Microbial life cycles link global modularity in regulation to mosaic evolution


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.

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.


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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.

Author information

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.

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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