Complete genome sequence of the termite hindgut bacterium Spirochaeta coccoides type strain (SPN1T), reclassification in the genus Sphaerochaeta as Sphaerochaeta coccoides comb. nov. and emendations of the family Spirochaetaceae and the genus Sphaerochaeta
- Birte Abt3,
- Cliff Han1, 2,
- Carmen Scheuner3,
- Megan Lu1, 2,
- Alla Lapidus1,
- Matt Nolan1,
- Susan Lucas1,
- Nancy Hammon1,
- Shweta Deshpande1,
- Jan-Fang Cheng1,
- Roxanne Tapia1, 2,
- Lynne A. Goodwin1, 2,
- Sam Pitluck1,
- Konstantinos Liolios1,
- Ioanna Pagani1,
- Natalia Ivanova1,
- Konstantinos Mavromatis1,
- Natalia Mikhailova1,
- Marcel Huntemann1,
- Amrita Pati1,
- Amy Chen4,
- Krishna Palaniappan4,
- Miriam Land1, 5,
- Loren Hauser1, 5,
- Evelyne-Marie Brambilla3,
- Manfred Rohde6,
- Stefan Spring3,
- Sabine Gronow3,
- Markus Göker3,
- Tanja Woyke1,
- James Bristow1,
- Jonathan A. Eisen1, 7,
- Victor Markowitz4,
- Philip Hugenholtz1, 8,
- Nikos C. Kyrpides1,
- Hans-Peter Klenk3 and
- John C. Detter1, 2
© The Author(s) 2012
Published: 25 May 2012
Spirochaeta coccoides Dröge et al. 2006 is a member of the genus Spirochaeta Ehrenberg 1835, one of the oldest named genera within the Bacteria. S. coccoides is an obligately anaerobic, Gram-negative, non-motile, spherical bacterium that was isolated from the hindgut contents of the termite Neotermes castaneus. The species is of interest because it may play an important role in the digestion of breakdown products from cellulose and hemicellulose in the termite gut. Here we provide a taxonomic re-evaluation for strain SPN1T, and based on physiological and genomic characteristics, we propose its reclassification as a novel species in the genus Sphaerochaeta, a recently published sister group of the Spirochaeta. The 2,227,296 bp long genome of strain SPN1T with its 1,866 protein-coding and 58 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.
Keywordsobligately anaerobic non-motile termite hindgut Gram-negative di- and oligosaccharide-degrading mesophilic chemoorganotrophic Spirochaetaceae Sphaerochaeta GEBA
Strain SPN1T (= DSM 17374 = ATCC BAA-1237) is the type strain of Spirochaeta coccoides and was isolated from the hindgut contents of the lower dry-wood termite Neotermes castaneus [1,2]. The genus Spirochaeta currently consists of 19 validly named species . The genus name was derived from the Latinized Greek words speira, ‘a coil’ and chaitê, ‘hair’, yielding the Neo-Latin ‘Spirochaeta’, the coiled hair . The species epithet was derived from the neo-Greek words coccos, ‘a berry’ and eidos, meaning ‘shape’, yielding the Neo-Latin word coccoides, meaning berry-shaped . Based on the nucleotide sequence of the 16S rRNA gene strain SPN1T was assigned to the genus Spirochaeta, although its coccoid, non-motile cells differ from the morphology of all known validly named spirochetes . Recently, Ritalahti et al. proposed that Spirochaeta sp. Buddy and Spirochaeta sp. Grapes belonged to the novel genus Sphaerochaeta based on their unique morphology and the 16S rRNA sequence similarity to their closest relatives. The two spherical isolates Spirochaeta sp. Buddy and Spirochaeta sp. Grapes were named Sphaerochaeta globosa and Sphaerochaeta pleomorpha, respectively . On the basis of its morphological, physiological and genomic characteristics, S. coccoides is more closely related to Sphaerochaeta than to the remaining Spirochaeta species, and we therefore propose the placement of S. coccoides SPN1T into the genus Sphaerochaeta. Here we thus present a summary classification and a set of features for S. coccoides SPN1T, a description of the complete genome sequencing and annotation, and a proposal to reclassify S. coccoides as a member of the genus Sphaerochaeta as Sphaerochaeta coccoides comb. nov.
