Genome sequence of the moderately thermophilic sulfur-reducing bacterium Thermanaerovibrio velox type strain (Z-9701T) and emended description of the genus Thermanaerovibrio
- Krishna Palaniappan1,
- Jan P. Meier-Kolthoff2,
- Hazuki Teshima1, 3,
- Matt Nolan1,
- Alla Lapidus4, 5,
- Hope Tice1,
- Tijana Glavina Del Rio1,
- Jan-Fang Cheng1,
- Cliff Han1, 3,
- Roxanne Tapia1, 3,
- Lynne A. Goodwin1, 3,
- Sam Pitluck1,
- Konstantinos Liolios1,
- Konstantinos Mavromatis1,
- Ioanna Pagani1,
- Natalia Ivanova1,
- Natalia Mikhailova1,
- Amrita Pati1,
- Amy Chen6,
- Manfred Rohde7,
- Shanmugam Mayilraj8,
- Stefan Spring2,
- John C. Detter1, 3,
- Markus Göker2,
- James Bristow1,
- Jonathan A. Eisen1, 9,
- Victor Markowitz6,
- Philip Hugenholtz1, 10,
- Nikos C. Kyrpides1,
- Hans-Peter Klenk2Email author and
- Tanja Woyke1
© The Author(s) 2013
Published: 16 October 2013
Thermanaerovibrio velox Zavarzina et al. 2000 is a member of the Synergistaceae, a family in the phylum Synergistetes that is already well-characterized at the genome level. Members of this phylum were described as Gram-negative staining anaerobic bacteria with a rod/vibrioid cell shape and possessing an atypical outer cell envelope. They inhabit a large variety of anaerobic environments including soil, oil wells, wastewater treatment plants and animal gastrointestinal tracts. They are also found to be linked to sites of human diseases such as cysts, abscesses, and areas of periodontal disease. The moderately thermophilic and organotrophic T. velox shares most of its morphologic and physiologic features with the closely related species, T. acidaminovorans. In addition to Su883T, the type strain of T. acidaminovorans, stain Z-9701T is the second type strain in the genus Thermanaerovibrio to have its genome sequence published. Here we describe the features of this organism, together with the non-contiguous genome sequence and annotation. The 1,880,838 bp long chromosome (non-contiguous finished sequence) with its 1,751 protein-coding and 59 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.
Keywordsobligate anaerobic motile curved rods organotrophic S0-reduction cyanobacterial mat Synergistaceae Synergistetes GEBA
Strain Z-9701T (= DSM 12556) is the type strain of the species Thermanaerovibrio velox  in the bispecific genus Thermanaerovibrio . The strain was isolated in 1997 from a sample of a cyanobacterial mat from the Uzon caldera in Kamchatka (Russia) . The genus name is derived from the Greek words “thermos”, hot, “an”, not, and “aeros”, air, and the Neo-Latin “vibrio”, that vibrates, meaning a thermophilic vibrating anaerobe . The species epithet is derived from the Latin adjective “velox”, quick, rapid . In addition to the type species, Thermanaerovibrio acidaminovorans , T. velox is the only other member of the genus Thermanaerovibrio . In the decade following the isolation of strain Z-9701T and description of the species T. velox, the name was never mentioned in any abstract appearing in PubMed. Here we present a summary classification and a set of features for T. velox Z-9701T, together with the description of the genomic sequencing and annotation.
