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Can Scaling Relations Help Us Predict the Response of Drug-Resistant Cells to Drug Combinations?

Wood, Wood, Nishida, Cluzel, Cell Reports 6, 1073 (2014).

Complex physical systems can often be described by simple, empirical laws which unite seemingly disparate systems.  These laws are of great scientific importance because they point to shared structural or dynamical features of systems that appear, on the surface, to be very different.  In this work, we identified a series of widely applicable scaling relationships that relate the multi-drug response of drug sensitive cells to that of drug resistant cells from the same parental cell line.  The goal of the work is to provide a unified description of two-drug response surfaces that does not require a detailed molecular understanding of the resistance mechanism.

 

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Pairwise Interactions Between Antibiotics Underlie the Response of Bacterial Populations to Larger Drug Combinations.

Wood, Nishida, Sontag, Cluzel.  PNAS, 2012.

Drugs combinations are commonly employed in the treatment of severe bacterial infections. However, the actions of individual drugs are often coupled through their effects on complex intracellular networks. As a result, it is generally impossible to infer the net effect of a multi-drug combination directly from the effects of individual drugs.  In this work, we show that knowing how drugs interact in pairs allows one to predict the effects of larger drug combinations.  This surprising result raises a number of questions about how biochemical networks, and dynamical systems more generally, respond to combined perturbations.

 

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How Does the Interplay Between Drug Toxicity and Drug-Induced Efflux Shape Interactions Between Multiple Drugs?

Wood and Cluzel, BMC Systems Biology, 2012.

Efflux is a widespread mechanism of reversible drug resistance in bacteria and can be triggered by a host of environmental stressors, including many classes of drugs. While such chemicals are typically toxic to the cell, they can also induce the efflux of a broad range of agents and may therefore prove beneficial to cells in the presence of multiple stressors. The goal of this work is to develop and experimentally verify a theoretical framework for disentangling the cost-benefit interplay in E. coli exposed to multiple drugs.

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