Functional shifts in microbial mats recapitulate early Earth metabolic transitions

Abstract

Phototrophic microbial mats dominated terrestrial ecosystems for billions of years, largely causing, through cyanobacterial oxygenic photosynthesis, but also undergoing, the Great Oxidation Event approximately 2.5 billion years ago. Taking a space-for-time approach based on the universality of core metabolic pathways expressed at ecosystem level, we studied gene content and co-occurrence networks in high-diversity metagenomes from spatially close microbial mats along a steep redox gradient. The observed functional shifts suggest that anoxygenic photosynthesis was present but not predominant under early Precambrian conditions, being accompanied by other autotrophic processes. Our data also suggest that, in contrast to general assumptions, anoxygenic photosynthesis largely expanded in parallel with the subsequent evolution of oxygenic photosynthesis and aerobic respiration. Finally, our observations might represent space-for-time evidence that the Wood–Ljungdahl carbon fixation pathway dominated phototrophic mats in early ecosystems, whereas the Calvin cycle probably evolved from pre-existing variants before becoming the dominant contemporary form of carbon fixation.

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Fig. 1: Microbial diversity in microbial mat metagenomes along a redox gradient in a pond from the Salar de Llamara (Atacama Desert, Chile).
Fig. 2: Major energy and carbon metabolisms in Llamara microbial mats based on diagnostic genes.
Fig. 3: Co-occurrence networks of diagnostic KOs involved in major energy and carbon fixation metabolic pathways in Llamara microbial mats from pond LLA9.
Fig. 4: Distribution of key energy and carbon fixation metabolisms in microbial mats across a redox gradient and, probably, time.

Data availability

The sequence datasets of the Llamara metagenomes have been deposited in GenBank with the BioProject accession code PRJNA438773 (corresponding to BioSample accessions SAMN08688543 to SAMN08688553). All codes generated for this study are available at Gitlab https://gitlab.com/DeemTeam/LLA9-Metagenomes. To facilitate colour identification in figures, numbers used to build all histograms are provided in the supplementary file Tables_for_Figures.xlsx

Change history

  • 05 November 2018

    In the version of this Article originally published, Supplementary Data 1 was incorrectly linked to Supplementary Table 8, Supplementary Table 1 was incorrectly linked to Supplementary Table 5, Supplementary Table 2 was incorrectly linked to Supplementary Data 1, Supplementary Table 3 was incorrectly linked to Supplementary Table 1, Supplementary Table 4 was incorrectly linked to Supplementary Table 2, Supplementary Table 5 was incorrectly linked to Supplementary Table 3, Supplementary Table 6 was incorrectly linked to Supplementary Table 4, and Supplementary Table 8 was incorrectly linked to Supplementary Table 6. The files have now been replaced to rectify this.

References

  1. 1.

    Allwood, A. C., Walter, M. R., Kamber, B. S., Marshall, C. P. & Burch, I. W. Stromatolite reef from the early Archaean era of Australia. Nature 441, 714–718 (2006).

  2. 2.

    Nutman, A. P., Bennett, V. C., Friend, C. R., Van Kranendonk, M. J. & Chivas, A. R. Rapid emergence of life shown by discovery of 3,700-million-year-old microbial structures. Nature 537, 535–538 (2016).

  3. 3.

    Knoll, A. H., Bergmann, K. D. & Strauss, J. V. Life: the first two billion years. Phil. Trans. R. Soc. B 371, 20150493 (2016).

  4. 4.

    Hamilton, T. L., Bryant, D. A. & Macalady, J. L. The role of biology in planetary evolution: cyanobacterial primary production in low-oxygen Proterozoic oceans. Environ. Microbiol. 18, 325–340 (2016).

  5. 5.

    Lenton, T. M. & Daines, S. J. Matworld – the biogeochemical effects of early life on land. New Phytol. 215, 531–537 (2017).

  6. 6.

    Andrault, D. et al. Large oxygen excess in the primitive mantle could be the source of the Great Oxygenation Event. Geochem. Persp. Lett. 6, 5–10 (2018).

  7. 7.

    Bolhuis, H., Cretoiu, M. S. & Stal, L. J. Molecular ecology of microbial mats. FEMS Microbiol. Ecol. 90, 335–350 (2014).

  8. 8.

    Des Marais, D. J. Microbial mats and the early evolution of life. Trends Ecol. Evol. 5, 140–144 (1990).

  9. 9.

    Paerl, H. W., Pinckney, J. L. & Steppe, T. F. Cyanobacterial-bacterial mat consortia: examining the functional unit of microbial survival and growth in extreme environments. Environ. Microbiol. 2, 11–26 (2000).

