HIV Populations Are Large and Accumulate High Genetic Diversity in a Nonlinear Fashion

Abstract

HIV infection is characterized by rapid and error-prone viral replication resulting in genetically diverse virus populations. The rate of accumulation of diversity and the mechanisms involved are under intense study to provide useful information to understand immune evasion and the development of drug resistance. To characterize the development of viral diversity after infection, we carried out an in-depth analysis of single genome sequences of HIV pro-pol to assess diversity and divergence and to estimate replicating population sizes in a group of treatment-naive HIV-infected individuals sampled at single (n ‫؍‬ 22) or multiple, longitudinal (n ‫؍‬ 11) time points. Analysis of single genome sequences revealed nonlinear accumulation of sequence diversity during the course of infection. Diversity accumulated in recently infected individuals at rates 30-fold higher than in patients with chronic infection. Accumulation of synonymous changes accounted for most of the diversity during chronic infection. Accumulation of diversity resulted in population shifts, but the rates of change were low relative to estimated replication cycle times, consistent with relatively large population sizes. Analysis of changes in allele frequencies revealed effective population sizes that are substantially higher than previous estimates of approximately 1,000 infectious particles/infected individual. Taken together, these observations indicate that HIV populations are large, diverse, and slow to change in chronic infection and that the emergence of new mutations, including drug resistance mutations, is governed by both selection forces and drift.

Association between Latent Proviral Characteristics and Immune Activation in Antiretrovirus-Treated Human Immunodeficiency Virus Type 1-Infected Adults

“…Subsequent studies have revealed that the proviral HIV-1 DNA sequences can remain dynamic even during antiretroviral therapy, acting as an archive of circulating plasma viruses found throughout the course of HIV infection (49,50). However, given that HIV-1 diversity accumulates more quickly in acute infection (59), it is likely that much of the env and pol diversity and divergence observed in our cohort accumulated prior to ART initiation. We were unable to directly assess this, as we did not have a reliable history documenting the duration of HIV-1 infection prior to ART initiation.…”

Identifying Signatures of Selection in Genetic Time Series

“…The underlying reason for this problem is that the likelihood-ratio statistic is x 2 -distributed only asymptotically, and convergence to this distribution is slow (Wilks 1938). In most practical applications, such as when sampling from natural populations (Reid et al 2011;Denef and Banfield 2012;Winters et al 2012;Daniels et al 2013;Maldarelli et al 2013; Pennings et al 2013) or competing two microbial strains (Lenski et al 1991;Bollback and Huelsenbeck 2007;Lang et al 2013), the number of sampled time points is typically small (,10) and the distribution of the likelihood-ratio statistic is far from x 2 under neutrality, leading to more false positives then expected. We propose two solutions to fix this problem, providing unbiased tests for natural selection in time-series data sampled at a single genetic locus.…”

“…P OPULATION geneticists typically seek to understand the forces responsible for patterns observed in contemporaneous samples of genetic data, such as the nucleotide differences fixed between species, polymorphisms within populations, and the structure of linkage disequilibrium. Recently, however, there has been a rapid increase in the availability of dynamic data, where the frequencies of segregating alleles in an evolving population are monitored through time, both in laboratory experiments (Hegreness et al 2006;Bollback and Huelsenbeck 2007;Barrick et al 2009;Lang et al 2011;Orozco-terWengel et al 2012;Lang et al 2013) and in natural populations (Barrett et al 2008;Reid et al 2011;Denef and Banfield 2012;Winters et al 2012;Daniels et al 2013;Maldarelli et al 2013; Pennings et al 2013). One important question is whether the changes in allele frequencies observed in such data are the result of natural selection or are simply consequences of genetic drift or sampling noise.…”

Fifteen to Twenty Percent of HIV Substitution Mutations Are Associated with Recombination

“…Genetic diversity underpins the ability of HIV to evolve resistance to antiretroviral therapy and to successfully evade the immune system. Viral diversity increases rapidly during initial infection (1) and is driven by mutation, recombination, and population size. Mutations are introduced primarily during reverse transcription by the error-prone reverse transcriptase (RT) enzyme (2) or by host cellular defense mechanisms (3,4).…”