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Microbial life cycles link global modularity in regulation to mosaic evolution

Abstract

Microbes are exposed to changing environments, to which they can respond by adopting various lifestyles such as swimming, colony formation or dormancy. These lifestyles are often studied in isolation, thereby giving a fragmented view of the life cycle as a whole. Here, we study lifestyles in the context of this whole. We first use machine learning to reconstruct the expression changes underlying life cycle progression in the bacterium Bacillus subtilis, based on hundreds of previously acquired expression profiles. This yields a timeline that reveals the modular organization of the life cycle. By analysing over 380 Bacillales genomes, we then show that life cycle modularity gives rise to mosaic evolution in which life stages such as motility and sporulation are conserved and lost as discrete units. We postulate that this mosaic conservation pattern results from habitat changes that make these life stages obsolete or detrimental. Indeed, when evolving eight distinct Bacillales strains and species under laboratory conditions that favour colony growth, we observe rapid and parallel losses of the sporulation life stage across species, induced by mutations that affect the same global regulator. We conclude that a life cycle perspective is pivotal to understanding the causes and consequences of modularity in both regulation and evolution.

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Fig. 1: Lifestyles of B. subtilis.
Fig. 2: Global transcriptional regulation shows a modular organization.
Fig. 3: Expression profiles can be sorted along a single (pseudo-time) dimension.
Fig. 4: Expression of life stages and regulators in pseudo-time.
Fig. 5: Mosaic conservation patterns in the phylogenetic order of the Bacillales.
Fig. 6: Rapid mosaic adaptation in experiment evolution with Bacillales strains and species.

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Data availability

The flow cytometry data are publically available through the FlowRepository, accession No. FR-FCM-ZYVN. The sequencing reads are publically available on the European Nucleotide Archive (ENA) database, accession No. PRJEB32792. The remaining data are included in the Supplementary information or available through public repositories as mentioned in the Supplementary information.

References

  1. Kolenbrander, P. E., Palmer, R. J., Periasamy, S. & Jakubovics, N. S. Oral multispecies biofilm development and the key role of cell–cell distance. Nat. Rev. Microbiol. 8, 471–480 (2010).

    Article  CAS  PubMed  Google Scholar 

  2. Flores, E. & Herrero, A. Compartmentalized function through cell differentiation in filamentous cyanobacteria. Nat. Rev. Microbiol. 8, 39–50 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. McDougald, D., Rice, S. A., Barraud, N., Steinberg, P. D. & Kjelleberg, S. Should we stay or should we go: Mechanisms and ecological consequences for biofilm dispersal. Nat. Rev. Microbiol. 10, 39–50 (2012).

    Article  CAS  Google Scholar 

  4. Boutte, C. C. & Crosson, S. Bacterial lifestyle shapes stringent response activation. Trends Microbiol. 21, 174–180 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Claessen, D., Rozen, D. E., Kuipers, O. P., Søgaard-Andersen, L. & van Wezel, G. P. Bacterial solutions to multicellularity: a tale of biofilms, filaments and fruiting bodies. Nat. Rev. Microbiol. 12, 115–124 (2014).

    Article  CAS  PubMed  Google Scholar 

  6. van Gestel, J., Vlamakis, H. & Kolter, R. Division of labor in biofilms: the ecology of cell differentiation. Microbiol. Spectr. 3, MB-0002–MB-2014 (2015).

    Google Scholar 

  7. Yan, J., Nadell, C. D. & Bassler, B. L. Environmental fluctuation governs selection for plasticity in biofilm production. ISME J. 11, 1569–1577 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Mhatre, E., Monterrosa, R. G. & Kovács, Á. T. From environmental signals to regulators: modulation of biofilm development in Gram-positive bacteria. J. Basic Microbiol. 54, 616–632 (2014).

    Article  PubMed  Google Scholar 

  9. Winslow, C. E. A. What do we mean by a bacterial life cycle? Science 81, 314–315 (1935).

    Article  CAS  PubMed  Google Scholar 

  10. O’Toole, G., Kaplan, H. B. & Kolter, R. Biofilm formation as microbial development. Annu. Rev. Microbiol. 54, 49–79 (2000).

