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Whether freshwater fish colonize remote islands following tectonic or transoceanic dispersal remains an evolutionary puzzle. Integrating dating of known tectonic events with phylogenomics and current species distribution, we find that killifish species distribution is not explained by species dispersal by tectonic drift only. Investigating the colonization of a nonannual killifish (golden panchax, Pachypanchax playfairii) on the Seychelle islands, we found genetic support for transoceanic dispersal and experimentally discovered an adaptation to complete tolerance to seawater. At the macroevolutionary scale, despite their long-lasting isolation, nonannual golden panchax show stronger genome-wide purifying selection than annual killifishes from continental Africa. However, progressive decline in effective population size over a more recent timescale has probably led to the segregation of slightly deleterious mutations across golden panchax populations, which represents a potential threat for species preservation in the long term.

Unmitigated spread in Brazil Despite an extensive network of primary care availability, Brazil has suffered profoundly during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Using daily data from state health offices, Castro et al. analyzed the pattern of spread of COVID-19 cases and deaths in the country from February to October 2020. Clusters of deaths before cases became apparent indicated unmitigated spread. SARS-CoV-2 circulated undetected in Brazil for more than a month as it spread north from Sã o Paulo. In Manaus, transmission reached unprecedented levels after a momentary respite in mid-2020. Faria et al. tracked the evolution of a new, more aggressive lineage called P.1, which has 17 mutations, including three (K417T, E484K, and N501Y) in the spike protein. After a period of accelerated evolution, this variant emerged in Brazil during November 2020. Coupled with the emergence of P.1, disease spread was accelerated by stark local inequalities and political upheaval, which compromised a prompt federal response. Science , abh1558 and abh2644, this issue p. 821 and p. 815

Continued uncontrolled transmission of SARS-CoV-2 in many parts of the world is creating conditions for substantial evolutionary changes to the virus1,2. Here we describe a newly arisen lineage of SARS-CoV-2 (designated 501Y.V2; also known as B.1.351 or 20H) that is defined by eight mutations in the spike protein, including three substitutions (K417N, E484K and N501Y) at residues in its receptor-binding domain that may have functional importance3,4,5. This lineage was identified in South Africa after the first wave of the epidemic in a severely affected metropolitan area (Nelson Mandela Bay) that is located on the coast of the Eastern Cape province. This lineage spread rapidly, and became dominant in Eastern Cape, Western Cape and KwaZulu–Natal provinces within weeks. Although the full import of the mutations is yet to be determined, the genomic data—which show rapid expansion and displacement of other lineages in several regions—suggest that this lineage is associated with a selection advantage that most plausibly results from increased transmissibility or immune escape6,7,8.

BackgroundThe human norovirus GII.2 outbreak during the 2016–2017 winter season was of unprecedented scale and geographic distribution.MethodsWe analyzed 519 complete VP1 gene sequences of the human norovirus GII.2 genotype sampled during the 2016–2017 winter season, as well as prior (dating back to 1976) from 7 countries. Phylodynamic analyses of these sequences were performed using maximum likelihood and Bayesian statistical frameworks in order to estimate viral evolutionary and population dynamics associated with the outbreak.ResultsOur results revealed an increase in the genetic diversity of human norovirus GII.2 during the recent Asian outbreak and diversification was characterized by at least eight distinct clusters. Bayesian estimation of viral population dynamics revealed a highly fluctuating effective population size, increasing in frequency during the past 15 years.ConclusionDespite an increasing viral diversity, we found no evidence of an elevated evolutionary rate or significant selection pressure in human norovirus GII.2, indicating viral evolutionary adaptation was not responsible for the volatility of or spread of the virus during this time.

Staphylococcus aureus, a common cause of serious and often fatal infections, is well-armed with secreted factors that disarm host immune defenses. Highly expressed in vivo during infection, Staphylococcal protein A (SpA) is reported to also contribute to nasal colonization that can be a prelude to invasive infection. Co-evolution with the host immune system has provided SpA with an Fc-antibody binding site, and a Fab-binding site responsible for non-immune superantigen interactions via germline-encoded surfaces expressed on many human BCRs. We wondered whether the recurrent exposures to S. aureus commonly experienced by adults, result in the accumulation of memory B-cell responses to other determinants on SpA. We therefore isolated SpA-specific class-switched memory B cells, and characterized their encoding VH : VL antibody genes. In SpA-reactive memory B cells, we confirmed a striking bias in usage for VH genes, which retain the surface that mediates the SpA-superantigen interaction. We postulate these interactions reflect co-evolution of the host immune system and SpA, which during infection results in immune recruitment of an extraordinarily high prevalence of B cells in the repertoire that subverts the augmentation of protective defenses. Herein, we provide the first evidence that human memory responses are supplemented by B-cell clones, and circulating-antibodies, that bind to SpA determinants independent of the non-immune Fc- and Fab-binding sites. In parallel, we demonstrate that healthy individuals, and patients recovering from S. aureus infection, both have circulating antibodies with these conventional binding specificities. These findings rationalize the potential utility of incorporating specially engineered SpA proteins into a protective vaccine.