Classification and features
A representative genomic 16S rRNA sequence of strain SPN1T was compared using NCBI BLAST [5,6] 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 Spirochaeta (57.6%), Sphaerochaeta (39.7%) and Cytophaga (2.7%) (22 hits in total). Regarding the six hits to sequences from other members of the genus, the average identity within HSPs was 90.2%, whereas the average coverage by HSPs was 30.9%. Among all other species, the one yielding the highest score was Spirochaeta bajacaliforniensis (AJ698859), which corresponded to an identity of 90.3% and an HSP coverage of 32.6%. (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 AY570600 (‘biodegraded Canadian oil reservoir clone PL-16B9’), which showed an identity of 91.0% and an HSP coverage of 85.9%. The most frequently occurring keywords within the labels of all environmental samples which yielded hits were ‘microbi’ (6.5%), ‘mat’ (4.5%), ‘hypersalin’ (3.1%), ‘termit’ (2.8%) and ‘hindgut’ (2.6%) (228 hits in total). Environmental samples which yielded hits of a higher score than the highest scoring species were not found. The keywords are partially in agreement with the known environmental preferences of S. coccoides SPN1T, but the results also indicate that the species itself is rarely found in environmental probes.
Species Spirochaeta coccoides
Type strain SPN1
pentoses (arabinose, xylose), oligosaccharides (maltose, cellobiose, maltotriose, maltotetraose), yeast extract
digestive tract of lower dry-wood termites
host associated commensal
hindgut of Neotermes castaneus
Sample collection time
2005 or before
Genome sequencing and annotation
Genome project history
Genome sequencing project information
Three genomic libraries: one 454 pyrosequence standard library, one 454 PE library (8.9 kb insert size), one Illumina library
Illumina GAii, 454 GS FLX Titanium
960.0 × Illumina; 40.0 × pyrosequence
Newbler version 2.3, Velvet version 0.7.63, phrap version SPS - 4.24
Gene calling method
Prodigal 1.4, GenePRIMP
Genbank Date of Release
April 27, 2011
NCBI project ID
Source material identifier
Tree of Life, GEBA
Growth conditions and DNA isolation
S. coccoides strain SPN1T, DSM 17374, was grown anaerobically in DSMZ medium 1204 (Spirochaeta coccoides medium)  at 30°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. 2009 . 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 97 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 (2,245.3 Mb) was assembled with Velvet  and the consensus sequences were shredded into 2.0 kb overlapped fake reads and assembled together with the 454 data. The 454 draft assembly was based on 142.5 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  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 308 additional reactions 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 . 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 1,000.0 × coverage of the genome. The final assembly contained 137,682 pyrosequence and 58,694,953 Illumina reads.
Genes were identified using Prodigal  as part of the Oak Ridge National Laboratory 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) 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 .
% of Total
Genome size (bp)
DNA coding region (bp)
DNA G+C content (bp)
Number of replicons
Genes with function prediction
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/envelope biogenesis
Intracellular trafficking, 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 from the genome sequence, and taxonomic conclusions for S. coccoides
Taxonomic interpretation for S. coccoides and neighboring species in the family Spirochaetaceae according to 16S rRNA data
Based on its 16S rRNA sequence strain SPN1T was placed into the genus Spirochaeta , although it lacks the typical spiral morphology and is non-motile. SPN1T showed highest similarity in 16S rRNA gene sequences to Spirochaeta sp. strain Buddy and Spirochaeta sp. strain Grapes , two spherical isolates that were not formally named at that time, but preliminarily named ‘free-living pleomorphic spirochaetes’ . Recently, these isolates were placed into the novel genus Sphaerochaeta, and validly published as S. globosa and S. pleomorpha, respectively .
The phylogenetic tree shown in Figure 1 demonstrates that the current classification of the group suffers from a non-homogenous location of species featured as members of the genus Spirochaeta. Not only is Borrelia placed within Spirochaeta (without much branch support), but S. coccoides also appears as the sister group of Sphaerochaeta with maximum support. Support for a placement of S. caldaria, S. stenostrepta and S. zuelzerae more closely to Treponema than to the other Spirochaeta species (a topological arrangement that was observed earlier ) is also high and could only be considered a matter of rooting for the former two species (but note that the rooting is confirmed by a phylogenomic analysis described below and see the tree topology of the entire order Spirochaetales in [46,47]).