    Article  PubMed  Google Scholar 

  11. Hammerschmidt, K., Rose, C. J., Kerr, B. & Rainey, P. B. Life cycles, fitness decoupling and the evolution of multicellularity. Nature 515, 75–79 (2014).

    Article  CAS  PubMed  Google Scholar 

  12. Stragier, P. & Losick, R. Molecular genetics of sporulation in Bacillus subtilis. Annu. Rev. Genet. 30, 297–341 (1996).

    Article  CAS  PubMed  Google Scholar 

  13. Curtis, P. D. & Brun, Y. V. Getting in the loop: regulation of development in Caulobacter crescentus. Microbiol. Mol. Biol. Rev. 74, 13–41 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Norman, T. M., Lord, N. D., Paulsson, J. & Losick, R. Memory and modularity in cell-fate decision making. Nature 503, 481–486 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Russell, J. R., Cabeen, M. T., Wiggins, P. A., Paulsson, J. & Losick, R. Noise in a phosphorelay drives stochastic entry into sporulation in Bacillus subtilis. EMBO J. 36, 2856–2869 (2017). e201796988.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kearns, D. B. A field guide to bacterial swarming motility. Nat. Rev. Microbiol. 8, 634–644 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Grau, R. R. et al. A duo of potassium-responsive histidine kinases govern the multicellular destiny of Bacillus subtilis. mBio 6, e00581 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Cairns, L. S., Hobley, L. & Stanley-Wall, N. R. Biofilm formation by Bacillus subtilis: new insights into regulatory strategies and assembly mechanisms. Mol. Microbiol. 93, 587–598 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Mielich-Süss, B. & Lopez, D. Molecular mechanisms involved in Bacillus subtilis biofilm formation. Environ. Microbiol. 17, 555–565 (2015).

    Article  PubMed  Google Scholar 

  20. van Gestel, J., Vlamakis, H. & Kolter, R. From cell differentiation to cell collectives: Bacillus subtilis uses division of labor to migrate. PLoS Biol. 13, e1002141 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  21. Beauregard, P. B., Chai, Y., Vlamakis, H., Losick, R. & Kolter, R. Bacillus subtilis biofilm induction by plant polysaccharides. Proc. Natl Acad. Sci. USA 110, E1621–E1630 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Higgins, D. & Dworkin, J. Recent progress in Bacillus subtilis sporulation. FEMS Microbiol. Rev. 36, 131–148 (2012).

    Article  CAS  PubMed  Google Scholar 

  23. Setlow, P. Spore germination. Curr. Opin. Microbiol. 6, 550–556 (2003).

    Article  CAS  PubMed  Google Scholar 

  24. Smits, W. K., Kuipers, O. P. & Veening, J. W. Phenotypic variation in bacteria: the role of feedback regulation. Nat. Rev. Microbiol. 4, 259–271 (2006).

    Article  CAS  PubMed  Google Scholar 

  25. Bonneau, R. et al. The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo. Genome Biol. 7, R36 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Aguilar, C., Vlamakis, H., Losick, R. & Kolter, R. Thinking about Bacillus subtilis as a multicellular organism. Curr. Opin. Microbiol. 10, 638–643 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Veening, J. W., Smits, W. K. & Kuipers, O. P. Bistability, epigenetics, and bet-hedging in bacteria. Annu. Rev. Microbiol. 62, 193–210 (2008).

    Article  CAS  PubMed  Google Scholar 

  28. Sierro, N., Makita, Y., de Hoon, M. & Nakai, K. DBTBS: a database of transcriptional regulation in Bacillus subtilis containing upstream intergenic conservation information. Nucleic Acids Res. 36, D93–D96 (2008).

    Article  CAS  PubMed  Google Scholar 

  29. Fadda, A. et al. Inferring the transcriptional network of Bacillus subtilis. Mol. Biosyst. 5, 1840–1852 (2009).

    Article  CAS  PubMed  Google Scholar 

  30. Kobayashi, K. Gradual activation of the response regulator DegU controls serial expression of genes for flagellum formation and biofilm formation in Bacillus subtilis. Mol. Microbiol. 66, 395–409 (2007).

    Article  CAS  PubMed  Google Scholar 

  31. Lopez, D. & Kolter, R. Extracellular signals that define distinct and coexisting cell fates in Bacillus subtilis. FEMS Microbiol. Rev. 34, 134–149 (2010).

