Fifteen years later: hard and soft selection sweeps confirm a large population number for HIV in vivo

A large effective population size for established within-host influenza virus infection

Strains of the influenza virus form coherent global populations, yet exist at the level of single infections in individual hosts. The relationship between these scales is a critical topic for understanding viral evolution. Here we investigate the within-host relationship between selection and the stochastic effects of genetic drift, estimating an effective population size of infection Ne for influenza infection. Examining whole-genome sequence data describing a chronic case of influenza B in a severely immunocompromised child we infer an Ne of 2.5 × 107 (95% confidence range 1.0 × 107 to 9.0 × 107) suggesting that genetic drift is of minimal importance during an established influenza infection. Our result, supported by data from influenza A infection, suggests that positive selection during within-host infection is primarily limited by the typically short period of infection. Atypically long infections may have a disproportionate influence upon global patterns of viral evolution.

Interaction of virus populations with their hosts

Viral population numbers are extremely large compared with those of their host species. Population bottlenecks are frequent during the life cycle of viruses and can reduce viral populations transiently to very few individuals. Viruses have to confront several types of constraints that can be divided into basal, cell-dependent, and organism-dependent constraints. Viruses overcome them exploiting a number of molecular mechanisms, with an important contribution of population numbers and genome variation. The adaptive potential of viruses is reflected in modifications of cell tropism and host range, escape to components of the host immune response, and capacity to alternate among different host species, among other phenotypic changes. Despite a fitness cost of most mutations required to overcome a selective constraint, viruses can find evolutionary pathways that ensure their survival in equilibrium with their hosts.

Allele Age Under Non-Classical Assumptions is Clarified by an Exact Computational Markov Chain Approach

Determination of the age of an allele based on its population frequency is a well-studied problem in population genetics, for which a variety of approximations have been proposed. We present a new result that, surprisingly, allows the expectation and variance of allele age to be computed exactly (within machine precision) for any finite absorbing Markov chain model in a matter of seconds. This approach makes none of the classical assumptions (e.g., weak selection, reversibility, infinite sites), exploits modern sparse linear algebra techniques, integrates over all sample paths, and is rapidly computable for Wright-Fisher populations up to N_e = 100,000. With this approach, we study the joint effect of recurrent mutation, dominance, and selection, and demonstrate new examples of “selective strolls” where the classical symmetry of allele age with respect to selection is violated by weakly selected alleles that are older than neutral alleles at the same frequency. We also show evidence for a strong age imbalance, where rare deleterious alleles are expected to be substantially older than advantageous alleles observed at the same frequency when population-scaled mutation rates are large. These results highlight the under-appreciated utility of computational methods for the direct analysis of Markov chain models in population genetics.

Coalescent Inference Using Serially Sampled, High-Throughput Sequencing Data from Intrahost HIV Infection

Human immunodeficiency virus (HIV) is a rapidly evolving pathogen that causes chronic infections, so genetic diversity within a single infection can be very high. High-throughput "deep" sequencing can now measure this diversity in unprecedented detail, particularly since it can be performed at different time points during an infection, and this offers a potentially powerful way to infer the evolutionary dynamics of the intrahost viral population. However, population genomic inference from HIV sequence data is challenging because of high rates of mutation and recombination, rapid demographic changes, and ongoing selective pressures. In this article we develop a new method for inference using HIV deep sequencing data, using an approach based on importance sampling of ancestral recombination graphs under a multilocus coalescent model. The approach further extends recent progress in the approximation of so-called conditional sampling distributions, a quantity of key interest when approximating coalescent likelihoods. The chief novelties of our method are that it is able to infer rates of recombination and mutation, as well as the effective population size, while handling sampling over different time points and missing data without extra computational difficulty. We apply our method to a data set of HIV-1, in which several hundred sequences were obtained from an infected individual at seven time points over 2 years. We find mutation rate and effective population size estimates to be comparable to those produced by the software BEAST. Additionally, our method is able to produce local recombination rate estimates. The software underlying our method, Coalescenator, is freely available.

The role of HIV integration in viral persistence: no more whistling past the proviral graveyard

A substantial research effort has been directed to identifying strategies to eradicate or control HIV infection without a requirement for combination antiretroviral therapy (cART). A number of obstacles prevent HIV eradication, including low-level viral persistence during cART, long-term persistence of HIV-infected cells, and latent infection of resting CD4+ T cells. Mechanisms of persistence remain uncertain, but integration of the provirus into the host genome represents a central event in replication and pathogenesis of all retroviruses, including HIV. Analysis of HIV proviruses in CD4+ lymphocytes from individuals after prolonged cART revealed that a substantial proportion of the infected cells that persist have undergone clonal expansion and frequently have proviruses integrated in genes associated with regulation of cell growth. These data suggest that integration may influence persistence and clonal expansion of HIV-infected cells after cART is introduced, and these processes may represent key mechanisms for HIV persistence. Determining the diversity of host genes with integrants in HIV-infected cells that persist for prolonged periods may yield useful information regarding pathways by which infected cells persist for prolonged periods. Moreover, many integrants are defective, and new studies are required to characterize the role of clonal expansion in the persistence of replication-competent HIV.

Interaction of Virus Populations with Their Hosts

Viral population numbers are extremely large compared with those of their host species. Population bottlenecks are frequent during the life cycle of viruses and can reduce viral populations transiently to very few individuals. Viruses have to confront several types of constraints that can be divided in basal, cell-dependent, and organism-dependent constraints. Viruses overcome them exploiting a number of molecular mechanisms, with an important contribution of population numbers and genome variation. The adaptive potential of viruses is reflected in modifications of cell tropism and host range, escape to components of the host immune response, and capacity to alternate among different host species, among other phenotypic changes. Despite a fitness cost of most mutations required to overcome a selective constraint, viruses can find evolutionary pathways that ensure their survival in equilibrium with their hosts.

HIV-infected cells are frequently clonally expanded after prolonged antiretroviral therapy: implications for HIV persistence

HIV infection is controlled but not eradicated by combination antiretroviral therapy (cART), and persistence during therapy represents a substantial barrier to strategies to eradicate infection. The nature of persistence is uncertain, and a number of mechanisms have been proposed to explain HIV persistence in vivo, including low-level HIV replication, sanctuary sites for HIV-infected cells, and latent HIV residing within long-lived cells. Analysis of residual viraemia and of cell-associated HIV revealed evidence of multiple copies of identical HIV sequences suggesting infected cells can undergo cellular expansion. Recently, analysis of integration sites in HIV-infected cells derived from peripheral blood lymphocytes of patients undergoing long-term cART revealed direct evidence that HIV-infected cells undergo clonal expansion. These studies demonstrated that clonally expanded populations are common in HIV-infected individuals, persist for prolonged periods and increase in frequency during prolonged therapy. Several analyses reported that site of integration may affect persistence, clonal expansion, or both. As such, expanded populations may represent an important source of infectious HIV during cART. Many HIV integrants are defective for replication, however, and additional research is essential to determine to what degree clonally expanded populations represent a reservoir of replication-competent HIV.