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Volume 73, Issue 11

sp. nov., a hydrogen- and thiosulfate-oxidizing mesophilic chemolithoautotroph isolated from diffuse-flow fluids on the East Pacific Rise, and an emended description of the genus No Access

Abstract

A novel mesophilic, hydrogen- and thiosulfate-oxidizing bacterium, strain ISO32, was isolated from diffuse-flow hydrothermal fluids from the Crab Spa vent on the East Pacific Rise. Cells of ISO32 were rods, being motile by means of a single polar flagellum. The isolate grew at a temperature range between 30 and 55 °C (optimum, 43 °C), at a pH range between 5.3 and 7.6 (optimum, pH 5.8) and in the presence of 2.0–4.0 % NaCl (optimum, 2.5 %). The isolate was able to grow chemolithoautotrophically with molecular hydrogen, thiosulfate or elemental sulfur as the sole electron donor. Thiosulfate, elemental sulfur, nitrate and molecular oxygen were each used as a sole electron acceptor. Phylogenetic analysis of 16S rRNA gene sequences placed ISO32 in the genus of the class , with EP1-55–1 % as its closest relative (95.95 % similarity). On the basis of the phylogenetic, physiological and genomic characteristics, it is proposed that the organism represents a novel species within the genus , sp. nov. The type strain is ISO32 (=JCM 39185 =KCTC 25252). Furthermore, the genomic properties of members of the genus are distinguished from those of members of other thermophilic genera in the orders ( and ) and (, and ), with larger genome sizes and lower 16S rRNA G+C content values. Comprehensive metabolic comparisons based on genomes revealed that genes responsible for the Pta–AckA pathway were observed exclusively in members of mesophilic genera in the order and of the genus . Our results indicate that the genus contributes to elucidating the evolutionary history of in terms of metabolism and transition from a thermophilic to a mesophilic lifestyle.

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  • Accepted:
  • Published Online:
Keyword(s): chemolithoautotroph , deep-sea hydrothermal vents , East-Pacific Rise , Epsilonproteobacteria and “Campylobacteria”
Funding
This study was supported by the:
  • the WHOI Investment in Science Fund
    • Principle Award Recipient: StefanM. Sievert
  • U.S. National Science Foundation grant (Award OCE-1131095)
    • Principle Award Recipient: StefanM. Sievert
  • JSPS Research Fellowship for Young Scientists
    • Principle Award Recipient: MinoSayaka
  • Japan Society for the Promotion of Science (Award 21K14913)
    • Principle Award Recipient: SayakaMino
© 2023 The Authors
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/content/journal/ijsem/10.1099/ijsem.0.006132
2023-11-03
2024-04-28
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References

  1. Waite DW, Vanwonterghem I, Rinke C, Parks DH, Zhang Y et al. Comparative genomic analysis of the class Epsilonproteobacteria and proposed reclassification to Epsilonbacteraeota (phyl. nov.). Front Microbiol 2017; 8:682 [View Article] [PubMed]
     [Google Scholar]
  2. Nakagawa S, Takaki Y. Nonpathogenic Epsilonproteobacteria. In Encyclopedia of Life Sciences (ELS) Chichester: John Wiley & Sons Ltd; 2009 pp 1–11 [View Article]
     [Google Scholar]
  3. Nakagawa S, Takaki Y, Shimamura S, Reysenbach A-L, Takai K et al. Deep-sea vent ε-proteobacterial genomes provide insights into emergence of pathogens. Proc Natl Acad Sci U S A 2007; 104:12146–12150 [View Article] [PubMed]
