Abstract
Methanogenic archaea are main contributors to methane emissions, and have a crucial role in carbon cycling and global warming. Until recently, methanogens were confined to Euryarchaeota, but metagenomic studies revealed the presence of genes encoding the methyl coenzyme M reductase complex in other archaeal clades1,2,3,4, thereby opening up the premise that methanogenesis is taxonomically more widespread. Nevertheless, laboratory cultivation of these non-euryarchaeal methanogens was lacking to corroborate their potential methanogenic ability and physiology. Here we report the isolation of a thermophilic archaeon LWZ-6 from an oil field. This archaeon belongs to the class Methanosuratincolia (originally affiliated with ‘Candidatus Verstraetearchaeota’) in the phylum Thermoproteota. Methanosuratincola petrocarbonis LWZ-6 is a strict hydrogen-dependent methylotrophic methanogen. Although previous metagenomic studies speculated on the fermentative potential of Methanosuratincolia members, strain LWZ-6 does not ferment sugars, peptides or amino acids. Its energy metabolism is linked only to methanogenesis, with methanol and monomethylamine as electron acceptors and hydrogen as an electron donor. Comparative (meta)genome analysis confirmed that hydrogen-dependent methylotrophic methanogenesis is a widespread trait among Methanosuratincolia. Our findings confirm that the diversity of methanogens expands beyond the classical Euryarchaeota and imply the importance of hydrogen-dependent methylotrophic methanogenesis in global methane emissions and carbon cycle.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
27,99 € / 30 days
cancel any time
Subscribe to this journal
Receive 51 print issues and online access
199,00 € per year
only 3,90 € per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout




Similar content being viewed by others
Data availability
The 16S rRNA gene amplicon sequences, metagenomic, genomic and transcriptome data generated in the current study are publicly available under BioProject accession number PRJNA992765 and at the NODE database (https://www.biosino.org/node/project/detail/OEP003742). Further details are provided in Supplementary Table 7. All other data are presented in the Article and its Supplementary Information. Source data are provided with this paper.
Code availability
The codes and programs used for analyses are mentioned in the Methods, and they are available at GitHub (https://github.com/zhuozhou1993/Methanosuratus/blob/main/code).
Change history
02 September 2024
A Correction to this paper has been published: https://doi.org/10.1038/s41586-024-08000-z
References
Evans, P. N. et al. Methane metabolism in the archaeal phylum Bathyarchaeota revealed by genome-centric metagenomics. Science 350, 434–438 (2015).
Vanwonterghem, I. et al. Methylotrophic methanogenesis discovered in the archaeal phylum Verstraetearchaeota. Nat. Microbiol. 1, 16170 (2016).
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).
Wang, Y., Wegener, G., Hou, J., Wang, F. & Xiao, X. Expanding anaerobic alkane metabolism in the ___domain of Archaea. Nat. Microbiol. 4, 595–602 (2019).
Martin, W. & Russell, M. J. On the origin of biochemistry at an alkaline hydrothermal vent. Philos. Trans. R. Soc. Lond. B 362, 1887–1925 (2007).
Saunois, M. et al. The global methane budget 2000-2017. Earth Syst. Sci. Data 12, 1561–1623 (2020).
Ferry, J. G. Methanogenesis: Ecology, Physiology, Biochemistry & Genetics (Springer, 2012).
Woese, C. R., Kandler, O. & Wheelis, M. L. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc. Natl Acad. Sci. USA 87, 4576–4579 (1990).
Ermler, U., Grabarse, W., Shima, S., Goubeaud, M. & Thauer, R. K. Crystal structure of methyl-coenzyme M reductase: the key enzyme of biological methane formation. Science 278, 1457–1462 (1997).
Wang, J. et al. Evidence for nontraditional mcr-containing archaea contributing to biological methanogenesis in geothermal springs. Sci. Adv. 9, eadg6004 (2023).
