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Ecological selection for small microbial genomes along a temperate-to-thermal soil gradient

Nature Microbiology (2018) | Download Citation

Abstract

Small bacterial and archaeal genomes provide insights into the minimal requirements for life1 and are phylogenetically widespread2. However, the precise environmental pressures that constrain genome size in free-living microorganisms are unknown. A study including isolates has shown that thermophiles and other bacteria with high optimum growth temperatures often have small genomes3. It is unclear whether this relationship extends generally to microorganisms in nature4,5 and more specifically to microorganisms that inhabit complex and highly variable environments, such as soils3,6,7. To understand the genomic traits of thermally adapted microorganisms, here we investigated metagenomes from a 45 °C gradient of temperate-to-thermal soils that lie over the ongoing Centralia, Pennsylvania (USA) coal-seam fire. We found that hot soils harboured distinct communities with small genomes and small cell sizes relative to those in ambient soils. Hot soils notably lacked genes that encode known two-component regulatory systems, and antimicrobial production and resistance genes. Our results provide field evidence for the inverse relationship between microbial genome size and temperature in a diverse, free-living community over a wide range of temperatures that support microbial life.

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Data availability

Metagenome data are available on IMG under the GOLD Study ID GS0114513. MG-RAST data are available under Project IDs mgp3731, mgp252, mgp5588, mgp14596, mgp6377, mgp6368, mgp2592, mgp2076, mgp11628, mgp13948, mgp7176 and mgp15600.

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

References

  1. 1.

    Hutchison, C. A. et al. Design and synthesis of a minimal bacterial genome. Science 351, aad6253 (2016).

  2. 2.

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

  3. 3.

    Sabath, N., Ferrada, E., Barve, A. & Wagner, A. Growth temperature and genome size in bacteria are negatively correlated, suggesting genomic streamlining during thermal adaptation. Genome Biol. Evol. 5, 966–977 (2013).

  4. 4.

    Huete-Stauffer, T. M., Arandia-Gorostidi, N., Alonso-Sáez, L. & Morán, X. A. G. Experimental warming decreases the average size and nucleic acid content of marine bacterial communities. Front. Microbiol. 7, 730 (2016).

  5. 5.

    Swan, B. K. et al. Prevalent genome streamlining and latitudinal divergence of planktonic bacteria in the surface ocean. Proc. Natl Acad. Sci. USA 110, 11463–11468 (2013).

  6. 6.

    Brewer, T. E., Handley, K. M., Carini, P., Gilbert, J. A. & Fierer, N. Genome reduction in an abundant and ubiquitous soil bacterium ‘Candidatus Udaeobacter copiosus’. Nat. Microbiol. 2, 16198 (2016).

  7. 7.

    Giovannoni, S. J., Thrash, J. C. & Temperton, B. Implications of streamlining theory for microbial ecology. ISME J. 8, 1553–1565 (2014).

  8. 8.

    Janzen, C. & Tobin-Janzen, T. in Microbiology of Extreme Soils (eds Dion, P. & Nautiyal, C. S.) 299–316 (Springer, Berlin, 2008).

  9. 9.

    Tobin-Janzen, T. et al. Nitrogen changes and domain bacteria ribotype diversity in soils overlying the Centralia, Pennsylvania underground coal mine fire. Soil Sci. 170, 191–201 (2005).

  10. 10.

    Lee, S.-H., Sorensen, J. W., Grady, K. L., Tobin, T. C. & Shade, A. Divergent extremes but convergent recovery of bacterial and archaeal soil communities to an ongoing subterranean coal mine fire. ISME J. 11, 1447–1459 (2017).

  11. 11.

    Shade, A. Understanding microbiome stability in a changing world. mSystems 3, e00157-17 (2018).

  12. 12.

    Raes, J., Korbel, J. O., Lercher, M. J., von Mering, C. & Bork, P. Prediction of effective genome size in metagenomic samples. Genome Biol. 8, R10 (2007).

  13. 13.

    Tecon, R. & Or, D. Biophysical processes supporting the diversity of microbial life in soil. FEMS Microbiol. Rev. 41, 599–623 (2017).

  14. 14.

    Schattenhofer, M. et al. Latitudinal distribution of prokaryotic picoplankton populations in the Atlantic Ocean. Environ. Microbiol. 11, 2078–2093 (2009).

