Correction: HIV Reactivation from Latency after Treatment Interruption Occurs on Average Every 5-8 Days-Implications for HIV Remission.

[This corrects the article DOI: 10.1371/journal.ppat.1005000.][This corrects the article DOI: 10.1371/journal.ppat.1005740.][This corrects the article DOI: 10.1371/journal.ppat.1005679.].

HIV-1 Mutation and Recombination Rates Are Different in Macrophages and T-cells.

High rates of mutation and recombination help human immunodeficiency virus (HIV) to evade the immune system and develop resistance to antiretroviral therapy. Macrophages and T-cells are the natural target cells of HIV-1 infection. A consensus has not been reached as to whether HIV replication results in differential recombination between primary T-cells and macrophages. Here, we used HIV with silent mutation markers along with next generation sequencing to compare the mutation and the recombination rates of HIV directly in T lymphocytes and macrophages. We observed a more than four-fold higher recombination rate of HIV in macrophages compared to T-cells (p < 0.001) and demonstrated that this difference is not due to different reliance on C-X-C chemokine receptor type 4 (CXCR4) and C-C chemokine receptor type 5 (CCR5) co-receptors between T-cells and macrophages. We also found that the pattern of recombination across the HIV genome (hot and cold spots) remains constant between T-cells and macrophages despite a three-fold increase in the overall recombination rate. This indicates that the difference in rates is a general feature of HIV DNA synthesis during macrophage infection. In contrast to HIV recombination, we found that T-cells have a 30% higher mutation rate than macrophages (p < 0.001) and that the mutational profile is similar between these cell types. Unexpectedly, we found no association between mutation and recombination in macrophages, in contrast to T-cells. Our data highlights some of the fundamental difference of HIV recombination and mutation amongst these two major target cells of infection. Understanding these differences will provide invaluable insights toward HIV evolution and how the virus evades immune surveillance and anti-retroviral therapeutics.

Estimating the in-vivo HIV template switching and recombination rate.

BACKGROUND: HIV recombination has been estimated in vitro using a variety of approaches, and shows a high rate of template switching per reverse transcription event. In-vivo studies of recombination generally measure the accumulation of recombinant strains over time, and thus do not directly estimate a comparable template switching rate. METHOD: To examine whether the estimated in-vitro template switching rate is representative of the rate that occurs during HIV infection in vivo, we adopted a novel approach, analysing single genome sequences from early founder viruses to study the in-vivo template switching rate in the env region of HIV. RESULTS: We estimated the in-vivo per cycle template switching rate to be between 0.5 and 1.5/1000 nt, or approximately 5-14 recombination events over the length of the HIV genome. CONCLUSION: The in-vivo estimated template switching rate is close to the in-vitro estimated rate found in primary T lymphocytes but not macrophages, which is consistent with the majority of HIV infection occurring in T lymphocytes.

HIV Reactivation from Latency after Treatment Interruption Occurs on Average Every 5-8 Days--Implications for HIV Remission.

HIV infection can be effectively controlled by anti-retroviral therapy (ART) in most patients. However therapy must be continued for life, because interruption of ART leads to rapid recrudescence of infection from long-lived latently infected cells. A number of approaches are currently being developed to 'purge' the reservoir of latently infected cells in order to either eliminate infection completely, or significantly delay the time to viral recrudescence after therapy interruption. A fundamental question in HIV research is how frequently the virus reactivates from latency, and thus how much the reservoir might need to be reduced to produce a prolonged antiretroviral-free HIV remission. Here we provide the first direct estimates of the frequency of viral recrudescence after ART interruption, combining data from four independent cohorts of patients undergoing treatment interruption, comprising 100 patients in total. We estimate that viral replication is initiated on average once every ≈6 days (range 5.1- 7.6 days). This rate is around 24 times lower than previous thought, and is very similar across the cohorts. In addition, we analyse data on the ratios of different 'reactivation founder' viruses in a separate cohort of patients undergoing ART-interruption, and estimate the frequency of successful reactivation to be once every 3.6 days. This suggests that a reduction in the reservoir size of around 50-70-fold would be required to increase the average time-to-recrudescence to about one year, and thus achieve at least a short period of anti-retroviral free HIV remission. Our analyses suggests that time-to-recrudescence studies will need to be large in order to detect modest changes in the reservoir, and that macaque models of SIV latency may have much higher frequencies of viral recrudescence after ART interruption than seen in human HIV infection. Understanding the mean frequency of recrudescence from latency is an important first step in approaches to prolong antiretroviral-free viral remission in HIV.

Epitope-specific CD8+ T cell kinetics rather than viral variability determine the timing of immune escape in simian immunodeficiency virus infection.

CD8(+) T cells are important for the control of chronic HIV infection. However, the virus rapidly acquires "escape mutations" that reduce CD8(+) T cell recognition and viral control. The timing of when immune escape occurs at a given epitope varies widely among patients and also among different epitopes within a patient. The strength of the CD8(+) T cell response, as well as mutation rates, patterns of particular amino acids undergoing escape, and growth rates of escape mutants, may affect when escape occurs. In this study, we analyze the epitope-specific CD8(+) T cells in 25 SIV-infected pigtail macaques responding to three SIV epitopes. Two epitopes showed a variable escape pattern and one had a highly monomorphic escape pattern. Despite very different patterns, immune escape occurs with a similar delay of on average 18 d after the epitope-specific CD8(+) T cells reach 0.5% of total CD8(+) T cells. We find that the most delayed escape occurs in one of the highly variable epitopes, and that this is associated with a delay in the epitope-specific CD8(+) T cells responding to this epitope. When we analyzed the kinetics of immune escape, we found that multiple escape mutants emerge simultaneously during the escape, implying that a diverse population of potential escape mutants is present during immune selection. Our results suggest that the conservation or variability of an epitope does not appear to affect the timing of immune escape in SIV. Instead, timing of escape is largely determined by the kinetics of epitope-specific CD8(+) T cells.

Fifteen to twenty percent of HIV substitution mutations are associated with recombination.

HIV undergoes high rates of mutation and recombination during reverse transcription, but it is not known whether these events occur independently or are linked mechanistically. Here we used a system of silent marker mutations in HIV and a single round of infection in primary T lymphocytes combined with a high-throughput sequencing and mathematical modeling approach to directly estimate the viral recombination and mutation rates. From >7 million nucleotides (nt) of sequences from HIV infection, we observed 4,801 recombination events and 859 substitution mutations (≈1.51 and 0.12 events per 1,000 nt, respectively). We used experimental controls to account for PCR-induced and transfection-induced recombination and sequencing error. We found that the single-cycle virus-induced mutation rate is 4.6 × 10(-5) mutations per nt after correction. By sorting of our data into recombined and nonrecombined sequences, we found a significantly higher mutation rate in recombined regions (P = 0.003 by Fisher's exact test). We used a permutation approach to eliminate a number of potential confounding factors and confirm that mutation occurs around the site of recombination and is not simply colocated in the genome. By comparing mutation rates in recombined and nonrecombined regions, we found that recombination-associated mutations account for 15 to 20% of all mutations occurring during reverse transcription.

Identifying recombination hot spots in the HIV-1 genome.

UNLABELLED: HIV-1 infection is characterized by the rapid generation of genetic diversity that facilitates viral escape from immune selection and antiretroviral therapy. Despite recombination's crucial role in viral diversity and evolution, little is known about the genomic factors that influence recombination between highly similar genomes. In this study, we use a minimally modified full-length HIV-1 genome and high-throughput sequence analysis to study recombination in gag and pol in T cells. We find that recombination is favored at a number of recombination hot spots, where recombination occurs six times more frequently than at corresponding cold spots. Interestingly, these hot spots occur near important features of the HIV-1 genome but do not occur at sites immediately around protease inhibitor or reverse transcriptase inhibitor drug resistance mutations. We show that the recombination hot and cold spots are consistent across five blood donors and are independent of coreceptor-mediated entry. Finally, we check common experimental confounders and find that these are not driving the location of recombination hot spots. This is the first study to identify the location of recombination hot spots between two similar viral genomes with great statistical power and under conditions that closely reflect natural recombination events among HIV-1 quasispecies. IMPORTANCE: The ability of HIV-1 to evade the immune system and antiretroviral therapy depends on genetic diversity within the viral quasispecies. Retroviral recombination is an important mechanism that helps to generate and maintain this genetic diversity, but little is known about how recombination rates vary within the HIV-1 genome. We measured recombination rates in gag and pol and identified recombination hot and cold spots, demonstrating that recombination is not random but depends on the underlying gene sequence. The strength and location of these recombination hot and cold spots can be used to improve models of viral dynamics and evolution, which will be useful for the design of robust antiretroviral therapies.

Accurately measuring recombination between closely related HIV-1 genomes.

Retroviral recombination is thought to play an important role in the generation of immune escape and multiple drug resistance by shuffling pre-existing mutations in the viral population. Current estimates of HIV-1 recombination rates are derived from measurements within reporter gene sequences or genetically divergent HIV sequences. These measurements do not mimic the recombination occurring in vivo, between closely related genomes. Additionally, the methods used to measure recombination make a variety of assumptions about the underlying process, and often fail to account adequately for issues such as co-infection of cells or the possibility of multiple template switches between recombination sites. We have developed a HIV-1 marker system by making a small number of codon modifications in gag which allow recombination to be measured over various lengths between closely related viral genomes. We have developed statistical tools to measure recombination rates that can compensate for the possibility of multiple template switches. Our results show that when multiple template switches are ignored the error is substantial, particularly when recombination rates are high, or the genomic distance is large. We demonstrate that this system is applicable to other studies to accurately measure the recombination rate and show that recombination does not occur randomly within the HIV genome.

Interpreting missense variants: comparing computational methods in human disease genes CDKN2A, MLH1, MSH2, MECP2, and tyrosinase (TYR).

The human genome contains frequent single-basepair variants that may or may not cause genetic disease. To characterize benign vs. pathogenic missense variants, numerous computational algorithms have been developed based on comparative sequence and/or protein structure analysis. We compared computational methods that use evolutionary conservation alone, amino acid (AA) change alone, and a combination of conservation and AA change in predicting the consequences of 254 missense variants in the CDKN2A (n = 92), MLH1 (n = 28), MSH2 (n = 14), MECP2 (n = 30), and tyrosinase (TYR) (n = 90) genes. Variants were validated as either neutral or deleterious by curated locus-specific mutation databases and published functional data. All methods that use evolutionary sequence analysis have comparable overall prediction accuracy (72.9-82.0%). Mutations at codons where the AA is absolutely conserved over a sufficient evolutionary distance (about one-third of variants) had a 91.6 to 96.8% likelihood of being deleterious. Three algorithms (SIFT, PolyPhen, and A-GVGD) that differentiate one variant from another at a given codon did not significantly improve predictive value over conservation score alone using the BLOSUM62 matrix. However, when all four methods were in agreement (62.7% of variants), predictive value improved to 88.1%. These results confirm a high predictive value for methods that use evolutionary sequence conservation, with or without considering protein structural change, to predict the clinical consequences of missense variants. The methods can be generalized across genes that cause different types of genetic disease. The results support the clinical use of computational methods as one tool to help interpret missense variants in genes associated with human genetic disease.