Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community

Abstract

Microbes rarely exist in isolation, rather, they form intricate multi-species communities that colonize our bodies and inserted medical devices. However, the efficacy of antimicrobials is measured in clinical laboratories exclusively using microbial monocultures. Here, to determine how multi-species interactions mediate selection for resistance during antibiotic treatment, particularly following drug withdrawal, we study a laboratory community consisting of two microbial pathogens. Single-species dose responses are a poor predictor of community dynamics during treatment so, to better understand those dynamics, we introduce the concept of a dose-response mosaic, a multi-dimensional map that indicates how species’ abundance is affected by changes in abiotic conditions. We study the dose-response mosaic of a two-species community with a ‘Gene × Gene × Environment × Environment’ ecological interaction whereby Candida glabrata, which is resistant to the antifungal drug fluconazole, competes for survival with Candida albicans, which is susceptible to fluconazole. The mosaic comprises several zones that delineate abiotic conditions where each species dominates. Zones are separated by loci of bifurcations and tipping points that identify what environmental changes can trigger the loss of either species. Observations of the laboratory communities corroborated theory, showing that changes in both antibiotic concentration and nutrient availability can push populations beyond tipping points, thus creating irreversible shifts in community composition from drug-sensitive to drug-resistant species. This has an important consequence: resistant species can increase in frequency even if an antibiotic is withdrawn because, unwittingly, a tipping point was passed during treatment.

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Fig. 1: C. albicans and C. glabrata dynamics.
Fig. 2: Population dynamics theory states that one can deduce multi-season frequency dynamics from the ‘cobweb diagram’ determined from the initial C. albicans frequency plotted versus the final frequency each season.
Fig. 3: The dose-response mosaic shows tipping points are encountered in many ways.
Fig. 4: Exploring the dose-response mosaic.

Change history

  • 19 September 2018

    In the version of this Article originally published, the following sentence was missing from the Acknowledgements: “R.E.B. is an EPSRC Healthcare Technologies Impact Fellow EP/N033671/1; I.G. is funded by ERC Consolidator grant 647292 MathModExp; A.J.P.B., N.A.R.G. and A.T. were funded by BBSRC grant BB/F00513X/1; K.H., I.G., S.N. and E.C. were funded by BBSRC grant BB/F005210/2.” This text has now been added.

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Acknowledgements

In memory of our friend and colleague Ken Haynes who sadly passed away on 19 March 2018. R.E.B. is an EPSRC Healthcare Technologies Impact Fellow EP/N033671/1; I.G. is funded by ERC Consolidator grant 647292 MathModExp; A.J.P.B., N.A.R.G. and A.T. were funded by BBSRC grant BB/F00513X/1; K.H., I.G., S.N. and E.C. were funded by BBSRC grant BB/F005210/2.

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I.G. and R.E.B. conceived the idea. R.E.B., I.G. and E.C. designed all experiments (apart from Supplementary Fig. 5). T.C.W. designed the experiment in Slementary Fig. 5. E.C., S.N., A.R.S., A.T., B.D.E., K.H., N.A.R.G. and A.J.P.B. carried out experiments. I.G. and R.E.B. developed and numerically simulated the mathematical model. R.E.B., I.G., E.C., T.C.W., K.H., N.A.R.G. and A.J.P.B. discussed the results. R.E.B., E.C. and I.G. wrote the manuscript.

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Correspondence to Robert E. Beardmore or Ivana Gudelj.

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Supplementary figures 1–12; supplementary experimental details; supplementary modelling

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Beardmore, R.E., Cook, E., Nilsson, S. et al. Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community. Nat Ecol Evol 2, 1312–1320 (2018). https://doi.org/10.1038/s41559-018-0582-7

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