No abstract

Accurate identification of the transmitted virus and sequences evolving from it could be instrumental in elucidating the transmission of human immunodeficiency virus type 1 (HIV-1) and in developing vaccines, drugs, or microbicides to prevent infection. Here we describe an experimental approach to analyze HIV-1 env genes as intact genetic units amplified from plasma virion RNA by single-genome amplification (SGA), followed by direct sequencing of uncloned DNA amplicons. We show that this strategy precludes in vitro artifacts caused by Taq-induced nucleotide substitutions and template switching, provides an accurate representation of the env quasispecies in vivo, and has an overall error rate (including nucleotide misincorporation, insertion, and deletion) of less than 8 ؋ 10 ؊5 . Applying this method to the analysis of virus in plasma from 12 Zambian subjects from whom samples were obtained within 3 months of seroconversion, we show that transmitted or early founder viruses can be identified and that molecular pathways and rates of early env diversification can be defined. Specifically, we show that 8 of the 12 subjects were each infected by a single virus, while 4 others acquired more than one virus; that the rate of virus evolution in one subject during an 80-day period spanning seroconversion was 1.7 ؋ 10 ؊5 substitutions per site per day; and that evidence of strong immunologic selection can be seen in Env and overlapping Rev sequences based on nonrandom accumulation of nonsynonymous mutations. We also compared the results of the SGA approach with those of moreconventional bulk PCR amplification methods performed on the same patient samples and found that the latter is associated with excessive rates of Taq-induced recombination, nucleotide misincorporation, template resampling, and cloning bias. These findings indicate that HIV-1 env genes, other viral genes, and even full-length viral genomes responsible for productive clinical infection can be identified by SGA analysis of plasma virus sampled at intervals typical in large-scale vaccine trials and that pathways of viral diversification and immune escape can be determined accurately.

Identifying the specific genetic characteristics of successfully transmitted variants may prove central to the development of effective vaccine and microbicide interventions. Although human immunodeficiency virus transmission is associated with a population bottleneck, the extent to which different factors influence the diversity of transmitted viruses is unclear. We estimate here the number of transmitted variants in 69 heterosexual men and women with primary subtype C infections. From 1,505 env sequences obtained using a single genome amplification approach we show that 78% of infections involved single variant transmission and 22% involved multiple variant transmissions (median of 3). We found evidence for mutations selected for cytotoxic-T-lymphocyte or antibody escape and a high prevalence of recombination in individuals infected with multiple variants representing another potential escape pathway in these individuals. In a combined analysis of 171 subtype B and C transmission events, we found that infection with more than one variant does not follow a Poisson distribution, indicating that transmission of individual virions cannot be seen as independent events, each occurring with low probability. While most transmissions resulted from a single infectious unit, multiple variant transmissions represent a significant fraction of transmission events, suggesting that there may be important mechanistic differences between these groups that are not yet understood.

We describe a mathematical model and Monte-Carlo (MC) simulation of viral evolution during acute infection. We consider both synchronous and asynchronous processes of viral infection of new target cells. The model enables an assessment of the expected sequence diversity in new HIV-1 infections originating from a single transmitted viral strain, estimation of the most recent common ancestor (MRCA) of the transmitted viral lineage, and estimation of the time to coalesce back to the MRCA. We also calculate the probability of the MRCA being the transmitted virus or an evolved variant. Excluding insertions and deletions, we assume HIV-1 evolves by base substitution without selection pressure during the earliest phase of HIV-1 infection prior to the immune response. Unlike phylogenetic methods that follow a lineage backwards to coalescence, we compare the observed data to a model of the diversification of a viral population forward in time. To illustrate the application of these methods, we provide detailed comparisons of the model and simulations results to 306 envelope sequences obtained from 8 newly infected subjects at a single time point. The data from 6/8 patients were in good agreement with model predictions, and hence compatible with a single-strain infection evolving under no selection pressure. The diversity of the samples from the other two patients was too great to be explained by the model, suggesting multiple HIV-1-strains were transmitted. The model can also be applied to longitudinal patient data to estimate within-host viral evolutionary parameters.

BackgroundThe occurrence of a genetic bottleneck in HIV sexual or mother-to-infant transmission has been well documented. This results in a majority of new infections being homogeneous, i.e., initiated by a single genetic strain. Early after infection, prior to the onset of the host immune response, the viral population grows exponentially. In this simple setting, an approach for estimating evolutionary and demographic parameters based on comparison of diversity measures is a feasible alternative to the existing Bayesian methods (e.g., BEAST), which are instead based on the simulation of genealogies.ResultsWe have devised a web tool that analyzes genetic diversity in acutely infected HIV-1 patients by comparing it to a model of neutral growth. More specifically, we consider a homogeneous infection (i.e., initiated by a unique genetic strain) prior to the onset of host-induced selection, where we can assume a random accumulation of mutations. Previously, we have shown that such a model successfully describes about 80% of sexual HIV-1 transmissions provided the samples are drawn early enough in the infection. Violation of the model is an indicator of either heterogeneous infections or the initiation of selection.ConclusionsWhen the underlying assumptions of our model (homogeneous infection prior to selection and fast exponential growth) are met, we are under a very particular scenario for which we can use a forward approach (instead of backwards in time as provided by coalescent methods). This allows for more computationally efficient methods to derive the time since the most recent common ancestor. Furthermore, the tool performs statistical tests on the Hamming distance frequency distribution, and outputs summary statistics (mean of the best fitting Poisson distribution, goodness of fit p-value, etc). The tool runs within minutes and can readily accommodate the tens of thousands of sequences generated through new ultradeep pyrosequencing technologies. The tool is available on the LANL website.