Tracking HIV-1 recombination to resolve its contribution to HIV-1 evolution in natural infection

Recombination in HIV-1 is well documented, but its importance in the low-diversity setting of within-host diversification is less understood. Here we develop a novel computational tool (RAPR (Recombination Analysis PRogram)) to enable a detailed view of in vivo viral recombination during early infection, and we apply it to near-full-length HIV-1 genome sequences from longitudinal samples. Recombinant genomes rapidly replace transmitted/founder (T/F) lineages, with a median half-time of 27 days, increasing the genetic complexity of the viral population. We identify recombination hot and cold spots that differ from those observed in inter-subtype recombinants. Furthermore, RAPR analysis of longitudinal samples from an individual with well-characterized neutralizing antibody responses shows that recombination helps carry forward resistance-conferring mutations in the diversifying quasispecies. These findings provide insight into molecular mechanisms by which viral recombination contributes to HIV-1 persistence and immunopathogenesis and have implications for studies of HIV transmission and evolution in vivo.

Recombination contributes to HIV evolution in patients, but its identification can be difficult. Here, the authors develop a computational tool called RAPR to track recombination in patients, identify recombination hot spots, and show contribution of recombination to antibody escape.

A multiple-alignment based primer design algorithm for genetically highly variable DNA targets

BACKGROUND

Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in relatively conserved regions, in addition to recognized constraints typically considered in primer design.

RESULTS

Design constraints include degenerate sites to maximize population coverage, matching of melting temperatures, optimizing de novo sequence length, finding optimal bio-barcodes to allow efficient downstream analyses, and minimizing risk of dimerization. To facilitate primer design addressing these and other constraints, we created a novel computer program (PrimerDesign) that automates this complex procedure. We show its powers and limitations and give examples of successful designs for the analysis of HIV-1 populations.

CONCLUSIONS

PrimerDesign is useful for researchers who want to design DNA primers and probes for analyzing highly variable DNA populations. It can be used to design primers for PCR, RT-PCR, Sanger sequencing, next-generation sequencing, and other experimental protocols targeting highly variable DNA samples.

Estimating time since infection in early homogeneous HIV-1 samples using a poisson model

Background

The 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.

Results

We 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.

Conclusions

When 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.

The evolutionary rate dynamically tracks changes in HIV-1 epidemics: application of a simple method for optimizing the evolutionary rate in phylogenetic trees with longitudinal data

Large-sequence datasets provide an opportunity to investigate the dynamics of pathogen epidemics. Thus, a fast method to estimate the evolutionary rate from large and numerous phylogenetic trees becomes necessary. Based on minimizing tip height variances, we optimize the root in a given phylogenetic tree to estimate the most homogenous evolutionary rate between samples from at least two different time points. Simulations showed that the method had no bias in the estimation of evolutionary rates and that it was robust to tree rooting and topological errors. We show that the evolutionary rates of HIV-1 subtype B and C epidemics have changed over time, with the rate of evolution inversely correlated to the rate of virus spread. For subtype B, the evolutionary rate slowed down and tracked the start of the HAART era in 1996. Subtype C in Ethiopia showed an increase in the evolutionary rate when the prevalence increase markedly slowed down in 1995. Thus, we show that the evolutionary rate of HIV-1 on the population level dynamically tracks epidemic events.

Unequal evolutionary rates in the human immunodeficiency virus type 1 (HIV-1) pandemic: the evolutionary rate of HIV-1 slows down when the epidemic rate increases

HIV-1 sequences in intravenous drug user (IDU) networks are highly homogenous even after several years, while this is not observed in most sexual epidemics. To address this disparity, we examined the human immunodeficiency virus type 1 (HIV-1) evolutionary rate on the population level for IDU and heterosexual transmissions. All available HIV-1 env V3 sequences from IDU outbreaks and heterosexual epidemics with known sampling dates were collected from the Los Alamos HIV sequence database. Evolutionary rates were calculated using phylogenetic trees with a t test root optimization of dated samples. The evolutionary rate of HIV-1 subtype A1 was found to be 8.4 times lower in fast spread among IDUs in the former Soviet Union (FSU) than in slow spread among heterosexual individuals in Africa. Mixed epidemics (IDU and heterosexual) showed intermediate evolutionary rates, indicating a combination of fast- and slow-spread patterns. Hence, if transmissions occur repeatedly during the initial stage of host infection, before selective pressures of the immune system have much impact, the rate of HIV-1 evolution on the population level will decrease. Conversely, in slow spread, where HIV-1 evolves under the pressure of the immune system before a donor infects a recipient, the virus evolution at the population level will increase. Epidemiological modeling confirmed that the evolutionary rate of HIV-1 depends on the rate of spread and predicted that the HIV-1 evolutionary rate in a fast-spreading epidemic, e.g., for IDUs in the FSU, will increase as the population becomes saturated with infections and the virus starts to spread to other risk groups.