Classification and features
A representative genomic 16S rRNA gene sequence of strain Z-9701T was compared using NCBI BLAST [4,5] under default settings (e.g., considering only the high-scoring segment pairs (HSPs) from the best 250 hits) with the most recent release of the Greengenes database  and the relative frequencies of taxa and keywords (reduced to their stem ) were determined, weighted by BLAST scores. The most frequently occurring genera were Thermanaerovibrio (83.8%), Aminomonas (8.5%) and Thermovirga (7.7%) (9 hits in total). Regarding the two hits to sequences from members of the species, the average identity within HSPs was 96.7%, whereas the average coverage by HSPs was 100.5%. Regarding the four hits to sequences from other members of the genus, the average identity within HSPs was 94.9%, whereas the average coverage by HSPs was 96.4%. Among all other species, the one yielding the highest score was T. acidaminovorans (CP001818), which corresponded to an identity of 95.3% and an HSP coverage of 99.7%. (Note that the Greengenes database uses the INSDC (= EMBL/NCBI/DDBJ) annotation, which is not an authoritative source for nomenclature or classification.) The highest-scoring environmental sequence was AF280820 (‘bioreactor clone tbr1-2’), which showed an identity of 94.7% and an HSP coverage of 99.7%. The most frequently occurring keywords within the labels of all environmental samples which yielded hits were ‘digest’ (12.2%), ‘anaerob’ (7.2%), ‘wastewat’ (6.6%), ‘mesophil’ (6.5%) and ‘treat’ (6.4%) (241 hits in total), indicating that close relatives of T. velox could also thrive at lower temperatures in anaerobic aqueous environments. Environmental samples which yielded hits of a higher score than the highest scoring species were not found.
Species Thermanaerovibrio velox
Type strain Z-9701
no NaCl required for growth, but can tolerate up to 35 g l−1
glucose, fructose, mannose, yeast extract
Uzon caldera, Kamchatka, Russia
Sample collection time
1997 or earlier
about 1617 m
Genome sequencing and annotation
Genome project history
Genome sequencing project information
Three genomic libraries: one 454 pyrosequence standard library, one 454 PE library (7 kb insert size), one Illumina library
Illumina GAii, 454 GS FLX Titanium
120.0 × Illumina; 7.9 × pyrosequence
Newbler version 2.3, Velvet 1.0.13, phrap version SPS - 4.24
Gene calling method
GenBank Date of Release
December 19, 2011
NCBI project ID
Source material identifier
Tree of Life, GEBA
Growth conditions and DNA isolation
T. velox strain Z-9701T, DSM 12556, was grown anaerobically (with 8:2 N2/CO2 v/v in the head space) in DSMZ medium 873 (Thermanaerovibrio medium)  at 60°C. DNA was isolated from 0.5–1 g of cell paste using Jetflex Genomic DNA Purification kit (GENOMED 600100) following the standard protocol as recommended by the manufacturer, but with an additional step for improved cell lysis: 30 min incubation with additional 40 µl protease K at 58°C. DNA is available through the DNA Bank Network .
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 . Pyrosequencing reads were assembled using the Newbler assembler (Roche). The initial Newbler assembly consisting of 32 contigs in one scaffold was converted into a phrap  assembly by making fake reads from the consensus, to collect the read pairs in the 454 paired end library. Illumina GAii sequencing data (5,956 Mb) was assembled with Velvet  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 29.5Mb 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  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 , Dupfinisher , or sequencing cloned bridging PCR fragments with subcloning. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F. Chang, unpublished). A total of 46 additional reactions and one shatter library were necessary to close gaps and to raise the quality of the final sequence. Illumina reads were also used to correct potential base errors and increase consensus quality using the software Polisher developed at JGI . The error rate of the final genome sequence is less than 1 in 100,000. Together, the combination of the Illumina and 454 sequencing platforms provided 127.9 × coverage of the genome. The final assembly contained 102,371 pyrosequence and 3,000,000 Illumina reads.
Genes were identified using Prodigal  as part of the DOE-JGI  genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline . The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) non-redundant database, UniProt, TIGRFam, Pfam, PRIAM, KEGG, COG, and InterPro databases. 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 Integrated Microbial Genomes - Expert Review (IMG-ER) platform .
