1. Genomics and Evolutionary Biology
  2. Microbiology and Infectious Disease
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Stochastic variation in the initial phase of bacterial infection predicts the probability of survival in D. melanogaster

  1. David Duneau Is a corresponding author
  2. Jean-Baptiste Ferdy
  3. Jonathan Revah
  4. Hannah Kondolf
  5. Gerardo A Ortiz
  6. Brian P Lazzaro
  7. Nicolas Buchon Is a corresponding author
  1. Cornell University, United States
  2. University of Toulouse 3, France
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Cite as: eLife 2017;6:e28298 doi: 10.7554/eLife.28298

Abstract

A central problem in infection biology is understanding why two individuals exposed to identical infections have different outcomes. We have developed an experimental model where genetically identical, co-housed Drosophila given identical systemic infections experience different outcomes, with some individuals succumbing to acute infection while others control the pathogen as an asymptomatic persistent infection. We found that differences in bacterial burden at the time of death did not explain the two outcomes of infection. Inter-individual variation in survival stems from variation in within-host bacterial growth, which is determined by the immune response. We developed a model that captures bacterial growth dynamics and identifies key factors that predict the infection outcome: the rate of bacterial proliferation and the time required for the host to establish an effective immunological control. Our results provide a framework for studying the individual host-pathogen parameters governing the progression of infection and lead ultimately to life or death.

Article and author information

Author details

  1. David Duneau

    Department of Entomology, Cornell University, Ithaca, United States
    For correspondence
    david.duneau@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon 0000-0002-8323-1511
  2. Jean-Baptiste Ferdy

    Laboratoire Évolution and Diversité Biologique, University of Toulouse 3, Toulouse, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Jonathan Revah

    Department of Entomology, Cornell University, Ithaca, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Hannah Kondolf

    Department of Entomology, Cornell University, Ithaca, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Gerardo A Ortiz

    Department of Entomology, Cornell University, Ithaca, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Brian P Lazzaro

    Department of Entomology, Cornell University, Ithaca, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Nicolas Buchon

    Department of Entomology, Cornell University, Ithaca, United States
    For correspondence
    nicolas.buchon@cornell.edu
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Science Foundation (1354421)

  • Nicolas Buchon

National Institutes of Health (RO1 AI083932)

  • Brian P Lazzaro

New York State Department of Health (Empire state stem cell fund C029542)

  • Nicolas Buchon

Swiss National Foundation (Fellowship from P300P3_147874)

  • David Duneau

Agence Nationale de la Recherche (French Laboratory of Excellence ANR-11-IDEX-0002-02)

  • David Duneau

Agence Nationale de la Recherche (French Laboratory of Excellence project ANR-10-LABX-41)

  • David Duneau

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Bruno Lemaître, Reviewing Editor, Ecole Polytechnique Fédérale de Lausanne, Switzerland

Publication history

  1. Received: May 2, 2017
  2. Accepted: October 11, 2017
  3. Accepted Manuscript published: October 12, 2017 (version 1)

Copyright

© 2017, Duneau et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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