Berghuis, B. A. et al. Hydrogenotrophic methanogenesis in archaeal phylum Verstraetearchaeota reveals the shared ancestry of all methanogens. Proc. Natl Acad. Sci. USA 116, 5037–5044 (2019).
Borrel, G. et al. Wide diversity of methane and short-chain alkane metabolisms in uncultured archaea. Nat. Microbiol. 4, 603–613 (2019).
Ou, Y.-F. et al. Expanding the phylogenetic distribution of cytochrome b-containing methanogenic archaea sheds light on the evolution of methanogenesis. ISME J. 16, 2373–2387 (2022).
Parks, D. H. et al. GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Res. 50, D785–D794 (2022).
Mand, T. D. & Metcalf, W. W. Energy conservation and hydrogenase function in methanogenic archaea, in particular the genus Methanosarcina. Microbiol. Mol. Biol. Rev. 83, e00020-19 (2019).
Zhou, Z. et al. Non-syntrophic methanogenic hydrocarbon degradation by an archaeal species. Nature 601, 257–262 (2022).
Mayumi, D. et al. Methane production from coal by a single methanogen. Science 354, 222–225 (2016).
Garcia, P. S., Gribaldo, S. & Borrel, G. Diversity and evolution of methane-related pathways in archaea. Annu. Rev. Microbiol. 76, 727–755 (2022).
Liu, Y.-F. et al. Long-term cultivation and meta-omics reveal methylotrophic methanogenesis in hydrocarbon-impacted habitats. Engineering 24, 265–274 (2023).
Hua, Z.-S. et al. Insights into the ecological roles and evolution of methyl-coenzyme M reductase-containing hot spring Archaea. Nat. Commun. 10, 4574 (2019).
Evans, P. N. et al. An evolving view of methane metabolism in the Archaea. Nat. Rev. Microbiol. 17, 219–232 (2019).
Cheng, L. et al. Isolation and characterization of Methanoculleus receptaculi sp. nov. from Shengli oil field, China. FEMS Microbiol. Lett. 285, 65–71 (2008).
Oren, A., Garrity, G. M., Parker, C. T., Chuvochina, M. & Trujillo, M. E. Lists of names of prokaryotic Candidatus taxa. Int. J. Syst. Evol. Microbiol. 70, 3956–4042 (2020).
Lang, K. et al. New mode of energy metabolism in the seventh order of methanogens as revealed by comparative genome analysis of Candidatus Methanoplasma termitum. Appl. Environ. Microbiol. 81, 1338–1352 (2015).
Thauer, R. K., Kaster, A.-K., Seedorf, H., Buckel, W. & Hedderich, R. Methanogenic archaea: ecologically relevant differences in energy conservation. Nat. Rev. Microbiol. 6, 579–591 (2008).
Yarza, P. et al. Uniting the classification of cultured and uncultured bacteria and archaea using 16S rRNA gene sequences. Nat. Rev. Microbiol. 12, 635–645 (2014).
Konstantinidis, K. T., Rosselló-Móra, R. & Amann, R. Uncultivated microbes in need of their own taxonomy. ISME J. 11, 2399–2406 (2017).
Speth, D. R. et al. Microbial communities of Auka hydrothermal sediments shed light on vent biogeography and the evolutionary history of thermophily. ISME J. 16, 1750–1764 (2022).
Wang, Y. et al. A methylotrophic origin of methanogenesis and early divergence of anaerobic multicarbon alkane metabolism. Sci. Adv. 7, eabj1453 (2021).
Liu, Y.-F. et al. Anaerobic degradation of paraffins by thermophilic Actinobacteria under methanogenic conditions. Environ. Sci. Technol. 54, 10610–10620 (2020).
Feldewert, C., Lang, K. & Brune, A. The hydrogen threshold of obligately methyl-reducing methanogens. FEMS Microbiol. Lett. 367, fnaa137 (2020).