    Article  CAS  PubMed  Google Scholar 

  32. Freyre-González, J. A. et al. Lessons from the modular organization of the transcriptional regulatory network of Bacillus subtilis. BMC Syst. Biol. 7, 127 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Leyn, S. A. et al. Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis. J. Bacteriol. 195, 2463–2473 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Arrieta‐Ortiz, M. L. et al. An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network. Mol. Syst. Biol. 11, 839 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Michna, R. H., Zhu, B., Mäder, U. & Stülke, J. SubtiWiki 2.0—an integrated database for the model organism Bacillus subtilis. Nucleic Acids Res. 44, D654–D662 (2016).

    Article  CAS  PubMed  Google Scholar 

  36. Lee, T. I. et al. Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 298, 799–804 (2002).

    Article  CAS  PubMed  Google Scholar 

  37. Sorrells, T. R. & Johnson, A. D. Making sense of transcription networks. Cell 161, 714–723 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Fang, X. et al. Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities. Proc. Natl Acad. Sci. USA 114, 10286–10291 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Santos-Zavaleta, A. et al. RegulonDB v 10.5: tackling challenges to unify classic and high throughput knowledge of gene regulation in E. coli K-12. Nucleic Acids Res. 47, D212–D220 (2019).

    Article  CAS  PubMed  Google Scholar 

  40. Haldenwang, W. G. The sigma factors of Bacillus subtilis. Microbiol. Rev. 59, 1–30 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Gruber, T. M. & Gross, C. A. Multiple sigma subunits and the partitioning of bacterial transcription space. Annu. Rev. Microbiol. 57, 441–466 (2003).

    Article  CAS  PubMed  Google Scholar 

  42. Nicolas, P. et al. Condition-dependent transcriptome reveals high-level regulatory architecture in Bacillus subtilis. Science 335, 1103–1106 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. Feklístov, A., Sharon, B. D., Darst, S. A. & Gross, C. A. Bacterial sigma factors: a historical, structural, and genomic perspective. Annu. Rev. Microbiol. 68, 357–376 (2014).

    Article  PubMed  CAS  Google Scholar 

  44. Veening, J. W. et al. Bet-hedging and epigenetic inheritance in bacterial cell development. Proc. Natl Acad. Sci. USA 105, 4393–4398 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Marlow, V. L. et al. The prevalence and origin of exoprotease-producing cells in the Bacillus subtilis biofilm. Microbiology 160, 56–66 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Vilain, S., Luo, Y., Hildreth, M. B. & Brozel, V. S. Analysis of the life cycle of the soil saprophyte Bacillus cereus in liquid soil extract and in soil. Appl. Environ. Microbiol. 72, 4970–4977 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Otto, A. et al. Systems-wide temporal proteomic profiling in glucose-starved Bacillus subtilis. Nat. Commun. 1, 137 (2010).

    Article  PubMed  CAS  Google Scholar 

  48. Omony, J., de Jong, A., Krawczyk, A. O., Eijlander, R. T. & Kuipers, O. P. Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model. Microb. Genom. 4, 1–13 (2018).

    CAS  Google Scholar 

  49. Bendall, S. C. et al. Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157, 714–725 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Anavy, L. et al. BLIND ordering of large-scale transcriptomic developmental timecourses. Development 141, 1161–1166 (2014).

    Article  CAS  PubMed  Google Scholar 

  51. Haghverdi, L., Büttner, M., Wolf, F. A., Buettner, F. & Theis, F. J. Diffusion pseudotime robustly reconstructs lineage branching. Nat. Methods 13, 845–848 (2016).

    Article  CAS  PubMed  Google Scholar 

  52. Levin, M. et al. The mid-developmental transition and the evolution of animal body plans. Nature 531, 637–641 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Setty, M. et al. Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat. Biotechnol. 34, 637–645 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Marioni, J. C. & Arendt, D. How single-cell genomics is changing evolutionary and developmental biology. Annu. Rev. Cell Dev. Biol. 33, 537–553 (2017).

    Article  CAS  PubMed  Google Scholar 

  55. Garrity, L. F. & Ordal, G. W. Chemotaxis in Bacillus subtilis: how bacteria monitor environmental signals. Pharmacol. Ther. 68, 87–104 (1995).

