While mutation is an intrinsically stochastic event, selection can steer the evolution of a particular species through many cycles of reproduction on a contrained subset of tolerable genetic permutations. Together with colleagues at the CNRS in France we develop (wet-& dry-lab) methods to unravel tolerable (combinations of) mutations, Smyth et al. 2015.
A major focus of our work is on viral drug resistance as a particular case of evolution, where the “steering” (selection pressure) is directly forced on the virus by antiviral medication (see e.g. Rath et al. 2013). Although this situation is inherent to most microbial/viral infections, the mechanisms of drug resistance emergence are still poorly understood. While drug treatment usually inhibits replication, and thus adaptation, it also induces selective pressure, which could promote resistance. Thus, there is some threshold efficacy, which promotes the selection of resistance D* and some threshold efficacy, which completely limits replication and thus resistance emergence D+ . In particular, the actual efficacy of a drug/treatment D would have to stay within the boundaries set by D* <= D <= D+ in order to allow for resistance to develop and persist. Preliminary results show that this range is unrealistically small to allow for some clinically observed resistance patterns to develop. We therefore suspect that resistance emerges by a mechanism in which multiple compartments are involved and “share” tasks to promote resistance. Our preliminary results of HIV-inhibition by the drug class of nucleoside reverse transcriptase inhibitors (NRTI) seem to support this hypothesis (von Kleist et al. 2012). Furthermore, we are currently exploring possible genetic constraints to resistance development (Meixenberger et al. 2015) to better understand how drug resistance can emerge clinically, and how it may be avoided.