Antibiotic collateral sensitivity is contingent on the repeatability of evolution

Daniel Nichol (), Joseph Rutter, Christopher Bryant, Andrea M. Hujer, Sai Lek, Mark D. Adams, Peter Jeavons, Alexander R. A. Anderson, Robert A. Bonomo and Jacob G. Scott ()
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Daniel Nichol: University of Oxford
Joseph Rutter: Louis Stokes Department of Veterans Affairs Hospital
Christopher Bryant: Case Western Reserve University School of Medicine
Andrea M. Hujer: Louis Stokes Department of Veterans Affairs Hospital
Sai Lek: The Jackson Laboratory for Genomic Medicine
Mark D. Adams: The Jackson Laboratory for Genomic Medicine
Peter Jeavons: University of Oxford
Alexander R. A. Anderson: H. Lee Moffitt Cancer Center and Research Institute
Robert A. Bonomo: Louis Stokes Department of Veterans Affairs Hospital
Jacob G. Scott: Case Western Reserve University School of Medicine

Nature Communications, 2019, vol. 10, issue 1, 1-10

Abstract: Abstract Antibiotic resistance represents a growing health crisis that necessitates the immediate discovery of novel treatment strategies. One such strategy is the identification of collateral sensitivities, wherein evolution under a first drug induces susceptibility to a second. Here, we report that sequential drug regimens derived from in vitro evolution experiments may have overstated therapeutic benefit, predicting a collaterally sensitive response where cross-resistance ultimately occurs. We quantify the likelihood of this phenomenon by use of a mathematical model parametrised with combinatorially complete fitness landscapes for Escherichia coli. Through experimental evolution we then verify that a second drug can indeed stochastically exhibit either increased susceptibility or increased resistance when following a first. Genetic divergence is confirmed as the driver of this differential response through targeted and whole genome sequencing. Taken together, these results highlight that the success of evolutionarily-informed therapies is predicated on a rigorous probabilistic understanding of the contingencies that arise during the evolution of drug resistance.

Date: 2019
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DOI: 10.1038/s41467-018-08098-6

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