The timing of HIV-1 infection of cells that persist on therapy is not strongly influenced by replication competency or cellular tropism of the provirus.

People with HIV-1 (PWH) on antiretroviral therapy (ART) can maintain undetectable virus levels, but a small pool of infected cells persists. This pool is largely comprised of defective proviruses that may produce HIV-1 proteins but are incapable of making infectious virus, with only a fraction (~10%) of these cells harboring intact viral genomes, some of which produce infectious virus following ex vivo stimulation (i.e. inducible intact proviruses). A majority of the inducible proviruses that persist on ART are formed near the time of therapy initiation. Here we compared proviral DNA (assessed here as 3' half genomes amplified from total cellular DNA) and inducible replication competent viruses in the pool of infected cells that persists during ART to determine if the original infection of these cells occurred at comparable times prior to therapy initiation. Overall, the average percent of proviruses that formed late (i.e. around the time of ART initiation, 60%) did not differ from the average percent of replication competent inducible viruses that formed late (69%), and this was also true for proviral DNA that was hypermutated (57%). Further, there was no evidence that entry into the long-lived infected cell pool was impeded by the ability to use the CXCR4 coreceptor, nor was the formation of long-lived infected cells enhanced during primary infection, when viral loads are exceptionally high. We observed that infection of cells that transitioned to be long-lived was enhanced among people with a lower nadir CD4+ T cell count. Together these data suggest that the timing of infection of cells that become long-lived is impacted more by biological processes associated with immunodeficiency before ART than the replication competency and/or cellular tropism of the infecting virus or the intactness of the provirus. Further research is needed to determine the mechanistic link between immunodeficiency and the timing of infected cells transitioning to the long-lived pool, particularly whether this is due to differences in infected cell clearance, turnover rates and/or homeostatic proliferation before and after ART.

Effective Human Immunodeficiency Virus Molecular Surveillance Requires Identification of Incident Cases of Infection.

BACKGROUND: Ending the human immunodeficiency virus (HIV) epidemic requires knowledge of key drivers of spread of HIV infection. METHODS: Between 1996 and 2018, 1119 newly and previously diagnosed, therapy-naive persons with HIV (PWH) from San Diego were followed. A genetic distance-based network was inferred using pol sequences, and genetic clusters grew over time through linkage of sequences from newly observed infections. Cox proportional hazards models were used to identify factors associated with the rate of growth. These results were used to predict the impact of a hypothetical intervention targeting PWH with incident infection. Comparison was made to the Centers for Disease Control and Prevention (CDC) Ending the HIV Epidemic (EHE) molecular surveillance strategy, which prioritizes clusters recently linked to all new HIV diagnoses and does not incorporate data on incident infections. RESULTS: Overall, 219 genetic linkages to incident infections were identified over a median follow-up of 8.8 years. Incident cluster growth was strongly associated with proportion of PWH in the cluster who themselves had incident infection (hazard ratio, 44.09 [95% confidence interval, 17.09-113.78]). The CDC EHE molecular surveillance strategy identified 11 linkages to incident infections a genetic distance threshold of 0.5%, and 24 linkages at 1.5%. CONCLUSIONS: Over the past 2 decades, incident infections drove incident HIV cluster growth in San Diego. The current CDC EHE molecular detection and response strategy would not have identified most transmission events arising from those with incident infection in San Diego. Molecular surveillance that includes detection of incident cases will provide a more effective strategy for EHE.

The replication-competent HIV-1 latent reservoir is primarily established near the time of therapy initiation.

Although antiretroviral therapy (ART) is highly effective at suppressing HIV-1 replication, the virus persists as a latent reservoir in resting CD4+ T cells during therapy. This reservoir forms even when ART is initiated early after infection, but the dynamics of its formation are largely unknown. The viral reservoirs of individuals who initiate ART during chronic infection are generally larger and genetically more diverse than those of individuals who initiate therapy during acute infection, consistent with the hypothesis that the reservoir is formed continuously throughout untreated infection. To determine when viruses enter the latent reservoir, we compared sequences of replication-competent viruses from resting peripheral CD4+ T cells from nine HIV-positive women on therapy to viral sequences circulating in blood collected longitudinally before therapy. We found that, on average, 71% of the unique viruses induced from the post-therapy latent reservoir were most genetically similar to viruses replicating just before ART initiation. This proportion is far greater than would be expected if the reservoir formed continuously and was always long lived. We conclude that ART alters the host environment in a way that allows the formation or stabilization of most of the long-lived latent HIV-1 reservoir, which points to new strategies targeted at limiting the formation of the reservoir around the time of therapy initiation.

Characterizing HIV transmission networks across the United States.

BACKGROUND: Clinically, human immunodeficiency virus type 1 (HIV-1) pol sequences are used to evaluate for drug resistance. These data can also be used to evaluate transmission networks and help describe factors associated with transmission risk. METHODS: HIV-1 pol sequences from participants at 5 sites in the CFAR Network of Integrated Clinical Systems (CNICS) cohort from 2000-2009 were analyzed for genetic relatedness. Only the first available sequence per participant was included. Inferred transmission networks ("clusters") were defined as ≥2 sequences with ≤1.5% genetic distance. Clusters including ≥3 patients ("networks") were evaluated for clinical and demographic associations. RESULTS: Of 3697 sequences, 24% fell into inferred clusters: 155 clusters of 2 individuals ("dyads"), 54 clusters that included 3-14 individuals ("networks"), and 1 large cluster that included 336 individuals across all study sites. In multivariable analyses, factors associated with being in a cluster included not using antiretroviral (ARV) drugs at time of sampling (P < .001), sequence collected after 2004 (P < .001), CD4 cell count >350 cells/mL (P < .01), and viral load 10,000-100,000 copies/mL (P < .001) or >100,000 copies/mL (P < .001). In networks, women were more likely to cluster with other women (P < .001), and African Americans with other African Americans (P < .001). CONCLUSIONS: Molecular epidemiology can be applied to study HIV transmission networks in geographically and demographically diverse cohorts. Clustering was associated with lack of ARV use and higher viral load, implying transmission may be interrupted by earlier diagnosis and treatment. Observed female and African American networks reinforce the importance of diagnosis and prevention efforts targeted by sex and race.

The relatedness of HIV epidemics in the United States-Mexico border region.

Phylogeography can improve the understanding of local and worldwide HIV epidemics, including the migration of subepidemics across national borders. We analyzed HIV-1 sequences sampled from Mexico and San Diego, California to determine the relatedness of these epidemics. We sampled the HIV epidemics in (1) Mexico by downloading all publicly available HIV-1 pol sequences from antiretroviral-naive individuals in GenBank (n = 100) and generating similar sequences from cohorts of injection drug users and female sex workers in Tijuana, Mexico (n = 27) and (2) in San Diego, California by pol sequencing well-characterized primary (n = 395) and chronic (n = 267) HIV infection cohorts. Estimates of population structure (F(ST)), genetic distance cluster analysis, and a cladistic measure of migration events (Slatkin-Maddison test) were used to assess the relatedness of the epidemics. Both a test of population differentiation (F(ST) = 0.06; p < 0.01) and a cladistic estimate of migration events (84 migrations, p < 0.01) indicated that the Tijuana and San Diego epidemics were not freely mixing. A conservative cluster analysis identified 72 clusters (two or more sequences), with two clusters containing both Mexican and San Diego sequences (permutation p < 0.01). Analysis of this very large dataset of HIV-1 sequences suggested that the HIV-1 epidemics in San Diego, California and Tijuana, Mexico are distinct. Larger epidemiological studies are needed to quantify the magnitude and associations of cross-border mixing.

Comparison of methods to detect HIV dual infection.

Current methods to detect intraclade HIV dual infection are poorly suited for determining its prevalence in large cohorts. To investigate the potential of ultra-deep sequencing to screen for dual infection, we compared it to bulk sequence-based synonymous mixture index and the current standard of single genome sequencing. The synonymous mixture index identified samples likely to harbor dual infection, while ultra-deep sequencing captured more intra-host viral diversity than single genome sequencing at approximately 40% of the cost and 20% of the laboratory and analysis time. The synonymous mixture index and ultra-deep sequencing are promising methods for rapid and cost-effective systematic identification of HIV dual infection.

Response to Comment on "The Origins of Sexually Transmitted HIV Among Men Who Have Sex with Men"

In this investigation, we evaluated explanations for the unusual degree of genetic diversity in HIV populations within the sampled seminal cell and plasma compartments observed in our previous study. These analyses included clonal sequencing of HIV DNA in peripheral blood mononuclear cells, ultradeep sequencing of HIV RNA in blood plasma, human leukocyte antigen (HLA) haplotyping of previously used samples, and a BLAST screen against both a local and public repository of HIV-1 sequences, and the investigations to determine whether these observations were secondary to contamination or artifact were unsuccessful. As there are very few HIV sequences from seminal cell tissues and transmission pairs described in the literature, future studies that evaluate more transmission pairs with sampling from multiple anatomic compartments and at multiple time points will most likely be required to resolve this controversy.

Protease polymorphisms in HIV-1 subtype CRF01_AE represent selection by antiretroviral therapy and host immune pressure.

BACKGROUND: Most of our knowledge about how antiretrovirals and host immune responses influence the HIV-1 protease gene is derived from studies of subtype B virus. We investigated the effect of protease resistance-associated mutations (PRAMs) and population-based HLA haplotype frequencies on polymorphisms found in CRF01_AE pro. METHODS: We used all CRF01_AE protease sequences retrieved from the LANL database and obtained regional HLA frequencies from the dbMHC database. Polymorphisms and major PRAMs in the sequences were identified using the Stanford Resistance Database, and we performed phylogenetic and selection analyses using HyPhy. HLA binding affinities were estimated using the Immune Epitope Database and Analysis. RESULTS: Overall, 99% of CRF01_AE sequences had at least 1 polymorphism and 10% had at least 1 major PRAM. Three polymorphisms (L10 V, K20RMI and I62 V) were associated with the presence of a major PRAM (P < 0.05). Compared to the subtype B consensus, six additional polymorphisms (I13 V, E35D, M36I, R41K, H69K, L89M) were identified in the CRF01_AE consensus; all but L89M were located within epitopes recognized by HLA class I alleles. Of the predominant HLA haplotypes in the Asian regions of CRF01_AE origin, 80% were positively associated with the observed polymorphisms, and estimated HLA binding affinity was estimated to decrease 19-40 fold with the observed polymorphisms at positions 35, 36 and 41. CONCLUSION: Polymorphisms in CRF01_AE protease gene were common, and polymorphisms at residues 10, 20 and 62 most likely represent selection by use of protease inhibitors, whereas R41K and H69K were more likely attributable to recognition of epitopes by the HLA haplotypes of the host population.

Rapid asymmetric evolution of a dual-coding tumor suppressor INK4a/ARF locus contradicts its function.

INK4a/ARF tumor suppressor locus encodes two protein products, INK4a and ARF, essential for controlling tumorigenesis and mutated in more than half of human cancers. There is no resemblance between the two proteins: their coding regions are assembled by alternative splicing of two mutually exclusive 5' exons into a constitutive one containing overlapping out-of-phase reading frames. We show that the dual-coding arrangement conflicts with the high cost of mutations within INK4a/ARF. Unexpectedly, the locus evolves rapidly and asymmetrically, with ARF accumulating the majority of amino acid replacements. Rapid evolution drives both INK4a and ARF proteins out of sync with other members of the RB and p53 tumor suppressor pathways, both of which are controlled by the locus. Yet, the asymmetric behavior may be an intrinsic property of dual-coding exons: INK4a/ARF closely mimics the evolution of 90 newly identified genes with similar dual-coding structure. Thus, the strong link between mutations in INK4a/ARF and cancer may be a direct consequence of the architecture of the locus.

A first look at ARFome: dual-coding genes in mammalian genomes.

Coding of multiple proteins by overlapping reading frames is not a feature one would associate with eukaryotic genes. Indeed, codependency between codons of overlapping protein-coding regions imposes a unique set of evolutionary constraints, making it a costly arrangement. Yet in cases of tightly coexpressed interacting proteins, dual coding may be advantageous. Here we show that although dual coding is nearly impossible by chance, a number of human transcripts contain overlapping coding regions. Using newly developed statistical techniques, we identified 40 candidate genes with evolutionarily conserved overlapping coding regions. Because our approach is conservative, we expect mammals to possess more dual-coding genes. Our results emphasize that the skepticism surrounding eukaryotic dual coding is unwarranted: rather than being artifacts, overlapping reading frames are often hallmarks of fascinating biology.

Site-to-site variation of synonymous substitution rates.

We develop a new model for studying the molecular evolution of protein-coding DNA sequences. In contrast to existing models, we incorporate the potential for site-to-site heterogeneity of both synonymous and nonsynonymous substitution rates. We demonstrate that within-gene heterogeneity of synonymous substitution rates appears to be common. Using the new family of models, we investigate the utility of a variety of new statistical inference procedures, and we pay particular attention to issues surrounding the detection of sites undergoing positive selection. We discuss how failure to model synonymous rate variation in the model can lead to misidentification of sites as positively selected.

Semen-specific genetic characteristics of human immunodeficiency virus type 1 env.

Human immunodeficiency virus type 1 (HIV-1) in the male genital tract may comprise virus produced locally in addition to virus transported from the circulation. Virus produced in the male genital tract may be genetically distinct, due to tissue-specific cellular characteristics and immunological pressures. HIV-1 env sequences derived from paired blood and semen samples from the Los Alamos HIV Sequence Database were analyzed to ascertain a male genital tract-specific viral signature. Machine learning algorithms could predict seminal tropism based on env sequences with accuracies exceeding 90%, suggesting that a strong genetic signature does exist for virus replicating in the male genital tract. Additionally, semen-derived viral populations exhibited constrained diversity (P < 0.05), decreased levels of positive selection (P < 0.025), decreased CXCR4 coreceptor utilization, and altered glycosylation patterns. Our analysis suggests that the male genital tract represents a distinct selective environment that contributes to the apparent genetic bottlenecks associated with the sexual transmission of HIV-1.