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A methanogen hydrolase reveals the structure of archaeal peptidoglycan

Nature作者：Robert Smith2026年9月23日正文已收录本站

Data availability

All data supporting the findings are available within the main paper and its Supplementary Information. The MS proteomics data have been deposited to the ProteomeXchange Consortium through the PRIDE partner repository with the dataset identifier PXD052257. Raw data of LC–MS/MS analysis of arcPG digest are available from the University of California, San Diego at ftp://massive-ftp.ucsd.edu/v13/MSV000102506/. Raw data used to make Extended Data Fig. 6 are provided as Source data. Source data are provided with this paper.

References

  1. Vollmer, W., Blanot, D. & De Pedro, M. A. Peptidoglycan structure and architecture. FEMS Microbiol. Rev. 32, 149–167 (2008).

    Article  CAS  PubMed  Google Scholar 

  2. Albers, S.-V. & Meyer, B. H. The archaeal cell envelope. Nat. Rev. Microbiol. 9, 414–426 (2011).

    Article  CAS  PubMed  Google Scholar 

  3. Kandler, O. Zellwandstrukturen bei Methan-Bakterien. Naturwissenschaften 66, 95–105 (1979).

    Article  ADS  CAS  Google Scholar 

  4. König, H., Kralik, R. & Kandler, O. Structure and modifications of pseudomurein in Methanobacleriales. Zentralblatt Für Bakteriol. Mikrobiol. Hyg. Abt Orig. C. 3, 179–191 (1982).

    Google Scholar 

  5. König, H., Kandler, O., Jensen, M. & Rietschel, E. T. The primary structure of the glycan moiety of pseudomurein from Methanobacterium thermoautotrophicum. Hoppe. Seylers Z. Physiol. Chem. 364, 627–636 (1983).

    Article  PubMed  Google Scholar 

  6. König, H. & Kandler, O. The amino acid sequence of the peptide moiety of the pseudomurein from Methanobacterium thermoautotrophicum. Arch. Microbiol. 121, 271–275 (1979).

    Article  PubMed  Google Scholar 

  7. Kandler, O. & König, H. Chemical composition of the peptidoglycan-free cell walls of methanogenic bacteria. Arch. Microbiol. 118, 141–152 (1978).

    Article  CAS  PubMed  Google Scholar 

  8. König, H. & Kandler, O. N-Acetyltalosaminuronic acid a constituent of the pseudomurein of the genus Methanobacterium. Arch. Microbiol. 123, 295–299 (1979).

    Article  Google Scholar 

  9. Borrel, G., Brugère, J.-F., Gribaldo, S., Schmitz, R. A. & Moissl-Eichinger, C. The host-associated archaeome. Nat. Rev. Microbiol. 18, 622–636 (2020).

    Article  CAS  PubMed  Google Scholar 

  10. Hook, S. E., Wright, A.-D. G. & McBride, B. W. Methanogens: methane producers of the rumen and mitigation strategies. Archaea 2010, 945785 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Hoegenauer, C., Hammer, H. F., Mahnert, A. & Moissl-Eichinger, C. Methanogenic archaea in the human gastrointestinal tract. Nat. Rev. Gastroenterol. Hepatol. 19, 805–813 (2022).

    Article  CAS  PubMed  Google Scholar 

  12. Claus, H. & König, H. in Prokaryotic Cell Wall Compounds: Structure and Biochemistry (eds. König, H. et al.) 231–251 https://doi.org/10.1007/978-3-642-05062-6_7 (Springer, 2010).

