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Antibiotics as a selective driver for conjugation dynamics

Nature Microbiology volume 1, Article number: 16044 (2016) Cite this article

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Abstract

It is generally assumed that antibiotics can promote horizontal gene transfer. However, because of a variety of confounding factors that complicate the interpretation of previous studies, the mechanisms by which antibiotics modulate horizontal gene transfer remain poorly understood. In particular, it is unclear whether antibiotics directly regulate the efficiency of horizontal gene transfer, serve as a selection force to modulate population dynamics after such gene transfer has occurred, or both. Here, we address this question by quantifying conjugation dynamics in the presence and absence of antibiotic-mediated selection. Surprisingly, we find that sublethal concentrations of antibiotics from the most widely used classes do not significantly increase the conjugation efficiency. Instead, our modelling and experimental results demonstrate that conjugation dynamics are dictated by antibiotic-mediated selection, which can both promote and suppress conjugation dynamics. Our findings suggest that the contribution of antibiotics to the promotion of horizontal gene transfer may have been overestimated. These findings have implications for designing effective antibiotic treatment protocols and for assessing the risks of antibiotic use.

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Figure 1: Potential influence of antibiotics on conjugation.
Figure 2: Antibiotics did not significantly increase conjugation efficiency.
Figure 3: Antibiotics can both promote and suppress conjugation dynamics.
Figure 4: Population structure influences the likelihood for conjugation frequency.

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Acknowledgements

The authors acknowledge support from the Shared Materials and Instrumentation Facility at Duke University in assisting with the fabrication of the microfluidic device. The authors also thank T. Dimitriu for plasmid constructs, insightful comments and advice, E. Gullberg for strain DA28102, Y. Feng for pESBL-283, C. Woods for the ESBL library, C. Biesel for plasmid pUA66 and B. Levin, L. David, C. Biesel, K. Koelle, J.C. Kreitz and H.R. Meredith for insightful comments and suggestions. This study was partially supported by the US Army Research Office under grant no. W911NF-14-1-0490 (to D.K., S.B. and L.Y.), the National Institutes of Health (1R01-GM098642, to L.Y.), a David and Lucile Packard Fellowship (to L.Y.) and the Howard G. Clark fellowship (A.J.L.).

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Authors and Affiliations

  1. Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA

    Allison J. Lopatkin, Shuqiang Huang, Jaydeep K. Srimani, Tatyana A. Sysoeva & Lingchong You

  2. Center for Genomic and Computational Biology, Duke University, Durham, North Carolina, USA

    Lingchong You

  3. Department of Biological Sciences, Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Fort Lauderdale, Florida, USA

    Robert P. Smith

  4. Department of Biology, University of Maryland, College Park, 20742, Maryland, USA

    Sharon Bewick

  5. Research and Exploratory Development Department, Applied Physics Laboratory, Johns Hopkins University Laurel, Maryland, USA

    David K. Karig

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Contributions

A.J.L. conceived the research, designed and performed both modelling and experimental analyses, interpreted the results, and wrote the manuscript. S.H. developed and optimized the microfluidic platform, and assisted in microfluidic experiments and manuscript revisions. R.P.S. conceived the research and assisted in manuscript revisions. J.K.S. assisted with data interpretation, experimental set-up and manuscript revisions. T.A.S. assisted with experiments and manuscript revisions. S.B. and D.K. assisted with manuscript revisions. L.Y. conceived the research, and assisted with research design, data interpretation and manuscript writing.

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Correspondence to Lingchong You.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Model Development, Supplementary Figures 1–7, Supplementary Tables 1–5, Supplementary Video Legends and Supplementary References. (PDF 3063 kb)

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Lopatkin, A., Huang, S., Smith, R. et al. Antibiotics as a selective driver for conjugation dynamics. Nat Microbiol 1, 16044 (2016). https://doi.org/10.1038/nmicrobiol.2016.44

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