To measure phylogenetic conflict caused by the taxonomic classification in detail, we conducted both unconstrained heuristic searches for the best tree under the maximum likelihood (ML)  and maximum parsimony (MP) criterion  as well as searches constrained for the monophyly of all genera (for details of the data matrix see the caption of Figure 1). Our own re-implementation of CopyCat  in conjunction with AxPcoords and AxParafit  was used to determine those leaves (species) whose placement significantly deviated between the constrained and the unconstrained tree. AxParafit was applied to the ML trees with 1,000 rounds of random permutations of the associations.
The ParaFit test was originally introduced for comparing host and parasite phylogenies , but can be applied to the comparison of all kinds of trees. In contrast to other measures for the comparison of trees, it includes a statistical test for whether individual leaves significantly contribute to the agreement between two trees (a p-value indicates how likely it is that this contribution is no more than random).
All other leaves apparently cause more conflict than agreement . The rationale of comparing unconstrained trees with constrained trees inferred from the very same data is that the constraint might be in conflict with the original tree. In addition to assessing whether the trees are overall significantly different according to the data and a given optimality criterion in a paired-site test (see, e.g. chapter 21 in  for an in-depth description of such tests), the ParaFit test is a straightforward extension for assessing which leaves of the trees cause the conflict, if any.
Result (p-values) from the test of individual links with ParaFit
p-value, constraint 1
p-value, constraint 2
Spirochaeta aurantia (M57740)
Sphaerochaeta globosa (AF357916)
Sphaerochaeta pleomorpha (AF357917)
Spirochaeta cellobiosiphila (EU448140)
Spirochaeta americana (AF373921)
Spirochaeta alkalica (X93927)
Spirochaeta asiatica (X93926)
Spirochaeta halophila (M88722)
Spirochaeta bajacaliforniensis (AJ698859)
Spirochaeta dissipatitropha (AY995150)
Spirochaeta africana (X93928)
Spirochaeta isovalerica (M88720)
Spirochaeta smaragdinae (U80597)
Spirochaeta thermophila (FR749903)
Spirochaeta litoralis (FR733665)
Spirochaeta coccoides (IMG2503956950)
Spirochaeta perfilievii (AY337318)
To assess whether placing S. coccoides in Sphaerochaeta  and the other three Spirochaeta species that cause conflict in Treponema  would solve the problem, an according second constraint was created and used in phylogenetic analysis. The resulting ML tree had a log likelihood of −16,025.93 and was significantly worse than the best-known ML tree only for α = 0.05. The MP trees inferred under the second constraint had a score of 3,123 and were not significantly worse than the best-known MP trees. Table 5 also shows the ParaFit test results obtained by comparing the unconstrained tree and the one obtained with the second constraint. Apparently the conflict is largely resolved; the only remaining p-value above 0.05 is the one for S. thermophilus, which is nevertheless only slightly above the chosen α-value (0.0539) and might become significant if more organisms were included .
According to the results from 16S rRNA analysis and the whole-genome phylogenies described below, for a comparative analysis the genome sequences of S. globosa (GenBank CP002541) and S. pleomorpha (CP003155) , as well as the sequences of S. smaragdinae (GenBank CP002659) were used.
The genomes of the sequenced Spirochaeta and Sphaerochaeta species differ significantly in their size. The genome of S. coccoides (2.2 Mb, 1,866 protein-coding genes, G+C content 51 mol%) is the smallest in size. The genomes of S. pleomorpha (3.6 Mb, 3,216 protein coding genes, G+C content 46 mol%), and S. globosa (3.3 Mb, 3,057 protein-coding genes, G+C content 49 mol%) are bigger in size and the genome of S. smaragdinae counts 4.7 Mb with 4,306 protein-coding genes and a G+C content of 49 mol%.
Pairwise comparison of S. coccoides with both Sphaerochaeta species and S. smaragdinae using the GGDC-Genome-to-Genome Distance Calculator.