  13. Alvarez, L., Cordier, B., Van Teeffelen, S. & Cava, F. Analysis of Gram-negative bacteria peptidoglycan by ultra-performance liquid chromatography. Bio-Protoc. 10, e3780 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Patel, A. V. et al. PGFinder, a novel analysis pipeline for the consistent, reproducible, and high-resolution structural analysis of bacterial peptidoglycans. eLife 10, e70597 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Luo, Y., Pfister, P., Leisinger, T. & Wasserfallen, A. The genome of archaeal prophage PsiM100 encodes the lytic enzyme responsible for autolysis of Methanothermobacter wolfeii. J. Bacteriol. 183, 5788–5792 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Pfister, P., Wasserfallen, A., Stettler, R. & Leisinger, T. Molecular analysis of Methanobacterium phage psiM2. Mol. Microbiol. 30, 233–244 (1998).

    Article  CAS  PubMed  Google Scholar 

  17. Leahy, S. C. et al. The genome sequence of the rumen methanogen Methanobrevibacter ruminantium reveals new possibilities for controlling ruminant methane emissions. PLoS One 5, e8926 (2010).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  18. Luo, Y., Pfister, P., Leisinger, T. & Wasserfallen, A. Pseudomurein endoisopeptidases PeiW and PeiP, two moderately related members of a novel family of proteases produced in Methanothermobacter strains. FEMS Microbiol. Lett. 208, 47–51 (2002).

    Article  CAS  PubMed  Google Scholar 

  19. Weinberger, V. et al. Expanding the cultivable human archaeome: Methanobrevibacter intestini sp. nov. and strain Methanobrevibacter smithii ‘GRAZ-2’ from human faeces. Int. J. Syst. Evol. Microbiol. 75, 006751 (2025).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Turner, R. D. et al. Peptidoglycan architecture can specify division planes in Staphylococcus aureus. Nat. Commun. 1, 26 (2010).

    Article  ADS  PubMed  Google Scholar 

  21. Wheeler, R., Mesnage, S., Boneca, I. G., Hobbs, J. K. & Foster, S. J. Super-resolution microscopy reveals cell wall dynamics and peptidoglycan architecture in ovococcal bacteria. Mol. Microbiol. 82, 1096–1109 (2011).

    Article  CAS  PubMed  Google Scholar 

  22. Blackman, S. A., Smith, T. J. & Foster, S. J. The role of autolysins during vegetative growth of Bacillus subtilis 168. Microbiology 144, 73–82 (1998).

    Article  CAS  PubMed  Google Scholar 

  23. Guo, L. et al. Insights into the catalytic mechanism of archaeal peptidoglycan endoisopeptidases from methanogenic phages. Int. J. Biol. Macromol. 296, 139672 (2025).

    Article  CAS  PubMed  Google Scholar 

  24. Makarova, K. S., Aravind, L. & Koonin, E. V. A superfamily of archaeal, bacterial, and eukaryotic proteins homologous to animal transglutaminases. Protein Sci. Publ. Protein Soc. 8, 1714–1719 (1999).

    Article  CAS  Google Scholar 

  25. Xu, N., Huang, Z. H., de Jonge, B. L. & Gage, D. A. Structural characterization of peptidoglycan muropeptides by matrix-assisted laser desorption ionization mass spectrometry and postsource decay analysis. Anal. Biochem. 248, 7–14 (1997).

    Article  CAS  PubMed  Google Scholar 

  26. Glauner, B., Höltje, J. V. & Schwarz, U. The composition of the murein of Escherichia coli. J. Biol. Chem. 263, 10088–10095 (1988).

    Article  CAS  PubMed  Google Scholar 

  27. Petitjean, C., Deschamps, P., López-García, P., Moreira, D. & Brochier-Armanet, C. Extending the conserved phylogenetic core of archaea disentangles the evolution of the third domain of life. Mol. Biol. Evol. 32, 1242–1254 (2015).

    Article  CAS  PubMed  Google Scholar 

  28. Schleifer, K. H. & Kandler, O. Peptidoglycan types of bacterial cell walls and their taxonomic implications. Bacteriol. Rev. 36, 407–477 (1972).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Baquero, D. P. et al. Stable coexistence between an archaeal virus and the dominant methanogen of the human gut. Nat. Commun. 15, 7702 (2024).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  30. Medvedeva, S., Borrel, G., Krupovic, M. & Gribaldo, S. A compendium of viruses from methanogenic archaea reveals their diversity and adaptations to the gut environment. Nat. Microbiol. 8, 2170–2182 (2023).

