Skip to main content

Complete genome sequence of Bacteroides helcogenes type strain (P 36–108T)


Bacteroides helcogenes Benno et al. 1983 is of interest because of its isolated phylogenetic location and, although it has been found in pig feces and is known to be pathogenic for pigs, occurrence of this bacterium is rare and it does not cause significant damage in intensive animal husbandry. The genome of B. helcogenes P 36–108T is already the fifth completed and published type strain genome from the genus Bacteroides in the family Bacteroidaceae. The 3,998,906 bp long genome with its 3,353 protein-coding and 83 RNA genes consists of one circular chromosome and is a part of the Genomic Encyclopedia of Bacteria and Archaea project.


Strain P 36–108T (= DSM 20613 = ATCC 35417 = JCM 6297) is the type strain of Bacteroides helcogenes, one of currently 39 species in the genus Bacteroides [12]. The species epithet of B. helcogenes is derived from the Greek noun helkos meaning ‘abscess’ and the Greek verb gennaio meaning ‘produce’, referring to the pathogenic, probably intestinal, abscess-producing properties of the species [2]. B. helcogenes strain P36-108T was isolated from a pig abscess in Japan, and described by Benno et al. in 1983 [2]. Nine further isolates of B. helcogenes have been obtained from pig abscesses whereas two other isolates originated from pig feces. Here we present a summary classification and a set of features for B. helcogenes P 36–108T, together with the description of the complete genomic sequencing and annotation.

Classification and features

A representative genomic 16S rRNA sequence of B. helcogenes was compared using NCBI BLAST under default values (e.g., considering only the high-scoring segment pairs (HSPs) from the best 250 hits) with the most recent release of the Greengenes database [3] and the relative frequencies, weighted by BLAST scores, of taxa and keywords (reduced to their stem [4]) were determined. The single most frequent genus was Bacteroides (100%) (33 hits in total). Regarding the 21 hits to sequences from other members of the genus, the average identity within HSPs was 92.7%, whereas the average coverage by HSPs was 84.5%. Among all other species, the one yielding the highest score was Bacteroides ovatus, which corresponded to an identity of 93.4% and a HSP coverage of 86.6%. The highest-scoring environmental sequence was AM275453 (‘fecal microbiota irritable bowel syndrome patients differs significantly from that of healthy subjects’), which showed an identity of 95.5% and a HSP coverage of 84.3%. The most frequently occurring keywords within the labels of environmental samples which yielded hits were ‘human’ (11.0%), ‘fecal’ (9.5%), ‘microbiota’ (8.8%), ‘sequenc’ (5.4%) and ‘gut’ (5.4%) (217 hits in total). The most frequently occurring keywords within the labels of environmental samples which yielded hits of a higher score than the highest scoring species were ‘fecal/human’ (13.3%), ‘feedlot’ (5.2%), ‘bowel, faecal, healthi, irrit, microbiota, patient, significantli, subject, syndrom’ (2.7%) and ‘beef, cattl, coli, escherichia, feedbunk, habitat, marc, materi, neg, pen, primari, secondari, stec, surfac, synecolog, top, west’ (2.6%) (6 hits in total). Most of these keywords are in accordance with the isolation sites of the different isolates and strongly suggest that B. helcogenes, like many other species of the genus Bacteroides, is associated with the intestinal tract of the host in the case of B. helcogenes, this host is the pig [2].

Figure 1 shows the phylogenetic neighborhood of B. helcogenes P 36–108T in a 16S rRNA based tree. The sequences of the five 16S rRNA gene copies in the genome differ from each other by up to 20 nucleotides, and differ by up to 13 nucleotides from the previously published 16S rRNA sequence (AB200227).

Figure 1.