     [Google Scholar]
  4. Vetriani C, Voordeckers JW, Crespo-Medina M, O’Brien CE, Giovannelli D et al. Deep-sea hydrothermal vent Epsilonproteobacteria encode a conserved and widespread nitrate reduction pathway (Nap). ISME J 2014; 8:1510–1521 [View Article] [PubMed]
     [Google Scholar]
  5. Pérez-Rodríguez I, Bolognini M, Ricci J, Bini E, Vetriani C. From deep-sea volcanoes to human pathogens: a conserved quorum-sensing signal in Epsilonproteobacteria. ISME J 2015; 9:1222–1234 [View Article] [PubMed]
     [Google Scholar]
  6. Takai K, Nealson KH, Horikoshi K. Hydrogenimonas thermophila gen. nov., sp. nov., a novel thermophilic, hydrogen-oxidizing chemolithoautotroph within the ε-Proteobacteria, isolated from a black smoker in a central indian ridge hydrothermal field. Int J Syst Evol Microbiol 2004; 54:25–32 [View Article] [PubMed]
     [Google Scholar]
  7. Mino S, Shiotani T, Nakagawa S, Takai K, Sawabe T. Hydrogenimonas urashimensis sp. nov., a hydrogen-oxidizing chemolithoautotroph isolated from a deep-sea hydrothermal vent in the Southern Mariana Trough. Syst Appl Microbiol 2021; 44:126170 [View Article] [PubMed]
     [Google Scholar]
  8. Nishimura H, Kitano Y, Inoue T, Nomura K, Sako Y. Purification and characterization of membrane-associated hydrogenase from the deep-sea epsilonproteobacterium Hydrogenimonas thermophila. Biosci Biotechnol Biochem 2010; 74:1624–1630 [View Article] [PubMed]
     [Google Scholar]
  9. Mino S, Yoneyama N, Nakagawa S, Takai K, Sawabe T. Enrichment and genomic characterization of a N2O-reducing chemolithoautotroph from a deep-sea hydrothermal vent. Front Bioeng Biotechnol 2018; 6:184 [View Article] [PubMed]
     [Google Scholar]
  10. McNichol J, Sylva SP, Thomas F, Taylor CD, Sievert SM et al. Assessing microbial processes in deep-sea hydrothermal systems by incubation at in situ temperature and pressure. Deep Res Part I Oceanogr Res Pap 2016; 115:221–232 [View Article]
     [Google Scholar]
  11. McNichol J, Stryhanyuk H, Sylva SP, Thomas F, Musat N et al. Primary productivity below the seafloor at deep-sea hot springs. Proc Natl Acad Sci U S A 2018; 115:6756–6761 [View Article] [PubMed]
     [Google Scholar]
  12. McNichol J, Dyksma S, Mußmann M, Seewald JS, Sylva SP et al. Genus-specific carbon fixation activity measurements reveal distinct responses to oxygen among hydrothermal vent Campylobacteria. Appl Environ Microbiol 2022; 88:e0208321 [View Article] [PubMed]
     [Google Scholar]
  13. Labonté JM, Pachiadaki M, Fergusson E, McNichol J, Grosche A et al. Single cell genomics-based analysis of gene content and expression of prophages in a diffuse-flow deep-sea hydrothermal system. Front Microbiol 2019; 10:1262 [View Article] [PubMed]
     [Google Scholar]
  14. Seewald JS, Doherty KW, Hammar TR, Liberatore SP. A new gas-tight isobaric sampler for hydrothermal fluids. Deep Sea Res 1 Oceanogr Res Pap 2002; 49:189–196 [View Article]
     [Google Scholar]
  15. Sako Y, Takai K, Ishida Y, Uchida A, Katayama Y. Rhodothermus obamensis sp. nov., a modern lineage of extremely thermophilic marine bacteria. Int J Syst Bacteriol 1996; 46:1099–1104 [View Article] [PubMed]
     [Google Scholar]
  16. Takai K, Inagaki F, Nakagawa S, Hirayama H, Nunoura T et al. Isolation and phylogenetic diversity of members of previously uncultivated ε-Proteobacteria in deep-sea hydrothermal fields. FEMS Microbiol Lett 2003; 218:167–174 [View Article] [PubMed]
     [Google Scholar]