    Article  CAS  PubMed  Google Scholar 

  31. Vollmer, W., Joris, B., Charlier, P. & Foster, S. Bacterial peptidoglycan (murein) hydrolases. FEMS Microbiol. Rev. 32, 259–286 (2008).

    Article  CAS  PubMed  Google Scholar 

  32. Sham, L.-T., Barendt, S. M., Kopecky, K. E. & Winkler, M. E. Essential PcsB putative peptidoglycan hydrolase interacts with the essential FtsXSpn cell division protein in Streptococcus pneumoniae D39. Proc. Natl Acad. Sci. USA 108, E1061–1069 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Bartual, S. G. et al. Structural basis of PcsB-mediated cell separation in Streptococcus pneumoniae. Nat. Commun. 5, 3842 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  34. Fink, C. et al. The targeted deletion of genes responsible for expression of the mth60 fimbriae leads to loss of cell-cell connections in Methanothermobacter thermautotrophicus ΔH. Appl. Environ. Microbiol. 89, e00575-23 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Zeikus, J. G. & Wolfe, R. S. Methanobacterium thermoautotrophicus sp. n., an anaerobic, autotrophic, extreme thermophile. J. Bacteriol. 109, 707–715 (1972).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wilson, S. A., Tank, R. K. J., Hobbs, J. K., Foster, S. J. & Garner, E. C. An exhaustive multiple knockout approach to understanding cell wall hydrolase function in Bacillus subtilis. mBio. 14, e0176023 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Rajguru, V., Chatterjee, S., Garde, S. & Reddy, M. Crosslink cleaving enzymes: the smart autolysins that remodel the bacterial cell wall. Trends Microbiol. 32, 494–506 (2024).

    Article  CAS  PubMed  Google Scholar 

  38. Egan, A. J. F., Errington, J. & Vollmer, W. Regulation of peptidoglycan synthesis and remodelling. Nat. Rev. Microbiol. 18, 446–460 (2020).

    Article  CAS  PubMed  Google Scholar 

  39. Pende, N. et al. SepF is the FtsZ anchor in archaea, with features of an ancestral cell division system. Nat. Commun. 12, 3214 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ithurbide, S., Gribaldo, S., Albers, S.-V. & Pende, N. Spotlight on FtsZ-based cell division in Archaea. Trends Microbiol. 30, 665–678 (2022).

    Article  CAS  PubMed  Google Scholar 

  41. van Wolferen, M., Pulschen, A. A., Baum, B., Gribaldo, S. & Albers, S.-V. The cell biology of archaea. Nat. Microbiol. 7, 1744–1755 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Rohs, P. D. A. & Bernhardt, T. G. Growth and division of the peptidoglycan matrix. Annu. Rev. Microbiol. 75, 315–336 (2021).

    Article  CAS  PubMed  Google Scholar 

  43. Garcia, P. S., Gribaldo, S. & Borrel, G. Diversity and evolution of methane-related pathways in archaea. Annu. Rev. Microbiol. 76, 727–755 (2022).

    Article  CAS  PubMed  Google Scholar 

  44. Bonin, A. S. & Boone, D. R. in The Prokaryotes (eds. Dworkin, M. et al.) 231–243 https://doi.org/10.1007/0-387-30743-5_11 (Springer, 2006).

  45. Thomas, C. M., Desmond-Le Quéméner, E., Gribaldo, S. & Borrel, G. Factors shaping the abundance and diversity of the gut archaeome across the animal kingdom. Nat. Commun. 13, 3358 (2022).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  46. Pfeifer, K. et al. Archaea biotechnology. Biotechnol. Adv. 47, 107668 (2021).