  10. 10.

    Souza, V. et al. An endangered oasis of aquatic microbial biodiversity in the Chihuahuan desert. Proc. Natl Acad. Sci. USA 103, 6565–6570 (2006).

  11. 11.

    Goh, F. et al. Determining the specific microbial populations and their spatial distribution within the stromatolite ecosystem of Shark Bay. ISME J. 3, 383–396 (2009).

  12. 12.

    Myshrall, K. L. et al. Biogeochemical cycling and microbial diversity in the thrombolitic microbialites of Highborne Cay, Bahamas. Geobiology 8, 337–354 (2010).

  13. 13.

    Saghaï, A. et al. Metagenome-based diversity analyses suggest a significant contribution of non-cyanobacterial lineages to carbonate precipitation in modern microbialites. Front. Microbiol. 6, 797 (2015).

  14. 14.

    Harris, J. K. et al. Phylogenetic stratigraphy in the Guerrero Negro hypersaline microbial mat. ISME J. 7, 50–60 (2013).

  15. 15.

    Fernandez, A. B. et al. Microbial diversity in sediment ecosystems (evaporites domes, microbial mats, and crusts) of hypersaline Laguna Tebenquiche, Salar de Atacama, Chile. Front. Microbiol. 7, 1284 (2016).

  16. 16.

    Thiel, V. et al. The dark side of the Mushroom Spring microbial mat: life in the shadow of chlorophototrophs. I. Microbial diversity based on 16S rRNA gene amplicons and metagenomic sequencing. Front. Microbiol. 7, 919 (2016).

  17. 17.

    Saghaï, A. et al. Unveiling microbial interactions in stratified mat communities from a warm saline shallow pond. Environ. Microbiol. 19, 2405–2421 (2017).

  18. 18.

    Berlanga, M., Palau, M. & Guerrero, R. Functional stability and community dynamics during spring and autumn seasons over 3 years in Camargue microbial mats. Front. Microbiol. 8, 2619 (2017).

  19. 19.

    Ruvindy, R., White, R. A.III., Neilan, B. A. & Burns, B. P. Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics. ISME J. 10, 183–196 (2016).

  20. 20.

    Casaburi, G., Duscher, A. A., Reid, R. P. & Foster, J. S. Characterization of the stromatolite microbiome from Little Darby Island, The Bahamas using predictive and whole shotgun metagenomic analysis. Environ. Microbiol. 18, 1452–1469 (2016).

  21. 21.

    Saghaï, A. et al. Comparative metagenomics unveils functions and genome features of microbialite-associated communities along a depth gradient. Environ. Microbiol. 18, 4990–5004 (2016).

  22. 22.

    Thiel, V., Hugler, M., Ward, D. M. & Bryant, D. A. The dark side of the Mushroom Spring microbial mat: life in the shadow of chlorophototrophs. II. Metabolic functions of abundant community members predicted from metagenomic analyses. Front. Microbiol. 8, 943 (2017).

  23. 23.

    Mobberley, J. M. et al. Organismal and spatial partitioning of energy and macronutrient transformations within a hypersaline mat. FEMS Microbiol. Ecol. 93, e00133–00116 (2017).

  24. 24.

    Dupraz, C. & Visscher, P. T. Microbial lithification in marine stromatolites and hypersaline mats. Trends Microbiol. 13, 429–438 (2005).

  25. 25.

    Gogarten, J. P. & Townsend, J. P. Horizontal gene transfer, genome innovation and evolution. Nat. Rev. Microbiol. 3, 679–687 (2005).

  26. 26.

    López-García, P., Zivanovic, Y., Deschamps, P. & Moreira, D. Bacterial gene import and mesophilic adaptation in archaea. Nat. Rev. Microbiol. 13, 447–456 (2015).

  27. 27.

    Martiny, J. B., Jones, S. E., Lennon, J. T. & Martiny, A. C. Microbiomes in light of traits: a phylogenetic perspective. Science 350, aac9323 (2015).

  28. 28.

    Hug, L. A. et al. A new view of the tree of life. Nat. Microbiol. 1, 16048 (2016).

  29. 29.

    Falkowski, P. G., Fenchel, T. & Delong, E. F. The microbial engines that drive Earth’s biogeochemical cycles. Science 320, 1034–1039 (2008).

  30. 30.

    Schoepp-Cothenet, B. et al. On the universal core of bioenergetics. Biochim. Biophys. Acta 1827, 79–93 (2013).

  31. 31.

