Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Bacterial chemolithoautotrophy via manganese oxidation

Abstract

Manganese is one of the most abundant elements on Earth. The oxidation of manganese has long been theorized1—yet has not been demonstrated2,3,4—to fuel the growth of chemolithoautotrophic microorganisms. Here we refine an enrichment culture that exhibits exponential growth dependent on Mn(II) oxidation to a co-culture of two microbial species. Oxidation required viable bacteria at permissive temperatures, which resulted in the generation of small nodules of manganese oxide with which the cells associated. The majority member of the culture—which we designate ‘Candidatus Manganitrophus noduliformans’—is affiliated to the phylum Nitrospirae (also known as Nitrospirota), but is distantly related to known species of Nitrospira and Leptospirillum. We isolated the minority member, a betaproteobacterium that does not oxidize Mn(II) alone, and designate it Ramlibacter lithotrophicus. Stable-isotope probing revealed 13CO2 fixation into cellular biomass that was dependent upon Mn(II) oxidation. Transcriptomic analysis revealed candidate pathways for coupling extracellular manganese oxidation to aerobic energy conservation and autotrophic CO2 fixation. These findings expand the known diversity of inorganic metabolisms that support life, and complete a biogeochemical energy cycle for manganese5,6 that may interface with other major global elemental cycles.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Bio-oxidation of MnCO3 produces manganese oxide nodules to which two species associate.
Fig. 2: Mn(II) oxidation coupled to co-culture growth of species A and species B.
Fig. 3: Phylogenetic analysis and metabolic reconstruction of species A (‘Candidatus Manganitrophus noduliformans’).
Fig. 4: Stable isotope probing of autotrophic CO2 fixation.

Data availability

All sequencing data has been deposited at the NCBI under BioProject PRJNA562312. The cloned 16S rRNA gene sequences of ‘Candidatus Manganitrophus noduliformans’ (species A) and R. lithotrophicus (species B) from the co-culture have been deposited at GenBank under accession numbers MN381734 and MN381735, respectively. The iTAG sequences from the different enrichments have been deposited at the Sequence Read Archive (SRA) under accession numbers SRR10031198, SRR10031199 and SRR10031200. Genome sequences of the co-culture, from which the genome of ‘Candidatus Manganitrophus noduliformans’ was reconstructed, have been deposited under BioSample SAMN12638105 with raw sequences deposited at SRA under accession number SRR10032644; the reconstructed genome of ‘Candidatus Manganitrophus noduliformans’ has been deposited at DDBJ/ENA/GenBank under accession number VTOW00000000. Genome sequences of R. lithotrophicus strain RBP-1 have been deposited under BioSample SAMN12638106, with raw sequences deposited at SRA under accession number SRR10031379; the reconstructed genome of R. lithotrophicus strain RBP-1 has been deposited at DDBJ/ENA/GenBank under accession number VTOX00000000. Additionally, reconstructed genomes have been deposited in Joint Genome Institute (JGI) Genomes Online Database Study ID Gs0134339, with Integrated Microbial Genome ID 2784132095 for ‘Candidatus Manganitrophus noduliformans’ and ID 2778260901 for R. lithotrophicus strain RBP-1. Transcriptome sequence data for the seven biological replicates have been deposited at SRA under accession numbers SRR10060009, SRR10060010, SRR10060011, SRR10060012, SRR10060013, SRR10060017 and SRR10060018. Unique biological materials are available from the corresponding author upon reasonable request. Source data are provided with this paper.

References

  1. Beijerinck, M. Oxydation des mangancarbonates durch Bakterien und Schimmelpilze. Folia Microbiol. (Delft) 2, 123–134 (1913).

    Google Scholar 

  2. Nealson, K. H., Tebo, B. M. & Rosson, R. A. Occurrence and mechanisms of microbial oxidation of manganese. Adv. Appl. Microbiol. 33, 279–318 (1988).

    CAS  Google Scholar 

  3. Tebo, B. M., Johnson, H. A., McCarthy, J. K. & Templeton, A. S. Geomicrobiology of manganese(II) oxidation. Trends Microbiol. 13, 421–428 (2005).

    CAS  PubMed  Google Scholar 

  4. Hansel, C. & Learman, D. R. in Ehrlich’s Geomicrobiology (eds Ehrlich, H. L. et al.) 401–452 (CRC, 2015).

  5. Myers, C. R. & Nealson, K. H. Bacterial manganese reduction and growth with manganese oxide as the sole electron acceptor. Science 240, 1319–1321 (1988).

    ADS  CAS  PubMed  Google Scholar 

  6. Lovley, D. R. & Phillips, E. J. Novel mode of microbial energy metabolism: organic carbon oxidation coupled to dissimilatory reduction of iron or manganese. Appl. Environ. Microbiol. 54, 1472–1480 (1988).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Winogradsky, S. Über schwefelbakterien. Bot. Ztg 45, 489ff (1887).

    Google Scholar 

  8. Kelly, D. P. & Wood, A. P. in The Prokaryotes: Prokaryotic Communities and Ecophysiology (eds Rosenberg, E. et al.) 275–287 (Springer, 2013).

  9. Daims, H. et al. Complete nitrification by Nitrospira bacteria. Nature 528, 504–509 (2015).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  10. Könneke, M. et al. Isolation of an autotrophic ammonia-oxidizing marine archaeon. Nature 437, 543–546 (2005).