% of Total
Genome size (bp)
DNA coding region (bp)
DNA G+C content (bp)
Number of replicons
Genes with function prediction (proteins)
Genes in paralog clusters
Genes assigned to COGs
Genes assigned Pfam domains
Genes with signal peptides
Genes with transmembrane helices
Number of genes associated with the general COG functional categories
Translation, ribosomal structure and biogenesis
RNA processing and modification
Replication, recombination and repair
Chromatin structure and dynamics
Cell cycle control, cell division, chromosome partitioning
Signal transduction mechanisms
Cell wall/membrane biogenesis
Intracellular trafficking and secretion, and vesicular transport
Posttranslational modification, protein turnover, chaperones
Energy production and conversion
Carbohydrate transport and metabolism
Amino acid transport and metabolism
Nucleotide transport and metabolism
Coenzyme transport and metabolism
Lipid transport and metabolism
Inorganic ion transport and metabolism
Secondary metabolites biosynthesis, transport and catabolism
General function prediction only
Not in COGs
Insights into the genome sequence
The phylum Synergistetes is one of the more recently proposed phyla in the domain Bacteria, posited only four years ago by Jumas-Bilak et al. . As of today the phylum contains only one order, Synergistales, with one family, Synergistaceae, including 11 genera with 18 species (see Figure 1). The members of the phylum are extremely well characterized on the genomic level, with 12 out of the 18 type strains for the member species having already completed or ongoing genome sequencing projects, one type strain targeted for sequencing (Anaerobacterium thermoterrum) and only four type strains currently not indicated for genome sequencing in the Genomes On Line Database (GOLD) . Here we present a brief comparison of the genome of T. velox with its closest phylogenetic neighbors (according to Figure 1): T. acidamonovorans  and A. paucivorans .
Pairwise comparison of T. velox with T. acidaminovorans and A. paucivorans using the GGDC-Genome-to-Genome Distance Calculator.
HSP length / total length [%]
Identities / HSP length [%]
Identities / total length [%]
The comparison of T. velox with T. acidaminovorans reached the highest scores using the GGDC, 44% of the average of genome length are covered with HSPs (Table 5). The identity within the HSPs was 78%, whereas the identity over the whole genome was 35%. Lower similarity scores were observed in the comparison of T. velox with A. paucivorans, only 17% of the average of both genome lengths are covered with HSPs. The identity within these HSPs was 77%, whereas the identity over the whole genome was only 13%.
With regard to T. velox and T. acidaminovorans the corresponding DDH estimates were below the 70% threshold under formulas 1–3 throughout: 27.2% (±3.5), 20.4% (±2.3) and 24.6% (±3.0). The DDH estimated confidence intervals are given in parentheses as provided by . These results are in line with a previously reported wet-lab DDH value of 15% (±1) 
As expected, those distances relating HSP coverage (formula 1) and number of identical base pairs within HSPs to total genome length (formula 3) are higher between the T. velox and T. acidaminovorans than between T. velox and A. paucivorans. That the distances relating the number of identical base pairs to total HSP length (formula 2) behave differently indicates that the genomic similarities between T. velox, T. acidaminovorans and A. paucivorans are strongly restricted to more conserved sequences, a kind of saturation phenomenon .
In order to compare the T. velox and T. acidaminovorans genomes, correlation values (Pearson coefficient) according to the similarity on the level of COG category, pfam and TIGRfam were calculated. A very high correlation value (0.98) was reached on the level of pfam data; the correlation values on the basis of COG and TIGRfam data were only slightly smaller; 0.95 and 0.97, respectively. As a correlation value of 1 indicates the highest correlation, we can find a near perfect correlation between the genomes of T. velox and T. acidaminovorans considering the above data .
The comparison of the number of genes belonging to different COG categories revealed no large differences in the genomes of T. velox and T. acidaminovorans, with only 0.2% deviation between the same COG categories on average. A slightly higher fraction of genes belonging to the categories amino acid metabolism (T. velox 11.8%, T. acidaminovorans 11.4%), carbohydrate metabolism (T. velox 5.7%, T. acidaminovorans 5.3%) and defense mechanisms (T. velox 1.0%, T. acidaminovorans 0.7%) were identified in T. velox. The gene count in further COG categories such as cell cycle control, cell motility, cell biogenesis, lipid metabolism, secondary catabolism, posttranslational modification and signal transduction was also slightly increased in T. velox, but differed at most by 5 genes. In contrast, a slightly smaller fraction of genes belonging to the categories translation (T. velox 8.8%, T. acidaminovorans 9.2%), nucleotide metabolism (T. velox 3.7%, T. acidaminovorans 4.0%), transcription (T. velox 4.9%, T. acidaminovorans 5.1%), replication systems (T. velox 4.1%, T. acidaminovorans 4.3%) and inorganic ion transport and metabolism (T. velox 3.7%, T. acidaminovorans 3.9%) were also identified in T. velox. The remaining COG categories of intracellular transport, energy production/conversion and coenzyme metabolism differed at most by two genes.