  15. 15.

    Dodsworth, J. A., Hungate, B., de la Torre, J. R., Jiang, H. & Hedlund, B. P. Measuring nitrification, denitrification, and related biomarkers in terrestrial geothermal ecosystems. Methods Enzymol. 486, 171–203 (2011).

  16. 16.

    Marchant, R. et al. Thermophilic bacteria in cool temperate soils: are they metabolically active or continually added by global atmospheric transport? Appl. Microbiol. Biotechnol. 78, 841–852 (2008).

  17. 17.

    Reigstad, L. J. et al. Nitrification in terrestrial hot springs of Iceland and Kamchatka. FEMS Microbiol. Ecol. 64, 167–174 (2008).

  18. 18.

    Santana, M., Gonzalez, J. & Clara, M. Inferring pathways leading to organic-sulfur mineralization in the Bacillales. Crit. Rev. Microbiol. 42, 31–45 (2016).

  19. 19.

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

  20. 20.

    Dunivin, T. K. & Shade, A. Community structure explains antibiotic resistance gene dynamics over a temperature gradient in soil. FEMS Microbiol. Ecol. 94, fiy016 (2018).

  21. 21.

    Gao, Z. M. et al. Symbiotic adaptation drives genome streamlining of the cyanobacterial sponge symbiont ‘Candidatus Synechococcus spongiarum’. mBio 5, e00079–14 (2014).

  22. 22.

    Grote, J. et al. Streamlining and core genome conservation among highly divergent members of the SAR11 clade. mBio 3, e00252–12 (2012).

  23. 23.

    Brouns, S. J. J. et al. Engineering a selectable marker for hyperthermophiles. J. Biol. Chem. 280, 11422–11431 (2005).

  24. 24.

    Hoseki, J., Yano, T., Koyama, Y. & Kuramitsu, S. Directed evolution of thermostable kanamycin-resistance gene: a convenient selection marker for Thermus thermophilus. J. Biochem. 126, 951–956 (1999).

  25. 25.

    Hoch, J. A. Two-component and phosphorelay signal transduction. Curr. Opin. Microbiol. 3, 165–170 (2000).

  26. 26.

    Whitworth, D. E. & Cock, P. J. A. Evolution of prokaryotic two-component systems: insights from comparative genomics. Amino Acids 37, 459–466 (2009).

  27. 27.

    Ranea, J. A. G., Grant, A., Thornton, J. M. & Orengo, C. A. Microeconomic principles explain an optimal genome size in bacteria. Trends Genet. 21, 21–25 (2005).

  28. 28.

    Moran, N. A. Microbial minimalism: genome reduction in bacterial pathogens. Cell 108, 583–586 (2002).

  29. 29.

    Wang, Q., Cen, Z. & Zhao, J. The survival mechanisms of thermophiles at high temperatures: an angle of omics. Physiology 30, 97–106 (2015).

  30. 30.

    Yus, E. et al. Impact of genome reduction on bacterial metabolism and its regulation. Science 326, 1263–1268 (2009).

  31. 31.

    McCutcheon, J. P. & Moran, N. A. Extreme genome reduction in symbiotic bacteria. Nat. Rev. Microbiol. 10, 13–26 (2012).

  32. 32.

    Kussell, E. & Leibler, S. S. Phenotypic diversity, population growth, and information in fluctuating environments. Science 309, 2075–2078 (2005).

  33. 33.

    Vellend, M. Conceptual synthesis in community ecology. Q. Rev. Biol. 85, 183–206 (2010).

  34. 34.

    Portillo, M. C., Santana, M. & Gonzalez, J. M. Presence and potential role of thermophilic bacteria in temperate terrestrial environments. Naturwissenschaften 99, 43–53 (2012).

  35. 35.

    Müller, A. L. et al. Endospores of thermophilic bacteria as tracers of microbial dispersal by ocean currents. ISME J. 8, 1153–1165 (2014).

  36. 36.

    Giovannoni, S. J. et al. Genetics: genome streamlining in a cosmopolitan oceanic bacterium. Science 309, 1242–1245 (2005).

  37. 37.