    Article  CAS  PubMed  Google Scholar 

  47. Wheeler, R., Veyrier, F., Werts, C. & Boneca, I. G. Peptidoglycan and Nod receptor. In Glycoscience: Biology and Medicine 737–747 https://doi.org/10.1007/978-4-431-54841-6_147 (Springer Japan, Tokyo, 2015).

  48. Mistry, J. et al. Pfam: the protein families database in 2021. Nucleic Acids Res. 49, D412–D419 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Yu, N. Y. et al. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics 26, 1608–1615 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Vranken, W. F. et al. The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins 59, 687–696 (2005).

    Article  CAS  PubMed  Google Scholar 

  51. Johnson, L. S., Eddy, S. R. & Portugaly, E. Hidden Markov model speed heuristic and iterative HMM search procedure. BMC Bioinf. 11, 431 (2010).

    Article  Google Scholar 

  52. Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Criscuolo, A. & Gribaldo, S. BMGE (block mapping and gathering with entropy): a new software for selection of phylogenetic informative regions from multiple sequence alignments. BMC Evol. Biol. 10, 210 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  54. 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).

    Article  CAS  PubMed  Google Scholar 

  55. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Hoang, D. T., Chernomor, O., von Haeseler, A., Minh, B. Q. & Vinh, L. S. UFBoot2: improving the ultrafast bootstrap approximation. Mol. Biol. Evol. 35, 518–522 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. 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).

    Article  PubMed  PubMed Central  Google Scholar 

  58. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The EBMC laboratory thanks C. Fink for advice with genetics of M. thermautotrophicus, D. P. Baquero for help with M. smithii and M. stadtmanae cultures, S. Medvedeva for help with statistical analysis, M. Doshi for preparing M. smithii cultures for SEM and B. Beaud for help with figures. R.R. and D.G. thank T. Hader and S. Dechant for technical assistance to cultivate M. smithii in large-scale bio-fermenters. S.G. and I.G.B. thank H. König for encouragement on this study and for his seminal work on archaeal PG.

Funding

R.S. was supported by a postdoctoral fellowship from Labex IBEID (Agence Nationale de la Recherche, grant no. ANR-10-LBX-62 IBEID). N.P. was supported by a Pasteur-Roux Postdoctoral Fellowship from the Institut Pasteur and by the Austrian Science Fund (FWF) Elise Richter Fellowship (FWF project no. V 931-B). C.M.G. acknowledges funding from Fondation pour la Recherche Médicale (FRM grant no. ARF202110013929). N.P., R.S., R.W. and A.R. thank the Department of Microbiology at Institut Pasteur for a Groot-21 seed funding shared between the EBMC and BGPB laboratories that initiated the project. The EBMC laboratory is supported by the Fondation pour la Recherche Médicale (Programme equipes FRM, project grant no. EQU202203014614); a Chair of Excellence by the French government and managed by the French National Research Agency (ANR) under the France 2030 program (grant no. ANR-25-CHBS-0007); the Labex ‘Integrative Biology of Emerging Infectious Diseases’ (grant no. ANR-10-LBX-62 IBEID) and the Bettencourt-Schueller Foundation through the programme Impulscience. The work on cell walls in the BGPB laboratory is supported by Labex ‘Integrative Biology of Emerging Infectious Diseases’ (grant no. ANR-10-LBX-62 IBEID) and the Fondation pour la Recherche Médicale (Programme equipes FRM, project grant no. EQU2024202403018034). A.S.-R. and M.J. acknowledge support for equipment at the Institut Pasteur Ultrastructural BioImaging Core Facility from the GIS-IBISA, the French Government Programme Investissements d’Avenir France BioImaging (FBI, grant no. ANR-10-INSB-04-01) and the Labex ‘Integrative Biology of Emerging Infectious Diseases’ (grant no. ANR-10-LABX-62-IBEID). S.-V.A. acknowledges funding from European Research Council (ERC Advanced grant no. ARCHCELLORG, project number 101142324) and from Germany’s Excellence Strategy DFG (CIBSS – EXC-2189 – Project ID 390939984). Research in the Grohmann laboratory is supported by the basic funds of the University of Regensburg. S.K.-M.R.R. was funded as part of the COMET Module DeSimplify, within the COMET: Competence Centers for Excellent Technologies programme by the BMIMI, the BMWET and the Federal Provinces of Upper Austria and Vienna. The COMET programme is managed by the Austrian Research Promotion Agency (FFG). N.P. and S.K.-M.R.R. gratefully acknowledge the BioOptics—Light Microscopy Facility from Max Perutz Laboratories, Vienna for the use of the Zeiss Elyra 7 microscope and for help during imaging. S.-V.A. and S.G. are funded by ANR/DFG with project DIVA (grant nos. DFG 505545313, ANR 22 CE92 0024 01). I.J.G. acknowledges the Région Ile de France for contributing to funding the 800-MHz NMR spectrometer of the Institut Pasteur (SESAME 2014 NMRCHR grant no. 4014526).

