany

    Manfred Rohde

  4. Center of Nanotechnology, King Abdulaziz University, Jeddah, Saudi Arabia

    Mohammed N. Baeshen & Nabih A. Baeshen

  5. Centre for Algorithmic Biotechnology, St. Petersburg State University, St. Petersburg, Russia

    Alla Lapidus

  6. Department of Energy Joint Genome Institute, Genome Biology Program, Walnut Creek, CA, USA

    Alex Copeland, T. B. K. Reddy, Marcel Huntemann, Amrita Pati, Natalia Ivanova, Tanja Woyke & Nikos C. Kyrpides

  7. Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Manoj Pillay & Victor Markowitz

  8. School of Biology, Newcastle University, Newcastle upon Tyne, UK

    Hans-Peter Klenk

Authors
  1. Nisreen Tashkandy
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sari Sabban
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mohammad Fakieh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jan P. Meier-Kolthoff
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sixing Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Brian J. Tindall
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Manfred Rohde
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Mohammed N. Baeshen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nabih A. Baeshen
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Alla Lapidus
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Alex Copeland
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Manoj Pillay
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. T. B. K. Reddy
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Marcel Huntemann
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Amrita Pati
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Natalia Ivanova
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Victor Markowitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Tanja Woyke
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Markus Göker
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Hans-Peter Klenk
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. Nikos C. Kyrpides
    View author publications

    You can also search for this author in PubMed Google Scholar

  22. Richard L. Hahnke
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nisreen Tashkandy.

Additional file

Additional file 1:

Table S1. Carbohydrate active enzymes (CAZymes) in the genome of F. suncheonense GH29-5T. Table S2. Sulfatases in the genome of F. suncheonense GH29-5T. Table S3. Peptidases or homologues in the genome of F. suncheonense GH29-5T. Table S4. Simple peptidases inhibitors in the genome of F. suncheonense GH29-5T. (DOCX 497 kb)

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Tashkandy, N., Sabban, S., Fakieh, M. et al. High-quality draft genome sequence of Flavobacterium suncheonense GH29-5T (DSM 17707T) isolated from greenhouse soil in South Korea, and emended description of Flavobacterium suncheonense GH29-5T . Stand in Genomic Sci 11, 42 (2016). https://doi.org/10.1186/s40793-016-0159-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40793-016-0159-5

Keywords

  • Aerobic
  • Gliding motility
  • Greenhouse soil
  • Flavobacteriaceae
  • Bacteroidetes
  • GEBA
  • KMG-1
  • Tree of Life
  • GGDC
  • Carbohydrate active enzyme
  • Polysaccharide utilization loci

Environmental Microbiome

ISSN: 2524-6372