  17. Takai K, Horikoshi K. Thermosipho japonicus sp. nov., an extremely thermophilic bacterium isolated from a deep-sea hydrothermal vent in Japan. Extremophiles 2000; 4:9–17 [View Article] [PubMed]
     [Google Scholar]
  18. Lane DJ. 16S/23S rRNA Sequencing. In Stackebrandt E, Goodfellow M. eds Nucleic Acid Techniques in Bacterial Systematic New York: John Wiley and Sons; 1991 pp 115–175
     [Google Scholar]
  19. Yamaki S, Kawai Y, Yamazaki K. Characterization of a novel bacteriophage, Phda1, infecting the histamine-producing Photobacterium damselae subsp. damselae. J Appl Microbiol 2015; 118:1541–1550 [View Article] [PubMed]
     [Google Scholar]
  20. Nakakoshi M, Nishioka H, Katayama E. New versatile staining reagents for biological transmission electron microscopy that substitute for uranyl acetate. J Electron Microsc 2011; 60:401–407 [View Article] [PubMed]
     [Google Scholar]
  21. Mino S, Kudo H, Arai T, Sawabe T, Takai K et al. Sulfurovum aggregans sp. nov., a hydrogen-oxidizing, thiosulfate-reducing chemolithoautotroph within the Epsilonproteobacteria isolated from a deep-sea hydrothermal vent chimney, and an emended description of the genus Sulfurovum. Int J Syst Evol Microbiol 2014; 64:3195–3201 [View Article] [PubMed]
     [Google Scholar]
  22. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410 [View Article] [PubMed]
     [Google Scholar]
  23. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 2013; 41:D590–D596 [View Article] [PubMed]
     [Google Scholar]
  24. Pruesse E, Peplies J, Glöckner FO. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 2012; 28:1823–1829 [View Article] [PubMed]
     [Google Scholar]
  25. Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: Molecular Evolutionary Genetics Analysis across computing platforms. Mol Biol Evol 2018; 35:1547–1549 [View Article] [PubMed]
     [Google Scholar]
  26. Matsumoto Y, Ando Y, Hiraoka Y, Tawa A, Ohshimo S. A simplified gas chromatographic fatty-acid analysis by the direct saponification/methylation procedure and its application on wild tuna larvae. Lipids 2018; 53:919–929 [View Article] [PubMed]
     [Google Scholar]
  27. Fukazawa S, Mino S, Tsuchiya J, Nakagawa S, Takai K et al. Nitrosophilus kaiyonis sp. nov., a hydrogen-, sulfur- and thiosulfate-oxidizing chemolithoautotroph within “Campylobacteria” isolated from a deep-sea hydrothermal vent in the Mid-Okinawa trough. Arch Microbiol 2022; 205:12 [View Article] [PubMed]
     [Google Scholar]
  28. Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 2017; 13:e1005595 [View Article] [PubMed]
     [Google Scholar]
  29. Tanizawa Y, Fujisawa T, Nakamura Y. DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication. Bioinformatics 2018; 34:1037–1039 [View Article] [PubMed]
     [Google Scholar]
  30. Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol 2016; 428:726–731 [View Article] [PubMed]
     [Google Scholar]
  31. Kanehisa M, Sato Y. KEGG mapper for inferring cellular functions from protein sequences. Protein Sci 2020; 29:28–35 [View Article] [PubMed]
     [Google Scholar]
  32. Nakagawa S, Takai K, Inagaki F, Horikoshi K, Sako Y. Nitratiruptor tergarcus gen. nov., sp. nov. and Nitratifractor salsuginis gen. nov., sp. nov., nitrate-reducing chemolithoautotrophs of the ε-Proteobacteria isolated from a deep-sea hydrothermal system in the Mid-Okinawa trough. Int J Syst Evol Microbiol 2005; 55:925–933 [View Article] [PubMed]
     [Google Scholar]
