Person:

Lozovsky, Elena

The spread of high-level pyrimethamine resistance in Africa threatens to curtail the therapeutic lifetime of antifolate antimalarials. We studied the possible evolutionary pathways in the evolution of pyrimethamine resistance using an approach in which all possible mutational intermediates were created by site-directed mutagenesis and assayed for their level of drug resistance. The coding sequence for dihydrofolate reductase (DHFR) from the malaria parasite Plasmodium falciparum was mutagenized, and tests were carried out in Escherichia coli under conditions in which the endogenous bacterial enzyme was selectively inhibited. We studied 4 key amino acid replacements implicated in pyrimethamine resistance: N51I, C59R, S108N, and I164L. Using empirical estimates of the mutational spectrum in P. falciparum and probabilities of fixation based on the relative levels of resistance, we found that the predicted favored pathways of drug resistance are consistent with those reported in previous kinetic studies, as well as DHFR polymorphisms observed in natural populations. We found that 3 pathways account for nearly 90% of the simulated realizations of the evolution of pyrimethamine resistance. The most frequent pathway (S108N and then C59R, N51I, and I164L) accounts for more than half of the simulated realizations. Our results also suggest an explanation for why I164L is detected in Southeast Asia and South America, but not at significant frequencies in Africa.

Fitness landscapes of drug resistance constitute powerful tools to elucidate mutational pathways of antibiotic escape. Here, we de- veloped a predictive biophysics-based fitness landscape of trimeth- oprim (TMP) resistance for Escherichia coli dihydrofolate reductase (DHFR). We investigated the activity, binding, folding stability, and intracellular abundance for a complete set of combinatorial DHFR mutants made out of three key resistance mutations and extended this analysis to DHFR originated from Chlamydia muridarum and Listeria grayi. We found that the acquisition of TMP resistance via decreased drug affinity is limited by a trade-off in catalytic efficiency. Protein stability is concurrently affected by the resistant mutants, which precludes a precise description of fitness from a single molec- ular trait. Application of the kinetic flux theory provided an accurate model to predict resistance phenotypes (IC50) quantitatively from a unique combination of the in vitro protein molecular properties. Fur- ther, we found that a controlled modulation of the GroEL/ES chap- eronins and Lon protease levels affects the intracellular steady-state concentration of DHFR in a mutation-specific manner, whereas IC50 is changed proportionally, as indeed predicted by the model. This un- veils a molecular rationale for the pleiotropic role of the protein quality control machinery on the evolution of antibiotic resistance, which, as we illustrate here, may drastically confound the evolution- ary outcome. These results provide a comprehensive quantitative genotype–phenotype map for the essential enzyme that serves as an important target of antibiotic and anticancer therapies.