Genome-wide analysis captures the determinants of the antibiotic cross-resistance interaction network

Viktória Lázár, István Nagy, Réka Spohn, Bálint Csörgő, Ádám Györkei, Ákos Nyerges, Balázs Horváth, Andrea Vörös, Róbert Busa-Fekete, Mónika Hrtyan, Balázs Bogos, Orsolya Méhi, Gergely Fekete, Balázs Szappanos, Balázs Kégl, Balázs Papp () and Csaba Pál ()
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Viktória Lázár: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
István Nagy: Sequencing Platform, Institute of Biochemistry, Biological Research Centre
Réka Spohn: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Bálint Csörgő: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Ádám Györkei: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Ákos Nyerges: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Balázs Horváth: Sequencing Platform, Institute of Biochemistry, Biological Research Centre
Andrea Vörös: Sequencing Platform, Institute of Biochemistry, Biological Research Centre
Róbert Busa-Fekete: MTA-SZTE Research Group on Artificial Intelligence
Mónika Hrtyan: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Balázs Bogos: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Orsolya Méhi: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Gergely Fekete: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Balázs Szappanos: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Balázs Kégl: Linear Accelerator Laboratory, University of Paris-Sud, CNRS
Balázs Papp: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre
Csaba Pál: Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre

Nature Communications, 2014, vol. 5, issue 1, 1-12

Abstract: Abstract Understanding how evolution of antimicrobial resistance increases resistance to other drugs is a challenge of profound importance. By combining experimental evolution and genome sequencing of 63 laboratory-evolved lines, we charted a map of cross-resistance interactions between antibiotics in Escherichia coli, and explored the driving evolutionary principles. Here, we show that (1) convergent molecular evolution is prevalent across antibiotic treatments, (2) resistance conferring mutations simultaneously enhance sensitivity to many other drugs and (3) 27% of the accumulated mutations generate proteins with compromised activities, suggesting that antibiotic adaptation can partly be achieved without gain of novel function. By using knowledge on antibiotic properties, we examined the determinants of cross-resistance and identified chemogenomic profile similarity between antibiotics as the strongest predictor. In contrast, cross-resistance between two antibiotics is independent of whether they show synergistic effects in combination. These results have important implications on the development of novel antimicrobial strategies.

Date: 2014
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DOI: 10.1038/ncomms5352

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