Dissimilatory sulfate reduction in the archaeon ‘Candidatus Vulcanisaeta moutnovskia’ sheds light on the evolution of sulfur metabolism


Dissimilatory sulfate reduction (DSR)—an important reaction in the biogeochemical sulfur cycle—has been dated to the Palaeoarchaean using geological evidence, but its evolutionary history is poorly understood. Several lineages of bacteria carry out DSR, but in archaea only Archaeoglobus, which acquired DSR genes from bacteria, has been proven to catalyse this reaction. We investigated substantial rates of sulfate reduction in acidic hyperthermal terrestrial springs of the Kamchatka Peninsula and attributed DSR in this environment to Crenarchaeota in the Vulcanisaeta genus. Community profiling, coupled with radioisotope and growth experiments and proteomics, confirmed DSR by ‘Candidatus Vulcanisaeta moutnovskia’, which has all of the required genes. Other cultivated Thermoproteaceae were briefly reported to use sulfate for respiration but we were unable to detect DSR in these isolates. Phylogenetic studies suggest that DSR is rare in archaea and that it originated in Vulcanisaeta, independent of Archaeoglobus, by separate acquisition of qmoABC genes phylogenetically related to bacterial hdrA genes.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Fig. 1: Growth of the binary culture on sulfate.
Fig. 2: Distribution of sulfate reduction and sulfur oxidation genes in archaea versus established bacterial groups.
Fig. 3: Phylogenetic analysis of AprA proteins.
Fig. 4: Gene synteny and cofactor composition of the Qmo/Hdr family.
Fig. 5: Phylogenetic analysis of HdrA-like proteins, including QmoA and QmoB.

Data availability

Candidatus Vulcanisaeta mountnovskia 768-28 has been deposited into the All-Russian Collection of Microorganisms (VKM) under accession number VKM B-3479. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE71 partner repository with the dataset identifier PXD012750. Pyrosequencing read data obtained for the 16S rRNA gene fragments were deposited in the Sequence Read Archive under the accession number PRJNA642261. To reproduce the results reported, the raw data are to be downloaded from the Sequence Read Archive and submitted to the SILVAngs analysis platform (https://ngs.arb-silva.de/silvangs/). We did not obtain any new genome assemblies, as the genomes used for computational analyses have already been reconstructed in previous and published work and are publicly available. The accession codes and taxonomic information of the genomes from the dataset are given in Supplementary Table 4. The binary culture genomes used here have been previously sequenced and published31,48 and have the GenBank accession codes CP002529 and CP002590. The alignments and phylogenies that form the basis of Figs. 3 and 5 and Extended Data Figs. 810 are available in Figshare (https://figshare.com/s/fb5a1541be68639f4026). Source data are provided with this paper.

Code availability

The small scripts used in this paper are available at https://figshare.com/s/fb5a1541be68639f4026.


  1. 1.

    Rabus, R. et al. A post-genomic view of the ecophysiology, catabolism and biotechnological relevance of sulphate-reducing prokaryotes. Adv. Microb. Physiol. 66, 55–321 (2015).

    CAS  PubMed  Google Scholar 

  2. 2.

    Wasmund, K., Mußmann, M. & Loy, A. The life sulfuric: microbial ecology of sulfur cycling in marine sediments. Environ. Microbiol. Rep. 9, 323–344 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Canfield, D. E., Rosing, M. T. & Bjerrum, C. Early anaerobic metabolisms. Phil. Trans. R. Soc. B Biol. Sci. 361, 1819–1836 (2006).

    CAS  Google Scholar 

  4. 4.

    Roerdink, D. L., Mason, P. R. D., Farquhar, J. & Reimer, T. Multiple sulfur isotopes in Paleoarchean barites identify an important role for microbial sulfate reduction in the early marine environment. Earth Planet. Sci. Lett. 331–332, 177–186 (2012).

    Google Scholar 

  5. 5.