    ADS  PubMed  Google Scholar 

  11. Strous, M. et al. Missing lithotroph identified as new planctomycete. Nature 400, 446–449 (1999).

    ADS  CAS  PubMed  Google Scholar 

  12. van Kessel, M. A. H. J. et al. Complete nitrification by a single microorganism. Nature 528, 555–559 (2015).

    ADS  PubMed  PubMed Central  Google Scholar 

  13. Watson, S. W. & Waterbury, J. B. Characteristics of two marine nitrite oxidizing bacteria, Nitrospina gracilis nov. gen. nov. sp. and Nitrococcus mobilis nov. gen. nov. sp. Arch. Mikrobiol. 77, 203–230 (1971).

    Google Scholar 

  14. Lovley, D. R., Holmes, D. E. & Nevin, K. P. in Advances in Microbial Physiology (ed Poole, R. K.) 219–286 (Elsevier, 2004).

  15. Henkel, J. V. et al. A bacterial isolate from the Black Sea oxidizes sulfide with manganese(IV) oxide. Proc. Natl Acad. Sci. USA 116, 12153–12155 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Ghiorse, W. C. & Ehrlich, H. L. Microbial biomineralization of iron and manganese. Catena Suppl. 21, 75–99 (1992).

    Google Scholar 

  17. Ehrlich, H. L. & Salerno, J. C. Energy coupling in Mn2+ oxidation by a marine bacterium. Arch. Microbiol. 154, 12–17 (1990).

    CAS  Google Scholar 

  18. Ehrlich, H. L. Manganese as an energy source for bacteria. Environ. Biogeochem. 2, 633–644 (1976).

    CAS  Google Scholar 

  19. Dick, G. J. et al. Genomic insights into Mn(II) oxidation by the marine alphaproteobacterium Aurantimonas sp. strain SI85-9A1. Appl. Environ. Microbiol. 74, 2646–2658 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Nealson, K. H. in The Prokaryotes (eds Dworkin, M. et al.) 222–231 (Springer, 2006).

  21. van Veen, W. L. Biological oxidation of manganese in soils. Antonie van Leeuwenhoek 39, 657–662 (1973).

    PubMed  Google Scholar 

  22. Morgan, J. J. Kinetics of reaction between O2 and Mn(II) species in aqueous solutions. Geochim. Cosmochim. Acta 69, 35–48 (2005).

    ADS  CAS  Google Scholar 

  23. Kits, K. D. et al. Kinetic analysis of a complete nitrifier reveals an oligotrophic lifestyle. Nature 549, 269–272 (2017).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  24. Flagan, S. F. & Leadbetter, J. R. Utilization of capsaicin and vanillylamine as growth substrates by Capsicum (hot pepper)-associated bacteria. Environ. Microbiol. 8, 560–565 (2006).

    CAS  PubMed  Google Scholar 

  25. Kanzler, B. E. M., Pfannes, K. R., Vogl, K. & Overmann, J. Molecular characterization of the nonphotosynthetic partner bacterium in the consortium “Chlorochromatium aggregatum”. Appl. Environ. Microbiol. 71, 7434–7441 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Emerson, D. & Moyer, C. Isolation and characterization of novel iron-oxidizing bacteria that grow at circumneutral pH. Appl. Environ. Microbiol. 63, 4784–4792 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Neidhardt, F. C. Escherichia coli and Salmonella: Cellular and Molecular Biology, vol. 1 (ASM, 1996).

  28. Kostanjšek, R., Pašić, L., Daims, H. & Sket, B. Structure and community composition of sprout-like bacterial aggregates in a dinaric karst subterranean stream. Microb. Ecol. 66, 5–18 (2013).

    PubMed  Google Scholar 

  29. Wrighton, K. C. et al. Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla. Science 337, 1661–1665 (2012).

    ADS  CAS  PubMed  Google Scholar 

  30. Parks, D. H. et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat. Microbiol. 2, 1533–1542 (2017).

    CAS  PubMed  Google Scholar 

  31. Castelle, C. et al. A new iron-oxidizing/O2-reducing supercomplex spanning both inner and outer membranes, isolated from the extreme acidophile Acidithiobacillus ferrooxidans. J. Biol. Chem. 283, 25803–25811 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  32. Jeans, C. et al. Cytochrome 572 is a conspicuous membrane protein with iron oxidation activity purified directly from a natural acidophilic microbial community. ISME J. 2, 542–550 (2008).

    CAS  PubMed  Google Scholar 

  33. Croal, L. R., Jiao, Y. & Newman, D. K. The fox operon from Rhodobacter strain SW2 promotes phototrophic Fe(II) oxidation in Rhodobacter capsulatus SB1003. J. Bacteriol. 189, 1774–1782 (2007).

    CAS  PubMed  Google Scholar 

  34. Jiao, Y. & Newman, D. K. The pio operon is essential for phototrophic Fe(II) oxidation in Rhodopseudomonas palustris TIE-1. J. Bacteriol. 189, 1765–1773 (2007).

    CAS  PubMed  Google Scholar 

  35. He, S., Barco, R. A., Emerson, D. & Roden, E. E. Comparative genomic analysis of neutrophilic iron(II) oxidizer genomes for candidate genes in extracellular electron transfer. Front. Microbiol. 8, 1584 (2017).

