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Standing genetic variation and the evolution of drug resistance in HIV.

ABSTRACT: Drug resistance remains a major problem for the treatment of HIV. Resistance can occur due to mutations that were present before treatment starts or due to mutations that occur during treatment. The relative importance of these two sources is unknown. Resistance can also be transmitted between patients, but this process is not considered in the current study. We study three different situations in which HIV drug resistance may evolve: starting triple-drug therapy, treatment with a single dose of nevirapine and interruption of treatment. For each of these three cases good data are available from literature, which allows us to estimate the probability that resistance evolves from standing genetic variation. Depending on the treatment we find probabilities of the evolution of drug resistance due to standing genetic variation between 0 and 39%. For patients who start triple-drug combination therapy, we find that drug resistance evolves from standing genetic variation in approximately 6% of the patients. We use a population-dynamic and population-genetic model to understand the observations and to estimate important evolutionary parameters under the assumption that treatment failure is caused by the fixation of a single drug resistance mutation. We find that both the effective population size of the virus before treatment, and the fitness of the resistant mutant during treatment, are key-arameters which determine the probability that resistance evolves from standing genetic variation. Importantly, clinical data indicate that both of these parameters can be manipulated by the kind of treatment that is used.

SUBMITTER: Pennings PS

PROVIDER: S-EPMC3369920 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:In "evolve-and-resequence" (E&R) experiments, whole-genome sequence data from laboratory-evolved populations can potentially uncover mechanisms of adaptive change. E&R experiments with initially isogenic, asexually reproducing microbes have repeatedly shown that beneficial de novo mutations drive adaptation, and these mutations are not shared among independently evolving replicate populations. Recent E&R experiments with higher eukaryotes that maintain genetic variation via sexual reproduction implicate largely different mechanisms; adaptation may act primarily on pre-existing genetic variation and occur in parallel among independent populations. But this is currently a debated topic, and generalizing these conclusions is problematic because E&R experiments with sexual species are difficult to implement and important elements of experimental design suffer for practical reasons. We circumvent potentially confounding limitations with a yeast model capable of shuffling genotypes via sexual recombination. Our starting population consisted of a highly intercrossed diploid Saccharomyces cerevisiae initiated from four wild haplotypes. We imposed a laboratory domestication treatment on 12 independent replicate populations for 18 weeks, where each week included 2 days as diploids in liquid culture and a forced recombination/mating event. We then sequenced pooled population samples at weeks 0, 6, 12, and 18. We show that adaptation is highly parallel among replicate populations, and can be localized to a modest number of genomic regions. We also demonstrate that despite hundreds of generations of evolution and large effective population sizes, de novo beneficial mutations do not play a large role in this adaptation. Further, we have high power to detect the signal of change in these populations but show how this power is dramatically reduced when fewer timepoints are sampled, or fewer replicate populations are analyzed. As ours is the most highly replicated and sampled E&R study in a sexual species to date, this evokes important considerations for past and future experiments.

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Standing genetic variation and the evolution of drug resistance in HIV.

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