    Crowe, S. A. et al. Sulfate was a trace constituent of Archean seawater. Science 346, 735–739 (2014).

    CAS  PubMed  Google Scholar 

  6. 6.

    Zhelezinskaia, I., Kaufman, A. J., Farquhar, J. & Cliff, J. Large sulfur isotope fractionations associated with Neoarchean microbial sulfate reduction. Science 346, 742–744 (2014).

    CAS  PubMed  Google Scholar 

  7. 7.

    Farquhar, J., Bao, H. M. & Thiemens, M. Atmospheric influence of Earth’s earliest sulfur cycle. Science 289, 756–758 (2000).

    CAS  PubMed  Google Scholar 

  8. 8.

    Loy, A., Kusel, K., Lehner, A., Drake, H. L. & Wagner, M. Microarray and functional gene analyses of sulfate-reducing prokaryotes in low-sulfate, acidic fens reveal cooccurrence of recognized genera and novel lineages. Appl. Env. Microbiol. 70, 6998–7009 (2004).

    CAS  Google Scholar 

  9. 9.

    Leloup, J. et al. Diversity and abundance of sulfate-reducing microorganisms in the sulfate and methane zones of a marine sediment, Black Sea. Environ. Microbiol. 9, 131–142 (2007).

    CAS  PubMed  Google Scholar 

  10. 10.

    Farquhar, J. et al. Pathways for Neoarchean pyrite formation constrained by mass-independent sulfur isotopes. Proc. Natl Acad. Sci. USA 110, 17638–17643 (2013).

    CAS  PubMed  Google Scholar 

  11. 11.

    Shen, Y., Buick, R. & Canfield, D. E. Isotopic evidence for microbial sulphate reduction in the early Archaean era. Nature 410, 77–81 (2001).

    CAS  PubMed  Google Scholar 

  12. 12.

    Wacey, D., Kilburn, M. R., Saunders, M., Cliff, J. & Brasier, M. D. Microfossils of sulphur-metabolizing cells in 3.4-billion-year-old rocks of Western Australia. Nat. Geosci. 4, 698–702 (2011).

    CAS  Google Scholar 

  13. 13.

    Ueno, Y., Ono, S., Rumble, D. & Maruyama, S. Quadruple sulfur isotope analysis of ca. 3.5 Ga Dresser Formation: new evidence for microbial sulfate reduction in the early Archean. Geochim. Cosmoch. Acta 72, 5675–5691 (2008).

    CAS  Google Scholar 

  14. 14.

    Anantharaman, K. et al. Expanded diversity of microbial groups that shape the dissimilatory sulfur cycle. ISME J. 12, 1715–1728 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Carr, S. A. et al. Carboxydotrophy potential of uncultivated Hydrothermarchaeota from the subseafloor crustal biosphere. ISME J. 13, 1457–1468 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    McKay, L. J. et al. Co-occurring genomic capacity for anaerobic methane and dissimilatory sulfur metabolisms discovered in the Korarchaeota. Nat. Microbiol. 4, 614–622 (2019).

    CAS  PubMed  Google Scholar 

  17. 17.

    Hua, Z. S. et al. Genomic inference of the metabolism and evolution of the archaeal phylum Aigarchaeota. Nat. Commun. 9, 2832 (2018).

    PubMed  PubMed Central  Google Scholar 

  18. 18.

    Tan, S. et al. Insights into ecological role of a new deltaproteobacterial order Candidatus Acidulodesulfobacterales by metagenomics and metatranscriptomics. ISME J. 13, 2044–2057 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Itoh, T., Suzuki, K., Sanchez, P. C. & Nakase, T. Caldivirga maquilingensis gen. nov., sp. nov., a new genus of rod-shaped crenarchaeote isolated from a hot spring in the Philippines. Int. J. Syst. Bacteriol. 49, 1157–1163 (1999).

    CAS  PubMed  Google Scholar 

  20. 20.