The significant difference between the previously reported G+C content of strain Z-9701T, 54.6%  and the G+C content as inferred from the draft genome sequence, 58.8% (Table 3), as well as the similarly significant difference between the G+C content reported for the type strain of the other validly named species in the genus, T. acidaminovorans , Su883T, 56.6%  vs. 63.8% from the genome sequence  demands the emendation of the species and genus descriptions, which were last updated by Baena et al. 1999  and Zavarzina et al. in 2000 .
Emended description of the species Thermanaerovibrio acetaminovorans Guangsheng et al. 1997 emend. Baena et al. 1999
Emended description of the species Thermanaerovibrio velox Zavarzina et al. 2000
The description of the species Thermanaerovibrio velox is the one given by Zavarzina et al. , with the following modification. The G+C content is 58.8 mol%.
Emended description of the genus Thermanaerovibrio Baena et al. 1999 emend. Zavarzina et al. 2000
The description of the genus Thermanaerovibrio is the one given by Zavarzina et al. , with the following modification. The G+C content is between 58.8 and 63.8 mol%.
We would like to gratefully acknowledge the help of Maren Schröder for growing T. velox cultures, and Evelyne-Marie Brambilla for DNA extraction and quality control (both at DSMZ). 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. The work was further supported by German Research Foundation (DFG) INST 599/1-2 (for DNA generation) and in part by the Russian Ministry of Science Mega-grant no.11.G34.31.0068; SJ O’Brien Principal Investigator. The Council of Scientific and Industrial Research (CSIR, India) and DAAD, Germany, provided a Fellowship to Shanmugam Mayilraj.
- Zavarzina DG, Zhilina TN, Tourova TP, Kuznetsov BB, Kostrikina NA, Bonch-Osmolovskaya EA. Thermanaerovibrio velox sp. nov., a new anaerobic, thermophilic, organotrophic bacterium that reduces elemental sulfur, and emended description of the genus Thermanaerovibrio. Int J Syst Evol Microbiol 2000; 50:1287–1295. PubMed http://dx.doi.org/10.1099/00207713-50-3-1287View ArticlePubMedGoogle Scholar
- Baena S, Faredeau ML, Woo THS, Ollivier B, Labat B, Patel BKC. Phylogenetic relationships of three amino-acid-utilizing anaerobes, Selenomonas acidaminovorans, “Selenomonas acidaminophila” and Eubacterium acidaminophilum, as inferred from partial 16S rDNA nucleotide sequences, and proposal of Thermanaerovibrio acidaminovorans gen. nov., comb. nov. and Anaeromusa acidaminophila gen. nov., comb. nov. Int J Syst Bacteriol 1999; 49:969–974. PubMed http://dx.doi.org/10.1099/00207713-49-3-969View ArticlePubMedGoogle Scholar
- Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today 2010; 37:9.Google Scholar
- Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410. PubMedView ArticlePubMedGoogle Scholar
- Korf I, Yandell M, Bedell J. BLAST, O’Reilly, Sebastopol, 2003.Google Scholar
- 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 http://dx.doi.org/10.1128/AEM.03006-05PubMed CentralView ArticlePubMedGoogle Scholar
- Porter MF. An algorithm for suffix stripping. Program: electronic library and information systems 1980; 14:130–137.View ArticleGoogle Scholar
- Lee C, Grasso C, Sharlow MF. Multiple sequence alignment using partial order graphs. Bioinformatics 2002; 18:452–464. PubMed http://dx.doi.org/10.1093/bioinformatics/18.3.452View ArticlePubMedGoogle Scholar
- Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000; 17:540–552. PubMed http://dx.doi.org/10.1093/oxfordjournals.molbev.a026334View ArticlePubMedGoogle Scholar
- Stamatakis A, Hoover P, Rougemont J. A rapid bootstrap algorithm for the RAxML web servers. Syst Biol 2008; 57:758–771. PubMed http://dx.doi.org/10.1080/10635150802429642View ArticlePubMedGoogle Scholar