    PubMed  PubMed Central  Google Scholar 

  36. Richardson, D. J. et al. The ‘porin-cytochrome’ model for microbe-to-mineral electron transfer. Mol. Microbiol. 85, 201–212 (2012).

    CAS  PubMed  Google Scholar 

  37. Luther, G. W., III. Manganese(II) oxidation and Mn(IV) reduction in the environment—two one-electron transfer steps versus a single two-electron Step. Geomicrobiol. J. 22, 195–203 (2005).

    CAS  Google Scholar 

  38. Lücker, S. et al. A Nitrospira metagenome illuminates the physiology and evolution of globally important nitrite-oxidizing bacteria. Proc. Natl Acad. Sci. USA 107, 13479–13484 (2010).

    ADS  PubMed  PubMed Central  Google Scholar 

  39. Mundinger, A. B., Lawson, C. E., Jetten, M. S. M., Koch, H. & Lücker, S. Cultivation and transcriptional analysis of a canonical Nitrospira under stable growth conditions. Front. Microbiol. 10, 1325 (2019).

    PubMed  PubMed Central  Google Scholar 

  40. Koch, H. et al. Growth of nitrite-oxidizing bacteria by aerobic hydrogen oxidation. Science 345, 1052–1054 (2014).

    ADS  CAS  PubMed  Google Scholar 

  41. Levicán, G., Ugalde, J. A., Ehrenfeld, N., Maass, A. & Parada, P. Comparative genomic analysis of carbon and nitrogen assimilation mechanisms in three indigenous bioleaching bacteria: predictions and validations. BMC Genomics 9, 581 (2008).

    PubMed  PubMed Central  Google Scholar 

  42. Berg, I. A. Ecological aspects of the distribution of different autotrophic CO2 fixation pathways. Appl. Environ. Microbiol. 77, 1925–1936 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Thauer, R. K., Jungermann, K. & Decker, K. Energy conservation in chemotrophic anaerobic bacteria. Bacteriol. Rev. 41, 100–180 (1977).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Baradaran, R., Berrisford, J. M., Minhas, G. S. & Sazanov, L. A. Crystal structure of the entire respiratory complex I. Nature 494, 443–448 (2013).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  45. Chadwick, G. L., Hemp, J., Fischer, W. W. & Orphan, V. J. Convergent evolution of unusual complex I homologs with increased proton pumping capacity: energetic and ecological implications. ISME J. 12, 2668–2680 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Lücker, S., Nowka, B., Rattei, T., Spieck, E. & Daims, H. The genome of Nitrospina gracilis illuminates the metabolism and evolution of the major marine nitrite oxidizer. Front. Microbiol. 4, 27 (2013).

    PubMed  PubMed Central  Google Scholar 

  47. Watson, S. W., Bock, E., Valois, F. W., Waterbury, J. B. & Schlosser, U. Nitrospira marina gen. nov. sp. nov.: a chemolithotrophic nitrite-oxidizing bacterium. Arch. Microbiol. 144, 1–7 (1986).

    Google Scholar 

  48. Hippe, H. Leptospirillum gen. nov. (ex Markosyan 1972), nom. rev., including Leptospirillum ferrooxidans sp. nov. (ex Markosyan 1972), nom. rev. and Leptospirillum thermoferrooxidans sp. nov. (Golovacheva et al. 1992). Int. J. Syst. Evol. Microbiol. 50, 501–503 (2000).

    Google Scholar 

  49. Henry, E. A. et al. Characterization of a new thermophilic sulfate-reducing bacterium Thermodesulfovibrio yellowstonii, gen. nov. and sp. nov.: its phylogenetic relationship to Thermodesulfobacterium commune and their origins deep within the bacterial domain. Arch. Microbiol. 161, 62–69 (1994).

    CAS  PubMed  Google Scholar 

  50. Lin, X., Kennedy, D., Fredrickson, J., Bjornstad, B. & Konopka, A. Vertical stratification of subsurface microbial community composition across geological formations at the Hanford site. Environ. Microbiol. 14, 414–425 (2012).

    CAS  PubMed  Google Scholar 

  51. Flagan, S., Ching, W.-K. & Leadbetter, J. R. Arthrobacter strain VAI-A utilizes acyl-homoserine lactone inactivation products and stimulates quorum signal biodegradation by Variovorax paradoxus. Appl. Environ. Microbiol. 69, 909–916 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Leadbetter, J. R. & Greenberg, E. P. Metabolism of acyl-homoserine lactone quorum-sensing signals by Variovorax paradoxus. J. Bacteriol. 182, 6921–6926 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Krumbein, W. E. & Altmann, H. J. A new method for the detection and enumeration of manganese oxidizing and reducing microorganisms. Helgol. Wiss. Meeresunters. 25, 347–356 (1973).

    CAS  Google Scholar 

  54. Emerson, D. & Revsbech, N. P. Investigation of an iron-oxidizing microbial mat community located near Aarhus, Denmark: laboratory studies. Appl. Environ. Microbiol. 60, 4032–4038 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).

    CAS  PubMed  Google Scholar 

  56. Illumina. 16S Metagenomic sequencing library preparation, https://support.illumina.com/downloads/16s_metagenomic_sequencing_library_preparation.html (2013).

  57. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).

    CAS  PubMed  Google Scholar 

  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 (2013).