Zhuang, G.-C., Lin, Y.-S., Elvert, M., Heuer, V. B. & Hinrichs, K.-U. Gas chromatographic analysis of methanol and ethanol in marine sediment pore waters: validation and implementation of three pretreatment techniques. Mar. Chem. 160, 82–90 (2014).
Zhuang, G.-C., Peña-Montenegro, T. D., Montgomery, A., Hunter, K. S. & Joye, S. B. Microbial metabolism of methanol and methylamine in the Gulf of Mexico: insight into marine carbon and nitrogen cycling. Environ. Microbiol. 20, 4543–4554 (2018).
Miller, T. L. & Wolin, M. J. Methanosphaera stadtmaniae gen. nov., sp. nov.: a species that forms methane by reducing methanol with hydrogen. Arch. Microbiol. 141, 116–122 (1985).
Sprenger, W. W., van Belzen, M. C., Rosenberg, J., Hackstein, J. H. & Keltjens, J. T. Methanomicrococcus blatticola gen. nov., sp. nov., a methanol- and methylamine-reducing methanogen from the hindgut of the cockroach Periplaneta americana. Int. J. Syst. Evol. Microbiol. 50, 1989–1999 (2000).
Dridi, B., Fardeau, M.-L., Ollivier, B., Raoult, D. & Drancourt, M. Methanomassiliicoccus luminyensis gen. nov., sp. nov., a methanogenic archaeon isolated from human faeces. Int. J. Syst. Evol. Microbiol. 62, 1902–1907 (2012).
Sorokin, D. Y. et al. Discovery of extremely halophilic, methyl-reducing euryarchaea provides insights into the evolutionary origin of methanogenesis. Nat. Microbiol. 2, 17081 (2017).
Verhees, C. H. et al. The unique features of glycolytic pathways in Archaea. Biochem. J 375, 231–246 (2003).
Tersteegen, A., Linder, D., Thauer, R. K. & Hedderich, R. Structures and functions of four anabolic 2‐oxoacid oxidoreductases in Methanobacterium thermoautotrophicum. Eur. J. Biochem. 244, 862–868 (1997).
Glasemacher, J., Bock, A. K., Schmid, R. & Schönheit, P. Purification and properties of acetyl‐CoA synthetase (ADP‐forming), an archaeal enzyme of acetate formation and ATP synthesis, from the hyperthermophile Pyrococcus furiosus. Eur. J. Biochem. 244, 561–567 (1997).
Adam, P. S., Kolyfetis, G. E., Bornemann, T. L., Vorgias, C. E. & Probst, A. J. Genomic remnants of ancestral methanogenesis and hydrogenotrophy in Archaea drive anaerobic carbon cycling. Sci. Adv. 8, eabm9651 (2022).
Beulig, F., Røy, H., McGlynn, S. E. & Jørgensen, B. B. Cryptic CH4 cycling in the sulfate-methane transition of marine sediments apparently mediated by ANME-1 archaea. ISME J. 13, 250–262 (2019).
Kohtz, A. J. et al. Cultivation and visualization of a methanogen of the phylum Thermoproteota. Nature https://doi.org/10.1038/s41586-024-07631-6 (2024).
Rabus, R., Hansen, T., Widdel, F. & Dworkin, M. The Prokaryotes: Ecophysiology and Biochemistry (Springer, 2006).
Wolin, E. A., Wolin, M. J. & Wolfe, R. S. Formation of methane by bacterial extracts. J. Biol. Chem. 238, 2882–2886 (1963).
Plugge, C. M. Anoxic media design, preparation, and considerations. Methods Enzymol. 397, 3–16 (2005).
Wu, K. et al. Gudongella oleilytica gen. nov., sp. nov., an aerotorelant bacterium isolated from Shengli oilfield and validation of family Tissierellaceae. Int. J. Syst. Evol. Microbiol. 70, 951–957 (2020).