- Hess PN, De Moraes Russo CA. An empirical test of the midpoint rooting method. Biol J Linn Soc Lond 2007; 92:669–674. http://dx.doi.org/10.1111/j.1095-8312.2007.00864.xView ArticleGoogle Scholar
- 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. http://dx.doi.org/10.1007/978-3-642-02008-7_13View ArticleGoogle Scholar
- Swofford DL. PAUP*: Phylogenetic Analysis Using Parsimony (*and Other Methods), Version 4.0 b10. Sinauer Associates, Sunderland, 2002.Google Scholar
- Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, Markowitz VM, Kyrpides NC. The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata. Nucleic Acids Res 2012; 40:D571–D579. PubMed http://dx.doi.org/10.1093/nar/gkr1100PubMed CentralView ArticlePubMedGoogle Scholar
- Chertkov O, Sikorski J, Brambilla E, Lapidus A, Copeland A, Glavina Del Rio T, Nolan M, Lucas S, Tice H, Cheng JF, et al. Complete genome sequence of Aminobacterium colombiense type strain (ALA-1T). Stand Genomic Sci 2010; 2:280–289. PubMed http://dx.doi.org/10.4056/sigs.902116PubMed CentralView ArticlePubMedGoogle Scholar
- Göker M, Saunders E, Lapidus A, Nolan M, Lucas S, Hammon N, Deshpande S, Cheng JF, Han C, Tapia R, et al. Genome sequence of the moderately thermophilic, amino-acid-degrading and sulfur-reducing bacterium Thermovirga lienii type strain (Cas60314T). Stand Genomic Sci 2012; 6:230–239. PubMed http://dx.doi.org/10.4056/sigs.2726028PubMed CentralView ArticlePubMedGoogle Scholar
- Chovatia M, Sikorski J, Schröder M, Lapidus A, Nolan M, Tice H, Glavina Del Rio T, Copeland A, Cheng JF, Lucas S, et al. Complete genome sequence of Thermanaerovibrio acetaminovorans type strain (Su883T). Stand Genomic Sci 2009; 1:254–261. PubMed http://dx.doi.org/10.4056/sigs.40645PubMed CentralView ArticlePubMedGoogle Scholar
- Pitluck S, Yasawong M, Held B, Lapidus A, Nolan M, Copeland A, Lucas S, Glavina Del Rio T, Tice H, Cheng JF, et al. Non-contiguous finished genome sequence of Aminomonas paucivorans type strain (GLU-3T). Stand Genomic Sci 2010; 3:285–293. PubMed http://dx.doi.org/10.4056/sigs.1253298PubMed CentralView ArticlePubMedGoogle Scholar
- Labutti K, Mayilraj S, Clum A, Lucas S, Glavina Del Rio T, Nolan M, Tice H, Cheng JF, Pitluck S, Liolios K, et al. Permanent draft genome sequence of Dethiosulfovibrio peptidovorans type strain (SEBR 4207T). Stand Genomic Sci 2010; 3:85–92. PubMed http://dx.doi.org/10.4056/sigs.1092865PubMed CentralView ArticlePubMedGoogle Scholar
- 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 http://dx.doi.org/10.1038/nbt1360PubMed CentralView ArticlePubMedGoogle Scholar
- Yarza P, Spröer C, Swiderski J, Mrozek N, Spring S, Tindall BJ, Gronow S, Pukall R, Klenk HP, Lang E, et al. Sequencing orphan species initiative (SOS): Filling the gaps in the 16S rRNA gene sequence database for all species with validly published names. Syst Appl Microbiol 2013; 36:69–73. PubMed http://dx.doi.org/10.1016/j.syapm.2012.12.006View ArticlePubMedGoogle Scholar
- Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms. Proposal for the domains Archaea and Bacteria. Proc Natl Acad Sci USA 1990; 87:4576–4579. PubMed http://dx.doi.org/10.1073/pnas.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
- Jumas-Bilak E, Roudière L, Marchandin H. Description of ‘Synergistetes’ phyl. nov. and emended description of the phylum ‘Deferribacteres’ and of the family Syntrophomonadaceae, phylum ‘Firmicutes’. [PubMed]. Int J Syst Evol Microbiol 2009; 59:1028–1035. PubMed http://dx.doi.org/10.1099/ijs.0.006718-0View ArticlePubMedGoogle Scholar
- BAuA. 2010, Classification of bacteria and archaea in risk groups. http://www.baua.de TRBA 466, p. 232.