HSP length / total length [%]
identities / HSP length [%]
identities / total length [%]
The comparison of S. coccoides with both Sphaerochaeta species revealed the highest scores using the GGDC. The comparison of S. coccoides with S. globosa and S. pleomorpha revealed that 4.5% and 3.9% of the average of genome length are covered with HSPs. The identity within the HSPs was 83.2% and 83.3%, respectively, whereas the identity over the whole genome was 3.7% and 3.3%, respectively. Lower similarity scores were observed in the comparison of S. coccoides with S. smaragdinae: only 1.2% of the average of either of the genome lengths are covered with HSPs. The identity within these HSPs was 84.6%, whereas the identity over the whole genome was only 1.0%.
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 S. coccoides and the Sphaerochaeta species than between S. coccoides and S. smaragdinae. That the distances relating the number of identical base pairs to total HSP length (formula 2) are different indicates that the genomic similarities between S. coccoides and S. smaragdinae are strongly restricted to more conserved sequences, a kind of saturation phenomenon .
For conducting phylogenomic analyses of the group, amino-acid sequences from 16 Spirochaetaceae and outgroup (other Spirochaeta families) completed type-strain genomes were retrieved from INSDC and investigated as described in  with minor modifications. Orthologs were determined with parallel genome-against-genome protein NCBI BLAST version 2.2.17  and our own re-implementation of the OrthoMCL algorithm  in conjunction with MCL version 08-312 [58,59] with the OrthoMCL default parameters (an e-value threshold of 10-5 and 2.0 as inflation parameter). OrthoMCL clusters containing inparalogs  were reduced as previously described  and aligned using MUSCLE version 3.7 under default settings . The resulting alignments were filtered using RASCAL version 1.3.4  and GBLOCKS version 0.91b  as in our earlier study . Filtered alignments comprising at least four sequences were concatenated to form a supermatrix. As an extension of the approach in , the supermatrix was cleaned from relatively uninformative genes using MARE  under default values (except that deleting taxa was disallowed). Maximum-likelihood trees were inferred with RAxML  version 7.28 in conjunction with rapid bootstrapping and the bootstopping criterion  with subsequent search for the best tree. The best amino acid substitution model was determined beforehand by comparing the resulting log likelihoods on a maximum-parsimony starting tree. Maximum-parsimony tree search was conducted with PAUP* version 4b10  as previously described .
In addition to the supermatrix analysis, homologous sequences were determined using our own re-implementation of the TribeMCL algorithm  in conjunction with MCL [58,59], applying an e-value threshold of 10-5 and an inflation parameter of 2.0. A gene-content (presence/absence) matrix was constructed, representing the occurrence of a gene of one genome within a cluster of homologs. Phylogenetic inference was done with the BINGAMMA model in RAxML and under maximum parsimony with PAUP*, other settings being as described above.
The sister-group relationship of S. coccoides and Sphaerochaeta was unanimously supported by all methods, much like the placement of S. caldaria within Treponema. The trees differed however, regarding the support for the placement of Borrelia as sister group to all other ingroup taxa. For this reason, we assessed via long-branch extraction  whether this positioning could be caused by long-branch attraction  between Borrelia and the outgroup. Removal of Borrelia and subsequent phylogenetic inference yielded a maximum-parsimony tree with the same topology that would have been obtained by pruning Borrelia from the tree depicted in Figure 3. Removal of the outgroup from the alignment, however, yielded a maximum-parsimony tree in which Borrelia was placed as sister group of S. thermophila, supporting the long-branch attraction hypothesis (data not shown).
The phylogenomic analysis thus confirms the 16S rRNA tree (Figure 1) regarding the paraphyly of Spirochaeta but, of course, based on much more characters. A first step to resolve this taxonomic problem is to assign S. coccoides to the genus Sphaerochaeta. Given that S. caldaria and some other species are situated within Treponema , and that Borrelia probably is placed within the remaining Spirochaeta species, further taxonomic changes will probably be necessary in the future. But apparently in addition to sampling more characters (by replacing 16S rRNA with genome sequences) sampling more taxa (by obtaining whole genomes from more type strains) might by necessary to obtain a natural classification of the spirochetes.
Phenotypic data and taxonomic interpretation
Typical features of reference taxa.
