The onion model, a simple neutral model for the evolution of diversity in bacterial biofilms

Authors

  • J. M. EASTMAN,

    1. Department of Biological Sciences, University of Idaho, Moscow, ID, USA
    2. Initiative for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA
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  • L. J. HARMON,

    1. Department of Biological Sciences, University of Idaho, Moscow, ID, USA
    2. Initiative for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA
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  • H.-J. LA,

    1. Department of Biological Sciences, University of Idaho, Moscow, ID, USA
    2. Initiative for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA
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  • P. JOYCE,

    1. Initiative for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA
    2. Departments of Statistics and Mathematics, University of Idaho, Moscow, ID, USA
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  • L. J. FORNEY

    1. Department of Biological Sciences, University of Idaho, Moscow, ID, USA
    2. Initiative for Bioinformatics and Evolutionary Studies (IBEST), University of Idaho, Moscow, ID, USA
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Larry J. Forney, Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA.
Tel.: +1 208 885 6011; fax: +1 208 885 6280; e-mail: lforney@uidaho.edu

Abstract

Bacterial biofilms are particularly resistant to a wide variety of antimicrobial compounds. Their persistence in the face of antibiotic therapies causes significant problems in the treatment of infectious diseases. Seldom have evolutionary processes like genetic drift and mutation been invoked to explain how resistance to antibiotics emerges in biofilms, and we lack a simple and tractable model for the genetic and phenotypic diversification that occurs in bacterial biofilms. Here, we introduce the ‘onion model’, a simple neutral evolutionary model for phenotypic diversification in biofilms. We explore its properties and show that the model produces patterns of diversity that are qualitatively similar to observed patterns of phenotypic diversity in biofilms. We suggest that models like our onion model, which explicitly invoke evolutionary process, are key to understanding biofilm resistance to bactericidal and bacteriostatic agents. Elevated phenotypic variance provides an insurance effect that increases the likelihood that some proportion of the population will be resistant to imposed selective agents and may thus enhance persistence of the biofilm. Accounting for evolutionary change in biofilms will improve our ability to understand and counter diseases that are caused by biofilm persistence.

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