- 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. The Gene Ontology Consortium. Nat Genet 2000; 25:25–29. PubMed http://dx.doi.org/10.1038/75556PubMed CentralView ArticlePubMedGoogle Scholar
- Meier-Kolthoff JP, Auch AF, Klenk HP, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 2013; 14:60. PubMed http://dx.doi.org/10.1186/1471-2105-14-60PubMed CentralView ArticlePubMedGoogle Scholar
- Klenk HP, Göker M. En route to a genome-based classification of Archaea and Bacteria? Syst Appl Microbiol 2010; 33:175–182. PubMed http://dx.doi.org/10.1016/j.syapm.2010.03.003View ArticlePubMedGoogle Scholar
- 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 http://dx.doi.org/10.1038/nature08656PubMed CentralView ArticlePubMedGoogle Scholar
- Mavromatis K, Land ML, Brettin TS, Quest DJ, Copeland A, Clum A, Goodwin L, Woyke T, Lapidus A, Klenk HP, et al. The fast changing landscape of sequencing technologies and their impact on microbial genome assemblies and annotation. PLoS ONE 2012; 7:e48837. PubMed http://dx.doi.org/10.1371/journal.pone.0048837PubMed CentralView ArticlePubMedGoogle Scholar
- List of growth media used at DSMZ: http://www.dsmz.de/catalogues/catalogue-microorganisms/culture-technology/list-of-media-for-microorganisms.html.
- 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. Biopreserv Biobank 2011; 9:51–55. http://dx.doi.org/10.1089/bio.2010.0029View ArticlePubMedGoogle Scholar
- The DOE Joint Genome Institute. www.jgi.doe.gov
- Phrap and Phred for Windows. MacOS, Linux, and Unix. www.phrap.com
- Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008; 18:821–829. PubMed http://dx.doi.org/10.1101/gr.074492.107PubMed CentralView ArticlePubMedGoogle Scholar
- Han C, Chain P. Finishing repeat regions automatically with Dupfinisher. In: Proceedings of the 2006 international conference on bioinformatics & computational biology. Arabnia HR, Valafar H (eds), CSREA Press. June 26–29, 2006: 141–146.
- 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
- Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal Prokaryotic Dynamic Programming Genefinding Algorithm. BMC Bioinformatics 2010; 11:119. PubMed http://dx.doi.org/10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
- Mavromatis K, Ivanova NN, Chen IM, Szeto E, Markowitz VM, Kyrpides NC. The DOE-JGI Standard operating procedure for the annotations of microbial genomes. Stand Genomic Sci 2009; 1:63–67. PubMed http://dx.doi.org/10.4056/sigs.632PubMed CentralView ArticlePubMedGoogle Scholar
- Pati A, Ivanova N, Mikhailova N, Ovchinikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: A Gene Prediction Improvement Pipeline for microbial genomes. Nat Methods 2010; 7:455–457. PubMed http://dx.doi.org/10.1038/nmeth.1457View ArticlePubMedGoogle Scholar
- 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 http://dx.doi.org/10.1093/bioinformatics/btp393View ArticlePubMedGoogle Scholar
- Auch AF, Von Jan M, Klenk HP, Göker M. Digital DNA-DNA hybridization for microbial species delineation by means of genome-to-genome sequence comparison. Stand Genomic Sci 2010; 2:117–134. PubMed http://dx.doi.org/10.4056/sigs.531120PubMed CentralView ArticlePubMedGoogle Scholar
- Auch AF, Klenk HP, Göker M. Standard operating procedure for calculating genome-to-genome distances based on high-scoring segment pairs. Stand Genomic Sci 2010; 2:142–148. PubMed http://dx.doi.org/10.4056/sigs.541628PubMed CentralView ArticlePubMedGoogle Scholar
- Field D, Amaral-Zettler L, Cochrane G, Cole JR, Dawyndt P, Garrity GM, Gilbert J, Glöckner FO, Hirschman L, Karsch-Mzrachi I, et al. Clarifying Concepts and Terms in Biodiversity Informatics. PLoS Biol 2013; 9:e1001088. PubMed http://dx.doi.org/10.1371/journal.pbio.1001088View ArticleGoogle Scholar