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Complete genome sequence of Spirochaeta smaragdinae type strain (SEBR 4228T)

Standards in Genomic Sciences volume 3, pages136–144(2010)Cite this article

Abstract

Spirochaeta smaragdinae Magot et al. 1998 belongs to the family Spirochaetaceae. The species is Gram-negative, motile, obligately halophilic and strictly anaerobic and is of interest because it is able to ferment numerous polysaccharides. S. smaragdinae is the only species of the family Spirochaetaceae known to reduce thiosulfate or element sulfur to sulfide. This is the first complete genome sequence in the family Spirochaetaceae. The 4,653,970 bp long genome with its 4,363 protein-coding and 57 RNA genes is a part of the Genomic Encyclopedia of Bacteria and Archaea project.

Introduction

Strain SEBR 4228T (= DSM 11293 = JCM 15392) is the type strain of the species Spirochaeta smaragdinae. Currently, there are eighteen species [1] and two subspecies in the genus Spirochaeta [1,2]. The generic name derives from the Greek word ‘speira’ meaning ‘a coil’ and the Greek word ‘chaitê’ meaning ‘hair’, referring to the spiral shape of bacterial cell. The species epithet is derived from the Latin word ‘smaragdinae’ meaning ‘from Emerald’, referring to the name Emerald of an oil field in Congo. Strain SEBR 4228T was isolated from an oil-injection production water sample of a Congo offshore oilfield [3] and described in 1997 by Magot et al. as ‘Spirochaeta smaragdinae’ [3]. Here we present a summary classification and a set of features for S. smaragdinae SEBR 4228T, together with the description of the complete genomic sequencing and annotation.

Classification and features

Strain SEBR 4228T shares 82.2–99.0% 16S rRNA gene sequence identity with the type strains from the other members of genus Spirochaeta [4], with the type strain of S. bajacaliforniensis [5], isolated from a mud sample in Laguna Figueroa (Baja California, Mexico) showing the highest degree of sequence similarity (99%). Notwithstanding the high degree of 16S rRNA gene sequence identity, these two strains are characterized by low genomic similarity (38%) in DNA-DNA hybridization studies and differ by numerous differences in carbon source utilization [3]. Several type strains from the genus Treponema show the highest degree of similarity for non-Spirochaeta strains (82.9-83.6%) [4]. A representative genomic 16S rRNA sequence of strain SEBR 4228T was compared using BLAST with the most recent release of the Greengenes database [6] and the relative frequencies of taxa and keywords, weighted by BLAST scores, were determined. The three most frequent genera were Spirochaeta (76.4%), ‘Sphaerochaeta’ (15.8%) and Cytophaga (7.8%). Within the five most frequent keywords in the labels of environmental samples were ‘microbial’ (11.7%), ‘mat’ (10.5%), ‘hypersaline’ (7.7%), and ‘sediment’ (1.7%). The environmental samples database (env_nt) contains the marine metagenome genomic clone 1061006082084 (EK988302) that is 92% identical to the 16S rRNA gene sequence of SEBR 4228T. No phylotypes from genomic surveys could be linked to the species S. smaragdinae or even the genus Spirochaeta, indicating a rather rare occurrence of these in the habitats screened so far (as of August 2010).

Figure 1 shows the phylogenetic neighborhood of S. smaragdinae SEBR 4228T in a 16S rRNA based tree. The sequences of the two 16S rRNA gene copies differ from each other by up to one nucleotide, and differ by up to five nucleotides from the previously published 16S rRNA sequence generated from DSM 11293 (U80597), which contains two ambiguous base calls.

Figure 1.
figure1

Phylogenetic tree highlighting the position of S. smaragdinae SEBR 4228T relative to the type strains of the other species within the genus and of the other genera within the genus Spirochaeta. The tree was inferred from 1,385 aligned characters [7,8] of the 16S rRNA gene sequence under the maximum likelihood criterion [9] and rooted in accordance with the current taxonomy [10]. The branches are scaled in terms of the expected number of substitutions per site. Numbers above branches are support values from 500 bootstrap replicates [11] if larger than 60%. Lineages with type strain genome sequencing projects registered in GOLD [12] are shown in blue, published genomes in bold.