Author information

Author notes

  1. Robert Smith

    Present address: Biozeroc, Unit GF1 Future Business Centre, Cambridge, UK

  2. Charlène Cornilleau

    Present address: INRAE, AgroParisTech, Micalis Institute, Université Paris-Saclay, Jouy-en-Josas, France

  3. Pierre Simon Garcia

    Present address: Laboratoire de Chimie Bactérienne, Institut de Microbiologie de la Méditerranée, Institut Microbiologie Bioénergies et Biotechnologie, Aix-Marseille Université, Centre National de la Recherche Scientifique, Marseille, France

  4. These authors contributed equally: Robert Smith, Nika Pende

Authors and Affiliations

  1. Institut Pasteur, Université Paris Cité, Unit Evolutionary Biology of the Microbial Cell, Paris, France

    Robert Smith, Nika Pende, Najwa Taib, Jerzy Witwinowski, Camille Martin-Gallausiaux, Charlène Cornilleau, Pierre Simon Garcia, Romain Villa, Guillaume Borrel & Simonetta Gribaldo

  2. Archaea Physiology and Biotechnology Group, University of Vienna, Vienna, Austria

    Nika Pende & Simon K.-M. R. Rittmann

  3. Institut Pasteur, Université Paris Cité, INSERM U1306, Unit Biology and Genetics of the Bacterial Cell Wall, Paris, France

    Aline Rifflet, Richard Wheeler & Ivo Gomperts Boneca

  4. Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, France

    Najwa Taib

  5. Institut Pasteur, Université Paris Cité, CNRS UAR2024, Proteomics Platform, Mass Spectrometry for Biology UtechS, Paris, France

    Thibaut Douché & Mariette Matondo

  6. Institut Pasteur, Université Paris Cité, Ultrastructural BioImaging Unit, Paris, France

    Manuel Majrouh

  7. Institute of Microbiology and Archaea Centre, University of Regensburg, Regensburg, Germany

    Robert Reichelt & Dina Grohmann

  8. Regensburg Center for Biochemistry (RCB), University of Regensburg, Regensburg, Germany

    Robert Reichelt & Dina Grohmann

  9. Molecular Biology of Archaea, Faculty of Biology, University of Freiburg, Freiburg, Germany

    Patrick Tripp & Sonja-Verena Albers

  10. CIBSS – Centre for Integrative Biological Signaling Studies, University of Freiburg, Freiburg, Germany

    Sonja-Verena Albers

  11. Institut Pasteur, Université Paris Cité, Centre de Ressources et Recherches Technologiques (C2RT), Nanoimaging Core Facility, Paris, France

    Anna Sartori-Rupp

  12. Institut Pasteur, Université Paris Cité, CNRS UMR3528, Biological NMR and HDX-MS Technological Platform, Paris, France