Phylogenetic tree highlighting the position of B. helcogenes relative to those type strains within the genus that appeared within a monophyletic Bacteroides main clade in preliminary analyses. Note that several of the Bacteroides type strain 16S rRNA sequences (from B. cellulosolvens, B. galacturonicus, B. pectinophilus, B. vulgatus) did not cluster together with this clade (data not shown, but see [5]) and were omitted from the main phylogenetic inference analysis. The same holds for the sequence from Anaerorhabdus furcosa (GU585668; also Bacteroidaceae). Other Bacteroides species lacked a sufficiently long 16S rRNA sequence and also had to be omitted (B. coagulans, B. xylanolyticus). The tree was inferred from 1,414 aligned characters [67] of the 16S rRNA gene sequence under the maximum likelihood criterion [8] and rooted with the type strain of the family ‘Prevotellaceae’. The branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values from 1,000 bootstrap replicates [9] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [10] are shown in blue, published genomes [11] and Prevotella melaninogenica released Genbank accession CP002122 in bold.

The cells of B. helcogenes generally have the shape of short rods (0.5–0.6 εm × 0.8–4.0 µm) which occur singly or in pairs (Figure 2). B. helcogenes is a Gram-negative, non-pigmented and non spore-forming bacterium (Table 1). The organism is originally described as nonmotile and only five genes associated with motility have been found in the genome (see below). The organism grows well at 37°C but does not grow at 4°C or at 45°C [2]. B. helcogenes is strictly anaerobic, chemoorganotrophic and is able to ferment glucose, mannose, fructose, galactose, sucrose, maltose, cellobiose, lactose, xylose, melibiose, raffinose, starch, glycogen, salicin, amygdalin, and xylan [2]. The organism hydrolyzes esculin and starch but does not digest casein, liquify gelatin, reduce nitrate nor produce indole from tryptophan [2]. B. helcogenes does not utilize arabinose, ramnose, ribose, trehalose, inulin, glycerol, mannitol, sorbitol, inositol, adonitol, erythritol or gum Arabic [2]. It does not require hemin for growth but does require the presence of CO2; it does not show hemolysis. Growth is not enhanced by the addition of 20% bile [2]. Major fermentation products from PYFG broth (peptone yeast extract Fildes glucose broth [26]) are acetic acid and succinic acid; propionic and isobutyric acid are produced in small amounts [2]. B. helcogenes is phosphatase, DNase, β-glucuronidase, and glutamic acid decarboxylase active and urease, catalase, lecithinase and lipase inactive [2]. The organism produces ammonium and chondroitin sulfatase [2]. B. helcogenes can grow in the presence of kanamycin (1mg/ml), vancomycin (10 µg/ml), colistin (10 µg/ml), erythromycin (60 µg/ml) or polymyxin B (10 µg/ml) but not in the presence of cepharothin (10 µg/ml) or Brilliant green (0.001%) [2].

Figure 2.

Scanning electron micrograph of B. helcogenes P 36–108T

Table 1. Classification and general features of B. helcogenes P 36–108T according to the MIGS recommendations [12].


Little chemotaxonomic information is available for strain P 36–108T. Thus far, only the fatty acid composition has been elucidated. The major fatty acids found (>10%) were anteiso-C15:0, C15:0 and iso-C15:0.3-OH. Also, iso-C15:0, C16:0, and cis C18:1 were detected in a proportion ranging between 5% to 10% of the total fatty acids (unpublished data).

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [27], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [28]. The genome project is deposited in the Genomes OnLine Database [10] and the complete genome sequence is deposited in GenBank. Sequencing, finishing and annotation were performed by the DOE Joint Genome Institute (JGI). A summary of the project information is shown in Table 2.

Table 2. Genome sequencing project information

Growth conditions and DNA isolation

B. helcogenes P 36–108T, DSM 20613, was grown anaerobically in medium 104 (PYG Medium) [29] at 37°C. DNA was isolated from 0.5–1 g of cell paste using MasterPure Gram-positive DNA purification kit (Epicentre MGP04100) following the standard protocol as recommended by the manufacturer, with modification st/DL for cell lysis as described in Wu et al. [28]. DNA is available through the DNA Bank Network [3031].

