Open Access

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

  • Amrita Pati1,
  • Sabine Gronow2,
  • Ahmet Zeytun1, 3,
  • Alla Lapidus1,
  • Matt Nolan1,
  • Nancy Hammon1,
  • Shweta Deshpande1,
  • Jan-Fang Cheng1,
  • Roxane Tapia1, 3,
  • Cliff Han1, 3,
  • Lynne Goodwin1, 3,
  • Sam Pitluck1,
  • Konstantinos Liolios1,
  • Ioanna Pagani1,
  • Natalia Ivanova1,
  • Konstantinos Mavromatis1,
  • Amy Chen4,
  • Krishna Palaniappan4,
  • Miriam Land1, 5,
  • Loren Hauser1, 5,
  • Yun-Juan Chang1, 5,
  • Cynthia D. Jeffries1, 5,
  • John C. Detter1,
  • Evelyne Brambilla2,
  • Manfred Rohde6,
  • Markus Göker2,
  • Tanja Woyke1,
  • James Bristow1,
  • Jonathan A. Eisen1, 7,
  • Victor Markowitz4,
  • Philip Hugenholtz1, 8,
  • Nikos C. Kyrpides1,
  • Hans-Peter Klenk2 and
  • Susan Lucas1
Standards in Genomic Sciences20114:4010045

https://doi.org/10.4056/sigs.1513795

Published: 4 March 2011

Abstract

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.

Keywords

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

Introduction

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].

MIGS ID

Property

Term

Evidence code

  

Domain Bacteria

TAS [13]

  

Phylum Bacteroidetes

TAS [14]

  

Class ‘Bacteroidia

TAS [15]

  

Order ‘Bacteroidales

TAS [16]

  

Family Bacteroidaceae

TAS [17,18]

  

Genus Bacteroides

TAS [17,1922]

  

Species Bacteroides helcogenes

TAS [2,23]

 

Current classification

Type strain P 36–108

TAS [2]

 

Gram stain

negative

TAS [2]

 

Cell shape

rod-shaped, single or in pairs

TAS [2]

 

Motility

non-motile

TAS [2]

 

Sporulation

none

TAS [2]

 

Temperature range

mesophile

TAS [2]

 

Optimum temperature

37°C

TAS [2]

 

Salinity

normal

TAS [2]

MIGS-22

Oxygen requirement

strictly anaerobic

TAS [2]

 

Carbon source

carbohydrates

TAS [2]

 

Energy source

chemoorganotroph

TAS [2]

MIGS-6

Habitat

host

TAS [2]

MIGS-15

Biotic relationship

free-living

TAS [2]

MIGS-14

Pathogenicity

animal pathogen

TAS [2]

 

Biosafety level

2

TAS [24]

 

Isolation

Sus scrofa abscess

TAS [2]

MIGS-4

Geographic location

Japan

TAS [2]

MIGS-5

Sample collection time

1974

TAS [2]

MIGS-4.1

Latitude

not reported

NAS

MIGS-4.2

Longitude

not reported

NAS

MIGS-4.3

Depth

not reported

NAS

MIGS-4.4

Altitude

not reported

NAS

Evidence codes - IDA: Inferred from Direct Assay (first time in publication); TAS: Traceable Author Statement (i.e., a direct report exists in the literature); NAS: Non-traceable Author Statement (i.e., not directly observed for the living, isolated sample, but based on a generally accepted property for the species, or anecdotal evidence). These evidence codes are from of the Gene Ontology project [25]. If the evidence code is IDA, then the property was directly observed by one of the authors or an expert mentioned in the acknowledgements.

Chemotaxonomy

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

MIGS ID

Property

Term

MIGS-31

Finishing quality

Finished

MIGS-28

Libraries used

Three genomic libraries: one 454 pyrosequence standard library, one 454 PE library (9 kb insert size), one Illumina library

MIGS-29

Sequencing platforms

Illumina GAii, 454 GS FLX Titanium

MIGS-31.2

Sequencing coverage

56.3 × Illumina; 36.7 × pyrosequence

MIGS-30

Assemblers

Newbler version 2.3-PreRelease-10-21-2009-gcc-4.1.2-threads, Velvet, phrap

MIGS-32

Gene calling method

Prodigal 1.4, GenePRIMP

 

INSDC ID

CP002352

 

Genbank Date of Release

January 18, 2011

 

GOLD ID

Gc01593

 

NCBI project ID

41913

 

Database: IMG-GEBA

2503538016

MIGS-13

Source material identifier

DSM 20613

 

Project relevance

Tree of Life, GEBA

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

Attribute

Value

% of Total

Genome size (bp)

3,998,906

100.00%

DNA coding region (bp)

3,583,947

89.62%

DNA G+C content (bp)

1,788,209

44.72%

Number of replicons

1

100.00%

Extrachromosomal elements

0

 

Total genes

3,436

100.00%

RNA genes

83

2.42%

rRNA operons

5

 

Protein-coding genes

3,353

97.58%

Pseudo genes

109

3.17%

Genes with function prediction

2,215

64.46%

Genes in paralog clusters

454

13.21%

Genes assigned to COGs

2103

61.20%

Genes assigned Pfam domains

2360

68.68%

Genes with signal peptides

980

28.52%

Genes with transmembrane helices

798

23.22%

CRISPR repeats

1

 
Table 4.