    J. Iñaki Guijarro

Authors

  1. Robert Smith
  2. Nika Pende
  3. Aline Rifflet
  4. Najwa Taib
  5. Jerzy Witwinowski
  6. Camille Martin-Gallausiaux
  7. Charlène Cornilleau
  8. Pierre Simon Garcia
  9. Romain Villa
  10. Thibaut Douché
  11. Mariette Matondo
  12. Manuel Majrouh
  13. Robert Reichelt
  14. Dina Grohmann
  15. Patrick Tripp
  16. Sonja-Verena Albers
  17. Guillaume Borrel
  18. Simon K.-M. R. Rittmann
  19. Anna Sartori-Rupp
  20. Richard Wheeler
  21. J. Iñaki Guijarro
  22. Ivo Gomperts Boneca
  23. Simonetta Gribaldo

Contributions

N.P. prepared M. smithii cells and sacculi and together with A.S.-R. performed cryo-EM image acquisition and analysis. M. Marjouh performed SEM of M. smithii cells. R.S. and N.P. carried out zymograms, cloning and heterologous expression of candidates, leading to the identification of ArmA. T.D. and M. Matondo performed proteomic analysis of bands extracted from the zymograms. P.S.G. conceived of the bioinformatic pipeline to identify a list of candidates. R.S. purified different versions of ArmA carrying alanine replacement of catalytic residues and domain truncations and established enzymatic activity on arcPG. N.P. cultivated diverse methanogens and prepared pellets, under the guidance of S.K.-M.R.R. N.P. and R.W. carried out initial M. smithii arcPG purifications, digestions with PeiW and preliminary analyses by LC–MS. R.S., R.W. and C.M.-G. purified arcPG from M. smithii and all other archaea, carried out purifications of ArmA, PeiW and PeiS, performed digestions of arcPG and prepared samples for LC–MS and NMR. A.R. performed LC–MS on purified arcPG and analysed the data together with R.W., R.S. and I.G.B. I.J.G. performed all NMR experiments and analysed the data. N.T. performed all sequence and phylogenetic analyses of ArmA. R.S. prepared ArmA samples for the development of antibodies. N.P. performed immunolabelling, epifluorescence microscopy and 3D SIM imaging for M. smithii, and quantitative and 3D SIM image analysis for M. smithii immunolabelled cells. J.W. constructed the M. thermautotrophicus ΔarmA strain. C.C. performed immunolabelling and epifluorescence microscopy for M. thermautotrophicus WT and ΔarmA. R.S. performed image analyses of the WT and ΔarmA strains and calculated statistics on filament length. R.V. performed lysis tests of ArmA on archaea and bacteria, under the supervision of C.M.-G. and G.B. D.G. and R.R. supervised and performed large-scale bio-fermentations of M. smithii to provide pellet for PG extraction. P.T. and S.-V.A. optimized the protocol for heterologous expression of M. smithii PeiS and carried out preliminary tests of activity. R.S., N.P., I.G.B. and S.G. wrote the paper, with input from all authors.

Corresponding authors

Correspondence to Ivo Gomperts Boneca or Simonetta Gribaldo.

Ethics declarations

Competing interests

Part of this work was submitted as patent application no. US 63/645,577 (filed on 10 May 2024) and PCT/IB2025/000214 (filed on 12 May 2025) by Institut Pasteur with the following authors: S.G., I.G.B., R.S., N.P. and A.R. The patent covers the use of ArmA as a mean to regulate populations of archaeal methanogens in industrial, agricultural and medical settings. The other authors declare no competing interests.

Peer review

Peer review information

Nature thanks Alexandre Bisson, Iain Duggin, Vitor Pomin, Malcolm Winkler and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

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Extended data figures and tables

Extended Data Fig. 1 Identification of putative hydrolases by Zymogram.