Spirochaeta coccoides 
Genus Sphaerochaeta 
Genus Spirochaeta 
coccoid, spherical, not spiral
coccoid, spherical, pleomorphic; not helical or spiral
helical or spiral; spherical bodies under unfavorable growth conditions
0.2–0.75 by 5–250 µm
2 periplasmic flagella (exception: S. plicatilis, with many flagella)
obligately anaerobe or facultatively anaerobe
acetate, ethanol, formate
acetate, ethanol, formate
acetate, ethanol, CO2, H2
56.6–57.4 mol%  51 mol%, this study
Emended description of the family Spirochaetaceae Swellengrebel 1907 (Spirochaetaceae Swellengrebel 1907 emend. Abt, Göker, Kyprides and Klenk)
The description of the family Spirochaetaceae is given by Swellengrebel 1907 [26,28]. Some species form coccoid cells, have no flagella and are not motile. Some do not have L-ornithine in the peptidoglycan.
Emended description of the genus Sphaerochaeta (Sphaerochaeta Ritalahti et al. 2012 emend. Abt, Göker, Kyprides and Klenk)
The description of the genus Sphaerochaeta is as that given by Ritalahti et al. 2012 , with the following modification: DNA G+C content is 45–51 mol%.
Description of Sphaerochaeta coccoides (Dröge et al. 2006) Abt, Göker, Kyrpides and Klenk, comb. nov.
Basonym: Spirochaeta coccoides Dröge et al. 2006.
The characteristics of the species are given in the species description by Dröge et al. 2006 . The type strain is SPN1T (= DSM 17374 = ATCC BAA-1237).
We would like to gratefully acknowledge the help of Sabine Welnitz (DSMZ) for growing S. coccoides 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.
- Dröge S, Fröhlich J, Radek R, König H. Spirochaeta coccoides sp. nov., a novel coccoid spirochete from the hindgut of the termite Neotermes castaneus. Appl Environ Microbiol 2006; 72:392–397. PubMed http://dx.doi.org/10.1128/AEM.72.1.392-397.2006PubMed CentralView ArticlePubMedGoogle Scholar
- Validation List No 110. Int J Syst Evol Microbiol 2006; 56:1459–1460. PubMed http://dx.doi.org/10.1099/ijs.0.64507-0
- Euzéby JP. List of bacterial names with standing in nomenclature: A folder available on the Internet. Int J Syst Bacteriol 1997; 47:590–592. PubMed http://dx.doi.org/10.1099/00207713-47-2-590View ArticlePubMedGoogle Scholar
- Ritalahti KM, Justicia-Leon SD, Cusick KD, Ramos-Hernandez N, Rubin M, Dornbush J, Löffler FE. Sphaerochaeta globosa gen. nov., sp. nov. and Sphaerochaeta pleomorpha sp. nov., free-living, spherical spirochaetes. Int J Syst Evol Microbiol 2012; 62:210–216. PubMed http://dx.doi.org/10.1099/ijs.0.023986-0View ArticlePubMedGoogle 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, 2003Google 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
- 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
- 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
- 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.10958312.2007.00864.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
- Seshadri R, Myers GS, Tettelin H, Eisen JA, Heidelberg JF, Dodson RJ, Davidsen TM, DeBoy RT, Fouts DE, Haft DH, et al. Comparison of the genome of the oral pathogen Treponema denticola with other spirochete genomes. Proc Natl Acad Sci USA 2004; 101:5646–5651. PubMed http://dx.doi.org/10.1073/pnas.0307639101PubMed CentralView ArticlePubMedGoogle Scholar