Number of genes associated with the general COG functional categories

Code

value

%age

Description

J

147

6.5

Translation, ribosomal structure and biogenesis

A

0

0

RNA processing and modification

K

157

6.9

Transcription

L

125

5.5

Replication, recombination and repair

B

0

0

Chromatin structure and dynamics

D

20

0.9

Cell cycle control, cell division, chromosome partitioning

Y

0

0

Nuclear structure

V

67

2.9

Defense mechanisms

T

125

5.5

Signal transduction mechanisms

M

245

10.8

Cell wall/membrane/envelope biogenesis

N

5

0.2

Cell motility

Z

0

0

Cytoskeleton

W

0

0

Extracellular structures

U

48

2.1

Intracellular trafficking, secretion, and vesicular transport

O

66

2.9

Posttranslational modification, protein turnover, chaperones

C

120

5.3

Energy production and conversion

G

185

8.1

Carbohydrate transport and metabolism

E

149

6.5

Amino acid transport and metabolism

F

67

2.9

Nucleotide transport and metabolism

H

120

5.3

Coenzyme transport and metabolism

I

64

2.8

Lipid transport and metabolism

P

161

7.6

Inorganic ion transport and metabolism

Q

20

0.9

Secondary metabolites biosynthesis, transport and catabolism

R

266

11.7

General function prediction only

S

122

5.4

Function unknown

-

1,333

38.8

Not in COGs

Declarations

Acknowledgements

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.

Authors’ Affiliations

(1)
DOE Joint Genome Institute
(2)
DSMZ - German Collection of Microorganisms and Cell Cultures GmbH
(3)
Bioscience Division, Los Alamos National Laboratory
(4)
Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory
(5)
Oak Ridge National Laboratory
(6)
HZI - Helmholtz Centre for Infection Research
(7)
University of California Davis Genome Center
(8)
Australian Centre for Ecogenomics, School of Chemistry and Molecular Biosciences, The University of Queensland

References

  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. 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.View ArticlePubMedGoogle Scholar
  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.03006-05PubMed CentralView ArticlePubMedGoogle Scholar
  4. Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137.View ArticleGoogle Scholar
  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.2008.07.001View ArticlePubMedGoogle Scholar
  6. Lee C, Grasso C, Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics 2002; 18:452–464. PubMed doi:10.1093/bioinformatics/18.3.452View ArticlePubMedGoogle Scholar
  7. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000; 17:540–552. PubMedView ArticlePubMedGoogle Scholar
  8. Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML web-servers. Syst Biol 2008; 57:758–771. PubMed doi:10.1080/10635150802429642View ArticlePubMedGoogle Scholar
  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_13View ArticleGoogle Scholar
  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/gkp848PubMed CentralView ArticlePubMedGoogle Scholar
  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.1107008View ArticlePubMedGoogle Scholar
  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/nbt1360PubMed CentralView ArticlePubMedGoogle Scholar
  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.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
  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.View ArticleGoogle Scholar
  15. Ludwig W, Euzeby J, Whitman WG. Draft taxonomic outline of the Bacteroidetes, Planctomycetes, Chlamydiae, Spirochaetes, Fibrobacteres, Fusobacteria, Acidobacteria, Verrucomicrobia, Dictyoglomi, and Gemmatimonadetes. http://www.bergeys.org/outlines/Bergeys_Vol_4_Outline.pdf. Taxonomic Outline 2008.
  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. Skerman VBD, McGowan V, Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol 1980; 30:225–420. doi:10.1099/00207713-30-1-225View ArticleGoogle Scholar
  18. Pribram E. Klassification der Schizomyceten. Klassifikation der Schizomyceten (Bakterien), Franz Deuticke, Leipzig, 1933, p. 1–143.Google Scholar
  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. 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. 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:10.1099/00207713-32-3-271View ArticleGoogle Scholar
  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:10.1099/00207713-39-1-85View ArticleGoogle Scholar
  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:10.1099/00207713-33-4-896Google Scholar
  24. Classification of bacteria and archaea in risk groups. http://www.baua.de TRBA 466.
  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:10.1038/75556PubMed CentralView ArticlePubMedGoogle Scholar
  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)90386-4View ArticlePubMedGoogle Scholar
  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.2010.03.003View ArticlePubMedGoogle Scholar
  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/nature08656PubMed CentralView ArticlePubMedGoogle Scholar
  29. List of growth media used at DSMZ: http://www.dsmz.de/microorganisms/media_list.php.
  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).Google Scholar
  31. DNA Bank Network. http://www.dnabank-network.org
  32. DOE Joint Genome Institute. http://www.jgi.doe.gov
  33. Phrap and Phred for Windows. MacOS, Linux, and Unix. http://www.phrap.com
  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.074492.107PubMed CentralView ArticlePubMedGoogle Scholar
  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.Google Scholar
  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. 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:10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
  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.1457View ArticlePubMedGoogle Scholar
  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/btp393View ArticlePubMedGoogle Scholar

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© The Author(s) 2011