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Edited by Luca Peliti, Santa Marinella Research Institute, Rome, Italy, and accepted by Editorial Board Member Curtis G. Callan, Jr. June 15, 2018 (received for review February 28, 2018)
Significance
Complex communities of microorganisms are important ecological forces and phages are integral components of microbial populations. Among the many bacterial defense mechanisms against phages, CRISPR-Cas is unique in its ability to learn from past infections by storing pieces of phage DNA (called spacers) in its own genome to neutralize future infections. Our work shows that the rank abundance distribution of spacers across the whole bacterial population, which is readily accessed using genomic sequencing, may provide a phenomenological observable that reflects important structural aspects of bacterial populations. This study lays out a path toward a phenomenological framework for understanding microbial dynamics and may provide insights into complex and diverse natural populations where microscopic modeling is plagued by overparameterization and overfitting.
Abstract
Features of the CRISPR-Cas system, in which bacteria integrate small segments of phage genome (spacers) into their DNA to neutralize future attacks, suggest that its effect is not limited to individual bacteria but may control the fate and structure of whole populations. Emphasizing the population-level impact of the CRISPR-Cas system, recent experiments show that some bacteria regulate CRISPR-associated genes via the quorum sensing (QS) pathway. Here we present a model that shows that from the highly stochastic dynamics of individual spacers under QS control emerges a rank-abundance distribution of spacers that is time invariant, a surprising prediction that we test with dynamic spacer-tracking data from literature. This distribution depends on the state of the competing phage–bacteria population, which due to QS-based regulation may coexist in multiple stable states that vary significantly in their phage-to-bacterium ratio, a widely used ecological measure to characterize microbial systems.
Footnotes
- ↵1To whom correspondence should be addressed. Email: goyal{at}physics.utoronto.ca.
Author contributions: M.B.-F., D.S., and S.G. designed research; M.B.-F. and D.S. performed research; M.B.-F. analyzed data; M.B.-F. and S.G. wrote the paper; and D.S. wrote simulations.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission. L.P. is a guest editor invited by the Editorial Board.
Data deposition: The processed data and simulation code have been deposited in GitHub, https://github.com/mbonsma/CRISPR-immunity.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1802887115/-/DCSupplemental.
Published under the PNAS license.
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How adaptive immunity constrains the composition and fate of large bacterial populations
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