Neubauer, S. et al. U13C cell extract of Pichia pastoris—a powerful tool for evaluation of sample preparation in metabolomics. J. Sep. Sci. 35, 3091–3105 (2012).
Ver Eecke, H. C., Akerman, N. H., Huber, J. A., Butterfield, D. A. & Holden, J. F. Growth kinetics and energetics of a deep-sea hyperthermophilic methanogen under varying environmental conditions. Environ. Micobiol. Rep. 5, 665–671 (2013).
Cheng, L., Dai, L., Li, X., Zhang, H. & Lu, Y. Isolation and characterization of Methanothermobacter crinale sp. nov., a novel hydrogenotrophic methanogen from the Shengli oil field. Appl. Environ. Microbiol. 77, 5212–5219 (2011).
Cheng, L., Rui, J., Li, Q., Zhang, H. & Lu, Y. Enrichment and dynamics of novel syntrophs in a methanogenic hexadecane-degrading culture from a Chinese oilfield. FEMS. Microbiol. Ecol. 83, 757–766 (2013).
Cheng, L. et al. DNA-SIP reveals that Syntrophaceae play an important role in methanogenic hexadecane degradation. PLoS ONE 8, e66784 (2013).
Stahl, D. A. & Amann, R. in Nucleic Acid Techniques in Bacterial Systematics (eds Stackebrandt, E. & Goodfellow, M.) (Wiley, 1991).
Pernthaler, A., Preston, C. M., Pernthaler, J., DeLong, E. F. & Amann, R. Comparison of fluorescently labeled oligonucleotide and polynucleotide probes for the detection of pelagic marine bacteria and archaea. Appl. Environ. Microbiol. 68, 661–667 (2002).
Chi, Z.-L., Yu, G.-H., Kappler, A., Liu, C.-Q. & Gadd, G. M. Fungal–mineral interactions modulating intrinsic peroxidase-like activity of iron nanoparticles: implications for the biogeochemical cycles of nutrient elements and attenuation of contaminants. Environ. Sci. Technol. 56, 672–680 (2021).
Yu, G.-H. et al. Fungal nanophase particles catalyze iron transformation for oxidative stress removal and iron acquisition. Curr. Biol. 30, 2943–2950 (2020).
Zeng, Z. et al. GDGT cyclization proteins identify the dominant archaeal sources of tetraether lipids in the ocean. Proc. Natl Acad. Sci. USA 116, 22505–22511 (2019).
Chen, Y. et al. The production of diverse brGDGTs by an Acidobacterium providing a physiological basis for paleoclimate proxies. Geochim. Cosmochim. Acta 337, 155–165 (2022).
Thiele, B. & Matsubara, S. in Plant and Food Carotenoids. Methods in Molecular Biology (eds Rodríguez-Concepción, M. & Welsch, R.) (263–277 (Humana, 2020).
Knappy, C. et al. Mono‐, di‐ and trimethylated homologues of isoprenoid tetraether lipid cores in archaea and environmental samples: mass spectrometric identification and significance. J. Mass Spectrom. 50, 1420–1432 (2015).
Lane, D. J. in Nucleic Acid Techniques in Bacterial Systematics (eds Stackebrandt, E. & Goodfellow, M.) 115–175 (Wiley, 1991).
Grosskopf, R., Janssen, P. H. & Liesack, W. Diversity and structure of the methanogenic community in anoxic rice paddy soil microcosms as examined by cultivation and direct 16S rRNA gene sequence retrieval. Appl. Environ. Microbiol. 64, 960–969 (1998).
Klindworth, A. et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 41, e1 (2012).
Hiergeist, A., Reischl, U. & Gessner, A. Multicenter quality assessment of 16S ribosomal DNA-sequencing for microbiome analyses reveals high inter-center variability. Int. J. Med. Microbiol. 306, 334–342 (2016).
