Letter

Exploiting rRNA operon copy number to investigate bacterial reproductive strategies

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Accepted:
Published online:

Abstract

The potential for rapid reproduction is a hallmark of microbial life, but microbes in nature must also survive and compete when growth is constrained by resource availability. Successful reproduction requires different strategies when resources are scarce and when they are abundant1,2, but a systematic framework for predicting these reproductive strategies in bacteria has not been available. Here, we show that the number of ribosomal RNA operons (rrn) in bacterial genomes predicts two important components of reproduction—growth rate and growth efficiency—which are favoured under contrasting regimes of resource availability3,4. We find that the maximum reproductive rate of bacteria doubles with a doubling of rrn copy number, and the efficiency of carbon use is inversely related to maximal growth rate and rrn copy number. We also identify a feasible explanation for these patterns: the rate and yield of protein synthesis mirror the overall pattern in maximum growth rate and growth efficiency. Furthermore, comparative analysis of genomes from 1,167 bacterial species reveals that rrn copy number predicts traits associated with resource availability, including chemotaxis and genome streamlining. Genome-wide patterns of orthologous gene content covary with rrn copy number, suggesting convergent evolution in response to resource availability. Our findings imply that basic cellular processes adapt in contrasting ways to long-term differences in resource availability. They also establish a basis for predicting changes in bacterial community composition in response to resource perturbations using rrn copy number measurements5 or inferences6,7.

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Author information

Author notes

    • Benjamin R. K. Roller

    Present address: Center for Adaptation to a Changing Environment, ETH Zürich, 8092 Zürich, Switzerland.

Affiliations

  1. Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA

    • Benjamin R. K. Roller
    • , Steven F. Stoddard
    •  & Thomas M. Schmidt
  2. Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan 48824, USA

    • Benjamin R. K. Roller
  3. Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan 48109, USA

    • Thomas M. Schmidt
  4. Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA

    • Thomas M. Schmidt

Authors

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Contributions

B.R.K.R. and T.M.S. conceived the study, interpreted the results and wrote the paper. B.R.K.R. performed the experiments, phylogenetic inferences and statistical analyses. S.F.S. provided custom relational databases, queries and Perl scripting to integrate the rrnDB, KEGG and NCBI taxonomy for genomic analyses.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Thomas M. Schmidt.

Supplementary information

PDF files

  1. 1.

    Supplementary information

    Supplementary Tables 1, 2, and 5, legends for Supplementary Tables 3 and 4, Supplementary Figures 1–5, Supplementary References

Excel files

  1. 1.

    Supplementary Table 3

    The 100 largest loadings on the first six pPCA axes in the separate analyses of modules and orthologues datasets.

  2. 2.

    Supplementary Table 4

    Bacteria included in this study.