Genome sequencing and assembly

The genome was sequenced using a combination of Illumina and 454 sequencing platforms. All general aspects of library construction and sequencing can be found at the JGI website [32]. Pyrosequencing reads were assembled using the Newbler assembler version 2.3-PreRelease-10-21-2009-gcc-4.1.2-threads (Roche). The initial Newbler assembly consisting of 48 contigs in two scaffolds was converted into a phrap assembly by [33] making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (225.3 Mb) was assembled with Velvet [34] and the consensus sequences were shredded into 1.5 kb overlapped fake reads and assembled together with the 454 data. The 454 draft assembly was based on 146.7 Mb 454 draft data and all of the 454 paired end data. Newbler parameters are -consed -a 50 -l 350 -g -m -ml 20. The Phred/Phrap/Consed software package [33] was used for sequence assembly and quality assessment in the subsequent finishing process. After the shotgun stage, reads were assembled with parallel phrap (High Performance Software, LLC). Possible mis-assemblies were corrected with gapResolution [32], Dupfinisher [35], or sequencing cloned bridging PCR fragments with subcloning or transposon bombing (Epicentre Biotechnologies, Madison, WI). Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F.Chang, unpublished). A total of 160 additional reactions and 4 shatter libraries were necessary to close gaps and to raise the quality of the finished sequence. Illumina reads were also used to correct potential base errors and increase consensus quality using a software Polisher developed at JGI [36]. The error rate of the completed genome sequence is less than 1 in 100,000. Together, the combination of the Illumina and 454 sequencing platforms provided 93 × coverage of the genome. The final assembly contained 500,148 pyrosequence and 6,257,254 Illumina reads.

Genome annotation

Genes were identified using Prodigal [37] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [38]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGR-Fam, Pfam, PRIAM, KEGG, COG, and InterPro databases. Additional gene prediction analysis and functional annotation was performed within the Integrated Microbial Genomes - Expert Review (IMG-ER) platform [39].

Genome properties

The genome consists of a 3,998,906 bp long chromosome with a GC content of 44.7% (Table 3 and Figure 3). Of the 3,436 genes predicted, 3,353 were protein-coding genes, and 83 RNAs; 109 pseudogenes were also identified. The majority of the protein-coding genes (64.5%) were assigned with a putative function while the remaining ones were annotated as hypothetical proteins. The distribution of genes into COGs functional categories is presented in Table 4.

Figure 3.

Graphical circular map of the chromosome. From outside to the center: Genes on forward strand (color by COG categories), Genes on reverse strand (color by COG categories), RNA genes (tRNAs green, rRNAs red, other RNAs black), GC content, GC skew.

Table 3. Genome Statistics
Table 4. Number of genes associated with the general COG functional categories


  1. 1.

    Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today 2010; 7:1.

    Google Scholar 

  2. 2.

    Benno Y, Watabe J, Mitsuoka T. Bacteroides pyogenes sp. nov., Bacteroides suis sp. nov., and Bacteroides helcogenes sp. nov., new species from abscesses and feces of pigs. Syst Appl Microbiol 1983; 4:396–407.

    Article  CAS  PubMed  Google Scholar 

  3. 3.

    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; 72:5069–5072. PubMed doi:10.1128/AEM.03006-05

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  4. 4.

    Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137.

    Article  Google Scholar 

  5. 5.

    Yarza P, Richter M, Peplies J, Euzeby J, Amann R, Schleifer KH, Ludwig W, Glöckner FO, Rosselló-Móra R. The all-species living tree project: A 16S rRNA-based phylogenetic tree of all sequenced type strains. Syst Appl Microbiol 2008; 31:241–250. PubMed doi:10.1016/j.syapm.2008.07.001

    Article  CAS  PubMed  Google Scholar 

  6. 6.

    Lee C, Grasso C, Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics 2002; 18:452–464. PubMed doi:10.1093/bioinformatics/18.3.452

    Article  CAS  PubMed  Google Scholar 

  7. 7.

    Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000; 17:540–552. PubMed

    Article  CAS  PubMed  Google Scholar 

  8. 8.

    Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML web-servers. Syst Biol 2008; 57:758–771. PubMed doi:10.1080/10635150802429642

    Article  PubMed  Google Scholar 

  9. 9.

    Pattengale ND, Alipour M, Bininda-Emonds ORP, Moret BME, Stamatakis A. How Many Bootstrap Replicates Are Necessary? Lect Notes Comput Sci 2009; 5541:184–200. doi:10.1007/978-3-642-02008-7_13

    Article  CAS  Google Scholar 

  10. 10.

    Liolios K, Chen IM, Mavromatis K, Tavernarakis N, Hugenholtz P, Markowitz VM, Kyrpides NC. The Genomes OnLine Database (GOLD) in 2009: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2010; 38:D346–D354. PubMed doi:10.1093/nar/gkp848

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  11. 11.

    Cerdeño-Tärraga AM, Patrick S, Crossman LC, Blakely G, Abratt V, Lennard N, Poxton I, Duerden B, Harris B, Quail MA, et al. Extensive DNA inversions in the B. fragilis genome control variable gene expression. Science 2005; 307:1463–1465. PubMed doi:10.1126/science.1107008

    Article  PubMed  Google Scholar 

  12. 12.

    Field D, Garrity G, Gray T, Morrison N, Selengut J, Sterk P, Tatusova T, Thomson N, Allen MJ, Angiuoli SV, et al. The minimum information about a genome sequence (MIGS) specification. Nat Biotechnol 2008; 26:541–547. PubMed doi:10.1038/nbt1360

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  13. 13.

    Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci USA 1990; 87:4576–4579. PubMed doi:10.1073/pnas.87.12.4576

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  14. 14.

    Garrity GM, Holt JG. The Road Map to the Manual. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 1. Springer, New York 2001:119–169.

    Chapter  Google Scholar 

  15. 15.

    Ludwig W, Euzeby J, Whitman WG. Draft taxonomic outline of the Bacteroidetes, Planctomycetes, Chlamydiae, Spirochaetes, Fibrobacteres, Fusobacteria, Acidobacteria, Verrucomicrobia, Dictyoglomi, and Gemmatimonadetes. Taxonomic Outline 2008.

  16. 16.

    Garrity GM, Holt JG. Taxonomic Outline of the Archaea and Bacteria. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 155–166.

    Google Scholar 

  17. 17.

    Skerman VBD, McGowan V, Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol 1980; 30:225–420. doi:10.1099/00207713-30-1-225

    Article  Google Scholar 

  18. 18.

    Pribram E. Klassification der Schizomyceten. Klassifikation der Schizomyceten (Bakterien), Franz Deuticke, Leipzig, 1933, p. 1–143.

    Google Scholar 

  19. 19.

    Castellani A, Chalmers AJ. Genus Bacteroides Castellani and Chalmers, 1918. Manual of Tropical Medicine, Third Edition, Williams, Wood and Co., New York, 1919, p. 959–960.

    Google Scholar 

  20. 20.

    Holdeman LV, Moore WEC. Genus I. Bacteroides Castellani and Chalmers 1919, 959. In: Buchanan RE, Gibbons NE (eds), Bergey’s Manual of Determinative Bacteriology, Eighth Edition, The Williams and Wilkins Co., Baltimore, 1974, p. 385–404.

    Google Scholar 

  21. 21.

    Cato EP, Kelley RW, Moore WEC, Holdeman LV. Bacteroides zoogleoformans, Weinberg, Nativelle, and Prévot 1937) corrig. comb. nov.: emended description. Int J Syst Bacteriol 1982; 32:271–274. doi:10.1099/00207713-32-3-271

    Article  CAS  Google Scholar 

  22. 22.

    Shah HN, Collins MD. Proposal to restrict the genus Bacteroides (Castellani and Chalmers) to Bacteroides fragilis and closely related species. Int J Syst Bacteriol 1989; 39:85–87. doi:10.1099/00207713-39-1-85

    Article  Google Scholar 

  23. 23.