Wei, S. et al. Comparative evaluation of three archaeal primer pairs for exploring archaeal communities in deep-sea sediments and permafrost soils. Extremophiles 23, 747–757 (2019).
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).
Magoč, T. & Salzberg, S. L. FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27, 2957–2963 (2011).
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).
Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).
Yilmaz, P. et al. The SILVA and “All-species Living Tree Project (LTP)” taxonomic frameworks. Nucleic Acids Res. 42, D643–D648 (2013).
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).
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 27, 824–834 (2017).
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).
Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36, 1925–1927 (2019).
Yoon, S. H., Ha, S. M., Lim, J., Kwon, S. & Chun, J. A large-scale evaluation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110, 1281–1286 (2017).
Qin, Q. L. et al. A proposed genus boundary for the prokaryotes based on genomic insights. J. Bacteriol. 196, 2210–2215 (2014).
Olm, M. R., Brown, C. T., Brooks, B. & Banfield, J. F. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 11, 2864–2868 (2017).
Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinform. 11, 119 (2010).
Kanehisa, M., Sato, Y. & Morishima, K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J. Mol. Biol. 428, 726–731 (2016).
Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).
The UniProt Consortium. UniProt: the universal protein knowledgebase in 2021. Nucleic Acids Res. 49, D480–D489 (2020).
Marchler-Bauer, A. & Bryant, S. H. CD-Search: protein ___domain annotations on the fly. Nucleic Acids Res. 32, W327–W331 (2004).
Uritskiy, G. V., DiRuggiero, J. & Taylor, J. MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome 6, 158 (2018).
Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res. 27, 722–736 (2017).
Kolmogorov, M. et al. metaFlye: scalable long-read metagenome assembly using repeat graphs. Nat. Methods 17, 1103–1110 (2020).
Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).
Wick, R. R., Schultz, M. B., Zobel, J. & Holt, K. E. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 31, 3350–3352 (2015).
Lee, M. D. GToTree: a user-friendly workflow for phylogenomics. Bioinformatics 35, 4162–4164 (2019).
Minh, B. Q. et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534 (2020).
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).
Katoh, K., Misawa, K., Kuma, K. I. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).
Kalyaanamoorthy, S., Minh, B. Q., Wong, T. K. F., von Haeseler, A. & Jermiin, L. S. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589 (2017).
Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).
Kopylova, E., Noé, L. & Touzet, H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics 28, 3211–3217 (2012).
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at arxiv.org/abs/1303.3997 (2013).
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Quinlan, A. R. BEDTools: the Swiss-army tool for genome feature analysis. Curr. Protoc. Bioinform. 47, 11.12.11–11.12.34 (2014).
Li, W. & Godzik, A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22, 1658–1659 (2006).
Brownrigg., R., Becker, R. A. & Wilks, A. R. maps: draw geographical maps. R package version 3.4.2 (2023); cran.r-project.org/web/packages/maps/maps.pdf
Wilkinson, L. ggplot2: elegant graphics for data analysis. Biometrics 67, 678–679 (2011).
Acknowledgements
We thank P. Geesink for performing Nanopore sequencing of strain LWZ-6; W. B. Whitman for comments on the manuscript; L.-r. Dai, M. Yang and L. Fu for assisting in cultivation and experiments; Z. Zhou for technical support; and P. Vandamme for advice on the etymology of the new names proposed. This study was supported by National Natural Science Foundation of China (92051108, 92351301, 31970066, 42203080 and 42207167), Agricultural Science and Technology Innovation Project of the Chinese Academy of Agriculture Science (CAAS-ASTIP-2021-BIOMA-01), CAAS Center for Science in Agricultural Green and Low Carbon (CAAS-CSGLCA-202301), Sichuan Science and Technology program (2024NSFTD0093), Netherlands Ministry of Education, Culture and Science (project 024.002.002: Soehngen Institute of Anaerobic Microbiology), European Research Council (grant 817834), the Dutch Research Council (grant VI.C.192.016), the Central Public-interest Scientific Institution Basal Research Fund (1610012017002_05103), the Stable Support Plan Program of Shenzhen Natural Science Fund (20200925173954005) and the Shenzhen Key Laboratory of Marine Archaea Geo-Omics, Southern University of Science and Technology (ZDSYS201802081843490). The Article is dedicated to our co-author W.-H.H.