    CAS  PubMed  Google Scholar 

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

  61. Ludwig, W. et al. ARB: a software environment for sequence data. Nucleic Acids Res. 32, 1363–1371 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Parks, D. H. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol. 36, 996–1004 (2018).

    CAS  PubMed  Google Scholar 

  63. Schönmann, S. et al. 16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia. Environ. Microbiol. 11, 779–800 (2009).

    PubMed  Google Scholar 

  64. Greuter, D., Loy, A., Horn, M. & Rattei, T. probeBase—an online resource for rRNA-targeted oligonucleotide probes and primers: new features 2016. Nucleic Acids Res. 44, D586–D589 (2016).

    CAS  PubMed  Google Scholar 

  65. Amann, R. I. et al. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56, 1919–1925 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Stoecker, K., Dorninger, C., Daims, H. & Wagner, M. Double labeling of oligonucleotide probes for fluorescence in situ hybridization (DOPE-FISH) improves signal intensity and increases rRNA accessibility. Appl. Environ. Microbiol. 76, 922–926 (2010).

    CAS  PubMed  Google Scholar 

  67. Schramm, A., Fuchs, B. M., Nielsen, J. L., Tonolla, M. & Stahl, D. A. Fluorescence in situ hybridization of 16S rRNA gene clones (Clone-FISH) for probe validation and screening of clone libraries. Environ. Microbiol. 4, 713–720 (2002).

    CAS  PubMed  Google Scholar 

  68. Daims, H., Stoecker, K. & Wagner, M. in Molecular Microbial Ecology (eds Osborn, M. A. and Smith, C. J.) 208–228 (Taylor & Francis, 2004).

  69. Daims, H., Lücker, S. & Wagner, M. daime, a novel image analysis program for microbial ecology and biofilm research. Environ. Microbiol. 8, 200–213 (2006).

    CAS  PubMed  Google Scholar 

  70. Taylor, G. J. & Crowder, A. A. Use of the DCB technique for extraction of hydrous iron oxides from roots of wetland plants. Am. J. Bot. 70, 1254 (1983).

    CAS  Google Scholar 

  71. Polerecky, L. et al. Look@NanoSIMS—a tool for the analysis of nanoSIMS data in environmental microbiology. Environ. Microbiol. 14, 1009–1023 (2012).

    CAS  PubMed  Google Scholar 

  72. Brewer, P. G. & Spencer, D. W. Colorimetric determination of manganse in anoxic waters. Limnol. Oceanogr. 16, 107–110 (1971).

    ADS  CAS  Google Scholar 

  73. Oldham, V. E., Miller, M. T., Jensen, L. T. & Luther, G. W. Revisiting Mn and Fe removal in humic rich estuaries. Geochim. Cosmochim. Acta 209, 267–283 (2017).

    ADS  CAS  Google Scholar 

  74. Suzuki, M. T., Taylor, L. T. & DeLong, E. F. Quantitative analysis of small-subunit rRNA genes in mixed microbial populations via 5′-nuclease assays. Appl. Environ. Microbiol. 66, 4605–4614 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. William, S., Feil, H. & Copeland, A. Bacterial genomic DNA isolation using CTAB, Department of Energy Joint Genome Institute, https://jgi.doe.gov/user-programs/pmo-overview/protocols-sample-preparation-information/ (2012).

  76. Arkin, A. P. et al. KBase: the United States Department of Energy systems biology knowledgebase. Nat. Biotechnol. 36, 566–569 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    MathSciNet  CAS  PubMed  PubMed Central  Google Scholar 

  79. Karst, S. M., Kirkegaard, R. H. & Albertsen, M. mmgenome: a toolbox for reproducible genome extraction from metagenomes. Preprint at https://www.biorxiv.org/content/ 10.1101/059121v1.full (2016).

  80. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Chen, I. A. et al. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 47, D666–D677 (2019).

    CAS  PubMed  Google Scholar 

  82. NCBI Resource Coordinators. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 46, D8–D13 (2018).

    Google Scholar 

  83. Bagos, P. G., Liakopoulos, T. D., Spyropoulos, I. C. & Hamodrakas, S. J. PRED-TMBB: a web server for predicting the topology of β-barrel outer membrane proteins. Nucleic Acids Res. 32, W400–W404 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Federhen, S. The NCBI taxonomy database. Nucleic Acids Res. 40, D136–D143 (2012).

    CAS  PubMed  Google Scholar 

  85. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Pruesse, E., Peplies, J. & Glöckner, F. O. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 28, 1823–1829 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Ronquist, F. et al. MrBayes 3.2: efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542 (2012).

    PubMed  PubMed Central  Google Scholar 

  88. Letunic, I. & Bork, P. Interactive tree of life (iTOL) v3: an online tool for the display and annotation of phylogenetic and other trees. Nucleic Acids Res. 44, W242–W245 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Sievers, F. et al. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol. Syst. Biol. 7, 539 (2011).

    PubMed  PubMed Central  Google Scholar 

  91. Lever, M. A. et al. A modular method for the extraction of DNA and RNA, and the separation of DNA pools from diverse environmental sample types. Front. Microbiol. 6, 476 (2015).