  33. Meier-Kolthoff JP, Auch AF, Klenk H-P, Göker M. Genome sequence-based species delimitation with confidence intervals and improved distance functions. BMC Bioinformatics 2013; 14:60 [View Article] [PubMed]
     [Google Scholar]
  34. Yoon S-H, Ha S-M, Kwon S, Lim J, Kim Y et al. Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies. Int J Syst Evol Microbiol 2017; 67:1613–1617 [View Article] [PubMed]
     [Google Scholar]
  35. Rodriguez-R LM, Konstantinidis KT. The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes. PeerJ Preprints 2016; 4:e1900v1 [View Article]
     [Google Scholar]
  36. Eren AM, Kiefl E, Shaiber A, Veseli I, Miller SE et al. Community-led, integrated, reproducible multi-omics with anvi’o. Nat Microbiol 2021; 6:3–6 [View Article] [PubMed]
     [Google Scholar]
  37. Campbell JH, O’Donoghue P, Campbell AG, Schwientek P, Sczyrba A et al. UGA is an additional glycine codon in uncultured SR1 bacteria from the human microbiota. Proc Natl Acad Sci U S A 2013; 110:5540–5545 [View Article] [PubMed]
     [Google Scholar]
  38. Kozlov AM, Darriba D, Flouri T, Morel B, Stamatakis A. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics 2019; 35:4453–4455 [View Article] [PubMed]
     [Google Scholar]
  39. Teng W, Liao B, Chen M, Shu W. Genomic legacies of ancient adaptation illuminate GC-content evolution in bacteria. Microbiol Spectr 2023; 11:e0214522 [View Article] [PubMed]
     [Google Scholar]
  40. McWilliam H, Li W, Uludag M, Squizzato S, Park YM et al. Analysis tool web services from the EMBL-EBI. Nucleic Acids Res 2013; 41:W597–W600 [View Article] [PubMed]
     [Google Scholar]
  41. Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 2009; 25:1972–1973 [View Article] [PubMed]
     [Google Scholar]
  42. Keane TM, Creevey CJ, Pentony MM, Naughton TJ, Mclnerney JO. Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified. BMC Evol Biol 2006; 6:29 [View Article] [PubMed]
     [Google Scholar]
  43. Yarza P, Yilmaz P, Pruesse E, Glöckner FO, Ludwig W et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat Rev Microbiol 2014; 12:635–645 [View Article] [PubMed]
     [Google Scholar]
  44. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci U S A 2009; 106:19126–19131 [View Article] [PubMed]
     [Google Scholar]
  45. Shiotani T, Mino S, Sato W, Nishikawa S, Yonezawa M et al. Nitrosophilus alvini gen. nov., sp. nov., a hydrogen-oxidizing chemolithoautotroph isolated from a deep-sea hydrothermal vent in the East Pacific Rise, inferred by a genome-based taxonomy of the phylum “Campylobacterota”. PLoS One 2020; 15:e0241366 [View Article] [PubMed]
     [Google Scholar]
  46. Sabath N, Ferrada E, Barve A, Wagner A. Growth temperature and genome size in bacteria are negatively correlated, suggesting genomic streamlining during thermal adaptation. Genome Biol Evol 2013; 5:966–977 [View Article] [PubMed]
     [Google Scholar]
  47. Galtier N, Lobry JR. Relationships between genomic G+C content, RNA secondary structures, and optimal growth temperature in prokaryotes. J Mol Evol 1997; 44:632–636 [View Article] [PubMed]
     [Google Scholar]
  48. Hu E-Z, Lan X-R, Liu Z-L, Gao J, Niu D-K. A positive correlation between GC content and growth temperature in prokaryotes. BMC Genomics 2022; 23:110 [View Article] [PubMed]
     [Google Scholar]
  49. Weissman JL, Fagan WF, Johnson PLF. Linking high GC content to the repair of double strand breaks in prokaryotic genomes. PLoS Genet 2019; 15:e1008493 [View Article] [PubMed]