Author information
Authors and Affiliations
Contributions
L.C. initiated the study. L.C., D.Z.S., K.-j.W., T.J.G.E. and L.Z. designed the research. L.-y.L. performed the initial cultivation. K.-j.W., L.Z., L.-y.L. and J.L. performed the isolation process and physiological experiments. G.T. and W.-h.H. performed all bioinformatics analyses. C.-p.D. performed CARD-FISH. J.-c.Z. performed NanoSIMS. F.-f.Z. and C.-l.Z. performed lipid-SIP. L.F. and L.-p.B. performed biochemical analysis. K.-j.W. and L.Z. analysed data. X.-z.D. provided constructive suggestions on the isolation process. K.-j.W., L.C., X.-z.D., T.J.G.E. and D.Z.S. wrote the manuscript with the contributions from all of the authors.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature thanks the anonymous reviewers for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data figures and tables
Extended Data Fig. 1 Methanosuratincolia communities were detected in numerous enrichments.
The enrichments were initially established from oily sludge or oil-produced water and incubated with various substrates such as acetate, propionate, butyrate, alkanes, and oil at temperatures ranging from 25 °C to 75 °C. Alkanes mix includes n-docosane, n-hexadecylcyclohexane, and n-hexadecylbenzene. The blank represents no enrichments performed on these conditions. Abundance 20, 40, and 60 show the relative abundance of Methanosuratincolia populations in total archaea by 16S rRNA gene amplicon sequencing.
Extended Data Fig. 2 Consecutive subcultures amended with methanol as a substrate to eliminate Methanoculleus recptaculi (Mcl).
a, CH4 production, b, the copy numbers of LWZ-6, c, the copy numbers of Mcl. Culture-1,2,3 represent triplicate tubes used for subcultures. The arrows indicate the subculture points, the subculture dilution varied from 0.1% to 10%. Copy numbers of LWZ-6 and Mcl were determined by qPCR with the primers mcr4F/mcr4R and ZC2F/ZC2R targeting their mcrA and 16S rRNA genes.
Extended Data Fig. 3 The microbial community compositions of the co-culture during 5 consecutive transfer incubations.
The relative abundance of strain LWZ-6 and CY-2 was determined by 16S rRNA gene amplicon sequencing using the primer 515FmodF/806RmodR66. The samples in each generation were collected from the cultures grown at the exponential phase of methane production.
Extended Data Fig. 4 Consecutive subcultures amended with antibiotics to eliminate Acetomicrobium sp. CY-2.
a, CH4 production, b, CO2 change, c, the copy numbers of LWZ-6 determined at the endpoint of each generation, d, the copy numbers of CY-2 determined at the endpoint of each generation, ND means the copy numbers are under detectable level, the subculture dilution varied from 1%-10%, e, the proportion of CY-2 in the total bacteria and archaea, f, gel electrophoresis of PCR products using 27F/1492R61 targeting bacteria, PC: positive control of coculture, NC: negative control of ddH2O. Samples were run on one gel and the lanes in images are representative blot of n = 3 biological replicates.
Extended Data Fig. 5 Microscopy observation of the Methanosuratincolia co-culture (strain LWZ-6/CY-2).
a, d, CARD-FISH showing cells hybridized with nucleotide probes that target archaea ARCH-915 (green) and bacteria EUB-338 (red). b, e, Fluorescence images hybridized with nucleotide probes that target archaea ARCH-915 (green), representative images are from 18 recorded images of n = 3 biological replicates. c, f, fluorescence images hybridized with nucleotide probes that target bacteria EUB-338 (red). g, h, TEM showing ultrathin section of the co-culture, the black arrows are strain LWZ-6, representative images are from 8 recorded images of n = 2 biological replicates. Scale bars: 10 μm in (a-c), 2 μm (d-f), 200 nm (g-h).