    Article  CAS  PubMed  Google Scholar 

  56. McKenney, P. T., Driks, A. & Eichenberger, P. The Bacillus subtilis endospore: assembly and functions of the multilayered coat. Nat. Rev. Microbiol. 11, 33–44 (2013).

    Article  CAS  PubMed  Google Scholar 

  57. Vlamakis, H., Chai, Y., Beauregard, P., Losick, R. & Kolter, R. Sticking together: building a biofilm the Bacillus subtilis way. Nat. Rev. Microbiol. 11, 157–168 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Kramer, M. A. Nonlinear principal component analysis using autoassociative neural networks. AIChE J. 37, 233–243 (1991).

    Article  CAS  Google Scholar 

  59. Scholz, M., Fraunholz, M. & Selbig, J. in Principal Manifolds for Data Visualization and Dimension Reduction 44–67 (Springer, 2008).

  60. Scholz, M. Validation of nonlinear PCA. Neural Process. Lett. 36, 21–30 (2012).

    Article  Google Scholar 

  61. Verhamme, D. T., Kiley, T. B. & Stanley-Wall, N. R. DegU co-ordinates multicellular behaviour exhibited by Bacillus subtilis. Mol. Microbiol. 65, 554–568 (2007).

    Article  CAS  PubMed  Google Scholar 

  62. Fujita, M., González-Pastor, J. E. & Losick, R. High- and low-threshold genes in the Spo0A regulon of Bacillus subtilis. J. Bacteriol. 187, 1357–1368 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Verhamme, D. T., Murray, E. J. & Stanley-Wall, N. R. DegU and Spo0A jointly control transcription of two loci required for complex colony development by Bacillus subtilis. J. Bacteriol. 191, 100–108 (2009).

    Article  CAS  PubMed  Google Scholar 

  64. Branda, S. S., González-Pastor, J. E., Ben-Yehuda, S., Losick, R. & Kolter, R. Fruiting body formation by Bacillus subtilis. Proc. Natl Acad. Sci. USA 98, 11621–11626 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Branda, S. S., Chu, F., Kearns, D. B., Losick, R. & Kolter, R. A major protein component of the Bacillus subtilis biofilm matrix. Mol. Microbiol. 59, 1229–1238 (2006).

    Article  CAS  PubMed  Google Scholar 

  66. Galperin, M. Y. Genome diversity of spore-forming firmicutes. Microbiol. Spectr. 1, 1–15 (2013).

    Article  Google Scholar 

  67. Kunst, F. et al. The complete genome sequence of the Gram-positive bacterium Bacillus subtilis. Nature 390, 249–256 (1997).

    Article  CAS  PubMed  Google Scholar 

  68. Barbe, V. et al. From a consortium sequence to a unified sequence: the Bacillus subtilis 168 reference genome a decade later. Microbiology 155, 1758–1775 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. de Hoon, M. J. L., Eichenberger, P. & Vitkup, D. Hierarchical evolution of the bacterial sporulation network. Curr. Biol. 20, R735–R745 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Wolf, Y. I. & Koonin, E. V. A tight link between orthologs and bidirectional best hits in bacterial and archaeal genomes. Genome Biol. Evol. 4, 1286–1294 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Gabaldón, T. & Koonin, E. V. Functional and evolutionary implications of gene orthology. Nat. Rev. Genet. 14, 360–366 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  72. Galperin, M. Y. et al. Genomic determinants of sporulation in Bacilli and Clostridia: towards the minimal set of sporulation-specific genes. Environ. Microbiol. 14, 2870–2890 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Abecasis, A. B. et al. A genomic signature and the identification of new sporulation genes. J. Bacteriol. 195, 2101–2115 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  75. Makarova, K. et al. Comparative genomics of the lactic acid bacteria. Proc. Natl Acad. Sci. USA 103, 15611–15616 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  76. Wolf, Y. I. & Koonin, E. V. Genome reduction as the dominant mode of evolution. BioEssays 35, 829–837 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Albalat, R. & Cañestro, C. Evolution by gene loss. Nat. Rev. Genet. 17, 379–391 (2016).

    Article  CAS  PubMed  Google Scholar 

  78. Duar, R. M. et al. Lifestyles in transition: evolution and natural history of the genus Lactobacillus. FEMS Microbiol. Rev. 41, S27–S48 (2017).