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Strain SEBR 4228T is a Gram-negative, chemoorganotrophic and strictly anaerobic bacterium with spiral shaped, 0.3–0.5 × 5–30 µm long cells (Figure 2 and Table 1). It possesses a multilayer, crenulating, Gram-negative cell envelope, which consists of an outer membrane and an inner membrane adjoining the cytoplasmic membrane [3]. Sillons, which are the contact point between the protoplasmic cylinder, the inner membrane and the outer membrane, are also observed from the cells of S. smaragdinae SEBR 4228T [3]. Strain SEBR 4228T forms translucent colonies with regular edges (0.5 mm of diameter) after two weeks of incubation on SEM agar plates at 37°C [3]. The strain is motile with a corkscrew-like motion, which is characteristic for the typical 1-2-1 periplasmic flagellar arrangement of the members of the genus Spirochaeta [3]. The periplasmic, non-extracellular location of the flagella make the Spirochaeta a valuable candidate for the study of flagella evolution [26]. The enlarged spherical bodies, which are typical for spirochetes, are also observed in strain SEBR 4228T [3]. The temperature range for growth is from 20°C to 40°C, with an optimum temperature at 37°C [3]. The pH range for growth is between 5.5 and 8.0, with an optimum pH of 7.0 [3]. Strain SEBR 4228T is obligately halophilic [3] and is able to grow on media that contains 1–10% of NaCl, with an optimum salinity at 5% NaCl [3]. Under optimum growth conditions, the doubling time is approximately 25 h in the presence of glucose and thiosulfate [3]. Strain SEBR 4228T is able to utilize biotrypcase, fructose, fumarate, galactose, D-glucose, glycerol, mannitol, mannose, ribose, D-xylose and yeast extract, but not acetate, D-arabinose, butyrate, casamino acids, lactate, maltose, propionate, pyruvate, rhamnose, sorbose, sucrose and L-xylose [3]. Yeast extract is required for growth and cannot be replaced by a vitamin mixture [3]. Strain SEBR 4228T ferments fumarate to acetate and succinate [3]. The major end-product of glucose fermentation of strain SEBR 4228T is lactate with traces of H2 and ethanol [3]. S. smaragdinae is the only species of Spirochaeta known to reduce thiosulfate or elemental sulfur to sulfide [3]. Strain SEBR 4228T produces lactate, acetate, CO2 and H2S as the end-products of glucose oxidation when thiosulfate is present in the growth medium [3]. The strain contains a rhodanese-like protein which expresses rhodanese activity [27]. This enzyme is able to reduce thiosulfate to sulfide [28]. Rhodanese is also widely found in other members of the domain Bacteria [29–31].

Figure 2.
figure2

Scanning electron micrograph of S. smaragdinae SEBR 4228T

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Table 1. Classification and general features of S. smaragdinae SEBR 4228T according to the MIGS recommendations [13].
Full size table

Chemotaxonomy

No cellular fatty acids profiles are currently available for S. smaragdinae SEBR 4228T. However, C16:0 dimethyl acetate is the major cellular fatty acids of the type strains of the closely related S. dissipatitropha, S. asiatica and S. americana, and C16:0 fatty acid methyl ester is the major cellular fatty acids of S. africana [20,32].

Genome sequencing and annotation

Genome project history

This organism was selected for sequencing on the basis of its phylogenetic position [33], and is part of the Genomic Encyclopedia of Bacteria and Archaea project [34]. The genome project is deposited in the Genome OnLine Database [12] 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
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Growth conditions and DNA isolation

S. smaragdinae SEBR 4228T, DSM 11293, was grown anaerobically in medium 819 (Spirochaeta smaragdinae medium) [35] at 35°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/LALMice for cell lysis as described in Wu et al. [34].

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 version 2.0.0-PostRelease-11/04/2008 (Roche). The initial Newbler assembly consisted of 51 contigs in one scaffold was converted into a phrap assembly by making fake reads from the consensus, collecting the read pairs in the 454 paired end library. Illumina GAii sequencing data was assembled with Velvet [36] and the consensus sequences were shredded into 1.5 kb overlapped fake reads and assembled together with the 454 data. Draft assemblies were based on 273 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 following 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 or transposon bombing (Epicentre Biotechnologies, Madison, WI) [37]. Gaps between contigs were closed by editing in Consed, by PCR and by Bubble PCR primer walks (J.-F.Chang, unpublished). A total of 147 additional reactions were necessary to close gaps and to raise the quality of the finished sequence. Illumina reads were also used to improve the final consensus quality using an in-house developed tool - the Polisher [38]. The error rate of the completed genome sequence is 0.2 in 100,000. Together, the combination of the Illumina and 454 sequencing platforms provided 65.7× coverage of the genome.

Genome annotation

Genes were identified using Prodigal [39] as part of the Oak Ridge National Laboratory genome annotation pipeline, followed by a round of manual curation using the JGI GenePRIMP pipeline [40]. The predicted CDSs were translated and used to search the National Center for Biotechnology Information (NCBI) nonredundant database, UniProt, TIGRFam, 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 [41].

Genome properties

The genome consists of a 4,653,970 bp long chromosome with a 49.0% GC content (Table 3 and Figure 3). Of the 4,363 genes predicted, 4,306 were protein-coding genes, and 57 RNAs; eighty seven pseudogenes were also identified. The majority of the protein-coding genes (74.2%) 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.
figure3

Graphical circular map of the genome. 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.