    Itoh, T., Suzuki, K. I. & Nakase, T. Vulcanisaeta distributa gen. nov., sp. nov., and Vulcanisaeta souniana sp. nov., novel hyperthermophilic, rod-shaped crenarchaeotes isolated from hot springs in Japan. Int. J. Syst. Evol. Microbiol. 52, 1097–1104 (2002).

    CAS  PubMed  Google Scholar 

  21. 21.

    Siebers, B. et al. The complete genome sequence of Thermoproteus tenax: a physiologically versatile member of the Crenarchaeota. PLoS ONE 6, e24222 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Yim, K. J., Song, H. S., Choi, J. S. & Roh, S. W. Thermoproteus thermophilus sp. nov., a hyperthermophilic crenarchaeon isolated from solfataric soil. Int. J. Syst. Evol. Microbiol. 65, 2507–2510 (2015).

    CAS  Google Scholar 

  23. 23.

    Pires, R. H. et al. A novel membrane-bound respiratory complex from Desulfovibrio desulfuricans ATCC 27774. Biochim. Biophys. Acta Bioenerg. 1605, 67–82 (2003).

    CAS  Google Scholar 

  24. 24.

    Pereira, I. A. C. et al. A comparative genomic analysis of energy metabolism in sulfate reducing bacteria and archaea. Front. Microbiol. 2, 69 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Santos, A. A. et al. A protein trisulfide couples dissimilatory sulfate reduction to energy conservation. Science 350, 1541–1545 (2015).

    CAS  PubMed  Google Scholar 

  26. 26.

    Wagner, M., Roger, A. J., Flax, J. L., Brusseau, G. A. & Stahl, D. A. Phylogeny of dissimilatory sulfite reductases supports an early origin of sulfate respiration. J. Bacteriol. 180, 2975–2982 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Müller, A. L., Kjeldsen, K. U., Rattei, T., Pester, M. & Loy, A. Phylogenetic and environmental diversity of DsrAB-type dissimilatory (bi)sulfite reductases. ISME J. 9, 1152–1165 (2015).

    PubMed  Google Scholar 

  28. 28.

    Meyer, B. & Kuever, J. Phylogeny of the alpha and beta subunits of the dissimilatory adenosine-5′-phosphosulfate (APS) reductase from sulfate-reducing prokaryotes—origin and evolution of the dissimilatory sulfate-reduction pathway. Microbiology 153, 2026–2044 (2007).

    CAS  PubMed  Google Scholar 

  29. 29.

    Frolov, E. N. et al. Sulfate reduction and inorganic carbon assimilation in acidic thermal springs of the Kamchatka peninsula. Microbiology 85, 471–480 (2016).

    CAS  Google Scholar 

  30. 30.

    Prokofeva, M. I. et al. Cultivated anaerobic acidophilic/acidotolerant thermophiles from terrestrial and deep-sea hydrothermal habitats. Extremophiles 9, 437–448 (2005).

    PubMed  Google Scholar 

  31. 31.

    Gumerov, V. M. et al. Complete genome sequence of Vulcanisaeta moutnovskia strain 768-28, a novel member of the hyperthermophilic crenarchaeal genus Vulcanisaeta. J. Bacteriol. 193, 2355–2356 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Brüchert, V., Knoblauch, C. & Jorgensen, B. B. Controls on stable sulfur isotope fractionation during bacterial sulfate reduction in arctic sediments. Geochim. Cosmochim. Acta 65, 763–776 (2001).

    Google Scholar 

  33. 33.

    Meier, J., Piva, A. & Fortin, D. Enrichment of sulfate-reducing bacteria and resulting mineral formation in media mimicking pore water metal ion concentrations and pH conditions of acidic pit lakes. FEMS Microbiol. Ecol. 79, 69–84 (2012).

    CAS  PubMed  Google Scholar 

  34. 34.