A Coomassie stained SDS PAGE and Zymogram of M. smithii whole cell lysate. For both gels, the endoisopeptidase PeiW was loaded as a control and run alongside the cell fractionated lysate. Six bands corresponding to lytic activity (indicated by asterisks) were cut and analysed for protein content by LC-MSMS (see Supplementary Data). B Coomassie stained SDS PAGE of cell lysates of E. coli expressing the 11 candidate hydrolases identified by bioinformatics and MS approaches. Columns correspond to the samples used for the zymogram shown in the main text Fig. 1. (L) represents the ladder indicating weight in kDa.

Extended Data Fig. 2 Domain organization of the 11 candidates from M. smithii.

They were identified using a combination of bioinformatics and MS analysis of bands of arcPG hydrolysis from a zymogram (Extended Data Fig. 1). Domains were annotated using hmmscan and the Pfam database.

Extended Data Fig. 3 Nature of the crosslink of M. smithii PG.

Amino acids sequences involved in the crosslink of M. smithii were released after PeiW digestion and are listed in the table. The availability of MS/MS data for structural elucidation is indicated by a yes/no. The exact mass m/z and MS/MS fragmentation profile of two different lengths of crosslink are diagrammed.

Extended Data Fig. 4 HPLC traces of M. smithii PG digested with Msm0219Cter derivatives compared to the WT enzyme.

Derivatives containing the separate predicted enzymatically active domains were tested for arcPG digestion. Mock digestions were also performed without PG as controls. Three alanine substitutions replacing putative catalytic residues (C1416A, H1451A, D1466A, Msm0219 residue numbering) were also tested.

Extended Data Fig. 5 Structural and catalytic conservation of the peptidase domain of ArmA homologues from Methanobacteriales.

Sequences from diverse representatives were chosen and aligned using MAFFT with the LINS-i algorithm. Structural elements of the M. smithii ArmA peptidase domain were inferred using Ali2D and alphaFold2. A graphical representation was made using the ENDscript server and manually edited. Dark green indicates a-helices whereas light green indicates b-strands. (*) below the alignment indicates conserved identical residues. Residues highlighted in purple represent the catalytic triad found in peptidases of this family.

Extended Data Fig. 6 Lytic activity of M. smithii ArmA.

B. subtilis, E. coli and M. smithii were treated with 100 µg ArmA (pink), 50 µg ArmA (purple), ArmA buffer (black) and no addition (grey) for 4 h. Results are expressed as the mean percentage of initial optical density, shaded ribbons represent standard deviation. The experiment was repeated two independent times and in triplicate. Raw data used to make this figure can be found as Source Data.

Source data

Extended Data Fig. 7 Anti-ArmA Western Blot of M. smithii (A) and PCR (B) and Western Blot (C) verification of the M. thermautotrophicus ΔarmA mutant.

For PCR, an internal fragment of the armA gene was amplified with primer pair JW419/JW420, giving a band at 432 bp if the gene is present. The absence of band for the M. thermautotrophicus ΔarmA mutant is well visible. For Western Blot, a primary guinea pig antibody raised against M. smithii ArmA was used followed by secondary anti-guinea pig goat antibody coupled to horseradish peroxidase. Even though the antibody was raised against ArmA of M. smithii, it remains specific and shows that the ArmA protein is absent in the M. thermautotrophicus ΔarmA mutant. For all panels the leftmost lane shows a molecular weight marker, in base pairs for the PCR and in kD for Western Blot.

Extended Data Fig. 8 Membrane and DNA staining of M. thermautotrophicus WT and ΔarmA mutant cells.

Phase contrast (left panel), DNA stain Hoechst (middle left panel, cyan), membrane staining with FM1-43 (middle right panel, magenta) and overlay (right panel) images of M. thermautotrophicus WT (A) and ΔarmA mutant (B). The scale bar indicated on the first left panel in A and B applies to all.

Extended Data Table 1 Statistical analysis of WT vs ΔarmA mutants

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Smith, R., Pende, N., Rifflet, A. et al. A methanogen hydrolase reveals the structure of archaeal peptidoglycan. Nature (2026). https://doi.org/10.1038/s41586-026-11028-y

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