    PubMed  PubMed Central  Google Scholar 

  92. Kopylova, E., Noé, L. & Touzet, H. SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics 28, 3211–3217 (2012).

    CAS  PubMed  Google Scholar 

  93. Bray, N. L., Pimentel, H., Melsted, P. & Pachter, L. Near-optimal probabilistic RNA-seq quantification. Nat. Biotechnol. 34, 525–527 (2016).

    CAS  PubMed  Google Scholar 

  94. Pimentel, H., Bray, N. L., Puente, S., Melsted, P. & Pachter, L. Differential analysis of RNA-seq incorporating quantification uncertainty. Nat. Methods 14, 687–690 (2017).

    CAS  PubMed  Google Scholar 

  95. van Waasbergen, L. G., Hildebrand, M. & Tebo, B. M. Identification and characterization of a gene cluster involved in manganese oxidation by spores of the marine Bacillus sp. strain SG-1. J. Bacteriol. 178, 3517–3530 (1996).

    PubMed  PubMed Central  Google Scholar 

  96. Jung, W. K. & Schweisfurth, R. Manganese oxidation by an intracellular protein of a Pseudomonas species. Z. Allg. Mikrobiol. 19, 107–115 (1979).

    CAS  PubMed  Google Scholar 

  97. Esteve-Núñez, A., Rothermich, M., Sharma, M. & Lovley, D. Growth of Geobacter sulfurreducens under nutrient-limiting conditions in continuous culture. Environ. Microbiol. 7, 641–648 (2005).

    PubMed  Google Scholar 

  98. Neubauer, S. C., Emerson, D. & Megonigal, J. P. Life at the energetic edge: kinetics of circumneutral iron oxidation by lithotrophic iron-oxidizing bacteria isolated from the wetland-plant rhizosphere. Appl. Environ. Microbiol. 68, 3988–3995 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Nowka, B., Daims, H. & Spieck, E. Comparison of oxidation kinetics of nitrite-oxidizing bacteria: nitrite availability as a key factor in niche differentiation. Appl. Environ. Microbiol. 81, 745–753 (2015).

    PubMed  PubMed Central  Google Scholar 

  100. Ehrich, S., Behrens, D., Lebedeva, E., Ludwig, W. & Bock, E. A new obligately chemolithoautotrophic, nitrite-oxidizing bacterium, Nitrospira moscoviensis sp. nov. and its phylogenetic relationship. Arch. Microbiol. 164, 16–23 (1995).

    CAS  PubMed  Google Scholar 

  101. Kim, S. & Lee, S. B. Catalytic promiscuity in dihydroxy-acid dehydratase from the thermoacidophilic archaeon Sulfolobus solfataricus. J. Biochem. 139, 591–596 (2006).

    CAS  PubMed  Google Scholar 

  102. Safarian, S. et al. Structure of a bd oxidase indicates similar mechanisms for membrane-integrated oxygen reductases. Science 352, 583–586 (2016).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  103. Lovley, D. R. & Phillips, E. J. P. Manganese inhibition of microbial iron reduction in anaerobic sediments. Geomicrobiol. J. 6, 145–155 (1988).

    CAS  Google Scholar 

  104. Perez-Benito, J. F., Arias, C. & Amat, E. A kinetic study of the reduction of colloidal manganese dioxide by oxalic acid. J. Colloid Interface Sci. 177, 288–297 (1996).

    ADS  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by NASA Astrobiology Institute Exobiology grant #80NSSC19K0480; and by Caltech’s Center for Environmental Microbial Interactions and Division of Geological and Planetary Sciences. We thank S. Connon for assistance with iTag sequencing preparations; G. Rossman and U. Lingappa for spectroscopic analyses and minerology insights; G. Chadwick for discussions on physiology and bioenergetics; I. Antoshechkin and V. Kumar for assistance with nucleic acid library preparation and sequencing at the Millard and Muriel Jacobs Genetics and Genomics Laboratory; N. Dalleska for assistance with ICP–MS analyses at the Environmental Analysis Center; F. Gao for inputs on RNA data analysis using kallisto software at the Bioinformatics Resource Center in the Beckman Institute; C. Ma for assistance with SEM analyses at the GPS Analytical Facility; Y. Guan for assistance with nanoSIMS analyses at the GPS Microanalysis Center; and multiple colleagues for feedback before publication.

Author information

Authors and Affiliations

Authors

Contributions

H.Y. and J.R.L. together applied for funding, designed and conducted the experiments, performed data analyses, prepared the figures and wrote the manuscript.

Corresponding author

Correspondence to Jared R. Leadbetter.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Edward F. DeLong, Philip Hugenholtz, Bradley M. Tebo, Michael Wagner and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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 Effect of temperature, anti-bacterials and Mn(II)Cl2 on biological Mn(II)CO3 oxidation.

a, Incubation temperature influences oxidation. An optimum between 34 °C and 40 °C was observed, but above these temperatures oxidation was inhibited. By contrast, non-biological reactions would generally be predicted to continue to increase in rate with increasing temperature. b, Sensitivity of Mn(II) oxidation to the presence of either of two antibiotics, or to prior pasteurization before extended incubation at 32 °C. c, When amended to active co-cultures at concentrations >2.0 mM, MnCl2 appeared to inhibit MnCO3 oxidation when an active culture containing about 2.2 mM unreacted MnCO3 was used as the inoculum. The number of points for each experimental condition represents independent cultivation experiments.

