Phenomenological relations such as Ohm’s or Fourier’s law have a venerable history in physics but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial “growth laws,” which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We provide analytical results for limiting cases, which agree well with numerical results. We systematically refine the model by including direct physical interactions of different antibiotics on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions that were derived using entropy maximization. We further refine the model to include the effects of antibiotics that mimic starvation and the presence of resistance genes. We describe the impact of a starvation-mimicking antibiotic on drug interactions analytically and verify it experimentally. Our extended model suggests a change in the type of drug interaction that depends on the strength of resistance, which challenges established rescaling paradigms. We experimentally show that the presence of unregulated resistance genes can lead to altered drug interaction, which agrees with the prediction of the model. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems.
PLOS Computational Biology
This work was supported in part by Tum stipend of Knafelj foundation (to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation (DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG) Collaborative Research Centre (SFB) 1310 (to T.B.).
Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. 17(1). doi:10.1371/journal.pcbi.1008529
Kavcic, B., Tkačik, G., & Bollenbach, M. T. (n.d.). Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1008529
Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical Model of Combined Antibiotic Action.” PLOS Computational Biology. Public Library of Science, n.d. https://doi.org/10.1371/journal.pcbi.1008529.
B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of combined antibiotic action,” PLOS Computational Biology, vol. 17, no. 1. Public Library of Science.
Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. 17(1), e1008529.
Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.” PLOS Computational Biology, vol. 17, no. 1, e1008529, Public Library of Science, doi:10.1371/journal.pcbi.1008529.
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