Bacterial interspecies interactions modulate pH-mediated antibiotic tolerance

  1. Andrés Aranda-Diaz
  2. Benjamin Obadia
  3. Ren Dodge
  4. Tani Thomsen
  5. Zachary F Hallberg
  6. Zehra Tüzün Güvener
  7. William B Ludington  Is a corresponding author
  8. Kerwyn Casey Huang  Is a corresponding author
  1. Stanford University, United States
  2. University of California, Berkeley, United States
  3. Carnegie Institute, United States

Abstract

Predicting antibiotic efficacy within microbial communities remains highly challenging. Interspecies interactions can impact antibiotic activity through many mechanisms, including alterations to bacterial physiology. Here, we studied synthetic communities constructed from the core members of the fruit fly gut microbiota. Co-culturing of Lactobacillus plantarum with Acetobacter species altered its tolerance to the transcriptional inhibitor rifampin. By measuring key metabolites and environmental pH, we determined that Acetobacter species counter the acidification driven by L. plantarum production of lactate. Shifts in pH were sufficient to modulate L. plantarum tolerance to rifampin and the translational inhibitor erythromycin. A reduction in lag time exiting stationary phase was linked to L. plantarum tolerance to rifampicin, opposite to a previously identified mode of tolerance to ampicillin in E. coli. This mechanistic understanding of the coupling among interspecies interactions, environmental pH, and antibiotic tolerance enables future predictions of growth and the effects of antibiotics in more complex communities.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files, excepting sequencing data that have been deposited in the sequence read archive of NCBI under accession number PRJNA530819 (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA530819/).

The following data sets were generated

Article and author information

Author details

  1. Andrés Aranda-Diaz

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0566-4901
  2. Benjamin Obadia

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3286-3236
  3. Ren Dodge

    Department of Embryology, Carnegie Institute, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Tani Thomsen

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Zachary F Hallberg

    Department of Chemistry, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Zehra Tüzün Güvener

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. William B Ludington

    Department of Embryology, Carnegie Institute, Baltimore, United States
    For correspondence
    ludington@carnegiescience.edu
    Competing interests
    The authors declare that no competing interests exist.
  8. Kerwyn Casey Huang

    Department of Bioengineering, Stanford University, Stanford, United States
    For correspondence
    kchuang@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8043-8138

Funding

National Institutes of Health (DP2OD006466)

  • Kerwyn Casey Huang

National Science Foundation (MCB-1149328)

  • Kerwyn Casey Huang

Allen Center for Systems Modeling of Infection (N/A)

  • Kerwyn Casey Huang

National Institutes of Health (DP5OD017851)

  • William B Ludington

Howard Hughes Medical Institute (International Student Research Fellowship)

  • Andrés Aranda-Diaz

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

Reviewing Editor

  1. Wenying Shou, Fred Hutchinson Cancer Research Center, United States

Publication history

  1. Received: August 30, 2019
  2. Accepted: January 28, 2020
  3. Accepted Manuscript published: January 29, 2020 (version 1)
  4. Version of Record published: February 17, 2020 (version 2)

Copyright

© 2020, Aranda-Diaz 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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  1. Andrés Aranda-Diaz
  2. Benjamin Obadia
  3. Ren Dodge
  4. Tani Thomsen
  5. Zachary F Hallberg
  6. Zehra Tüzün Güvener
  7. William B Ludington
  8. Kerwyn Casey Huang
(2020)
Bacterial interspecies interactions modulate pH-mediated antibiotic tolerance
eLife 9:e51493.
https://doi.org/10.7554/eLife.51493

Further reading

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    The global spread of antibiotic resistance could be due to a number of factors, and not just the overuse of antibiotics in agriculture and medicine as previously thought.

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    How the ecological process of community assembly interacts with intra-species diversity and evolutionary change is a longstanding question. Two contrasting hypotheses have been proposed: Diversity Begets Diversity (DBD), in which taxa tend to become more diverse in already diverse communities, and Ecological Controls (EC), in which higher community diversity impedes diversification. Previously, using 16S rRNA gene amplicon data across a range of microbiomes, we showed a generally positive relationship between taxa diversity and community diversity at higher taxonomic levels, consistent with the predictions of DBD (Madi et al., 2020). However, this positive 'diversity slope' plateaus at high levels of community diversity. Here we show that this general pattern holds at much finer genetic resolution, by analyzing intra-species strain and nucleotide variation in static and temporally sampled metagenomes from the human gut microbiome. Consistent with DBD, both intra-species polymorphism and strain number were positively correlated with community Shannon diversity. Shannon diversity is also predictive of increases in polymorphism over time scales up to ~4-6 months, after which the diversity slope flattens and becomes negative – consistent with DBD eventually giving way to EC. Finally, we show that higher community diversity predicts gene loss at a future time point. This observation is broadly consistent with the Black Queen Hypothesis, which posits that genes with functions provided by the community are less likely to be retained in a focal species' genome. Together, our results show that a mixture of DBD, EC, and Black Queen may operate simultaneously in the human gut microbiome, adding to a growing body of evidence that these eco-evolutionary processes are key drivers of biodiversity and ecosystem function.