Source data

Extended Data Fig. 2 Mn(II) oxidation and growth by the co-culture.

a, DNA yield of the two-species co-culture incubated in MOPS-buffered basal medium in the absence of Mn(II) substrate. No statistically significant changes in the mean DNA yields (P = 0.06, day 0 vs 10; P = 0.70, day 10 vs 21; P = 0.20, day 0 vs 21; two-tailed t-test with equal variance) are observed over the incubation period. b, c, Exponential increase in bacteria and biomass yields in a Mn(II)-oxidizing culture, which is coupled to exponential increases Mn(II) oxidation (same culture analysed in Fig. 2). Bacteria were measured via 16S rRNA gene copies using a general bacteria probe in quantitative PCR; points represent 3 technical replicates. Biomass was measured via DNA yield from same culture volumes. d, Exponential increases in Mn(II) oxidation (Fig. 2a) and DNA yields by this same culture (1 mM nitrate replicate 1, c) correlate. Similar relationships were observed in samples from independent cultivation experiments (n = 2). el, Kinetics of Mn(II) oxidation by the co-culture in basal medium; two phases of exponential Mn(II) oxidation were observed. eg, Basal medium with 1 mM nitrate (n = 4; for replicate 1, see b–d and Fig. 2). hl, Basal medium with 1 mM ammonia (n = 5). m, Exponential growth of species A and species B paralleled Mn(II) oxidation in basal medium with 1 mM ammonia as the nitrogen source (1 mM ammonia replicate 5, l), rather than 1 mM nitrate. n, Linear relationship between cell growth and the amount of Mn(II) oxidized (1 mM ammonia replicate 5, l and m). Values in n were normalized by subtracting the initial cell number and Mn oxide concentrations at the onset of the experiment, and negative values after normalization were excluded from the analysis. All data points included in the line fits are used to calculate the doubling times (Td), unless otherwise noted by ‘x’ symbols.

Source data

Extended Data Fig. 3 Properties of the refined co-culture.

a, Estimations of the relative ratio between species A and species B. Slow-growing microorganisms, in particular species A (which also has a smaller cell volume than species B or Escherichia coli) could have a lower number of ribosomes, resulting in lower signal intensity from rRNA-targeted fluorescent probes, relative to the fluorescent signal from DNA stain DAPI. The two species together account for 99.7% of assigned sequence reads (Supplementary Table 1). The two species together account for 97.54% of the sequence reads in the metagenome (f). §The two species together account for 99.576% (s.d. = 0.005%, n = 7) of the rRNA sequence reads and 100.1700% (s.d. = 0.0005%, n = 7) of the non-rRNA sequence reads in the co-culture metatranscriptomes (h). be, Possible metabolic interactions that may be occurring between species A (orange) and species B (blue). f, Genome statistics for species A and species B. g, Observed rates and yields of Mn(II) oxidation by the co-culture, in comparison to the literature values5,23,26,39,95,96,97,98,99,100 reported for other physiologically or phylogenetically related lithotrophs or metal-active heterotrophs. ||Conversion estimate based on Escherichia coli biomass of 2.8 × 10−13 g dry cell weight per cell, of which 55% is protein27. Co-culture values correspond to results from the single independent culture with nitrate as the nitrogen source for which extensive data on both oxidation kinetics and growth (genome copies) were collected. h, Transcriptome statistics for 7 co-cultures sampled at different degrees of Mn(II) oxidation.

Extended Data Fig. 4 Microscopy of Mn oxide nodules formed by the co-culture.

ae, Epifluorescence microscopy reveals distribution of cells of species A and species B associated with dissolved Mn oxide nodules. DAPI (blue) was used to stain DNA, in addition to applying species-specific FISH probes targeting the 16S rRNA of species A (magenta) and species B (green). Probe fluorescence for species A was dim and faded rapidly, but was associated with the cells that otherwise appear in photomicrographs to only be DAPI-stained. No third species is present, as observed in independent cultivation experiments (n = 2), and confirmed via independent methods (Extended Data Fig. 3a). fp, Scanning electron micrographs of Mn(II)CO3 substrate (f, g) and Mn oxide nodules collected from liquid cultures (hp). Representative nodules are from independent cultivation experiments (n = 4).

Extended Data Fig. 5 Phylogenetic analyses on species A.