    Rinke, C. et al. Insights into the phylogeny and coding potential of microbial dark matter. Nature 499, 431–437 (2013).

    CAS  PubMed  Google Scholar 

  35. 35.

    Huwiler, S. G. et al. One-megadalton metalloenzyme complex in Geobacter metallireducens involved in benzene ring reduction beyond the biological redox window. Proc. Natl Acad. Sci. USA 116, 2259–2264 (2019).

    CAS  PubMed  Google Scholar 

  36. 36.

    Colman, D. R. et al. Phylogenomic analysis of novel Diaforarchaea is consistent with sulfite but not sulfate reduction in volcanic environments on early Earth. ISME J. 14, 1316–1331 (2020).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Meyer, B. & Kuever, J. Molecular analysis of the distribution and phylogeny of dissimilatory adenosine-5′-phosphosulfate reductase-encoding genes (aprBA) among sulfur-oxidizing prokaryotes. Microbiology 153, 3478–3498 (2007).

    CAS  PubMed  Google Scholar 

  38. 38.

    Watanabe, T., Kojima, H. & Fukui, M. Identity of major sulfur-cycle prokaryotes in freshwater lake ecosystems revealed by a comprehensive phylogenetic study of the dissimilatory adenylylsulfate reductase. Sci. Rep. 6, 36262 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Ramos, A. R., Keller, K. L., Wall, J. D. & Cardoso Pereira, I. A. C. The membrane QmoABC complex interacts directly with the dissimilatory adenosine 5′-phosphosulfate reductase in sulfate reducing bacteria. Front. Microbiol. 3, 137 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Zane, G. M., Yen, H. C. & Wall, J. D. Effect of the deletion of qmoABC and the promoter-distal gene encoding a hypothetical protein on sulfate reduction in Desulfovibrio vulgaris Hildenborough. Appl. Environ. Microbiol. 76, 5500–5509 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Buckel, W. & Thauer, R. K. Flavin-based electron bifurcation, a new mechanism of biological energy coupling. Chem. Rev. 118, 3862–3886 (2018).

    CAS  PubMed  Google Scholar 

  42. 42.

    Wagner, T., Koch, J., Ermler, U. & Shima, S. Methanogenic heterodisulfide reductase (HdrABC-MvhAGD) uses two noncubane [4Fe–4S] clusters for reduction. Science 357, 699–703 (2017).

    CAS  PubMed  Google Scholar 

  43. 43.

    Roychoudhury, A. N. Sulfate respiration in extreme environments: a kinetic study. Geomicrobiol. J. 21, 33–43 (2004).

    CAS  Google Scholar 

  44. 44.

    Pimenov, N. V. & Bonch-Osmolovskaya, E. A. 2 in situ activity studies in thermal environments. Methods Microbiol. 35, 29–53 (2006).

    CAS  Google Scholar 

  45. 45.

    Chernyh, N. A. et al. Microbial life in Bourlyashchy, the hottest thermal pool of Uzon Caldera, Kamchatka. Extremophiles 19, 1157–1171 (2015).

    CAS  PubMed  Google Scholar 

  46. 46.

    Dhillon, A., Goswami, S., Riley, M., Teske, A. & Sogin, M. Domain evolution and functional diversification of sulfite reductases. Astrobiology 5, 18–29 (2005).

    CAS  PubMed  Google Scholar 

  47. 47.

    Sousa, F. L. et al. Early bioenergetic evolution. Phil. Trans. R. Soc. Lond. B Biol. Sci. 368, 20130088 (2013).

    Google Scholar 

  48. 48.

    Mardanov, A. V. et al. Complete genome sequence of the thermoacidophilic crenarchaeon Thermoproteus uzoniensis 768-20. J. Bacteriol. 193, 3156–3157 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Bonch-Osmolovskaya, E. A., Miroshnichenko, M. L., Kostrikina, N. A., Chernych, N. A. & Zavarzin, G. A. Thermoproteus uzoniensis sp. nov., a new extremely thermophilic archaebacterium from Kamchatka continental hot springs. Arch. Microbiol. 154, 556–559 (1990).