    Fuchs, G. Alternative pathways of carbon dioxide fixation: insights into the early evolution of life? Annu. Rev. Microbiol. 65, 631–658 (2011).

  32. 32.

    Kono, T. et al. A RuBisCO-mediated carbon metabolic pathway in methanogenic archaea. Nat. Commun. 8, 14007 (2017).

  33. 33.

    Hubbell, S. P. Neutral theory in community ecology and the hypothesis of functional equivalence. Funct. Ecol. 19, 166–172 2005).

  34. 34.

    Loreau, M. Does functional redundancy exist? Oikos 104, 606–611 (2004).

  35. 35.

    Louca, S. et al. High taxonomic variability despite stable functional structure across microbial communities. Nat. Ecol. Evol. 1, 0015 (2016).

  36. 36.

    Louca, S. Probing the metabolism of microorganisms. Science 358, 1264–1265 (2017).

  37. 37.

    Braakman, R. & Smith, E. The compositional and evolutionary logic of metabolism. Phys. Biol. 10, 011001 (2013).

  38. 38.

    Blois, J. L., Williams, J. W., Fitzpatrick, M. C., Jackson, S. T. & Ferrier, S. Space can substitute for time in predicting climate-change effects on biodiversity. Proc. Natl Acad. Sci. USA 110, 9374–9379 (2013).

  39. 39.

    Fitzpatrick, M. C. & Keller, S. R. Ecological genomics meets community-level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation. Ecol. Lett. 18, 1–16 (2015).

  40. 40.

    Rocha, E. P. & Danchin, A. Base composition bias might result from competition for metabolic resources. Trends Genet. 18, 291–294 (2002).

  41. 41.

    Grim, S. L. & Dick, G. J. Photosynthetic versatility in the genome of Geitlerinema sp. PCC 9228 (formerly Oscillatoria limnetica ‘Solar Lake’), a model anoxygenic photosynthetic cyanobacterium. Front. Microbiol. 7, 1546 (2016).

  42. 42.

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

  43. 43.

    Nelson, W. C. & Stegen, J. C. The reduced genomes of Parcubacteria (OD1) contain signatures of a symbiotic lifestyle. Front. Microbiol. 6, 713 (2015).

  44. 44.

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

  45. 45.

    Ragsdale, S. W. & Pierce, E. Acetogenesis and the Wood-Ljungdahl pathway of CO2 fixation. Biochim. Biophys. Acta 1784, 1873–1898 2008).

  46. 46.

    Braakman, R. & Smith, E. The emergence and early evolution of biological carbon-fixation. PLoS Comput. Biol. 8, e1002455 (2012).

  47. 47.

    Nunoura, T. et al. A primordial and reversible TCA cycle in a facultatively chemolithoautotrophic thermophile. Science 359, 559–563 (2018).

  48. 48.

    Mall, A. et al. Reversibility of citrate synthase allows autotrophic growth of a thermophilic bacterium. Science 359, 563–567 (2018).

  49. 49.

    Sato, T., Atomi, H. & Imanaka, T. Archaeal type III RuBisCOs function in a pathway for AMP metabolism. Science 315, 1003–1006 (2007).

  50. 50.

    Wrighton, K. C. et al. RubisCO of a nucleoside pathway known from archaea is found in diverse uncultivated phyla in bacteria. ISME J. 10, 2702–2714 (2016).

  51. 51.

    Ślesak, I., Slesak, H. & Kruk, J. C. RubisCO early oxygenase activity: a kinetic and evolutionary perspective. BioEssays 39, 1700071 (2017).

  52. 52.

    Ducluzeau, A. L. et al. Was nitric oxide the first deep electron sink?. Trends Biochem. Sci. 34, 9–15 (2009).

  53. 53.

    Bryant, D. A. & Frigaard, N. U. Prokaryotic photosynthesis and phototrophy illuminated. Trends Microbiol. 14, 488–496 (2006).

  54. 54.

    Norman, A. G., Richards, L. A. & Carlyle, R. E. Microbial thermogenesis in the decomposition of plant materials: Part I. An adiabatic fermentation apparatus. J. Bacteriol. 41, 689–697 (1941).

  55. 55.

    Canfield, D. E., Rosing, M. T. & Bjerrum, C. Early anaerobic metabolisms.Phil. Trans. R. Soc. B 361, 1819–1834 (2006).

  56. 56.

    May, B., Young, L. & Moore, A. L. Structural insights into the alternative oxidases: are all oxidases made equal? Biochem. Soc. Trans. 45, 731–740 (2017).

  57. 57.