a, 16S rRNA gene phylogram, based on a Bayesian analysis of 1,532 aligned nucleotide positions. NCBI82 taxonomic classifications are used, and sequences shown are all from the phylum Nitrospirae. The names and known physiologies for the previously described genera in this phylum are shown on the right. NCBI accession numbers for 16S rRNA sequences are included in the node names. Source environment for the sequences are shown in brackets. b, Multilocus phylogram, based on a Bayesian analysis of 5,036 aligned amino acid positions concatenated from 120 bacterial protein markers62. GTDB62 taxonomic classifications are used, and sequences shown are from the phylum under the headings ‘Nitrospirota’ and Nitrospirota_A’. The names and known physiologies for the previously described classes in this phylum are shown on the right. NCBI accession numbers for genome assemblies are included in the node names. For a, b, the dots on the branches indicate posterior probabilities greater than 0.80. c, Phylogenetic analyses of the phylum Nitrospirae (Nitrospirota) limited to only those species with reconstructed genomes yield a topology different from that observed in a and Fig. 3a. Bayesian phylogram based on 1,532 aligned 16S rRNA nucleotide positions (left); multilocus Bayesian phylogram, based on 5,036 aligned amino acid positions of 120 concatenated bacterial protein markers (right). Sequences clustering within the three previously described classes within this phylum are collapsed into separate nodes. d, Protein sequence phylogeny of dihydroxy-acid and 6-phosphogluconate dehydratases. Sequences were selected based on a previous study101, with the addition of homologues found in Nitrospira inopinata, Leptospirillum ferriphilum and species A (red). All 770 aligned amino acid positions were used in the maximum likelihood analysis. Protein accession numbers from the NCBI database or gene identifiers from the IMG database of the 3 new sequences are shown in parentheses. Black dots on the branches represent bootstrap values equal to 100%. Although dihydroxy-acid dehydratase and 6-phosphogluconate dehydratase are homologous, they form separate clusters phylogenetically as reported101. The homologues in Nitrospirae all belong to the dihydroxy-acid dehydratase clade, therefore are unlikely candidates for 6-phosphogluconate dehydratase activity and function in the ED pathway. All scale bars show evolutionary distance (0.1 substitutions-per-site average).

Extended Data Fig. 6 Phylogenetic analyses and aerobic heterotrophic growth of isolated species B.

a, 16S rRNA gene phylogram, based on a Bayesian analysis of 1,532 aligned nucleotide positions. NCBI82 taxonomic classifications are used, with sequences selected from the class Betaproteobacteria. The genus Ramlibacter, consistently identified in two phylogenetic approaches, is shaded in grey, with species B in bold. Source environments for the species in Ramlibacter are shown in brackets. The order and family classifications are included to the right separated by a semicolon. The black dots on the branches indicate posterior probabilities greater than 0.90. b, Multilocus phylogram, based on a maximum-likelihood analysis of 5,035 aligned amino acid positions concatenated from 120 bacterial protein markers62. GTDB62 taxonomic classifications are used, and sequences shown are from the order Betaproteobacteriales. The GTDB family classifications are included to the right of species names. NCBI accession numbers for 16S rRNA sequences or the genome assemblies are included after the species names. The black dots on the branches indicate bootstrap values greater than 90%. Scale bars shown evolutionary distance (0.1 substitutions-per-site average). c, d, Kinetics of species B growth basal media with either 5 g/l of tryptone (n = 3 biological replicates) (c) or 10 mM acetate (n = 2 biological replicates) (d).

Source data

Extended Data Fig. 7 Phylogenetic analyses of cytochrome bd oxidase subunit I and cytochrome bd-like oxidases.

Only cytochrome bd-like oxidases were identified in species A, in contrast to other classes in the phylum Nitrospirae (Nitrospirota). a, Unrooted maximum-likelihood tree, constructed using 242 amino acid positions shared between cytochrome bd and bd-like oxidases, using RAxML89 (model LGF). Deduced proteins from the genome of species A are in red, with their IMG gene identifiers and clade numbering (as shown in Fig. 3b) included in brackets. Other proteins from the phylum Nitrospirae (Nitrospirota) are coloured blue, orange or brown for classes Nitrospiria, Leptospirillia or Thermodesulfovibrionia, respectively. Cytochrome bd oxidase of species B, with its IMG identifier, is in green; it belongs to the cyanide insensitive oxidase clade in purple. b, Phylogenetic analysis of cytochrome bd-like oxidases from species A. Unrooted maximum-likelihood tree was constructed using 242 amino acid positions shared between different clades of cytochrome bd-like oxidases. Cytochrome bd-like oxidases are assigned to different clades, based on the phylogeny and their gene cluster structures. Species A encodes 8 cytochrome bd-like oxidases (bold), representing clades I, II, IIIb, Va and Vb; clade numbering as shown in Fig. 3b are included in brackets after the IMG identifiers. Black dots on branches represent bootstrap values greater than 90%. Scale bars show evolutionary distance (substitutions-per-site average).

Extended Data Fig. 8 Sequence alignment of cytochrome bd and bd-like oxidases.

Cytochrome bd-like oxidase in species A (sequence names starting with A, followed by their IMG gene identifier and clade numbering as shown in brackets in Fig. 3b) and cytochrome bd oxidase subunit I in species B (sequence name starting with B, followed by its IMG gene identifier) are aligned to characterized cytochrome bd oxidases in Escherichia coli (sequence name starting with Eco, followed by its NCBI identifier) and Geobacillus thermodenitrificans (sequence name starting with Geo, followed by its NCBI identifier). Key features as revealed by structure102 are indicated at the top of the alignment, using E. coli protein residue numbering. The cytochrome bd oxidase subunit I sequence from species B shows conservation of all key residues. By contrast, cytochrome bd-like oxidases in species A do not show conservation of many key residues; instead, they are predicted to have up to 14 transmembrane helixes (compared to 9 in E. coli). One cytochrome bd-like oxidase in species A has a C-terminus extension with a haem c binding motif (CXXCH).