    CAS  Google Scholar 

  50. 50.

    Wolin, E. A., Wolin, M. J. & Wolfe, R. S. Formation of methane by bacterial extracts. J. Biol. Chem. 238, 2882–2886 (1963).

    CAS  PubMed  Google Scholar 

  51. 51.

    Kevbrin, V. V. & Zavarzin, G. A. The effect of sulfur compounds on the growth of the halophilic homoacetic bacterium Acetohalobium arabaticum. Mikrobiologiya 61, 563–567 (1992).

    Google Scholar 

  52. 52.

    Lane, D. J. in Nucleic Acid Techniques in Bacterial Systematics (eds Stackebrandt, E. & Goodfellow, M.) 115–175 (John Wiley & Sons, 1991).

  53. 53.

    Muyzer, G. & Smalla, K. Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) in microbial ecology. Antonie Van Leeuwenhoek 73, 127–141 (1998).

    CAS  PubMed  Google Scholar 

  54. 54.

    Kublanov, I. V. et al. Biodiversity of thermophiiic prokaryotes with hydrolytic activities in hot springs of Uzon Caldera, Kamchatka (Russia). Appl. Environ. Microbiol. 75, 286–291 (2009).

    CAS  PubMed  Google Scholar 

  55. 55.

    Stahl, D. A. & Amann, R. in Nucleic Acid Techniques in Bacterial Systematics (eds Stackebrandt, E. & Goodfellow, M.) 205–248 (John Wiley & Sons, 1991).

  56. 56.

    Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. USA 108, 4516–4522 (2011).

    CAS  PubMed  Google Scholar 

  57. 57.

    Hugerth, L. W. et al. DegePrime, a program for degenerate primer design for broad-taxonomic-range PCR in microbial ecology studies. Appl. Environ. Microbiol. 80, 5116–5123 (2014).

    PubMed  PubMed Central  Google Scholar 

  58. 58.

    Arike, L. & Peil, L. in Methods in Molecular Biology (ed. Martins-de-Souza, D.) 213–222 (Springer Science+Business Media, 2014).

  59. 59.

    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012).

    PubMed  PubMed Central  Google Scholar 

  60. 60.

    Chao, A. Non-parametric estimation of the classes in a population. Scand. J. Stat. 11, 265–270 (1984).

    Google Scholar 

  61. 61.

    Trüper, H. G. & Schlegel, H. G. Sulphur metabolism in Thiorhodaceae I. Quantitative measurements on growing cells of Chromatium okenii. Antonie van Leeuwenhoek 30, 225–238 (1964).

    Google Scholar 

  62. 62.

    Sorokin, Di. Y. et al. Discovery of extremely halophilic, methyl-reducing euryarchaea provides insights into the evolutionary origin of methanogenesis. Nat. Microbiol. 2, 17081 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. 63.

    Altschul, S. F. et al. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res. 25, 3389–3402 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    Guy, L., Roat Kultima, J. & Andersson, S. G. E. genoPlotR: comparative gene and genome visualization in R. Bioinformatics 26, 2334–2335 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65.

    Krogh, A., Larsson, B., von Heijne, G. & Sonnhammer, E. L. Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 305, 567–580 (2001).

    CAS  PubMed  Google Scholar 

  66. 66.

    Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007).

    CAS  Google Scholar 

  67. 67.

    Capella-Gutiérrez, S., Silla-Martínez, J. M. & Gabaldón, T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics 25, 1972–1973 (2009).

    PubMed  PubMed Central  Google Scholar 

  68. 68.

    Nguyen, L.-T., Schmidt, H. A., von Haeseler, A. & Minh, B. Q. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).

    CAS  Google Scholar 

  69. 69.