    Validation List no. 12. Validation of the publication of new names and new combinations previously effectively published outside the IJSB. Int J Syst Bacteriol 1983; 33:896–897. doi:10.1099/00207713-33-4-896

  24. 24.

    Classification of bacteria and archaea in risk groups. TRBA 466.

  25. 25.

    Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT, et al. Gene Ontology: tool for the unification of biology. Nat Genet 2000; 25:25–29. PubMed doi:10.1038/75556

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  26. 26.

    Saito H, Miura K. Preparation of transfroming deoxyribonucleic acid by phenol treatment. Biochim Biophys Acta 1963; 72:619–629. PubMed doi:10.1016/0926-6550(63)90386-4

    Article  CAS  PubMed  Google Scholar 

  27. 27.

    Klenk HP, Goeker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol 2010; 33:175–182. PubMed doi:10.1016/j.syapm.2010.03.003

    Article  CAS  PubMed  Google Scholar 

  28. 28.

    Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova NN, Kunin V, Goodwin L, Wu M, Tindall BJ, et al. A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature 2009; 462:1056–1060. PubMed doi:10.1038/nature08656

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  29. 29.

    List of growth media used at DSMZ:

  30. 30.

    Gemeinholzer B, Dröge G, Zetzsche H, Haszprunar G, Klenk HP, Güntsch A, Berendsohn WG, Wägele JW. The DNA Bank Network: the start from a German initiative. Biopreservation and Biobanking. (In press).

  31. 31.

    DNA Bank Network.

  32. 32.

    DOE Joint Genome Institute.

  33. 33.

    Phrap and Phred for Windows. MacOS, Linux, and Unix.

  34. 34.

    Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829. PubMed doi:10.1101/gr.074492.107

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  35. 35.

    Han C, Chain P. 2006. Finishing repeat regions automatically with Dupfinisher. in Proceeding of the 2006 international conference on bioinformatics & computational biology. Edited by Hamid R. Arabnia & Homayoun Valafar, CSREA Press. June 26–29, 2006: 141–146.

  36. 36.

    Lapidus A, LaButti K, Foster B, Lowry S, Trong S, Goltsman E. POLISHER: An effective tool for using ultra short reads in microbial genome assembly and finishing. AGBT, Marco Island, FL, 2008.

    Google Scholar 

  37. 37.

    Hyatt D, Chen GL, LoCascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119. PubMed doi:10.1186/1471-2105-11-119

    PubMed Central  Article  PubMed  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; 7:455–457. PubMed doi:10.1038/nmeth.1457

    Article  CAS  PubMed  Google Scholar 

  39. 39.

    Markowitz VM, Ivanova NN, Chen IMA, Chu K, Kyrpides NC. IMG ER: a system for microbial genome annotation expert review and curation. Bioinformatics 2009; 25:2271–2278. PubMed doi:10.1093/bioinformatics/btp393

    Article  CAS  PubMed  Google Scholar 

Download references


We would like to gratefully acknowledge the help of Sabine Welnitz (DSMZ) for growing B. helcogenes cultures. This work was performed under the auspices of the US Department of Energy Office of Science, Biological and Environmental Research Program, and by the University of California, Lawrence Berkeley National Laboratory under contract No. DE-AC02-05CH11231, Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344, and Los Alamos National Laboratory under contract No. DE-AC02-06NA25396, UT-Battelle and Oak Ridge National Laboratory under contract DE-AC05-00OR22725, as well as German Research Foundation (DFG) INST 599/1-2.

Author information



Corresponding author

Correspondence to Hans-Peter Klenk.

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

Reprints and Permissions

About this article

Cite this article

Pati, A., Gronow, S., Zeytun, A. et al. Complete genome sequence of Bacteroides helcogenes type strain (P 36–108T). Stand in Genomic Sci 4, 45–53 (2011).

Download citation


  • strictly anaerobic
  • mesophilic
  • nonmotile
  • Gram-negative
  • chemoorganotrophic
  • pig abscess
  • animal pathogen
  • Bacteroidaceae
  • GEBA