    Article  PubMed  Google Scholar 

  79. Sokurenko, E. V., Hasty, D. L. & Dykhuizen, D. E. Pathoadaptive mutations: gene loss and variation in bacterial pathogens. Trends Microbiol. 7, 191–195 (1999).

    Article  CAS  PubMed  Google Scholar 

  80. Maughan, H. et al. The population genetics of phenotypic deterioration in experimental populations of Bacillus subtilis. Evol. Int. J. Org. Evol. 60, 686–695 (2006).

    Article  Google Scholar 

  81. Maughan, H., Masel, J., Birky, C. W. & Nicholson, W. L. The roles of mutation accumulation and selection in loss of sporulation in experimental populations of Bacillus subtilis. Genetics 177, 937–948 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Maughan, H., Birky, C. W. & Nicholson, W. L. Transcriptome divergence and the loss of plasticity in Bacillus subtilis after 6,000 generations of evolution under relaxed selection for sporulation. J. Bacteriol. 191, 428–433 (2009).

    Article  CAS  PubMed  Google Scholar 

  83. Brown, C. T. et al. Whole-genome sequencing and phenotypic analysis of Bacillus subtilis mutants following evolution under conditions of relaxed selection for sporulation. Appl. Environ. Microbiol. 77, 6867–6877 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Velicer, G. J. & Yu, Y. T. N. Evolution of novel cooperative swarming in the bacterium Myxococcus xanthus. Nature 425, 75–78 (2003).

    Article  CAS  PubMed  Google Scholar 

  85. van Ditmarsch, D. et al. Convergent evolution of hyperswarming leads to impaired biofilm formation in pathogenic bacteria. Cell Rep. 4, 697–708 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  86. Song, C., Kidarsa, T. A., van de Mortel, J. E., Loper, J. E. & Raaijmakers, J. M. Living on the edge: emergence of spontaneous gac mutations in Pseudomonas protegens during swarming motility. Environ. Microbiol. 18, 3453–3465 (2016).

    Article  CAS  PubMed  Google Scholar 

  87. Friedlander, T., Mayo, A. E., Tlusty, T. & Alon, U. Evolution of bow-tie architectures in biology. PLoS Comput. Biol. 11, e1004055 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Yan, J. et al. Bow-tie signaling in c-di-GMP: machine learning in a simple biochemical network. PLoS Comput. Biol. 13, e1005677 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Kitano, H. Biological robustness. Nat. Rev. Genet. 5, 826–837 (2004).

    Article  CAS  PubMed  Google Scholar 

  90. Bonner, J. T. The Evolution of Complexity by Means of Natural Selection (Princeton Univ. Press, 1988).

  91. Kashtan, N. & Alon, U. Spontaneous evolution of modularity and network motifs. Proc. Natl Acad. Sci. USA 102, 13773–13778 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Wagner, G. P., Pavlicev, M. & Cheverud, J. M. The road to modularity. Nat. Rev. Genet. 8, 921–931 (2007).

    Article  CAS  PubMed  Google Scholar 

  93. Espinosa-Soto, C. & Wagner, A. Specialization can drive the evolution of modularity. PLoS Comput. Biol. 6, e1000719 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  94. Lande, R. Evolution of phenotypic plasticity and environmental tolerance of a labile quantitative character in a fluctuating environment. J. Evol. Biol. 27, 866–875 (2014).

    Article  CAS  PubMed  Google Scholar 

  95. Huang, B. & Mackem, S. Evolutionary developmental biology: use it or lose it. Nature 511, 34–35 (2014).

    Article  CAS  PubMed  Google Scholar 

  96. Siljestam, M. & Östman, Ö. The combined effects of temporal autocorrelation and the costs of plasticity on the evolution of plasticity. J. Evol. Biol. 30, 1361–1371 (2017).

    Article  CAS  PubMed  Google Scholar 

  97. Mandic-Mulec, I., Stefanic, P. & van Elsas, J. D. Ecology of Bacillaceae. Microbiol. Spectr. 3, TBS-0017–TBS-2013 (2015).