    Cho, J. -C., Lee, D. -H., Cho, Y. -C., Cho, J. -C. & Kim, S. -J. Direct extraction of DNA from soil for amplification of 16S rRNA gene sequences by polymerase chain reaction. J. Microbiol. 34, 229–235 (2006).

  38. 38.

    Huntemann, M. et al. The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4). Stand. Genomic Sci. 11, 17 (2016).

  39. 39.

    Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y. & Morishima, K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 45, D353–D361 (2017).

  40. 40.

    He, S. et al. Patterns in wetland microbial community composition and functional gene repertoire associated with methane emissions. mBio 6, e00066-15 (2015).

  41. 41.

    Nayfach, S. & Pollard, K. S. Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiome. Genome Biol. 16, 51 (2015).

  42. 42.

    Balkwill, D. L. & Casida, L. E. Microflora of soil as viewed by freeze etching. J. Bacteriol. 114, 1319–1327 (1973).

  43. 43.

    Kang, D. D., Froula, J., Egan, R. & Wang, Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3, e1165 (2015).

  44. 44.

    Rodriguez-R, L. M. et al. Microbial Genomes Atlas: standardizing genomic and metagenomic analyses for Archaea and Bacteria. Nucleic Acids Res. 46, 282–288 (2018).

  45. 45.

    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).

  46. 46.

    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).

  47. 47.

    Andrews, S. FastQC: a quality control tool for high throughput sequence data (2010); http://www.bioinformatics.babraham.ac.uk/projects/fastqc

  48. 48.

    Choi, J. et al. Strategies to improve reference databases for soil microbiomes. ISME J. 11, 829–834 (2017).

  49. 49.

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

  50. 50.

    Komsta, L. outliers: Tests for outliers. R package v.0.14 (2011); http://CRAN.R-project.org/package=outliers

  51. 51.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, New York, 2009).

  52. 52.

    Warnes, G. R. et al. gplots: Various R programming tools for plotting data. R package v.3.0.1 (2016); https://rdrr.io/cran/gplots/

  53. 53.

    Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).

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Acknowledgements

This research was supported by Michigan State University and the National Science Foundation grant no. DEB1749544. Computational resources were provided by the Michigan State Institute for Cyber-Enabled Research. Metagenome sequencing was supported by the Joint Genome Institute Community Science Project no. 1834. The work conducted by the US Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported under Contract no. DE-AC02-05CH11231. We thank K. L. Grady and S. -H. Lee for technical support and S. Yeh and J. Lee (REU-ACRES NSF grant no. 1560168) for their contributions to metagenome analyses.

Author information

Affiliations

  1. Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA

    • Jackson W. Sorensen
    • , Taylor K. Dunivin
    •  & Ashley Shade
  2. Environmental and Integrative Toxicological Sciences, Michigan State University, East Lansing, MI, USA

    • Taylor K. Dunivin
  3. Department of Biology, Susquehanna University, Selinsgrove, PA, USA

    • Tammy C. Tobin
  4. Department of Plant, Soil and Microbial Sciences, Program in Ecology, Evolutionary Biology and Behavior and the Plant Resilience Institute, Michigan State University, East Lansing, MI, USA

    • Ashley Shade

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Contributions

A.S. and T.C.T. conceived the study and conducted the field work. J.W.S. and T.K.D. performed analyses with A.S. J.W.S., A.S. and T.K.D. wrote the manuscript. All authors discussed results, and commented on and edited the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Ashley Shade.

Supplementary information

  1. Supplementary Information

    Supplementary Results, Supplementary References, Supplementary Figures 1–3, Supplementary Table 1, Supplementary Table 3–5, Supplementary Table 7.

  2. Reporting Summary

  3. Supplementary Table 2

    Two-sided Pearson’s correlations of Eukaryotic-specific ribosomal KEGG orthologues and plasmid pfam categories with temperature (n = 12 soils). No adjustments for multiple comparisons were made.

  4. Supplementary Table 6

    Completeness, contamination, and taxonomy of MAGs.

  5. Supplementary Table 8

    Significant two-sided Pearson’s correlations (false-discovery-rate-adjusted P value.

  6. Supplementary Table 9

    Permanent finished genomes per phylum in the integrated microbial genomes database used in Supplementary Fig. 2.

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DOI

https://doi.org/10.1038/s41564-018-0276-6