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

References

  1. 1.

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

    Google Scholar 

  2. 2.

    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 doi:10.1099/00207713-47-2-590

    Article  PubMed  Google Scholar 

  3. 3.

    Magot M, Fardeau ML, Arnauld O, Lanau C, Ollivier B, Thomas P, Patel BK. Spirochaeta smaragdinae sp. nov., a new mesophilic strictly anaerobic spirochete from an oil field. FEMS Microbiol Lett 1997; 155:185–191. PubMed doi:10.1111/j.1574-6968.1997.tb13876.x

    Article  CAS  PubMed  Google Scholar 

  4. 4.

    Chun J, Lee JH, Jung Y, Kim M, Kim S, Kim BK, Lim YW. EzTaxon: a web-based tool for the identification of prokaryotes based on 16S ribosomal RNA gene sequences. Int J Syst Evol Microbiol 2007; 57:2259–2261. PubMed doi:10.1099/ijs.0.64915-0

    Article  CAS  PubMed  Google Scholar 

  5. 5.

    Fracek SP, Jr., Stolz JF. Spirochaeta bajacaliforniensis sp. n. from a microbial mat community at Laguna Figueroa, Baja California Norte, Mexico. [RRS]. Arch Microbiol 1985; 142:317–325. PubMed doi:10.1007/BF00491897

    Article  PubMed  Google Scholar 

  6. 6.

    DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, Huber T, Dalevi D, Hu P, Andersen GL. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 2006; 72:5069–5072. PubMed doi:10.1128/AEM.03006-05

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  7. 7.

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

    Article  CAS  PubMed  Google Scholar 

  8. 8.

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

    Article  CAS  PubMed  Google Scholar 

  9. 9.

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

    Article  PubMed  Google Scholar 

  10. 10.

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

    Article  CAS  PubMed  Google Scholar 

  11. 11.

    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:10.1007/978-3-642-02008-713

    Article  CAS  Google Scholar 

  12. 12.

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

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  13. 13.

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

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  14. 14.

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

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  15. 15.

    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, p. 119–169.

    Google Scholar 

  16. 16.

    Cavalier-Smith T. The neomuran origin of archaebacteria, the negibacterial root of the universal tree and bacterial megaclassification. Int J Syst Evol Microbiol 2002; 52:7–76. PubMed

    Article  CAS  PubMed  Google Scholar 

  17. 17.

    Buchanan RE. Studies in the nomenclature and classification of bacteria. II. The primary subdivisions of the Schizomycetes. J Bacteriol 1917; 2:155–164. PubMed

    PubMed Central  CAS  PubMed  Google Scholar 

  18. 18.

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

    Article  Google Scholar 

  19. 19.

    Swellengrebel NH. Sur la cytologie comparée des spirochètes et des spirilles. Ann Inst Pasteur (Paris) 1907; 21:562–586.

    Google Scholar 

  20. 20.

    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. PubMed

    Article  CAS  PubMed  Google Scholar 

  21. 21.

    Ehrenberg CG. Dritter Beitrag zur Erkenntniss grosser Organisation in der Richtung des kleinsten Raumes Abhandlungen der Preussischen Akademie der Wissenschaften (Berlin) 1835:143–336.

  22. 22.

    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 [The Williams and Wilkins Co., Baltimore.].

    Google Scholar 

  23. 23.

    Validation List No. 67. Validation of publication of new names and new combinations previously effectively published outside the IJSB. Int J Syst Bacteriol 1998; 48:1083–1084. doi:10.1099/00207713-48-4-1083

  24. 24.

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

  25. 25.

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

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  26. 26.

    Snyder LAS, Loman NJ, Fütterer K, Pallen MJ. Bacterial flagellar diversity and evolution: seek simplicity and distrust it? Trends Microbiol 2009; 17:1–5. PubMed doi:10.1016/j.tim.2008.10.002

    Article  CAS  PubMed  Google Scholar 

  27. 27.

    Ravot G, Casalot L, Ollivier B, Loison G, Magot M. rdlA, a new gene encoding a rhodanese-like protein in Halanaerobium congolense and other thiosulfate-reducing anaerobes. Res Microbiol 2005; 156:1031–1038. PubMed doi:10.1016/j.resmic.2005.05.009

    Article  CAS  PubMed  Google Scholar 

  28. 28.

    Singleton DR, Smith DW. Improved Assay for Rhodanese in Thiobacillus spp. Appl Environ Microbiol 1988; 54:2866–2867. PubMed

    PubMed Central  CAS  PubMed  Google Scholar 

  29. 29.

    Crolet JL, Magot M. Non-SRB sulfidogenic bacteria in oilfield production facilities. Mater Perform 1996; 35:60–64.

    Google Scholar 

  30. 30.