    Article  CAS  Google Scholar 

  98. Parter, M., Kashtan, N. & Alon, U. Facilitated variation: how evolution learns from past environments to generalize to new environments. PLoS Comput. Biol. 4, e1000206 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  99. Riedl, R. A systems-analytical approach to macro-evolutionary phenomena. Q. Rev. Biol. 52, 351–370 (1977).

    Article  CAS  PubMed  Google Scholar 

  100. Wagner, G. P. & Altenberg, L. Perspective: complex adaptations and the evolution of evolvability. Evolution 50, 967–976 (1996).

    Article  PubMed  Google Scholar 

  101. Schluter, D. Adaptive radiation along genetic lines of least resistance. Evolution 50, 1766–1774 (1996).

    Article  PubMed  Google Scholar 

  102. Watson, R. A. & Szathmáry, E. How can evolution learn? Trends Ecol. Evol. 31, 147–157 (2016).

    Article  PubMed  Google Scholar 

  103. Uller, T., Moczek, A. P., Watson, R. A., Brakefield, P. M. & Laland, K. N. Developmental bias and evolution: a regulatory network perspective. Genetics 209, 949–966 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Mead, D. A. et al. Complete genome sequence of Paenibacillus strain Y4.12MC10, a novel Paenibacillus lautus strain isolated from Obsidian hot spring in Yellowstone National Park. Stand. Genom. Sci. 6, 381–400 (2012).

    Article  CAS  Google Scholar 

  105. van Nimwegen, E. in Power Laws, Scale-Free Networks and Genome Biology 236–253 (Springer, 2006).

  106. Cordero, O. X. & Hogeweg, P. Large changes in regulome size herald the main prokaryotic lineages. Trends Genet. 23, 488–493 (2007).

    Article  CAS  PubMed  Google Scholar 

  107. Barka, E. A. et al. Taxonomy, physiology, and natural products of Actinobacteria. Microbiol. Mol. Biol. Rev. 80, 1–43 (2016).

    Article  PubMed  Google Scholar 

  108. Fall, R., Kearns, D. B. & Nguyen, T. A defined medium to investigate sliding motility in a Bacillus subtilis flagella-less mutant. BMC Microbiol. 6, 31 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  109. Scholz, M. & Fraunholz, M. J. A computational model of gene expression reveals early transcriptional events at the subtelomeric regions of the malaria parasite, Plasmodium falciparum. Genome Biol. 9, R88 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  110. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    Article  CAS  PubMed  Google Scholar 

  111. Wu, D. et al. A phylogeny-driven genomic encyclopaedia of Bacteria and Archaea. Nature 462, 1056–1060 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Wu, D., Jospin, G. & Eisen, J. A. Systematic identification of gene families for use as ‘markers’ for phylogenetic and phylogeny-driven ecological studies of Bacteria and Archaea and their major subgroups. PLoS ONE 8, e77033 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Eddy, S. R. Hidden markov models. Curr. Opin. Struct. Biol. 6, 361–365 (1996).

    Article  CAS  PubMed  Google Scholar 

  114. Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 39, W29–W37 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Castresana, J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol. Biol. Evol. 17, 540–552 (2000).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Katoh, K., Misawa, K., Kuma, K. & Miyata, T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res. 30, 3059–3066 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. 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 

  120. Löytynoja, A. & Goldman, N. An algorithm for progressive multiple alignment of sequences with insertions. Proc. Natl Acad. Sci. USA 102, 10557–10562 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  121. Löytynoja, A. & Goldman, N. Phylogeny-aware gap placement prevents errors in sequence alignment and evolutionary analysis. Science 320, 1632–1635 (2008).

    Article  PubMed  CAS  Google Scholar 

  122. Talavera, G. & Castresana, J. Improvement of phylogenies after removing divergent and ambiguously aligned blocks from protein sequence alignments. Syst. Biol. 56, 564–577 (2007).

    Article  CAS  PubMed  Google Scholar 

  123. 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  CAS  Google Scholar 

  124. Huerta-Cepas, J., Dopazo, J. & Gabaldón, T. ETE: a python environment for tree exploration. BMC Bioinformatics 11, 24 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  125. Huerta-Cepas, J., Serra, F. & Bork, P. ETE 3: reconstruction, analysis, and visualization of phylogenomic data. Mol. Biol. Evol. 33, 1635–1638 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Cock, P. J. A. et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25, 1422–1423 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Popescu, A. A., Huber, K. T. & Paradis, E. Ape 3.0: new tools for distance-based phylogenetics and evolutionary analysis in R. Bioinformatics 28, 1536–1537 (2012).

