Abstract
BACKGROUND: The study of reverse evolution from resistant to susceptible phenotypes can reveal constraints on biological evolution, a topic for which evolutionary theory has relatively few general principles. The public health catastrophe of antimicrobial resistance in malaria has brought these constraints on evolution into a practical realm, with one proposed solution: withdrawing anti-malarial medication use in high resistance settings, built on the assumption that reverse evolution occurs readily enough that populations of pathogens may revert to their susceptible states. While past studies have suggested limits to reverse evolution, there have been few attempts to properly dissect its mechanistic constraints. METHODS: Growth rates were determined from empirical data on the growth and resistance from a set of combinatorially complete set of mutants of a resistance protein (dihydrofolate reductase) in Plasmodium vivax, to construct reverse evolution trajectories. The fitness effects of individual mutations were calculated as a function of drug environment, revealing the magnitude of epistatic interactions between mutations and genetic backgrounds. Evolution across the landscape was simulated in two settings: starting from the population fixed for the quadruple mutant, and from a polymorphic population evenly distributed between double mutants. RESULTS: A single mutation of large effect (S117N) serves as a pivot point for evolution to high resistance regions of the landscape. Through epistatic interactions with other mutations, this pivot creates an epistatic ratchet against reverse evolution towards the wild type ancestor, even in environments where the wild type is the most fit of all genotypes. This pivot mutation underlies the directional bias in evolution across the landscape, where evolution towards the ancestor is precluded across all examined drug concentrations from various starting points in the landscape. CONCLUSIONS: The presence of pivot mutations can dictate dynamics of evolution across adaptive landscape through epistatic interactions within a protein, leaving a population trapped on local fitness peaks in an adaptive landscape, unable to locate ancestral genotypes. This irreversibility suggests that the structure of an adaptive landscape for a resistance protein should be understood before considering resistance management strategies. This proposed mechanism for constraints on reverse evolution corroborates evidence from the field indicating that phenotypic reversal often occurs via compensatory mutation at sites independent of those associated with the forward evolution of resistance. Because of this, molecular methods that identify resistance patterns via single SNPs in resistance-associated markers might be missing signals for resistance and compensatory mutation throughout the genome. In these settings, whole genome sequencing efforts should be used to identify resistance patterns, and will likely reveal a more complicated genomic signature for resistance and susceptibility, especially in settings where anti-malarial medications have been used intermittently. Lastly, the findings suggest that, given their role in dictating the dynamics of evolution across the landscape, pivot mutations might serve as future targets for therapy.