    Tria, F. D. K., Landan, G. & Dagan, T. Phylogenetic rooting using minimal ancestor deviation. Nat. Ecol. Evol. 1, 0193 (2017).

    Google Scholar 

  70. 70.

    Grein, F., Ramos, A. R., Venceslau, S. S. & Pereira, I. A. C. Unifying concepts in anaerobic respiration: insights from dissimilatory sulfur metabolism. Biochim. Biophys. Acta Bioenerg. 1827, 145–160 (2013).

    CAS  Google Scholar 

  71. 71.

    Perez-Riverol, Y. et al. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 47, D442–D450 (2019).

    CAS  PubMed  Google Scholar 

Download references


We thank G. Landan for sharing with us the updated version of the minimal ancestor deviation method. This work was supported by the Russian Science Foundation (grant number 17-74-30025) and in part by the grant from the Russian Ministry of Science and Higher Education (to N.A.C., A.V.L., E.N.F., M.L.M., A.Y.M., N.V.P. and E.A.B.-O.). Sequencing of PCR amplicons was performed using the scientific equipment of the core research facility ‘Bioengineering’ by T. Kolganova. The proteomics analysis was performed at the Proteomics Facility of the Spanish National Center for Biotechnology (CNB-CSIC), which belongs to ProteoRed, PRB2-ISCIII, supported by grant PT13/0001 (to S.C., M.C.M. and M.F.). P.N.G. acknowledges funding from the UK Biotechnology and Biological Sciences Research Council (BBSRC) within the ERA NET-IB2 programme, grant number ERA-IB-14-030 and the European Union Horizon 2020 Research and Innovation programme (Blue Growth: Unlocking the Potential of Seas and Oceans) under grant agreement number 634486, as well as support from the Centre for Environmental Biotechnology project, part funded by the European Regional Development Fund (ERDF) through the Welsh Government, and support from the Centre of Environmental Biotechnology. D.Y.S. was supported by the SIAM/Gravitation Program (Dutch Ministry of Education, Culture and Science; grant 24002002) and RFBR grant 19-04-00401. F.L.S. and S.N. acknowledge support from the Wiener Wissenschafts, Forschungs- und Technologiefonds (Austria) through the grant VRG15-007. F.L.S. gratefully acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation programme (grant agreement 803768). I.A.C.P. acknowledges support from the Fundação para a Ciência e Tecnologia (Portugal) through grant PTDC/BIA-BQM/29118/2017 and R&D unit MOSTMICRO-ITQB (UIDB/04612/2020 and UIDP/04612/2020).

Author information




N.A.C. designed the research. N.A.C. and E.N.F. performed the fieldwork and sediment activity determinations. E.N.F. and M.L.M. enriched and maintained archaeal cultures and performed microbiological studies on them. S.N., F.L.S., N.A.C. and A.V.L. performed genomic analysis and evolutionary reconstructions. A.Y.M. analysed 16S rRNA genes in sediments and carried out qPCR. N.V.P. performed radioisotope research. S.C., M.C.M., M.F. and P.N.G. performed the proteomic analysis. N.A.C., A.V.L., I.A.C.P., F.L.S., S.N., E.N.F., D.Y.S. and E.A.B.-O. analysed the data and wrote the paper. All authors have seen and approved the final version submitted.

Corresponding authors

Correspondence to Nikolay A. Chernyh or Filipa L. Sousa or Inês A. Cardoso Pereira.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 The microbial community composition of Oreshek Spring.

Analysis by high throughput sequencing of 16S rRNA gene fragments.

Extended Data Fig. 2 Growth of Thermoproteus tenax.

The error bars are SD from independent growth replicates (n = 3). Source data

Extended Data Fig. 3 Growth of Caldivirga maquilingensis.

Error bars represent standard deviations from independent growth replicates (n = 3). Source data

Extended Data Fig. 4 H35Sformation from 35SO4-2 the binary culture 768-28 and the cultures of hyperthermophilic Crenarchaeota strains earlier claimed to be capable of sulphate reduction, but without experimental evidence.