Extended Data Fig. 9 Stable isotope probing of Mn(II)-oxidizing co-culture measured using nanoSIMS.

a, Summary of stable isotope probing analysis of cells dissolved from Mn oxide nodules, either with paraformaldehyde fixation and FISH, or without (to avoid dilution with natural abundance isotopes). Cells of species A and species B were either identified by FISH or by elemental composition (species B cells were observed to have higher 14N/15N ratios), and their isotopic compositions were obtained via nanoSIMS (n = the total number of cell regions of interest analysed in the nanoSIMS images). For FISH–nanoSIMS analyses, a total of 2 and 5 nanoSIMS images from single cultures incubated with either MnCO3 or Mn13CO3, respectively, was examined. For nanoSIMS analyses without paraformaldehyde fixation and FISH, a total of 3 and 17 nanoSIMS images from single cultures incubated with either MnCO3 or Mn13CO3, respectively, was examined. bu, Individual secondary ion images from nanoSIMS showing incorporation of inorganic 13C and 15N into the cells of both species (dissolved from Mn oxide nodules grown in the presence of MnCO3 and 15NO3 (bk) or Mn13CO3 and 15NO3 (lu)), and species B cells could have higher 14N content than species A. Secondary ions 12C2 (mass 24 for 12C), 13C12C (mass 25 for 13C), 14N12C (mass 26 for 14N), 15N12C (mass 27 for 15N), 32S (mass 32 for 32S) were simultaneously measured. The counts of the secondary ions are shown in brackets (minimum–maximum) and displayed using the colour scale shown to the right of the images. bf and lp correspond to the top and bottom panels in Fig. 4, respectively. White arrows indicate species B cells identified in FISH showing high 14N in nanoSIMS. v, NanoSIMS measurement of residual Mn associated with cells grown with Mn13CO3 and 15NO3, after dissolving from Mn oxide nodules. The same nanoSIMS image area was analysed as in lp, except 55Mn16O (mass 71 for 55Mn) was measured (n = 1 nanoSIMS image) in addition to other secondary ions. Negligible amount of Mn was found in the biomass, indicating that any remaining Mn13CO3 substrate had been completely dissolved away during sample preparation, and thus did not interfere with the 13C analyses.

Extended Data Fig. 10 Evaluations of experimental methods.

ad, Evaluation of FISH oligonucleotide probes. Three probes (NLT499, black circles; BET359, white circles; BET867, white squares) were tested in different probe combinations and formamide concentrations, using 16S rRNA gene clones of species A (a, b) or species B (c, d). Each point in the dissociation profile represents the mean of fluorescence intensities of at least 100 different single cells in 5 distinct microscopic fields of 1 biological replicate. Lines connect the 95% confidence intervals of the points. No interference was found when targeting either species A or species B with different probe combinations and formamide concentrations. RU, relative units of fluorescence intensity. e, Evaluation of ICP–MS method to measure Mn compounds with different oxidation states. Mn(II) in its various forms can be almost entirely measured in the acid-soluble fraction with little in the acid-insoluble fraction, and any increase in the acid-insoluble fraction is an indication of oxidized Mn(II). We refer to the ‘acid-soluble fraction’ as Mn(II), and the ‘acid-insoluble fraction’ as Mn(II) oxidized representing Mn(III/IV). Supplementary Note 4 provides more details. MnO2 was synthesized according to two previously published methods103,104. f, Evaluation of transcriptome analysis software kallisto93. Average fragment length for RNA libraries was measured to be 230 bp. However, using 230 bp as the input parameter for fragment length caused a kallisto93 expression evaluation issue for genes <230 bp in length; thus, the fragment length was adjusted downward to 100 bp to evaluate the expression of genes <230 bp. This parameter change does not affect the overall transcript expression for genes >230 bp as seen in the correlation analysis, performed using transcriptome sample Mn03. g, h, Evaluation of quantification range and efficiency of quantitative PCR oligonucleotide probes. Three quantitative PCR oligonucleotide probes (bacteria (g) or species A- or species B-specific (h)) were tested using cloned 16S rRNA gene of either species A (open squares, solid lines) or species B (open triangles, dashed lines) as DNA templates. Threshold cycle (CT) versus gene copies show that all three probes had amplification efficiencies between 90–105% in the quantification ranges plotted. Points represent 3 technical replicates. i, j, Evaluation of specificity of quantitative PCR oligonucleotide probes. The percentage of species A (i) and species B (j) was estimated in reactions containing a mixture of cloned 16S rRNA genes from both species A and species B as DNA templates. Dashed lines represent theoretical 100% match in the expected versus measured values. The results indicate that the species-specific probes quantified their targeted species with minimal interference. Points represent 4 technical replicates.

Source data

Supplementary information

Supplementary Information

This file contains the Supplementary Taxonomic Proposal; Supplementary Notes; and Supplementary Information References. Together, these provide additional support and information underlying the main text and methods.

Reporting Summary

Supplementary Table 1

This table contains community profiles of Mn-oxidising enrichments by iTag sequencing of 16S rRNA genes.

Supplementary Table 2

This table contains a percent identity matrix of representative 16S rRNA gene sequences in the phylum Nitrospirae.

Supplementary Table 3

This table contains transcriptomics analyses of multiple biological replicates of the co-culture after oxidising different amounts of Mn(II).

Supplementary Table 4

This table contains key genomic features and their expression in Species A.

Supplementary Table 5

This table contains key genomic features and their expression in Species B.

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yu, H., Leadbetter, J.R. Bacterial chemolithoautotrophy via manganese oxidation. Nature 583, 453–458 (2020). https://doi.org/10.1038/s41586-020-2468-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-020-2468-5

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

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