Extended Data Fig. 6 Methane activity and growth dynamics of the Methanosuratincolia co-culture (strain LWZ-6/CY-2).
a, the CH4 production, b, methanol consumption, c, H2 change, d, copies numbers of strain LWZ-6, e, copies numbers of bacteria in the 50 ml fresh medium. Three groups with different substrates were set up: 0.5 g l−1 yeast extract (YE); 0.5 g l−1 YE, 10 mM methanol and 10 kPa H2 (YE + methanol + H2); without substrates addition, YE (-). All symbols represent means of three individual incubations; error bars represent SD of triplicates; the invisible error bars are smaller than symbols.
Extended Data Fig. 7 The changes of the carbon isotope composition of CH4 (a) and CO2 (b).
The Methanosuratincolia co-culture was incubated with initial different ratios of (1.76 ± 0.01)%, (2.3 ± 0.10)%, (3.65 ± 0.08)%, and (5.98 ± 0.79)%.
Extended Data Fig. 8 The physiological properties of strain LWZ-6.
a, C1-methylated compounds utilization, b, growth factors, c, Temperature, d, pH, e, NaCl tolerance concentration. µ represents the maximum specific growth rate of strain LWZ-6 or the specific CH4 production. MeOH: methanol, MMA: monomethylamine, DMA: dimethylamine, TMA: trimethylamine, MeSH: methanethiol, YE: yeast extract, CA: casamino acids, ND indicates no growth of strain LWZ-6 or CH4 detected. Data in a and b are mean ± standard deviation of triplicates. All symbols represent means of three individual incubations, error bars represent SD of triplicates, the invisible error bars are smaller than symbols.
Extended Data Fig. 9 Global distribution of Methanosuratincolia in different biotopes.
The bold circles represent the sampling locations of Methanosuratincolia MAGs. The numbers of the genomes in environments are anaerobic digester: 6, groundwater: 3, freshwater/sediment: 2, hot spring: 36, hydrothermal sediment: 10, petroleum field: 3. The triangles represent Methanosuratincolales 16S rRNA gene sequence derived from IMNGS (Detailed information was listed in Supplementary Table 5).
Supplementary information
Supplementary Information
Supplementary Figs. 1–3.
Supplementary Table 1
Genome annotation of M. petrocarbonis LWZ-6.
Supplementary Table 2
Transcript of M. petrocarbonis LWZ-6 grown on methanol and H2.
Supplementary Table 3
General information on the 23 Methanosuratincolia genomes obtained in our study.
Supplementary Table 4
Methanogenetic features and energy mechanism of five Methanosuratincolia clusters in our study, other Methanosuratincolales, ‘Ca. Nezhaarchaeales’ and ‘Ca. Culexarchaeales’ genomes and other H2-dependent methylotrophic methanogens in Euryarchaeota. 1, present; 0, absent.
Supplementary Table 5
Global distribution of 16S rRNA gene sequences and MAGs of Methanosuratincolia in different biotopes.
Supplementary Table 6
Primers and probes used in this study.
Supplementary Table 7
Summary of sequencing data submitted to the NCBI and The National Omics Data Encyclopedia.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Wu, K., Zhou, L., Tahon, G. et al. Isolation of a methyl-reducing methanogen outside the Euryarchaeota. Nature 632, 1124–1130 (2024). https://doi.org/10.1038/s41586-024-07728-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41586-024-07728-y
This article is cited by
-
Methanogens implicated by DNA evidence
Nature Reviews Microbiology (2025)
-
Cultivation and visualization of a methanogen of the phylum Thermoproteota
Nature (2024)