- Han C, Gronow S, Teshima H, Lapidus A, Nolan M, Lucas S, Hammon N, Deshpande S, Cheng JF, Zeytun A, et al. Complete genome sequence of Treponema succinifaciens type strain (6091T). Stand Genomic Sci 2011; 4:361–370. PubMed http://dx.doi.org/10.4056/sigs.1984594PubMed CentralView ArticlePubMedGoogle Scholar
- Rosenthal AZ, Matson EG, Eldar A, Leadbetter JR. RNA-seq reveals cooperative metabolic interactions between two termite-gut spirochaete species in co-culture. ISME J 2011; (In press). PubMed http://dx.doi.org/10.1038/ismej.2011.3
- Mavromatis K, Yasawong M, Chertkov O, Lapidus A, Lucas S, Nolan M, Glavina Del Rio T, Tice H, Cheng JF, Pitluck S, et al. Complete genome sequence of Spirochaeta smaragdinae type strain (SEBR4228T). Stand Genomic Sci 2010; 3:136–144. PubMedPubMed CentralPubMedGoogle 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
- Garrity G. NamesforLife. BrowserTool takes expertise out of the database and puts it right in the browser. Microbiol Today 2010; 37:9.Google Scholar
- 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 http://dx.doi.org/10.1073/pnas.87.12.4576PubMed CentralView ArticlePubMedGoogle Scholar
- Garrity G, Holt JG. Phylum B17 Spirochaetes phy. nov. Garrity and Holt. In: Garrity GM, Boone DR, Castenholz RW (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 1, Springer, New York, 2001, p. 138.Google Scholar
- Judicial Commission of the International Committee on Systematics of Prokaryotes. The nomenclatural types of the orders Acholeplasmatales, Halanaerobiales, Halobacteriales, Methanobacteriales, Methanococcales, Methanomicrobiales, Planctomycetales, Prochlorales, Sulfolobales, Thermococcales, Thermoproteales and Verrucomicrobiales are the genera Acholeplasma, Halanaerobium, Halobacterium, Methanobacterium, Methanococcus, Methanomicrobium, Planctomyces, Prochloron, Sulfolobus, Thermococcus, Thermoproteus and Verrucomicrobium, respectively. Opinion 79. Int J Syst Evol Microbiol 2005; 55:517–518. PubMed http://dx.doi.org/10.1099/ijs.0.63548-0View ArticleGoogle Scholar
- 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.
- Skerman VBD, McGowan V, Sneath PHA. Approved Lists of Bacterial Names. Int J Syst Bacteriol 1980; 30:225–420. http://dx.doi.org/10.1099/00207713-30-1-25View ArticleGoogle Scholar
- Buchanan RE. Studies in the nomenclature and classification of bacteria. II. The primary subdivisions of the Schizomycetes. J Bacteriol 1917; 2:155–164. PubMedPubMed CentralPubMedGoogle Scholar
- Swellengrebel NH. Sur la cytologie comparée des spirochètes et des spirilles. [Paris]. Ann Inst Pasteur (Paris) 1907; 21:562–586.Google Scholar
- Pikuta EV, Hoover RB, Bej AK, Marsic D, Whitman WB, Krader P. Spirochaeta dissipatitropha sp. nov., an alkaliphilic, obligately anaerobic bacterium, and emended description of the genus Spirochaeta Ehrenberg 1835. Int J Syst Evol Microbiol 2009; 59:1798–1804. PubMedView ArticlePubMedGoogle Scholar
- Canale-Parola E. Genus I. Spirochaeta Ehrenberg 1835, 313. In: Buchanan RE, Gibbons NE (eds), Bergey’s Manual of Determinative Bacteriology, Eighth Edition, The Williams and Wilkins Co., Baltimore, 1974, p. 168–171.Google Scholar
- Ehrenberg CG. Dritter Beitrag zur Erkenntniss grosser Organisation in der Richtung des kleinsten Raumes. Abhandlungen der Preussischen Akademie der Wissenschaften (Berlin), 1835, p. 143–336.Google Scholar
- BAuA. 2010, Classification of bacteria and archaea in risk groups. http://www.baua.de TRBA 466, p. 206.