    Miller, C. S., Baker, B. J., Thomas, B. C., Singer, S. W. & Banfield, J. F. EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data. Genome Biol. 12, R44 (2011).

  58. 58.

    Rodriguez, R. L. & Konstantinidis, K. T. Nonpareil: a redundancy-based approach to assess the level of coverage in metagenomic datasets. Bioinformatics 30, 629–635 (2014).

  59. 59.

    Cox, M. P., Peterson, D. A. & Biggs, P. J. SolexaQA: at-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinform. 11, 485 (2010).

  60. 60.

    Li, D., Liu, C. M., Luo, R., Sadakane, K. & Lam, T. W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).

  61. 61.

    Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

  62. 62.

    Buchfink, B., Xie, C. & Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59–60 (2015).

  63. 63.

    Mistry, J., Finn, R. D., Eddy, S. R., Bateman, A. & Punta, M. Challenges in homology search: HMMER3 and convergent evolution of coiled-coil regions. Nucleic Acids Res. 41, e121 (2013).

  64. 64.

    Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

  65. 65.

    Eddy, S. R. A new generation of homology search tools based on probabilistic inference. Genome Inform. 23, 205–211 (2009).

  66. 66.

    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).

  67. 67.

    Creevey, C. J., Doerks, T., Fitzpatrick, D. A., Raes, J. & Bork, P. Universally distributed single-copy genes indicate a constant rate of horizontal transfer. PLoS ONE 6, e22099 (2011).

  68. 68.

    Campbell, J. H. et al. UGA is an additional glycine codon in uncultured SR1 bacteria from the human microbiota. Proc. Natl Acad. Sci. USA 110, 5540–5545 (2013).

  69. 69.

    Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y. & Hattori, M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 32, D277–D280 (2004).

  70. 70.

    Manor, O. & Borenstein, E. MUSiCC: a marker genes based framework for metagenomic normalization and accurate profiling of gene abundances in the microbiome. Genome Biol. 16, 53 (2015).

  71. 71.

    R Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017).

  72. 72.

    Vegan: Community Ecology Package. R package version 1.17-9 (2011); http://CRAN.R-project.org/package=vegan

  73. 73.

    Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, e1002687 (2012).

  74. 74.

    Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).

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Acknowledgements

We thank R. Rodríguez de la Vega for discussions about bioinformatics tools, J. Friedman for advice on SparCC, A. Abdala for helping with MySQL database reconstruction and E. Merino for help in COG assignation. We also thank I. Aracena (Departamento de Medio Ambiente, Sociedad Química y Minera, Chile), J. M. López-García (Instituto Geológico y Minero de España) and J. M. García-Ruiz’s team (Universidad de Granada) for sampling access, georeferencing, and company during the field trip. This research was funded by the European Research Council grant no. 322669 to P.L.G. under the European Union’s Seventh Framework Programme.

Author information

A.G.-P. and A.S. performed the bioinformatic analyses, analysed the data and wrote a preliminary draft of the manuscript. Y.Z. supervised initial metagenome assembly and annotation. P.D. helped with software installation and use. D.M. and P.L.G. collected the samples and conceived the study. P.L.G. prepared the samples for sequencing, supervised the work, provided hypotheses and wrote the final manuscript.

Correspondence to Purificación López-García.

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Supplementary information

Supplementary Figures

Supplementary Figures 1–11.

Reporting Summary

Supplementary Data 1

Tables with the values used to build colour histograms in the manuscript.

Supplementary Table 1

Assembly and annotation statistics of the 11 metagenomes of the microbial mat layers from Llamara.

Supplementary Table 2

Distribution of clusters of orthologous genes (COGs) in Llamara microbial mats.

Supplementary Table 3

Distribution of PFAMs in the different Llamara microbial mats.

Supplementary Table 4

Distribution of KEGG orthologues (KOs) in the different Llamara microbial mats.

Supplementary Table 5

Single copy gene families (COGs) universally distributed in prokaryotic genomes used to characterize the phylogenetic composition of microbial communities in Llamara microbial mats.

Supplementary Table 6

Single copy gene families (PFAMs) universally distributed in bacteria and archaea used to characterize the phylogenetic composition of prokaryotic communities in Llamara microbial mats.

Supplementary Table 7

Diagnostic KOs used for network analyses.

Supplementary Table 8

Network properties.

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Gutiérrez-Preciado, A., Saghaï, A., Moreira, D. et al. Functional shifts in microbial mats recapitulate early Earth metabolic transitions. Nat Ecol Evol 2, 1700–1708 (2018). https://doi.org/10.1038/s41559-018-0683-3

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