    Magot M, Ravot G, Campaignolle X, Ollivier B, Patel BK, Fardeau ML, Thomas P, Crolet JL, Garcia JL. Dethiosulfovibrio peptidovorans gen. nov., sp. nov., a new anaerobic, slightly halophilic, thiosulfate-reducing bacterium from corroding offshore oil wells. Int J Syst Bacteriol 1997; 47:818–824. PubMed doi:10.1099/00207713-47-3-818

    Article  CAS  PubMed  Google Scholar 

  31. 31.

    Ravot G, Magot M. 2000. Detecting sulfate-reducing bacteria utilizing the APS-reductase gene patent GB 2354072 A.

  32. 32.

    Hoover RB, Pikuta EV, Bej AK, Marsic D, Whitman WB, Tang J, Krader P. Spirochaeta americana sp. nov., a new haloalkaliphilic, obligately anaerobic spirochaete isolated from soda Mono Lake in California. Int J Syst Evol Microbiol 2003; 53:815–821. PubMed doi:10.1099/ijs.0.02535-0

    Article  CAS  PubMed  Google Scholar 

  33. 33.

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

    Article  CAS  PubMed  Google Scholar 

  34. 34.

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

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  35. 35.

    List of growth media used at DSMZ: http://www.dsmz.de/microorganisms/media_list.php

  36. 36.

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

    PubMed Central  Article  CAS  PubMed  Google Scholar 

  37. 37.

    Sims D, Brettin T, Detter JC, Han C, Lapidus A, Copeland A, Glavina Del Rio T, Nolan M, Chen F, Lucas S, et al. Complete genome sequence of Kytococcus sedentarius type strain (541T). Stand Genomic Sci 2009; 1:12–20. doi:10.4056/sigs.761

    PubMed Central  Article  PubMed  Google Scholar 

  38. 38.

    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 

  39. 39.

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

    PubMed Central  Article  PubMed  Google Scholar 

  40. 40.

    Pati A, Ivanova NN, Mikhailova N, Ovchinnikova G, Hooper SD, Lykidis A, Kyrpides NC. GenePRIMP: a gene prediction improvement pipeline for prokaryotic genomes. Nat Methods 2010; 7:455–457. PubMed doi:10.1038/nmeth.1457

    Article  CAS  PubMed  Google Scholar 

  41. 41.

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

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We would like to gratefully acknowledge the help of Maren Schröder (DSMZ) for growing cultures of S. smarasgdinae. 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 599/1-1 and Thailand Research Fund Royal Golden Jubilee Ph.D. Program No. PHD/0019/2548 for MY.

Author information

Affiliations

  1. DOE Joint Genome Institute, Walnut Creek, California, USA

    Konstantinos Mavromatis, Olga Chertkov, Alla Lapidus, Susan Lucas, Matt Nolan, Tijana Glavina Del Rio, Hope Tice, Jan-Fang Cheng, Sam Pitluck, Konstantinos Liolios, Natalia Ivanova, Roxanne Tapia, Cliff Han, David Bruce, Lynne Goodwin, Amrita Pati, Miriam Land, Loren Hauser, Yun-Juan Chang, Cynthia D. Jeffries, John C. Detter, Tanja Woyke, James Bristow, Jonathan A. Eisen, Philip Hugenholtz & Nikos C. Kyrpides

  2. HZI - Helmholtz Centre for Infection Research, Braunschweig, Germany

    Montri Yasawong & Manfred Rohde

  3. Bioscience Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA

    Olga Chertkov, Roxanne Tapia, Cliff Han, David Bruce, Lynne Goodwin & John C. Detter

  4. Biological Data Management and Technology Center, Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Ami Chen, Krishna Palaniappan & Victor Markowitz

  5. Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA

    Miriam Land, Loren Hauser, Yun-Juan Chang & Cynthia D. Jeffries

  6. DSMZ - German Collection of Microorganisms and Cell Cultures GmbH, Braunschweig, Germany

    Evelyne Brambilla, Stefan Spring, Markus Göker, Johannes Sikorski & Hans-Peter Klenk

  7. University of California Davis Genome Center, Davis, California, USA

    Jonathan A. Eisen

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  36. Nikos C. Kyrpides
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Correspondence to Nikos C. Kyrpides.

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Mavromatis, K., Yasawong, M., Chertkov, O. et al. Complete genome sequence of Spirochaeta smaragdinae type strain (SEBR 4228T). Stand in Genomic Sci 3, 136–144 (2010). https://doi.org/10.4056/sigs.1143106

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Keywords

  • spiral shaped
  • corkscrew-like motility
  • chemoorganotroph
  • strictly anaerobe
  • obligately halophile
  • rhodanese-like protein
  • Spirochaetaceae
  • GEBA

Environmental Microbiome

ISSN: 2524-6372