- 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 http://dx.doi.org/10.1038/75556PubMed 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
- 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
- JGI website. http://www.jgi.doe.gov
- The Phred/Phrap/Consed software package. http://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: Proceeding 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 gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119. PubMed http://dx.doi.org/10.1186/1471-2105-11-119PubMed CentralView ArticlePubMedGoogle Scholar
- 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 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
- Paster BJ. Phylum XV Spirochaetes Garrity and Holt 2001. In: Goodfellow MJ, Kämpfer P, Chun J, De Vos P, Rainey FA, Whitman WB (eds), Bergey’s Manual of Systematic Bacteriology, Second Edition, Volume 4, Springer, New York, 2011, p. 471.Google Scholar
- Yarza P, Ludwig W, Euzéby J, Amann R, Schleifer KH, Glöckner FO, Rosselló-Móra R. Update of the All-Species Living Tree Project based on 16S and 23S rRNA sequence analyses. Syst Appl Microbiol 2010; 33:291–299. PubMed http://dx.doi.org/10.1016/j.syapm.2010.08.001View ArticlePubMedGoogle Scholar
- Meier-Kolthoff JP, Auch AF, Huson DH, Göker M. COPYCAT: Co-phylogenetic Analysis tool. Bioinformatics 2007; 23:898–900. PubMed http://dx.doi.org/10.1093/bioinformatics/btm027View ArticlePubMedGoogle Scholar
- Stamatakis A, Auch AF, Meier-Kolthoff J, Göker M. AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa. BMC Bioinformatics 2007; 8:405. PubMed http://dx.doi.org/10.1186/1471-2105-8-405PubMed CentralView ArticlePubMedGoogle Scholar
- Legendre P, Desdevises Y, Bazen E. A Statistical Test for Host-Parasite Coevolution. Syst Biol 2002; 51:217–234. PubMed http://dx.doi.org/10.1080/10635150252899734View ArticlePubMedGoogle Scholar
- Felsenstein J. Inferring phylogenies. Sinauer Associates Inc., Sunderland, Massachusetts 2004.Google Scholar
- Bermudes D, Chase D, Margulis L. Morphology as a basis for taxonomy of large spirochetes symbiotic in wood-eating cockroaches and termites: Pillotina gen. nov., nom. rev.; Pillotina calotermitidis sp. nov., nom. rev.; Diplocalyx gen. nov., nom. rev.; Diplocalyx calotermitidis sp. nov., nom. rev.; Hollandina gen. nov., nom. rev.; Hollandina pterotermitidis sp. nov., nom. rev.; and Clevelandina reticulitermitidis gen. nov., sp. nov. Int J Syst Bacteriol 1988; 38:291–302. PubMed http://dx.doi.org/10.1099/00207713-38-3-291View 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
- Anderson I, Scheuner C, Göker M, Mavromatis K, Hooper SD, Porat I, Klenk HP, Ivanova N, Kyrpides N. Novel insights into the diversity of catabolic metabolism from ten haloarchaeal genomes. PLoS ONE 2011; 6:e20237. PubMed http://dx.doi.org/10.1371/journal.pone.0020237PubMed CentralView ArticlePubMedGoogle Scholar
- NCBI BLAST version 2.2.17. ftp://ftp.ncbi.nih.gov/blast/execuTables/release/2.2
- Li L, Stoeckert CJ, Roos DS. OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes. Genome Res 2003; 13:2178–2189. PubMed http://dx.doi.org/10.1101/gr.1224503PubMed CentralView ArticlePubMedGoogle Scholar
- van Dongen S. Graph Clustering by Flow Simulation. PhD Thesis, University of Utrecht, The Netherlands, 2000 (http://www.library.uu.nl/digiarchief/dip/diss/1895_620/inhoud.htm).Google Scholar
- MCL version 08-312. http://micans.org/mcl
- Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797. PubMed http://dx.doi.org/10.1093/nar/gkh340PubMed CentralView ArticlePubMedGoogle Scholar
- Thompson JD, Thierry JC, Poch O. RASCAL: rapid scanning and correction of multiple sequence alignments. Bioinformatics 2003; 19:1155–1161. PubMed http://dx.doi.org/10.1093/bioinformatics/btg133View ArticlePubMedGoogle Scholar
- Meusemann K, von Reumont BM, Simon S, Roeding F, Strauss S, Kück P, Ebersberger I, Walzl M, Pass G, Breuers S. A Phylogenomic approach to resolve the arthropod tree oflLife. Mol Biol Evol 2010; 27:2451–2464. PubMed http://dx.doi.org/10.1093/molbev/msq130View ArticlePubMedGoogle Scholar
- Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 2002; 30:1575–1584. PubMed http://dx.doi.org/10.1093/nar/30.7.1575PubMed CentralView ArticlePubMedGoogle Scholar
- Siddall ME, Whiting MF. Long-branch abstractions. Cladistics 1999; 15:9–24. http://dx.doi.org/10.1111/j.1096-0031.1999.tb00391.xView ArticleGoogle Scholar