     [Google Scholar]
  50. Naya H, Romero H, Zavala A, Alvarez B, Musto H. Aerobiosis increases the genomic guanine plus cytosine content (GC%) in prokaryotes. J Mol Evol 2002; 55:260–264 [View Article] [PubMed]
     [Google Scholar]
  51. Foerstner KU, von Mering C, Hooper SD, Bork P. Environments shape the nucleotide composition of genomes. EMBO Rep 2005; 6:1208–1213 [View Article] [PubMed]
     [Google Scholar]
  52. Hershberg R, Petrov DA. Evidence that mutation is universally biased towards AT in bacteria. PLoS Genet 2010; 6:e1001115 [View Article] [PubMed]
     [Google Scholar]
  53. Raghavan R, Kelkar YD, Ochman H. A selective force favoring increased G+C content in bacterial genes. Proc Natl Acad Sci U S A 2012; 109:14504–14507 [View Article] [PubMed]
     [Google Scholar]
  54. Wolfe AJ. The acetate switch. Microbiol Mol Biol Rev 2005; 69:12–50 [View Article] [PubMed]
     [Google Scholar]
  55. Kakuda H, Shiroishi K, Hosono K, Ichihara S. Construction of Pta–Ack pathway deletion mutants of Escherichia coli and characteristic growth profiles of the mutants in a rich medium. Biosci Biotechnol Biochem 1994; 58:2232–2235 [View Article] [PubMed]
     [Google Scholar]
  56. Cao Q, Wang Y, Chen F, Xia Y, Lou J et al. A novel signal transduction pathway that modulates rhl quorum sensing and bacterial virulence in Pseudomonas aeruginosa. PLoS Pathog 2014; 10:e1004340 [View Article] [PubMed]
     [Google Scholar]
  57. Wolfe AJ, Chang D-E, Walker JD, Seitz-Partridge JE, Vidaurri MD et al. Evidence that acetyl phosphate functions as a global signal during biofilm development. Mol Microbiol 2003; 48:977–988 [View Article] [PubMed]
     [Google Scholar]
  58. Fields JA, Li J, Gulbronson CJ, Hendrixson DR, Thompson SA. Campylobacter jejuni CsrA regulates metabolic and virulence associated proteins and is necessary for mouse colonization. PLoS ONE 2016; 11:e0156932 [View Article] [PubMed]
     [Google Scholar]
  59. Hendrixson DR, DiRita VJ. Identification of Campylobacter jejuni genes involved in commensal colonization of the chick gastrointestinal tract. Mol Microbiol 2004; 52:471–484 [View Article] [PubMed]
     [Google Scholar]
  60. Luethy PM, Huynh S, Ribardo DA, Winter SE, Parker CT et al. Microbiota-derived short-chain fatty acids modulate expression of Campylobacter jejuni determinants required for commensalism and virulence. mBio 2017; 8:e00407-17 [View Article] [PubMed]
     [Google Scholar]
  61. Gao B, Vorwerk H, Huber C, Lara-Tejero M, Mohr J et al. Metabolic and fitness determinants for in vitro growth and intestinal colonization of the bacterial pathogen Campylobacter jejuni. PLoS Biol 2017; 15:e2001390 [View Article] [PubMed]
     [Google Scholar]
  62. Fukushi M, Mino S, Tanaka H, Nakagawa S, Takai K et al. Biogeochemical implications of N2O-reducing thermophilic "Campylobacteria" in deep-sea vent fields, and the description of Nitratiruptor labii sp. nov. iScience 2020; 23:101462 [View Article]
     [Google Scholar]
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Hydrogenimonas cancrithermarum sp. nov., a hydrogen- and thiosulfate-oxidizing mesophilic chemolithoautotroph isolated from diffuse-flow fluids on the East Pacific Rise, and an emended description of the genus Hydrogenimonas
Int J Syst Evol Microbiol 73, 006132 (2023); https://doi.org/10.1099/ijsem.0.006132
/content/journal/ijsem/10.1099/ijsem.0.006132
/content/journal/ijsem/10.1099/ijsem.0.006132
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