    Article  CAS  PubMed  Google Scholar 

  128. Revell, L. J. Phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2011).

    Article  Google Scholar 

  129. Pateiro-López, B. & Rodrıguez-Casal, A. Generalizing the convex hull of a sample: the R package alphahull. J. Stat. Softw. 34, 1–28 (2010).

    Article  Google Scholar 

  130. VanDerWal, J., Falconi, L., Januchowski, S., Shoo, L. & Storlie, C. SDMTools: tools for processing data associated with species distribution modelling exercises. R version 1 (2014); https://cran.r-project.org/web/packages/SDMTools/index.html

  131. Adler, D. et al. Rgl: 3D visualization using OpenGL. R version 095 (2016); https://cran.r-project.org/web/packages/rgl/index.html

  132. Ross, K. F. A. & Billing, E. The water and solid content of living bacterial spores and vegetative cells as indicated by refractive index measurements. Microbiology 16, 418–425 (1957).

    CAS  Google Scholar 

  133. Lee, J. A. et al. MIFlowCyt: the minimum information about a flow cytometry experiment. Cytometry A 73, 926–930 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  134. Spidlen, J., Breuer, K., Rosenberg, C., Kotecha, N. & Brinkman, R. R. FlowRepository: a resource of annotated flow cytometry datasets associated with peer-reviewed publications. Cytometry A 81, 727–731 (2012).

    Article  PubMed  Google Scholar 

  135. Barrick, J. E. et al. Identifying structural variation in haploid microbial genomes from short-read resequencing data using breseq. BMC Genom. 15, 1039 (2014).

    Article  CAS  Google Scholar 

  136. Deatherage, D. E. & Barrick, J. E. in Engineering and Analyzing Multicellular Systems: Methods and Protocols (eds Sun, L. & Shou, W.) 165–188 (Springer, 2014).

  137. Zhu, B. & Stülke, J. SubtiWiki in 2018: from genes and proteins to functional network annotation of the model organism Bacillus subtilis. Nucleic Acids Res. 46, D743–D748 (2018).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

J.v.G. thanks M. Olombrada, M. Toll-Riera, N. Lyons and J. Payne for discussions. We thank R. Kolter for providing strains. J.v.G. thanks the Wierenga Rengerink PhD Prize from the University of Groningen, Rubicon Fellowship (No. 2015-2) from the Netherlands Organisation for Scientific Research (NWO), EMBO long-term fellowship (ALTF, No. 1101-2016), Marie Sklodowska-Curie Individual Fellowship (No. 742235), Swiss Federal Institute of Aquatic Science and Technology (Eawag) and ETH Zürich for financial support. A.W. acknowledges support by ERC Advanced Grant No. 739874, Swiss National Science Foundation grant No. 31003A_172887 as well as by the University Priority Research Program in Evolutionary Biology at the University of Zurich. M.A. was supported by Swiss National Science Foundation grant No. 31003A_169978, Eawag and ETH Zürich.

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J.v.G. conceived the project. All authors were involved in designing the project, planning the research and interpreting the results. J.v.G. conducted the research, created the figures and wrote a first version of the manuscript. M.A. and A.W. contributed to subsequent versions of the manuscript.

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Correspondence to Jordi van Gestel or Andreas Wagner.

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Supplementary information

Supplementary Information

Supplementary Text 1–4, Supplementary Figs. 1–34, Supplementary Tables 4, 7–11.

Reporting Summary

Supplementary Table 1

Reconstructions of global transcription network of Bacillus subtilis

Supplementary Table 2

List of expression profiles included from study of Nicolas and colleagues

Supplementary Table 3

Gene regulatory network underlying lifestyle switches

Supplementary Table 5

List of genomes included in phylogenetic analysis

Supplementary Table 6

Bi-directional best BLAST hits for all genomes with respect to reference genome

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van Gestel, J., Ackermann, M. & Wagner, A. Microbial life cycles link global modularity in regulation to mosaic evolution. Nat Ecol Evol 3, 1184–1196 (2019). https://doi.org/10.1038/s41559-019-0939-6

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