Error bars represent standard deviations of independent radioisotopic measurement experiments (n = 3). Source data

Extended Data Fig. 5 Genes related to sulphate reduction.

The key sulphate reduction genes from genomes of selected sulphate reducing archaea (‘Candidatus V. moutnovskia’, Caldivirga sp. Obs2 and A. fulgidus) and bacteria (D. vulgaris Hildenborough and A. degensii) are shown, as well as from genomes of archaea not capable of sulphate reduction (V. distributa, V. souniana, Caldivirga sp. MU80, Ca. Methanodesulfokores washburnensis MDKW and unclassified Aigarchaeota JZ bin 15).

Extended Data Fig. 6 Proteomic analysis of the soluble fraction of cells in the binary culture.

Protein extraction was performed with a non-denaturing detergent. Only the 150 most abundant proteins of ‘Candidatus V. moutnovskia’ are shown. a. Binary culture grown on medium with yeast extract and sulphate as the electron acceptor. b. Binary culture grown on medium with yeast extract and elemental sulphur as the electron acceptor. Protein abundances in mol% were estimated from nemPAI values58. Data are shown as the mean of n = 2 independent experiments fitted into a model. Source data

Extended Data Fig. 7 Proteomic analysis of the binary culture after protein extraction with denaturing detergent.

Only proteins of ‘Candidatus V. moutnovskia’ are shown. The binary culture was grown on medium with yeast extract and sulphate as the electron acceptor. Protein abundances in mol% were estimated from nemPAI values58. Data are shown as the mean of n = 3 independent experiments fitted into a model. Source data

Extended Data Fig. 8 Phylogenetic analysis of AprAB.

Maximum likelihood phylogenetic reconstruction (LG+I+G4) of a. AprA and b. AprB proteins present in the selected dataset. Only support values above 50 are shown. The scale bar indicates number of substitutions per site.

Extended Data Fig. 9 Phylogenetic analysis of Sat.

Maximum likelihood phylogenetic reconstruction (LG+I+G4) of Sat proteins within the selected dataset. Only non-parametric support values above 70 are shown. The scale bar indicates number of substitutions per site.

Extended Data Fig. 10 Phylogenetic analysis of HdrA-like proteins.

Maximum-likelihood reconstruction (LG+I+G4) of the HdrA-domain present in 1,391 non-redundant HdrA, QmoA and QmoB proteins. The ‘Candidatus V. moutnovskia’ sequences are marked in red. Expanded insets of the ‘Candidatus V. moutnovskia’ QmoA (a) and QmoB (b) clades (marked in blue) are shown in Fig. 5. The scale bar indicates number of substitutions per site.

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Tables 1–3.

Reporting Summary

Supplementary Table 4

Genomic dataset used in the analysis, including accession codes, taxonomic information and file location in the original database.

Source data

Source Data Fig. 1

Binary culture growth source data.

Source Data Fig. 2

Protein accessions of the hits underlying each symbol in Fig. 2.

Source Data Extended Data Fig. 2

Raw data and calculations supporting Extended Data Fig. 2.

Source Data Extended Data Fig. 3

Raw data and calculations supporting Extended Data Fig. 3.

Source Data Extended Data Fig. 4

Raw data and calculations supporting Extended Data Fig. 4.

Source Data Extended Data Fig. 6

Raw data and calculations supporting Extended Data Fig. 6.

Source Data Extended Data Fig. 7

Raw data and calculations supporting Extended Data Fig. 7.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chernyh, N.A., Neukirchen, S., Frolov, E.N. et al. Dissimilatory sulfate reduction in the archaeon ‘Candidatus Vulcanisaeta moutnovskia’ sheds light on the evolution of sulfur metabolism. Nat Microbiol 5, 1428–1438 (2020). https://doi.org/10.1038/s41564-020-0776-z

Download citation


Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing