Dynamic correlation between intrahost HIV-1 quasispecies evolution and disease progression

Recombination smooths the time signal disrupted by latency in within-host HIV phylogenies

Within-host Human immunodeficiency virus (HIV) evolution involves several features that may disrupt standard phylogenetic reconstruction. One important feature is reactivation of latently integrated provirus, which has the potential to disrupt the temporal signal, leading to variation in the branch lengths and apparent evolutionary rates in a tree. Yet, real within-host HIV phylogenies tend to show clear, ladder-like trees structured by the time of sampling. Another important feature is recombination, which violates the fundamental assumption that evolutionary history can be represented by a single bifurcating tree. Thus, recombination complicates the within-host HIV dynamic by mixing genomes and creating evolutionary loop structures that cannot be represented in a bifurcating tree. In this paper, we develop a coalescent-based simulator of within-host HIV evolution that includes latency, recombination, and effective population size dynamics that allows us to study the relationship between the true, complex genealogy of within-host HIV evolution, encoded as an ancestral recombination graph (ARG), and the observed phylogenetic tree. To compare our ARG results to the familiar phylogeny format, we calculate the expected bifurcating tree after decomposing the ARG into all unique site trees, their combined distance matrix, and the overall corresponding bifurcating tree. While latency and recombination separately disrupt the phylogenetic signal, remarkably, we find that recombination recovers the temporal signal of within-host HIV evolution caused by latency by mixing fragments of old, latent genomes into the contemporary population. In effect, recombination averages over extant heterogeneity, whether it stems from mixed time signals or population bottlenecks. Furthermore, we establish that the signals of latency and recombination can be observed in phylogenetic trees despite being an incorrect representation of the true evolutionary history. Using an approximate Bayesian computation method, we develop a set of statistical probes to tune our simulation model to nine longitudinally sampled within-host HIV phylogenies. Because ARGs are exceedingly difficult to infer from real HIV data, our simulation system allows investigating effects of latency, recombination, and population size bottlenecks by matching decomposed ARGs to real data as observed in standard phylogenies.

Intrahost Genetic Diversity of Dengue Virus in Human Hosts and Mosquito Vectors under Natural Conditions Which Impact Replicative Fitness In Vitro

Dengue virus (DENV) is an arbovirus whose transmission cycle involves disparate hosts: humans and mosquitoes. The error-prone nature of viral RNA replication drives the high mutation rates, and the consequently high genetic diversity affects viral fitness over this transmission cycle. A few studies have been performed to investigate the intrahost genetic diversity between hosts, although their mosquito infections were performed artificially in the laboratory setting. Here, we performed whole-genome deep sequencing of DENV-1 (n = 11) and DENV-4 (n = 13) derived from clinical samples and field-caught mosquitoes from the houses of naturally infected patients, in order to analyze the intrahost genetic diversity of DENV between host types. Prominent differences in DENV intrahost diversity were observed in the viral population structure between DENV-1 and DENV-4, which appear to be associated with differing selection pressures. Interestingly, three single amino acid substitutions in the NS2A (K81R), NS3 (K107R), and NS5 (I563V) proteins in DENV-4 appear to be specifically acquired during infection in Ae. aegypti mosquitoes. Our in vitro study shows that the NS2A (K81R) mutant replicates similarly to the wild-type infectious clone-derived virus, while the NS3 (K107R), and NS5 (I563V) mutants have prolonged replication kinetics in the early phase in both Vero and C6/36 cells. These findings suggest that DENV is subjected to selection pressure in both mosquito and human hosts. The NS3 and NS5 genes may be specific targets of diversifying selection that play essential roles in early processing, RNA replication, and infectious particle production, and they are potentially adaptive at the population level during host switching.

Deep-sequencing of viral genomes from a large and diverse cohort of treatment-naive HIV-infected persons shows associations between intrahost genetic diversity and viral load

BACKGROUND

Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, the association between intrahost diversity and disease progression markers has not been investigated in large and diverse cohorts for which the majority of the genome has been deep-sequenced. Viral load (VL) is a key progression marker and understanding of its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment.

METHODS

We analysed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between VL and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure.

RESULTS

We confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Finally, equivalent analysis based on variation in HIV consensus sequences explained only 2% of VL variance.

CONCLUSIONS

Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes.

TRIAL REGISTRATION

Samples included in this study were derived from participants who consented in the clinical trial, START (NCT00867048) (23), run by the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT). All the participant sites are listed here: http://www.insight-trials.org/start/my_phpscript/participating.php?by=site.

In Depth Viral Diversity Analysis in Atypical Neurological and Neonatal Chikungunya Infections in Rio de Janeiro, Brazil

Chikungunya virus (CHIKV) is an arthropod-borne virus (arbovirus) transmitted by Aedes mosquitoes. The human infection usually manifests as a febrile and incapacitating arthritogenic illness, self-limiting and non-lethal. However, since 2013, CHIKV spreading through the tropics and to the Americas was accompanied by an increasing number of cases of atypical disease presentation, namely severe neuropathies and neonatal infection due to intrapartum vertical transmission. The pathophysiological mechanisms underlying these conditions have not been fully elucidated. However, arbovirus intrahost genetic diversity is thought to be linked to viral pathogenesis. To determine whether particular viral variants could be somehow associated, we analyzed the intrahost genetic diversity of CHIKV in three infected patients with neurological manifestations and three mothers infected during the intrapartum period, as well as their babies following vertical transmission. No statistically supported differences were observed for the genetic variability (nucleotide substitutions/gene length) along the genome between the groups. However, the newborn and cerebrospinal fluid samples (corresponding to virus passed through the placenta and/or the blood–brain barrier (BBB)) presented a different composition of their intrahost mutant ensembles compared to maternal or patient serum samples, even when concurrent. This finding could be consistent with the unidirectional virus transmission through these barriers, and the effect of selective bottlenecks during the transmission event. In addition, a higher proportion of defective variants (insertions/deletions and stop codons) was detected in the CSF and maternal samples and those were mainly distributed within the viral non-structural genes. Since defective viral genomes in RNA viruses are known to contribute to the outcome of acute viral infections and influence disease severity, their role in these atypical cases should be further investigated. Finally, with the in silico approach adopted, we detected no relevant non-conservative mutational pattern that could provide any hint of the pathophysiological mechanisms underlying these atypical cases. The present analysis represents a unique contribution to our understanding of the transmission events in these cases and generates hypotheses regarding underlying mechanisms, that can be explored further.

In Silico Analysis of Dengue Virus Serotype 2 Mutations Detected at the Intrahost Level in Patients with Different Clinical Outcomes

Intrahost genetic diversity is thought to facilitate arbovirus adaptation to changing environments and hosts, and it may also be linked to viral pathogenesis. Intending to shed light on the viral determinants for severe dengue pathogenesis, we previously analyzed the DENV-2 intrahost genetic diversity in 68 patients clinically classified as dengue fever (n = 31), dengue with warning signs (n = 19), and severe dengue (n = 18), performing viral whole-genome deep sequencing from clinical samples with an amplicon-free approach. From it, we identified a set of 141 relevant mutations distributed throughout the viral genome that deserved further attention. Therefore, we employed molecular modeling to recreate three-dimensional models of the viral proteins and secondary RNA structures to map the mutations and assess their potential effects. Results showed that, in general lines, disruptive variants were identified primarily among dengue fever cases. In contrast, potential immune-escape variants were associated mainly with warning signs and severe cases, in line with the latter's longer intrahost evolution times. Furthermore, several mutations were located on protein-surface regions, with no associated function. They could represent sites of further investigation, as the interaction of viral and host proteins is critical for both host immunomodulation and virus hijacking of the cellular machinery. The present analysis provides new information about the implications of the intrahost genetic diversity of DENV-2, contributing to the knowledge about the viral factors possibly involved in its pathogenesis within the human host. Strengthening our results with functional studies could allow many of these variants to be considered in the design of therapeutic or prophylactic compounds and the improvement of diagnostic assays. IMPORTANCE Previous evidence showed that intrahost genetic diversity in arboviruses may be linked to viral pathogenesis and that one or a few amino acid replacements within a single protein are enough to modify a biological feature of an RNA virus. To assess dengue virus serotype 2 determinants potentially involved in pathogenesis, we previously analyzed the intrahost genetic diversity of the virus in patients with different clinical outcomes and identified a set of 141 mutations that deserved further study. Thus, through a molecular modeling approach, we showed that disruptive variants were identified primarily among cases with mild dengue fever, while potential immune-escape variants were mainly associated with cases of greater severity. We believe that some of the variants pointed out in this study were attractive enough to be potentially considered in future intelligent designs of therapeutic or prophylactic compounds or the improvement of diagnostic tools. The present analysis provides new information about DENV-2 viral factors possibly involved in its pathogenesis within the human host.

Classification of small ruminant lentivirus subtype A2, subgroups 1 and 2 based on whole genome comparisons and complex recombination patterns

Background: Small ruminant lentiviruses (SRLVs) cause a multisystemic chronic wasting disease in sheep across much of the world. SRLV subtype A2 is prevalent in North America and further classified into multiple subgroups based on variation in the group antigens gene (gag) and envelope (env) genes. In sheep, the ovine transmembrane protein 154 (TMEM154) gene is associated with SRLV susceptibility. Ewes with at least one copy of TMEM154 encoding a full-length protein with glutamate at position 35 (E35; haplotypes 2 and 3), are highly susceptible to SRLV infection while ewes with any combination of TMEM154 haplotypes which encodes lysine (K35; haplotype 1), or truncated proteins (haplotypes 4 and 6) are several times less so. A2 subgroups 1 and 2 are associated with host TMEM154 genotypes; subgroup 1 with the K35/K35 genotype and subgroup 2 with the E35/E35 genotype.

Methods:  Sequence variation within and among full-length assemblies of SRLV subtype A2 subgroups 1 and 2 was analyzed to identify genome-scale recombination patterns and subgroup-specific variants.

Results:  Consensus viral genomes were assembled from 23 infected sheep, including animals of assorted TMEM154 genotypes comprised of haplotypes 1, 2, or 3. Viral genome analysis identified viral subgroups 1 and 2 among the samples, and revealed additional sub-structure within subgroup 2 based on models predicting complex patterns of recombination between the two subgroups in several genomes. Animals with evidence of dual subgroup infection also possessed the most diverse quasi-species and the most highly recombined consensus genomes. After accounting for recombination, 413 subgroup diagnostic single nucleotide polymorphisms (SNPs) were identified.

Conclusions:  The viral subgroup framework developed to classify SRLV consensus genomes along a continuum of recombination suggests that animals with the TMEM154 E35/K35 genotype may represent a reservoir for producing viral genomes representing recombination between A2 subgroups 1 and 2.

Machine Learning Based Clinical Decision Support System for Early COVID-19 Mortality Prediction

The coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, is an acute respiratory disease that has been classified as a pandemic by the World Health Organization (WHO). The sudden spike in the number of infections and high mortality rates have put immense pressure on the public healthcare systems. Hence, it is crucial to identify the key factors for mortality prediction to optimize patient treatment strategy. Different routine blood test results are widely available compared to other forms of data like X-rays, CT-scans, and ultrasounds for mortality prediction. This study proposes machine learning (ML) methods based on blood tests data to predict COVID-19 mortality risk. A powerful combination of five features: neutrophils, lymphocytes, lactate dehydrogenase (LDH), high-sensitivity C-reactive protein (hs-CRP), and age helps to predict mortality with 96% accuracy. Various ML models (neural networks, logistic regression, XGBoost, random forests, SVM, and decision trees) have been trained and performance compared to determine the model that achieves consistently high accuracy across the days that span the disease. The best performing method using XGBoost feature importance and neural network classification, predicts with an accuracy of 90% as early as 16 days before the outcome. Robust testing with three cases based on days to outcome confirms the strong predictive performance and practicality of the proposed model. A detailed analysis and identification of trends was performed using these key biomarkers to provide useful insights for intuitive application. This study provide solutions that would help accelerate the decision-making process in healthcare systems for focused medical treatments in an accurate, early, and reliable manner.

Dengue Virus Serotype 2 Intrahost Diversity in Patients with Different Clinical Outcomes

Intrahost genetic diversity is thought to facilitate arbovirus adaptation to changing environments and hosts, and it might also be linked to viral pathogenesis. Dengue virus serotype 2 (DENV-2) has circulated in Brazil since 1990 and is associated with severe disease and explosive outbreaks. Intending to shed light on the viral determinants for severe dengue pathogenesis, we sought to analyze the DENV-2 intrahost genetic diversity in 68 patient cases clinically classified as dengue fever (n = 31), dengue with warning signs (n = 19), and severe dengue (n = 18). Unlike previous DENV intrahost diversity studies whose approaches employed PCR, here we performed viral whole-genome deep sequencing from clinical samples with an amplicon-free approach, representing the real intrahost diversity scenario. Striking differences were detected in the viral population structure between the three clinical categories, which appear to be driven mainly by different infection times and selection pressures, rather than being linked with the clinical outcome itself. Diversity in the NS2B gene, however, showed to be constrained, irrespective of clinical outcome and infection time. Finally, 385 non-synonymous intrahost single-nucleotide variants located along the viral polyprotein, plus variants located in the untranslated regions, were consistently identified among the samples. Of them, 124 were exclusively or highly detected among cases with warning signs and among severe cases. However, there was no variant that by itself appeared to characterize the cases of greater severity, either due to its low intrahost frequency or the conservative effect on amino acid substitution. Although further studies are necessary to determine their real effect on viral proteins, this heightens the possibility of epistatic interactions. The present analysis represents an initial effort to correlate DENV-2 genetic diversity to its pathogenic potential and thus contribute to understanding the virus’s dynamics within its human host.

Classification of small ruminant lentivirus subtype A2, subgroups 1 and 2 based on whole genome comparisons and complex recombination patterns

Background: Small ruminant lentiviruses (SRLVs) cause a multisystemic chronic wasting disease in sheep across much of the world. SRLV subtype A2 is prevalent in North America and further classified into multiple subgroups based on variation in the group antigens gene (gag) and envelope (env) genes. In sheep, the ovine transmembrane protein 154 (TMEM154) gene is associated with SRLV susceptibility. Ewes with at least one copy of TMEM154 encoding a full-length protein with glutamate at position 35 (E35; haplotypes 2 and 3), are highly susceptible to SRLV infection while ewes with any combination of TMEM154 haplotypes which encodes lysine (K35; haplotype 1), or truncated proteins (haplotypes 4 and 6) are several times less so. A2 subgroups 1 and 2 are associated with host TMEM154 genotypes; subgroup 1 with the K35/K35 genotype and subgroup 2 with the E35/E35 genotype. Methods:  Sequence variation within and among full-length assemblies of SRLV subtype A2 subgroups 1 and 2 was analyzed to identify genome-scale recombination patterns and subgroup-specific variants. Results:  Consensus viral genomes were assembled from 23 infected sheep, including animals of assorted TMEM154 genotypes comprised of haplotypes 1, 2, or 3. Viral genome analysis identified viral subgroups 1 and 2 among the samples, and revealed additional sub-structure within subgroup 2 based on models predicting complex patterns of recombination between the two subgroups in several genomes. Animals with evidence of dual subgroup infection also possessed the most diverse quasi-species and the most highly recombined consensus genomes. After accounting for recombination, 413 subgroup diagnostic single nucleotide polymorphisms (SNPs) were identified. Conclusions:  The viral subgroup framework developed to classify SRLV consensus genomes along a continuum of recombination suggests that animals with the TMEM154 E35/K35 genotype may represent a reservoir for producing viral genomes representing recombination between A2 subgroups 1 and 2.

Evolutive Temporal Footprint of an HIV-1 Envelope Protein in an Epidemiologically Linked Cluster

Background:

The C2V3C3 region of gp 120, encoded by the HIV-1 envelope gene (env), is an important antigenic target, a key determinant for viral evolution and essential for determining epitopes for vaccines.

Methods:

The relationships among genetic sequence diversity, selective pressure, constraints on HIV-1 envelope protein were explored and also correlated this analysis with information entropy; hypermutation; HIV tropism; CD4+ T cell counts or HIV viral load. A total of 179 HIV-1 C2V3C3 sequences derived from cell-free plasma were used, determined from serial samples, in four epidemiologically linked individuals (one infected blood donor, two transfusion recipients and a sexual partner infected by one of the recipients) over a maximum period of 8 years. This study is important because it considers the analysis of patterns in genomic sequences, without drugs and over time.

Results:

A temporal relationship among information entropy, hypermutation, tropism switch, viral load, and CD4+ T cell count was determined. Changes in information entropy were time-dependent, and an increase in entropy was observed in the C2V3C3 region at amino acids G313 and F317-I320 (related to the GPGR-motif and coreceptor tropism), and at amino acids A281 in C2 and A346 in C3, related to immune escape.

Conclusion:

The increase of information entropy over time was correlated with hypermutation and the emergence of nonR5- strains, which are both associated with more variable genomes.

Phylogenetics in HIV transmission: taking within-host diversity into account

PURPOSE OF REVIEW

Within-host diversity complicates transmission models because it recognizes that between-host virus phylogenies are not identical to the transmission history among the infected hosts. This review presents the biological and theoretical foundations for recent development in this field, and shows that modern phylodynamic methods are capable of inferring realistic transmission histories from HIV sequence data.

RECENT FINDINGS

Transmission of single or multiple genetic variants from a donor's HIV population results in donor-recipient phylogenies with combinations of monophyletic, paraphyletic, and polyphyletic patterns. Large-scale simulations and analyses of many real HIV datasets have established that transmission direction, directness, or common source often can be inferred based on HIV sequence data. Phylodynamic reconstruction of HIV transmissions that include within-host HIV diversity have recently been established and made available in several software packages.

SUMMARY

Phylodynamic methods that include realistic features of HIV genetic diversification have come of age, significantly improving inference of key epidemiological parameters. This opens the door to more accurate surveillance and better-informed prevention campaigns.

A new method for inferring timetrees from temporally sampled molecular sequences

Pathogen timetrees are phylogenies scaled to time. They reveal the temporal history of a pathogen spread through the populations as captured in the evolutionary history of strains. These timetrees are inferred by using molecular sequences of pathogenic strains sampled at different times. That is, temporally sampled sequences enable the inference of sequence divergence times. Here, we present a new approach (RelTime with Dated Tips [RTDT]) to estimating pathogen timetrees based on a relative rate framework underlying the RelTime approach that is algebraic in nature and distinct from all other current methods. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. In analyses of an extensive collection of computer-simulated datasets, we found the accuracy of RTDT time estimates and the coverage probabilities of their confidence intervals (CIs) to be excellent. In analyses of empirical datasets, RTDT produced dates that were similar to those reported in the literature. In comparative benchmarking with Bayesian and non-Bayesian methods (LSD, TreeTime, and treedater), we found that no method performed the best in every scenario. So, we provide a brief guideline for users to select the most appropriate method in empirical data analysis. RTDT is implemented for use via a graphical user interface and in high-throughput settings in the newest release of cross-platform MEGA X software, freely available from http://www.megasoftware.net.

Pathogen timetrees trace the origins and evolutionary histories of strains in populations, hosts, and outbreaks. The tips of these molecular phylogenies often contain sampling time information because the sequences were generally obtained at different times during the disease outbreaks and propagation. We have developed a new method for inferring divergence times and confidence intervals for phylogenies with tip dates. The new Relative Times with Dated Tips (RTDT) methods showed excellent performance in the analysis of computer-simulated datasets, producing similar or better results in several evolutionary scenarios as compared to other fast, non-Bayesian methods. The new method is available in the cross-platform MEGA software package (version 10.1 and higher) that provides a graphical user interface and allows usage via a command line in scripting and high throughput analysis (www.megasoftware.net).

Variation in Intra-individual Lentiviral Evolution Rates: a Systematic Review of Human, Nonhuman Primate, and Felid Species

Lentiviral replication mediated by reverse transcriptase is considered to be highly error prone, leading to a high intra-individual evolution rate that promotes evasion of neutralization and persistent infection. Understanding lentiviral intra-individual evolutionary dynamics on a comparative basis can therefore inform research strategies to aid in studies of pathogenesis, vaccine design, and therapeutic intervention. We conducted a systematic review of intra-individual evolution rates for three species groups of lentiviruses-feline immunodeficiency virus (FIV), simian immunodeficiency virus (SIV), and human immunodeficiency virus (HIV). Overall, intra-individual rate estimates differed by virus but not by host, gene, or viral strain. Lentiviral infections in spillover (nonadapted) hosts approximated infections in primary (adapted) hosts. Our review consistently documents that FIV evolution rates within individuals are significantly lower than the rates recorded for HIV and SIV. FIV intra-individual evolution rates were noted to be equivalent to FIV interindividual rates. These findings document inherent differences in the evolution of FIV relative to that of primate lentiviruses, which may signal intrinsic difference of reverse transcriptase between these viral species or different host-viral interactions. Analysis of lentiviral evolutionary selection pressures at the individual versus population level is valuable for understanding transmission dynamics and the emergence of virulent and avirulent strains and provides novel insight for approaches to interrupt lentiviral infections.IMPORTANCE To the best of our knowledge, this is the first study that compares intra-individual evolution rates for FIV, SIV, and HIV following systematic review of the literature. Our findings have important implications for informing research strategies in the field of intra-individual virus dynamics for lentiviruses. We observed that FIV evolves more slowly than HIV and SIV at the intra-individual level and found that mutation rates may differ by gene sequence length but not by host, gene, strain, an experimental setting relative to a natural setting, or spillover host infection relative to primary host infection.

Applied shotgun metagenomics approach for the genetic characterization of dengue viruses

Dengue virus (DENV), an arthropod-borne virus, has rapidly spread in recent years. DENV diagnosis is performed through virus serology, isolation or molecular detection, while genotyping is usually done through Sanger sequencing of the envelope gene. This study aimed to optimize the use of shotgun metagenomics and subsequent bioinformatics analysis to detect and type DENV directly from clinical samples without targeted amplification. Additionally, presence of DENV quasispecies (intra-host variation) was revealed by detecting single nucleotide variants. Viral RNA was isolated with or without DNase-I treatment from 17 DENV (1-4) positive blood samples. cDNA libraries were generated using either a combination of the NEBNext® RNA to synthesize cDNA followed by Nextera XT DNA library preparation, or the TruSeq RNA V2 (TS) library preparation kit. Libraries were sequenced using both the MiSeq and NextSeq. Bioinformatic analysis showed complete ORFs for all samples by all approaches, but longer contigs and higher sequencing depths were obtained with the TS kit. No differences were observed between MiSeq and NextSeq sequencing. Detection of multiple DENV serotypes in a single sample was feasible. Finally, results were obtained within three days with associated reagents costs between €130-170/sample. Therefore, shotgun metagenomics is suitable for identification and typing of DENV in a clinical setting.

Insight into treatment of HIV infection from viral dynamics models

The odds of living a long and healthy life with HIV infection have dramatically improved with the advent of combination antiretroviral therapy. Along with the early development and clinical trials of these drugs, and new field of research emerged called viral dynamics, which uses mathematical models to interpret and predict the time-course of viral levels during infection and how they are altered by treatment. In this review, we summarize the contributions that virus dynamics models have made to understanding the pathophysiology of infection and to designing effective therapies. This includes studies of the multiphasic decay of viral load when antiretroviral therapy is given, the evolution of drug resistance, the long-term persistence latently infected cells, and the rebound of viremia when drugs are stopped. We additionally discuss new work applying viral dynamics models to new classes of investigational treatment for HIV, including latency-reversing agents and immunotherapy.

Intrahost Selection Pressures Drive Rapid Dengue Virus Microevolution in Acute Human Infections

Dengue, caused by four dengue virus serotypes (DENV-1 to DENV-4), is a highly prevalent mosquito-borne viral disease in humans. Yet, selection pressures driving DENV microevolution within human hosts (intrahost) remain unknown. We employed a whole-genome segmented amplification approach coupled with deep sequencing to profile DENV-3 intrahost diversity in peripheral blood mononuclear cell (PBMC) and plasma samples from 77 dengue patients. DENV-3 intrahost diversity appears to be driven by immune pressures as well as replicative success in PBMCs and potentially other replication sites. Hotspots for intrahost variation were detected in 59%-78% of patients in the viral Envelope and pre-Membrane/Membrane proteins, which together form the virion surface. Dominant variants at the hotspots arose via convergent microevolution, appear to be immune-escape variants, and were evolutionarily constrained at the macro level due to viral replication defects. Dengue is thus an example of an acute infection in which selection pressures within infected individuals drive rapid intrahost virus microevolution.

Identifying predictors of time-inhomogeneous viral evolutionary processes

Various factors determine the rate at which mutations are generated and fixed in viral genomes. Viral evolutionary rates may vary over the course of a single persistent infection and can reflect changes in replication rates and selective dynamics. Dedicated statistical inference approaches are required to understand how the complex interplay of these processes shapes the genetic diversity and divergence in viral populations. Although evolutionary models accommodating a high degree of complexity can now be formalized, adequately informing these models by potentially sparse data, and assessing the association of the resulting estimates with external predictors, remains a major challenge. In this article, we present a novel Bayesian evolutionary inference method, which integrates multiple potential predictors and tests their association with variation in the absolute rates of synonymous and non-synonymous substitutions along the evolutionary history. We consider clinical and virological measures as predictors, but also changes in population size trajectories that are simultaneously inferred using coalescent modelling. We demonstrate the potential of our method in an application to within-host HIV-1 sequence data sampled throughout the infection of multiple patients. While analyses of individual patient populations lack statistical power, we detect significant evidence for an abrupt drop in non-synonymous rates in late stage infection and a more gradual increase in synonymous rates over the course of infection in a joint analysis across all patients. The former is predicted by the immune relaxation hypothesis while the latter may be in line with increasing replicative fitness during the asymptomatic stage.

Detecting primary drug-resistant mutations in Korean HIV patients using ultradeep pyrosequencing

HIV primary resistance, drug resistance in treatment-naïve patients, is an emerging public health issue. The prevalence of HIV primary resistance mutations down to the level of 1% minor variants was investigated using ultradeep pyrosequencing (UDPS) in HIV-positive Korean blood donors and in treatment naïve chronic patients for the comparison. The entire pol region was sequenced from 25 HIV-positive blood donors, and 18 treatment-naïve chronic HIV patients. UDPS was successful in 19 blood donors and 18 chronic patients. In total, 1,011,338 sequence reads were aligned, and 28,093 sequence reads were aligned on average per sample. The prevalence of HIV primary resistance mutations in the HIV-positive blood donors and chronic HIV patients were 63.2% and 44.4% according to UDPS, respectively. Protease inhibitor (PI) drugs demonstrated different patterns in HIV-positive blood donors and chronic HIV patients, whereas non-nucleoside reverse transcriptase inhibitors (NNRTI), nucleoside reverse transcriptase inhibitors (NRTI), and integrase inhibitor (INI) drugs showed similar patterns between the two groups. Higher level of primary resistance prevalence was observed mainly because UDPS method could detect mutations in minor variants with 1-10% frequency. The higher resistance prevalence was observed in HIV-positive blood donors than in chronic patients. Considering that treatments for HIV-infected patients were recently amended to start at an earlier stage, information about degree of drug resistance to each drug between the two groups would help to establish future policies, design additional clinical trials, assess HIV patient care in Korea.

Recombination elevates the effective evolutionary rate and facilitates the establishment of HIV-1 infection in infants after mother-to-child transmission

BACKGROUND

Previous studies have demonstrated that single HIV-1 genotypes are commonly transmitted from mother to child, but such analyses primarily used single samples from mother and child. It is possible that in a single sample, obtained early after infection, only the most replication competent virus is detected even when other forms may have been transmitted. Such forms may have advantages later in infection, and may thus be detected in follow-up samples. Because HIV-1 frequently recombines, phylogenetic analyses that ignore recombination may miss transmission of multiple forms if they recombine after transmission. Moreover, recombination may facilitate adaptation, thus providing an advantage in establishing infection. The effect of recombination on viral evolution in HIV-1 infected children has not been well defined.

RESULTS

We analyzed full-length env sequences after single genome amplification from the plasma of four subtype B HIV-1 infected women (11-67 env clones from 1 time point within a month prior to delivery) and their non-breastfed, intrapartum-infected children (3-6 longitudinal time points per child starting at the time of HIV-1 diagnosis). To address the potential beneficial or detrimental effects of recombination, we used a recently developed hierarchical recombination detection method based on the pairwise homoplasy index (PHI)-test. Recombination was observed in 9-67% of the maternal sequences and in 25-60% of the child sequences. In the child, recombination only occurred between variants that had evolved after transmission; taking recombination into account, we identified transmission of only 1 or 2 phylogenetic lineages from mother to child. Effective HIV-1 evolutionary rates of HIV-1 were initially high in the child and slowed over time (after 1000 days). Recombination was associated with elevated evolutionary rates.

CONCLUSIONS

Our results confirm that 1-2 variants are typically transmitted from mothers to their newborns. They also demonstrate that early abundant recombination elevates the effective evolutionary rate, suggesting that recombination increases the rate of adaptation in HIV-1 evolution.

Genetic and functional characterization of HIV-1 Vif on APOBEC3G degradation: First report of emergence of B/C recombinants from North India

HIV-1 is characterized by high genetic heterogeneity which is a challenge for developing therapeutics. Therefore, it is necessary to understand the extent of genetic variations that HIV is undergoing in North India. The objective of this study was to determine the role of genetic and functional role of Vif on APOBEC3G degradation. Vif is an accessory protein involved in counteracting APOBEC3/F proteins. Genetic analysis of Vif variants revealed that Vif C variants were closely related to South African Vif C whereas Vif B variants and Vif B/C showed distinct geographic locations. This is the first report to show the emergence of Vif B/C in our population. The functional domains, motifs and phosphorylation sites were well conserved. Vif C variants differed in APOBEC3G degradation from Vif B variants. Vif B/C revealed similar levels of APOBEC3G degradation to Vif C confirming the presence of genetic determinants in C-terminal region. High genetic diversity was observed in Vif variants which may cause the emergence of more complex and divergent strains. These results reveal the genetic determinants of Vif in mediating APOBEC3G degradation and highlight the genetic information for the development of anti-viral drugs against HIV. Importance: Vif is an accessory HIV-1 protein which plays significant role in the degradation of human DNA-editing factor APOBEC3G, thereby impeding the antiretroviral activity of APOBEC3G. It is known that certain natural polymorphisms in Vif could degrade APOBEC3G relatively higher rate, suggesting its role in HIV-1 pathogenesis. This is the first report from North India showcasing genetic variations and novel polymorphisms in Vif gene. Subtype C is prevalent in India, but for the first time we observed putative B/C recombinants with a little high ability to degrade APOBEC3G indicating adaptation and evolving nature of virus in our population. Indian Vif C variants were able to degrade APOBEC3G well in comparison to Vif B variants. These genetic changes were most likely selected during adaptation of HIV to our population. These results elucidate that the genetic determinants of Vif and highlights the potential targets for therapeutics.

Identifying Recent HIV Infections: From Serological Assays to Genomics

In this paper, we review serological and molecular based methods to identify HIV infection recency. The accurate identification of recent HIV infection continues to be an important research area and has implications for HIV prevention and treatment interventions. Longitudinal cohorts that follow HIV negative individuals over time are the current gold standard approach, but they are logistically challenging, time consuming and an expensive enterprise. Methods that utilize cross-sectional testing and biomarker information have become an affordable alternative to the longitudinal approach. These methods use well-characterized biological makers to differentiate between recent and established HIV infections. However, recent results have identified a number of limitations in serological based assays that are sensitive to the variability in immune responses modulated by HIV subtypes, viral load and antiretroviral therapy. Molecular methods that explore the dynamics between the timing of infection and viral evolution are now emerging as a promising approach. The combination of serological and molecular methods may provide a good solution to identify recent HIV infection in cross-sectional data. As part of this review, we present the advantages and limitations of serological and molecular based methods and their potential complementary role for the identification of HIV infection recency.

The effect of genetic structure on molecular dating and tests for temporal signal

‘Dated‐tip’ methods of molecular dating use DNA sequences sampled at different times, to estimate the age of their most recent common ancestor. Several tests of ‘temporal signal’ are available to determine whether data sets are suitable for such analysis. However, it remains unclear whether these tests are reliable.

We investigate the performance of several tests of temporal signal, including some recently suggested modifications. We use simulated data (where the true evolutionary history is known), and whole genomes of methicillin‐resistant Staphylococcus aureus (to show how particular problems arise with real‐world data sets).

We show that all of the standard tests of temporal signal are seriously misleading for data where temporal and genetic structures are confounded (i.e. where closely related sequences are more likely to have been sampled at similar times). This is not an artefact of genetic structure or tree shape per se, and can arise even when sequences have measurably evolved during the sampling period. More positively, we show that a ‘clustered permutation’ approach introduced by Duchêne et al. (Molecular Biology and Evolution, 32, 2015, 1895) can successfully correct for this artefact in all cases and introduce techniques for implementing this method with real data sets.

The confounding of temporal and genetic structures may be difficult to avoid in practice, particularly for outbreaks of infectious disease, or when using ancient DNA. Therefore, we recommend the use of ‘clustered permutation’ for all analyses. The failure of the standard tests may explain why different methods of dating pathogen origins have reached such wildly different conclusions.

Baseline CD4+ T cell counts correlates with HIV-1 synonymous rate in HLA-B*5701 subjects with different risk of disease progression

HLA-B*5701 is the host factor most strongly associated with slow HIV-1 disease progression, although risk of progression may vary among patients carrying this allele. The interplay between HIV-1 evolutionary rate variation and risk of progression to AIDS in HLA-B*5701 subjects was studied using longitudinal viral sequences from high-risk progressors (HRPs) and low-risk progressors (LRPs). Posterior distributions of HIV-1 genealogies assuming a Bayesian relaxed molecular clock were used to estimate the absolute rates of nonsynonymous and synonymous substitutions for different set of branches. Rates of viral evolution, as well as in vitro viral replication capacity assessed using a novel phenotypic assay, were correlated with various clinical parameters. HIV-1 synonymous substitution rates were significantly lower in LRPs than HRPs, especially for sets of internal branches. The viral population infecting LRPs was also characterized by a slower increase in synonymous divergence over time. This pattern did not correlate to differences in viral fitness, as measured by in vitro replication capacity, nor could be explained by differences among subjects in T cell activation or selection pressure. Interestingly, a significant inverse correlation was found between baseline CD4⁺ T cell counts and mean HIV-1 synonymous rate (which is proportional to the viral replication rate) along branches representing viral lineages successfully propagating through time up to the last sampled time point. The observed lower replication rate in HLA-B*5701 subjects with higher baseline CD4⁺ T cell counts provides a potential model to explain differences in risk of disease progression among individuals carrying this allele.

The clinical course of HIV-1 infection is characterized by considerable variability in the rate of progression to acquired immunodeficiency syndrome (AIDS) among patients with different genetic background. The human leukocyte antigen (HLA) B*5701 is the host factor most strongly associated with slow HIV-1 disease progression. However, the risk of progression to AIDS also varies among patients carrying this specific allele. To gain a better understanding of the interplay between HIV-1 evolutionary rate variation and risk of disease progression, we followed untreated HLA-B*5701 subjects from early infection up to the onset of AIDS. The analysis of longitudinal viral sequences with advanced computational biology techniques based on coalescent Bayesian methods showed a highly significant association between lower synonymous substitution rates and higher baseline CD4⁺ T cell counts in HLA-B*5701 subjects. The finding provides a potential model to explain differences in risk of disease progression among individuals carrying this allele and might have translational impact on clinical practice, since synonymous rates, which are proportional to in vivo viral replication rates, could be used as a novel evolutionary marker of disease progression.

Reliable reconstruction of HIV-1 whole genome haplotypes reveals clonal interference and genetic hitchhiking among immune escape variants

BACKGROUND

Following transmission, HIV-1 evolves into a diverse population, and next generation sequencing enables us to detect variants occurring at low frequencies. Studying viral evolution at the level of whole genomes was hitherto not possible because next generation sequencing delivers relatively short reads.

RESULTS

We here provide a proof of principle that whole HIV-1 genomes can be reliably reconstructed from short reads, and use this to study the selection of immune escape mutations at the level of whole genome haplotypes. Using realistically simulated HIV-1 populations, we demonstrate that reconstruction of complete genome haplotypes is feasible with high fidelity. We do not reconstruct all genetically distinct genomes, but each reconstructed haplotype represents one or more of the quasispecies in the HIV-1 population. We then reconstruct 30 whole genome haplotypes from published short sequence reads sampled longitudinally from a single HIV-1 infected patient. We confirm the reliability of the reconstruction by validating our predicted haplotype genes with single genome amplification sequences, and by comparing haplotype frequencies with observed epitope escape frequencies.

CONCLUSIONS

Phylogenetic analysis shows that the HIV-1 population undergoes selection driven evolution, with successive replacement of the viral population by novel dominant strains. We demonstrate that immune escape mutants evolve in a dependent manner with various mutations hitchhiking along with others. As a consequence of this clonal interference, selection coefficients have to be estimated for complete haplotypes and not for individual immune escapes.

High-accuracy identification of incident HIV-1 infections using a sequence clustering based diversity measure

Accurate estimates of HIV-1 incidence are essential for monitoring epidemic trends and evaluating intervention efforts. However, the long asymptomatic stage of HIV-1 infection makes it difficult to effectively distinguish incident infections from chronic ones. Current incidence assays based on serology or viral sequence diversity are both still lacking in accuracy. In the present work, a sequence clustering based diversity (SCBD) assay was devised by utilizing the fact that viral sequences derived from each transmitted/founder (T/F) strain tend to cluster together at early stage, and that only the intra-cluster diversity is correlated with the time since HIV-1 infection. The dot-matrix pairwise alignment was used to eliminate the disproportional impact of insertion/deletions (indels) and recombination events, and so was the proportion of clusterable sequences (P_c) as an index to identify late chronic infections with declined viral genetic diversity. Tested on a dataset containing 398 incident and 163 chronic infection cases collected from the Los Alamos HIV database (last modified 2/8/2012), our SCBD method achieved 99.5% sensitivity and 98.8% specificity, with an overall accuracy of 99.3%. Further analysis and evaluation also suggested its performance was not affected by host factors such as the viral subtypes and transmission routes. The SCBD method demonstrated the potential of sequencing based techniques to become useful for identifying incident infections. Its use may be most advantageous for settings with low to moderate incidence relative to available resources. The online service is available at http://www.bioinfo.tsinghua.edu.cn:8080/SCBD/index.jsp.

Timing and order of transmission events is not directly reflected in a pathogen phylogeny

Pathogen phylogenies are often used to infer spread among hosts. There is, however, not an exact match between the pathogen phylogeny and the host transmission history. Here, we examine in detail the limitations of this relationship. First, all splits in a pathogen phylogeny of more than 1 host occur within hosts, not at the moment of transmission, predating the transmission events as described by the pretransmission interval. Second, the order in which nodes in a phylogeny occur may be reflective of the within-host dynamics rather than epidemiologic relationships. To investigate these phenomena, motivated by within-host diversity patterns, we developed a two-phase coalescent model that includes a transmission bottleneck followed by linear outgrowth to a maximum population size followed by either stabilization or decline of the population. The model predicts that the pretransmission interval shrinks compared with predictions based on constant population size or a simple transmission bottleneck. Because lineages coalesce faster in a small population, the probability of a pathogen phylogeny to resemble the transmission history depends on when after infection a donor transmits to a new host. We also show that the probability of inferring the incorrect order of multiple transmissions from the same host is high. Finally, we compare time of HIV-1 infection informed by genetic distances in phylogenies to independent biomarker data, and show that, indeed, the pretransmission interval biases phylogeny-based estimates of when transmissions occurred. We describe situations where caution is needed not to misinterpret which parts of a phylogeny that may indicate outbreaks and tight transmission clusters.

Inferring heterogeneous evolutionary processes through time: from sequence substitution to phylogeography

Molecular phylogenetic and phylogeographic reconstructions generally assume time-homogeneous substitution processes. Motivated by computational convenience, this assumption sacrifices biological realism and offers little opportunity to uncover the temporal dynamics in evolutionary histories. Here, we propose an evolutionary approach that explicitly relaxes the time-homogeneity assumption by allowing the specification of different infinitesimal substitution rate matrices across different time intervals, called epochs, along the evolutionary history. We focus on an epoch model implementation in a Bayesian inference framework that offers great modeling flexibility in drawing inference about any discrete data type characterized as a continuous-time Markov chain, including phylogeographic traits. To alleviate the computational burden that the additional temporal heterogeneity imposes, we adopt a massively parallel approach that achieves both fine- and coarse-grain parallelization of the computations across branches that accommodate epoch transitions, making extensive use of graphics processing units. Through synthetic examples, we assess model performance in recovering evolutionary parameters from data generated according to different evolutionary scenarios that comprise different numbers of epochs for both nucleotide and codon substitution processes. We illustrate the usefulness of our inference framework in two different applications to empirical data sets: the selection dynamics on within-host HIV populations throughout infection and the seasonality of global influenza circulation. In both cases, our epoch model captures key features of temporal heterogeneity that remained difficult to test using ad hoc procedures. [Bayesian inference; BEAGLE; BEAST; Epoch Model; phylogeography; Phylogenetics.]

Mathematical models of HIV replication and pathogenesis

This review outlines how mathematical models have been helpful, and continue to be so, for obtaining insights into the in vivo dynamics of HIV infection. The review starts with a discussion of a basic mathematical model that has been frequently used to study HIV dynamics. Some crucial results are described, including the estimation of key parameters that characterize the infection, and the generation of influential theories which argued that in vivo virus evolution is a key player in HIV pathogenesis. Subsequently, more recent concepts are reviewed that have relevance for disease progression, including the multiple infection of cells and the direct cell-to-cell transmission of the virus through the formation of virological synapses. These are important mechanisms that can influence the rate at which HIV spreads through its target cell population, which is tightly linked to the rate at which the disease progresses towards AIDS.

HIV-1 transmission during early infection in men who have sex with men: a phylodynamic analysis

BACKGROUND

Conventional epidemiological surveillance of infectious diseases is focused on characterization of incident infections and estimation of the number of prevalent infections. Advances in methods for the analysis of the population-level genetic variation of viruses can potentially provide information about donors, not just recipients, of infection. Genetic sequences from many viruses are increasingly abundant, especially HIV, which is routinely sequenced for surveillance of drug resistance mutations. We conducted a phylodynamic analysis of HIV genetic sequence data and surveillance data from a US population of men who have sex with men (MSM) and estimated incidence and transmission rates by stage of infection.

METHODS AND FINDINGS

We analyzed 662 HIV-1 subtype B sequences collected between October 14, 2004, and February 24, 2012, from MSM in the Detroit metropolitan area, Michigan. These sequences were cross-referenced with a database of 30,200 patients diagnosed with HIV infection in the state of Michigan, which includes clinical information that is informative about the recency of infection at the time of diagnosis. These data were analyzed using recently developed population genetic methods that have enabled the estimation of transmission rates from the population-level genetic diversity of the virus. We found that genetic data are highly informative about HIV donors in ways that standard surveillance data are not. Genetic data are especially informative about the stage of infection of donors at the point of transmission. We estimate that 44.7% (95% CI, 42.2%-46.4%) of transmissions occur during the first year of infection.

CONCLUSIONS

In this study, almost half of transmissions occurred within the first year of HIV infection in MSM. Our conclusions may be sensitive to un-modeled intra-host evolutionary dynamics, un-modeled sexual risk behavior, and uncertainty in the stage of infected hosts at the time of sampling. The intensity of transmission during early infection may have significance for public health interventions based on early treatment of newly diagnosed individuals.

Quantitative modeling of virus evolutionary dynamics and adaptation in serial passages using empirically inferred fitness landscapes

We describe a stochastic virus evolution model representing genomic diversification and within-host selection during experimental serial passages under cell culture or live-host conditions. The model incorporates realistic descriptions of the virus genotypes in nucleotide and amino acid sequence spaces, as well as their diversification from error-prone replications. It quantitatively considers factors such as target cell number, bottleneck size, passage period, infection and cell death rates, and the replication rate of different genotypes, allowing for systematic examinations of how their changes affect the evolutionary dynamics of viruses during passages. The relative probability for a viral population to achieve adaptation under a new host environment, quantified by the rate with which a target sequence frequency rises above 50%, was found to be most sensitive to factors related to sequence structure (distance from the wild type to the target) and selection strength (host cell number and bottleneck size). For parameter values representative of RNA viruses, the likelihood of observing adaptations during passages became negligible as the required number of mutations rose above two amino acid sites. We modeled the specific adaptation process of influenza A H5N1 viruses in mammalian hosts by simulating the evolutionary dynamics of H5 strains under the fitness landscape inferred from multiple sequence alignments of H3 proteins. In light of comparisons with experimental findings, we observed that the evolutionary dynamics of adaptation is strongly affected not only by the tendency toward increasing fitness values but also by the accessibility of pathways between genotypes constrained by the genetic code.

Evolution of the human immunodeficiency virus type 2 envelope in the first years of infection is associated with the dynamics of the neutralizing antibody response

BACKGROUND

Differently from HIV-1, HIV-2 disease progression usually takes decades without antiretroviral therapy and the majority of HIV-2 infected individuals survive as elite controllers with normal CD4⁺ T cell counts and low or undetectable plasma viral load. Neutralizing antibodies (Nabs) are thought to play a central role in HIV-2 evolution and pathogenesis. However, the dynamic of the Nab response and resulting HIV-2 escape during acute infection and their impact in HIV-2 evolution and disease progression remain largely unknown. Our objective was to characterize the Nab response and the molecular and phenotypic evolution of HIV-2 in association with Nab escape in the first years of infection in two children infected at birth.

RESULTS

CD4⁺ T cells decreased from about 50% to below 30% in both children in the first five years of infection and the infecting R5 viruses were replaced by X4 viruses within the same period. With antiretroviral therapy, viral load in child 1 decreased to undetectable levels and CD4+ T cells recovered to normal levels, which have been sustained at least until the age of 12. In contrast, viral load increased in child 2 and she progressed to AIDS and death at age 9. Beginning in the first year of life, child 1 raised high titers of antibodies that neutralized primary R5 isolates more effectively than X4 isolates, both autologous and heterologous. Child 2 raised a weak X4-specific Nab response that decreased sharply as disease progressed. Rate of evolution, nucleotide and amino acid diversity, and positive selection, were significantly higher in the envelope of child 1 compared to child 2. Rates of R5-to-X4 tropism switch, of V1 and V3 sequence diversification, and of convergence of V3 to a β-hairpin structure were related with rate of escape from the neutralizing antibodies.

CONCLUSION

Our data suggests that the molecular and phenotypic evolution of the human immunodeficiency virus type 2 envelope are related with the dynamics of the neutralizing antibody response providing further support for a model in which Nabs play an important role in HIV-2 pathogenesis.

Intra-host evolutionary rates in HIV-1C env and gag during primary infection

BACKGROUND

HIV-1 nucleotide substitution rates are central for understanding the evolution of HIV-1. Their accurate estimation is critical for analysis of viral dynamics, identification of divergence time of HIV variants, inference of HIV transmission clusters, and modeling of viral evolution.

METHODS

Intra-patient nucleotide substitution rates in HIV-1C gag and env gp120 V1C5 were analyzed in a longitudinal cohort of 32 individuals infected with a single viral variant. Viral quasispecies were derived by single genome amplification/sequencing from serially sampled blood specimens collected at median (IQR) of 5 (4-6) times per subject from enrollment (during Fiebig stages II to V) over a median (IQR) of 417 (351-471) days post-seroconversion (p/s). HIV-1C evolutionary rates were estimated by BEAST v.1.7 using a relaxed lognormal molecular clock model. The effect of antiretroviral therapy (ART) on substitution rates in gag and env was assessed in a subset of six individuals who started ARV therapy during the follow-up period.

RESULTS

During primary HIV-1C infection, the intra-patient substitution rates were estimated at a median (IQR) of 5.22E-03 (3.28E-03-7.55E-03) substitutions per site per year of infection within gag, and 1.58E-02 (9.99E-03-2.04E-02) substitutions per site per year within env gp120 V1C5. The substitution rates in env gp120 V1C5 were higher than in gag (p<0.001, Wilcoxon signed rank test). The median (IQR) relative rates of evolution at codon positions 1, 2, and 3 were 0.73 (0.48-0.84), 0.67 (0.52-0.86), and 1.54 (1.21-1.71) in gag, and 1.01 (0.86-1.15), 1.05 (0.99-1.21), and 0.86 (0.67-0.94) in env gp120 V1C5, respectively. A first to the third position codon rate ratio >1.0 within env was found in 25 (78.1%) cases, but only in 4 (12.5%) cases in gag, while a second to the third position codon rate ratio >1.0 in env was observed in 26 (81.3%) cases, but in gag only in 2 (6.3%) cases (p<0.001 for both comparisons, Fisher's exact test). No ART effect on substitution rates in gag and env was found, at least within the first 3-4 months after ART initiation. Individuals with early viral set point ⩾4.0 log10 copies/ml had higher substitution rates in env gp120 V1C5 (median (IQR) 1.88E-02 (1.54E-02-2.46E-02) vs. 1.04E (7.24E-03-1.55E-02) substitutions per site per year; p=0.017, Mann-Whitney sum rank test), while individuals with early viral set point ⩾3.0 log10 copies/ml had higher substitution rates in gag (median (IQR) 5.66E-03 (3.45E-03-7.94E-03) vs. 1.78E-03 (4.57E-04-5.15E-03); p=0.028; Mann-Whitney sum rank test).

CONCLUSIONS

The results suggest that in primary HIV-1C infection, (1) intra-host evolutionary rates in env gp120 V1C5 are about 3-fold higher than in gag; (2) selection pressure in env is more frequent than in gag; (3) initiation of ART does not change substitution rates in HIV-1C env or gag, at least within the first 3-4 months after starting ART; and (4) intra-host evolutionary rates in gag and env gp120 V1C5 are higher in individuals with elevated levels of early viral set point.

The intra-host evolutionary and population dynamics of human immunodeficiency virus type 1: a phylogenetic perspective

The intra-host evolutionary and population dynamics of the human immunodeficiency virus type 1 (HIV-1), the cause of the acquired immunodeficiency syndrome, have been the focus of one of the most extensive study efforts in the field of molecular evolution over the past three decades. As HIV-1 is among the fastest mutating organisms known, viral sequence data sampled over time from infected patients can provide, through phylogenetic analysis, significant insights about the tempo and mode of evolutionary processes shaped by complex interaction with the host milieu. Five main aspects are discussed: the patterns of HIV-1 intra-host diversity and divergence over time in relation to different phases of disease progression; the impact of selection on the temporal structure of HIV-1 intra-host genealogies inferred from longitudinally sampled viral sequences; HIV-1 intra-host sub-population structure; the potential relationship between viral evolutionary rate and disease progression and the central evolutionary role played by recombination occurring in super-infected cells.

Translating HIV sequences into quantitative fitness landscapes predicts viral vulnerabilities for rational immunogen design

A prophylactic or therapeutic vaccine offers the best hope to curb the HIV-AIDS epidemic gripping sub-Saharan Africa, but it remains elusive. A major challenge is the extreme viral sequence variability among strains. Systematic means to guide immunogen design for highly variable pathogens like HIV are not available. Using computational models, we have developed an approach to translate available viral sequence data into quantitative landscapes of viral fitness as a function of the amino acid sequences of its constituent proteins. Predictions emerging from our computationally defined landscapes for the proteins of HIV-1 clade B Gag were positively tested against new in vitro fitness measurements and were consistent with previously defined in vitro measurements and clinical observations. These landscapes chart the peaks and valleys of viral fitness as protein sequences change and inform the design of immunogens and therapies that can target regions of the virus most vulnerable to selection pressure.

High intrapatient HIV-1 evolutionary rate is associated with CCR5-to-CXCR4 coreceptor switch

In approximately 70% of individuals infected with HIV-1 subtype B, the virus switches coreceptor use from exclusively CCR5 use (R5 virus) to either inclusion of or exclusively CXCR4 use (X4 virus) during infection. This switch is associated with an accelerated loss of CD4(+) T-cells and a faster progression to AIDS. Despite intensive research, the mechanisms responsible for coreceptor switch remains elusive. In the present study, we investigated associations between viral evolutionary rate and selection pressure versus viral coreceptor use and rate of disease progression in eight patients with longitudinally sampled HIV-1 env V1-V3 sequences. By employing a Bayesian hierarchical phylogenetic model, we found that the HIV-1 evolutionary rate was more strongly associated with coreceptor switch than with rate of disease progression in terms of CD4(+)T-cell decline. Phylogenetic analyses showed that X4 variants evolved from R5 populations. In addition, coreceptor switch was associated with higher evolutionary rates on both the synonymous and non-synonymous substitution level, but not with dN/dS ratio rates. Our findings suggest that X4 viruses evolved from pre-existing R5 viral populations and that the evolution of coreceptor switch is governed by high replication rates rather than by selective pressure. Furthermore, the association of viral evolutionary rate was more strongly associated with coreceptor switch than disease progression. This adds to the understanding of the complex virus-host interplay that influences the evolutionary dynamics of HIV-1 coreceptor use.

Chikungunya fever: a clinical and virological investigation of outpatients on Reunion Island, South-West Indian Ocean

Background

Chikungunya virus (CHIKV) is responsible for acute febrile polyarthralgia and, in a proportion of cases, severe complications including chronic arthritis. CHIKV has spread recently in East Africa, South-West Indian Ocean, South-Asia and autochthonous cases have been reported in Europe. Although almost all patients are outpatients, medical investigations mainly focused on hospitalised patients.

Methodology/Principal Findings

Here, we detail clinico-biological characteristics of Chikungunya (CHIK) outpatients in Reunion Island (2006). 76 outpatients with febrile arthralgia diagnosed within less than 48 hours were included by general practitioners during the CuraChik clinical trial. CHIK was confirmed in 54 patients and excluded in 22. A detailed clinical and biological follow-up was organised, that included analysis of viral intrahost diversity and telephone survey until day 300. The evolution of acute CHIK included 2 stages: the ‘viral stage’ (day 1–day 4) was associated with rapid decrease of viraemia and improvement of clinical presentation; the ‘convalescent stage’ (day 5–day 14) was associated with no detectable viraemia but a slower clinical improvement. Women and elderly had a significantly higher number of arthralgia at inclusion and at day 300. Based on the study clinico-biological dataset, scores for CHIK diagnosis in patients with recent febrile acute polyarthralgia were elaborated using arthralgia on hands and wrists, a minor or absent myalgia and the presence of lymphopenia (<1G/L) as major orientation criteria. Finally, we observed that CHIKV intra-host genetic diversity increased over time and that a higher viral amino-acid complexity at the acute stage was associated with increased number of arthralgia and intensity of sequelae at day 300.

Conclusions/Significance

This study provided a detailed picture of clinico-biological CHIK evolution at the acute phase of the disease, allowed the elaboration of scores to assist CHIK diagnosis and investigated for the first time the impact of viral intra-host genetic diversity on the disease course.

The mosquito-transmitted chikungunya virus is responsible for acute febrile polyarthralgia and, in a proportion of cases, complications including chronic arthritis. Since 2005, it has massively re-emerged in the Old World. Although the large majority of patients are outpatients, the most detailed studies have focused previously on hospitalised patients (i.e., severe cases). Here, we report the detailed clinico-biological characteristics of ‘standard’ clinical presentations in patients followed-up by general practitioners in Reunion Island (2006) during the CuraChik clinical trial. At the onset of the disease, two stages were observed: (i) a ‘viral stage’ during the first 4 days, associated with an acute febrile polyarthralgic syndrome and a subsequent rapid clinical improvement; the main clinico-biological characteristics during that period were used to elaborate supportive chikungunya diagnostic scores, (ii) a ‘convalescent stage’ (days 5–14) with no detectable viraemia but a slower clinical improvement. Woman and elderly patients were found at risk for more symptomatic forms of the disease at both the acute and late stages (day 300) and we observed that the viral intra-host genetic diversity increased over time and that a higher viral amino-acid complexity at the acute stage was associated with more symptomatic illness at the late stage of the disease.

Interrelationship between HIV-1 fitness and mutation rate

Differences in replication fidelity, as well as mutator and antimutator strains, suggest that virus mutation rates are heritable and prone to natural selection. Human immunodeficiency virus type 1 (HIV-1) has many distinct advantages for the study of mutation rate optimization given the wealth of structural and biochemical data on HIV-1 reverse transcriptase (RT) and mutants. In this study, we conducted parallel analyses of mutation rate and viral fitness. In particular, a panel of 10 RT mutants-most having drug resistance phenotypes-was analyzed for their effects on viral fidelity and fitness. Fidelity differences were measured using single-cycle vector assays, while fitness differences were identified using ex vivo head-to-head competition assays. As anticipated, virus mutants possessing either higher or lower fidelity had a corresponding loss in fitness. While the virus panel was not chosen randomly, it is interesting that it included more viruses possessing a mutator phenotype rather than viruses possessing an antimutator phenotype. These observations provide the first description of an interrelationship between HIV-1 fitness and mutation rate and support the conclusion that mutator and antimutator phenotypes correlate with reduced viral fitness. In addition, the findings here help support a model in which fidelity comes at a cost of replication kinetics and may help explain why retroviruses like HIV-1 and RNA viruses maintain replication fidelity near the extinction threshold.

Vector-borne transmission imposes a severe bottleneck on an RNA virus population

RNA viruses typically occur in genetically diverse populations due to their error-prone genome replication. Genetic diversity is thought to be important in allowing RNA viruses to explore sequence space, facilitating adaptation to changing environments and hosts. Some arboviruses that infect both a mosquito vector and a mammalian host are known to experience population bottlenecks in their vectors, which may constrain their genetic diversity and could potentially lead to extinction events via Muller's ratchet. To examine this potential challenge of bottlenecks for arbovirus perpetuation, we studied Venezuelan equine encephalitis virus (VEEV) enzootic subtype IE and its natural vector Culex (Melanoconion) taeniopus, as an example of a virus-vector interaction with a long evolutionary history. Using a mixture of marked VEEV clones to infect C. taeniopus and real-time RT-PCR to track these clones during mosquito infection and dissemination, we observed severe bottleneck events that resulted in a significant drop in the number of clones present. At higher initial doses, the midgut was readily infected and there was a severe bottleneck at the midgut escape. Following a lower initial dose, the major bottleneck occurred at initial midgut infection. A second, less severe bottleneck was identified at the salivary gland infection stage following intrathoracic inoculation. Our results suggest that VEEV consistently encounters bottlenecks during infection, dissemination and transmission by its natural enzootic vector. The potential impacts of these bottlenecks on viral fitness and transmission, and the viral mechanisms that prevent genetic drift leading to extinction, deserve further study.

The ability of arboviruses to perpetuate in nature given that they must infect two disparate hosts (the mosquito vector and the vertebrate host) remains a mystery. We studied how viral genetic diversity is impacted by the dual host transmission cycle. Our studies of an enzootic cycle using Venezuelan equine encephalitis virus (VEEV) and its natural mosquito, Culex taeniopus, revealed the stages of infection that result in a viral population bottleneck. Using a set of marked VEEV clones and repeated sampling at various time points following C. taeniopus infection, we determined the number of clones in various mosquito tissues culminating in transmission. Bottlenecks were identified but the stage of occurrence was dependent on the dose that initiated infection. Understanding the points at which mosquito-borne viruses are constrained will shed light on the ways in which virus diversity varies, leading to selection of mutants that may result in host range changes or alterations in virulence.

HIV-1 envelope diversity 1 year after seroconversion predicts subsequent disease progression

OBJECTIVE

Recent studies have suggested that the dynamics of HIV-1 evolutionary rate reflect the rate of disease progression. We wished to determine whether viral diversity early in infection is predictive of the subsequent disease course.

DESIGN

HIV-1 envelope diversity at seroconversion and 1 year thereafter from 89 homosexual participants of the Amsterdam Cohort Studies on HIV infection and AIDS was correlated with clinical endpoints and markers of disease progression.

METHODS

Heteroduplex mobility assay (HMA) and sequencing followed by calculation of pairwise genetic distances were applied to determine HIV-1 envelope diversity. The HMA pattern (presence or absence of heteroduplexes) and sequence diversity were each tested for correlation with the clinical course of infection.

RESULTS

HMA pattern at 1-year postseroconversion was significantly associated with progression to AIDS and AIDS-related death, with presence of heteroduplexes associated with accelerated disease progression. Moreover, not only this dichotomous measure of viral diversity (absence or presence of heteroduplexes), but also genetic diversity itself was associated with disease course. HMA pattern was an independent predictor of accelerated disease progression, also when CCR5 genotype, human leukocyte antigen (HLA)-type, viral load, CD4 T-cell counts, and coreceptor use at viral load set point were included in the analysis.

CONCLUSION

Viral diversity early in HIV-1 infection is predictive of the subsequent disease progression. It remains to be established whether viral diversity itself plays a causal role in the increased damage to the immune system or whether it is a reflection of immune pressure or other selective forces.

A quantitative quasispecies theory-based model of virus escape mutation under immune selection

Viral infections involve a complex interplay of the immune response and escape mutation of the virus quasispecies inside a single host. Although fundamental aspects of such a balance of mutation and selection pressure have been established by the quasispecies theory decades ago, its implications have largely remained qualitative. Here, we present a quantitative approach to model the virus evolution under cytotoxic T-lymphocyte immune response. The virus quasispecies dynamics are explicitly represented by mutations in the combined sequence space of a set of epitopes within the viral genome. We stochastically simulated the growth of a viral population originating from a single wild-type founder virus and its recognition and clearance by the immune response, as well as the expansion of its genetic diversity. Applied to the immune escape of a simian immunodeficiency virus epitope, model predictions were quantitatively comparable to the experimental data. Within the model parameter space, we found two qualitatively different regimes of infectious disease pathogenesis, each representing alternative fates of the immune response: It can clear the infection in finite time or eventually be overwhelmed by viral growth and escape mutation. The latter regime exhibits the characteristic disease progression pattern of human immunodeficiency virus, while the former is bounded by maximum mutation rates that can be suppressed by the immune response. Our results demonstrate that, by explicitly representing epitope mutations and thus providing a genotype-phenotype map, the quasispecies theory can form the basis of a detailed sequence-specific model of real-world viral pathogens evolving under immune selection.

Inhibition of HIV-1 disease progression by contemporaneous HIV-2 infection

BACKGROUND

Progressive immune dysfunction and the acquired immunodeficiency syndrome (AIDS) develop in most persons with untreated infection with human immunodeficiency virus type 1 (HIV-1) but in only approximately 20 to 30% of persons infected with HIV type 2 (HIV-2); among persons infected with both types, the natural history of disease progression is poorly understood.

METHODS

We analyzed data from 223 participants who were infected with HIV-1 after enrollment (with either HIV-1 infection alone or HIV-1 and HIV-2 infection) in a cohort with a long follow-up duration (approximately 20 years), according to whether HIV-2 infection occurred first, the time to the development of AIDS (time to AIDS), CD4+ and CD8+ T-cell counts, and measures of viral evolution.

RESULTS

The median time to AIDS was 104 months (95% confidence interval [CI], 75 to 133) in participants with dual infection and 68 months (95% CI, 60 to 76) in participants infected with HIV-1 only (P=0.003). CD4+ T-cell levels were higher and CD8+ T-cell levels increased at a lower rate among participants with dual infection, reflecting slower disease progression. Participants with dual infection with HIV-2 infection preceding HIV-1 infection had the longest time to AIDS and highest levels of CD4+ T-cell counts. HIV-1 genetic diversity was significantly lower in participants with dual infections than in those with HIV-1 infection alone at similar time points after infection.

CONCLUSIONS

Our results suggest that HIV-1 disease progression is inhibited by concomitant HIV-2 infection and that dual infection is associated with slower disease progression. The slower rate of disease progression was most evident in participants with dual infection in whom HIV-2 infection preceded HIV-1 infection. These findings could have implications for the development of HIV-1 vaccines and therapeutics. (Funded by the Swedish International Development Cooperation Agency-Swedish Agency for Research Cooperation with Developing Countries and others.).

Viral quasispecies evolution

Evolution of RNA viruses occurs through disequilibria of collections of closely related mutant spectra or mutant clouds termed viral quasispecies. Here we review the origin of the quasispecies concept and some biological implications of quasispecies dynamics. Two main aspects are addressed: (i) mutant clouds as reservoirs of phenotypic variants for virus adaptability and (ii) the internal interactions that are established within mutant spectra that render a virus ensemble the unit of selection. The understanding of viruses as quasispecies has led to new antiviral designs, such as lethal mutagenesis, whose aim is to drive viruses toward low fitness values with limited chances of fitness recovery. The impact of quasispecies for three salient human pathogens, human immunodeficiency virus and the hepatitis B and C viruses, is reviewed, with emphasis on antiviral treatment strategies. Finally, extensions of quasispecies to nonviral systems are briefly mentioned to emphasize the broad applicability of quasispecies theory.

Genome-wide patterns of intrahuman dengue virus diversity reveal associations with viral phylogenetic clade and interhost diversity

Analogous to observations in RNA viruses such as human immunodeficiency virus, genetic variation associated with intrahost dengue virus (DENV) populations has been postulated to influence viral fitness and disease pathogenesis. Previous attempts to investigate intrahost genetic variation in DENV characterized only a few viral genes or a limited number of full-length genomes. We developed a whole-genome amplification approach coupled with deep sequencing to capture intrahost diversity across the entire coding region of DENV-2. Using this approach, we sequenced DENV-2 genomes from the serum of 22 Nicaraguan individuals with secondary DENV infection and captured ∼75% of the DENV genome in each sample (range, 40 to 98%). We identified and quantified variants using a highly sensitive and specific method and determined that the extent of diversity was considerably lower than previous estimates. Significant differences in intrahost diversity were detected between genes and also between antigenically distinct domains of the Envelope gene. Interestingly, a strong association was discerned between the extent of intrahost diversity in a few genes and viral clade identity. Additionally, the abundance of viral variants within a host, as well as the impact of viral mutations on amino acid encoding and predicted protein function, determined whether intrahost variants were observed at the interhost level in circulating Nicaraguan DENV-2 populations, strongly suggestive of purifying selection across transmission events. Our data illustrate the value of high-coverage genome-wide analysis of intrahost diversity for high-resolution mapping of the relationship between intrahost diversity and clinical, epidemiological, and virological parameters of viral infection.

Evolutionary dynamics of HIV at multiple spatial and temporal scales

Infectious diseases remain a formidable challenge to human health, and understanding pathogen evolution is crucial to designing effective therapeutics and control strategies. Here, we review important evolutionary aspects of HIV infection, highlighting the concept of selection at multiple spatial and temporal scales. At the smallest scale, a single cell may be infected by multiple virions competing for intracellular resources. Recombination and phenotypic mixing introduce novel evolutionary dynamics. As the virus spreads between cells in an infected individual, it continually evolves to circumvent the immune system. We discuss evolutionary mechanisms of HIV pathogenesis and progression to AIDS. Viral spread throughout the human population can lead to changes in virulence and the transmission of immune-evading variation. HIV emerged as a human pathogen due to selection occurring between different species, adapting from related viruses of primates. HIV also evolves resistance to antiretroviral drugs within a single infected host, and we explore the possibility for the spread of these strains between hosts, leading to a drug-resistant epidemic. We investigate the role of latency, drug-protected compartments, and direct cell-to-cell transmission on viral evolution. The introduction of an HIV vaccine may select for viral variants that escape vaccine control, both within an individual and throughout the population. Due to the strong selective pressure exerted by HIV-induced morbidity and mortality in many parts of the world, the human population itself may be co-evolving in response to the HIV pandemic. Throughout the paper, we focus on trade-offs between costs and benefits that constrain viral evolution and accentuate how selection pressures differ at different levels of selection.

Genetic diversity and molecular epidemiology of HIV transmission

The high genetic diversity of HIV is one of its most significant features, as it has consequences in global distribution, vaccine design, therapy success, disease progression, transmissibility and viral load testing. Studying HIV diversity helps to understand its origins, migration patterns, current distribution and transmission events. New advances in sequencing technologies based on the parallel acquisition of data are now used to characterize within-host and population processes in depth. Additionally, we have seen similar advances in statistical methods designed to model the past history of lineages (the phylodynamic framework) to ultimately gain better insights into the evolutionary history of HIV. We can, for example, estimate population size changes, lineage dispersion over geographic areas and epidemiological parameters solely from sequence data. In this article, we review some of the evolutionary approaches used to study transmission patterns and processes in HIV and the insights gained from such studies.

HIV-1 evolution in relation to molecular epidemiology and antiretroviral resistance

HIV/AIDS has become one of the most important infectious diseases with a cumulative number of almost 60 million infections worldwide. The prevalence and epidemiological patterns are unevenly distributed across the globe and also within countries. HIV is one of the fastest evolving organisms known. Several genetically distinct subtypes are present and new circulating recombinant forms are continuously emerging. This review discusses HIV-1 evolution in relation to molecular epidemiology and antiretroviral resistance. Factors and concepts that influence global spread and within-patient evolution of HIV-1 are discussed as well as future perspectives on the use of phylodynamics in HIV epidemiology.

Designing a genome-based HIV incidence assay with high sensitivity and specificity

OBJECTIVE

Considerable inaccuracy in estimates of HIV incidence has been a serious obstacle to the development of efficient HIV/AIDS prevention and interventions. Accurately distinguishing recent or incident infections from chronic infections enables one to monitor epidemics and evaluate the impact of HIV prevention/intervention trials. However, serological testing has not been able to realize these promises due to a number of critical limitations. Our study is to design a novel scheme of identifying incident infections in a highly accurate manner, based on the characteristics of HIV gene diversification within an infected individual.

METHODS

We perform a comprehensive meta-analysis on 5596 full envelope HIV genes generated by single genome amplification-direct sequencing from 182 incident and 43 chronic cases. We devise a binary classification test based on the tail characteristics of the Hamming distance distribution of sequences.

RESULTS

We identify a clear signature of incident infections, the presence of closely related strains in the sampled HIV envelope gene sequences in each HIV-infected patient, in both single-variant and multivariant transmissions. The sequence similarity used as a biomarker is found to have high specificity and sensitivity, greater than 95%, and is robust to viral and host-specific factors such as the clade of the viral strain, viral load, and the length and location of sequences in the HIV envelope gene.

CONCLUSION

Because of rapid and continuing improvements in sequencing technology and cost, sequence-based incidence assays hold great promise as a means of quantifying HIV incidence from a single blood test.

Daily sampling of an HIV-1 patient with slowly progressing disease displays persistence of multiple env subpopulations consistent with neutrality

The molecular evolution of HIV-1 is characterized by frequent substitutions, indels and recombination events. In addition, a HIV-1 population may adapt through frequency changes of its variants. To reveal such population dynamics we analyzed HIV-1 subpopulation frequencies in an untreated patient with stable, low plasma HIV-1 RNA levels and close to normal CD4+ T-cell levels. The patient was intensively sampled during a 32-day period as well as approximately 1.5 years before and after this period (days −664, 1, 2, 3, 11, 18, 25, 32 and 522). 77 sequences of HIV-1 env (approximately 3100 nucleotides) were obtained from plasma by limiting dilution with 7–11 sequences per time point, except day −664. Phylogenetic analysis using maximum likelihood methods showed that the sequences clustered in six distinct subpopulations. We devised a method that took into account the relatively coarse sampling of the population. Data from days 1 through 32 were consistent with constant within-patient subpopulation frequencies. However, over longer time periods, i.e. between days 1…32 and 522, there were significant changes in subpopulation frequencies, which were consistent with evolutionarily neutral fluctuations. We found no clear signal of natural selection within the subpopulations over the study period, but positive selection was evident on the long branches that connected the subpopulations, which corresponds to >3 years as the subpopulations already were established when we started the study. Thus, selective forces may have been involved when the subpopulations were established. Genetic drift within subpopulations caused by de novo substitutions could be resolved after approximately one month. Overall, we conclude that subpopulation frequencies within this patient changed significantly over a time period of 1.5 years, but that this does not imply directional or balancing selection. We show that the short-term evolution we study here is likely representative for many patients of slow and normal disease progression.

Modelling the impact of acute infection dynamics on the accumulation of HIV-1 mutations

Events over the past year have brought hope and have re-energized the interest in targeting pre-infection or early infection period with preventative or therapeutic interventions such as vaccines and pre-exposure prophylaxis (PrEP). In breakthrough infections, the incidence, long term prognosis and clinical significance of early infection events is not well understood but it is possible that these early events may be crucial in determining the subsequent course of disease. We use a branching process model in a deterministically varying environment to explore how the dynamics of early infection affects the accumulation of mutations which lay the seeds for long term evolution of drug resistance and immune system evasion. We relate this exploration to regimes of impact, on diversity, of tropical interventions strategies such as PrEP and vaccines. As a metric of diversity we compute the probability of existence of particular genomes which potentially arise. Using several model scenarios, we demonstrate various regimes of 'response' of evolution to 'intervention'. Transient effects of therapeutic interventions early in infection that impose a fitness cost on early viruses can significantly reduce the probability of diversity later during the chronic state of infection. This stands in contrast to the concern that early selective pressure may increase the probability of later existence of drug resistance mutations, for example. The branching process paradigm offers the ability to efficiently compute important indicators of viral diversity, in a framework with a modest number of simplifying assumptions, without simulating the full range of individual level scenarios. These models may be useful to illustrate the impact of vaccines and PrEP on viral evolution in the case of breakthrough infection. They also suggest that new measures of viral diversity which correlate to prognosis should be sought in trials for PrEP and vaccines.