Our evolutionary and structural analyses revealed that the severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) spike gene is a complex mosaic resulting from several recombination events. Additionally, the fixation of variants has mainly been driven by purifying selection, suggesting the presence of conserved structural features. Our dynamic simulations identified two main long-range covariant dynamic movements of the novel glycoprotein, and showed that, as a result of the evolutionary duality, they are preserved. The first movement involves the receptor binding domain with the N-terminal domain and the C-terminal domain 2 and is maintained across human, bat and pangolin coronaviruses. The second is a complex network of long-range dynamics specific to SARS-CoV-2 involving the novel PRRA and the conserved KR*SF cleavage sites, as well as conserved segments in C-terminal domain 3. These movements, essential for host cell binding, are maintained by hinges conserved across human, bat, and pangolin coronaviruses glycoproteins. The hinges, located around Threonine 333 and Proline 527 within the N-terminal domain and C-terminal domain 2, represent candidate targets for the future development of novel pan-coronavirus inhibitors. In summary, we show that while recombination created a new configuration that increased the covariant dynamic movements of the SARS-CoV-2 glycoprotein, negative selection preserved its inter-domain structure throughout evolution in different hosts and inter-species transmissions.

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

Virus host shifts are generally associated with novel adaptations to exploit the cells of the new host species optimally. Surprisingly, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has apparently required little to no significant adaptation to humans since the start of the Coronavirus Disease 2019 (COVID-19) pandemic and to October 2020. Here we assess the types of natural selection taking place in Sarbecoviruses in horseshoe bats versus the early SARS-CoV-2 evolution in humans. While there is moderate evidence of diversifying positive selection in SARS-CoV-2 in humans, it is limited to the early phase of the pandemic, and purifying selection is much weaker in SARS-CoV-2 than in related bat Sarbecoviruses. In contrast, our analysis detects evidence for significant positive episodic diversifying selection acting at the base of the bat virus lineage SARS-CoV-2 emerged from, accompanied by an adaptive depletion in CpG composition presumed to be linked to the action of antiviral mechanisms in these ancestral bat hosts. The closest bat virus to SARS-CoV-2, RmYN02 (sharing an ancestor about 1976), is a recombinant with a structure that includes differential CpG content in Spike; clear evidence of coinfection and evolution in bats without involvement of other species. While an undiscovered “facilitating” intermediate species cannot be discounted, collectively, our results support the progenitor of SARS-CoV-2 being capable of efficient human–human transmission as a consequence of its adaptive evolutionary history in bats, not humans, which created a relatively generalist virus., A study of the natural origins of SARS-CoV-2 reveals very little adaptive evolution occurring since it emerged in humans, but strong evolutionary signals in the bat virus lineage from which SARS-CoV-2 arose. Evolution in bats involved lineage-specific depletion of CpG nucleotides (linked to host anti-viral molecules), and clear evidence of recombination across these lineages, supporting bat host species’ influence on the ancestral viruses.

Global sequencing of genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to reveal new genetic variants that are the key to unraveling its early evolutionary history and tracking its global spread over time. Here we present the heretofore cryptic mutational history and spatiotemporal dynamics of SARS-CoV-2 from an analysis of thousands of high-quality genomes. We report the likely most recent common ancestor of SARS-CoV-2, reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient. This progenitor genome differs from genomes of the first coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the United States harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide months before and after the first reported cases of COVID-19 in China. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains that have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic in 2020. There have been multiple replacements of predominant coronavirus strains in Europe and Asia as well as continued presence of multiple high-frequency strains in Asia and North America. We have developed a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).

Due to the scope and impact of the COVID-19 pandemic there exists a strong desire to understand where the SARS-CoV-2 virus came from and how it jumped species boundaries to humans. Molecular evolutionary analyses can trace viral origins by establishing relatedness and divergence times of viruses and identifying past selective pressures. However, we must uphold rigorous standards of inference and interpretation on this topic because of the ramifications of being wrong. Here, we dispute the conclusions of Xia (2020. Extreme genomic CpG deficiency in SARS-CoV-2 and evasion of host antiviral defense. Mol Biol Evol. doi:10.1093/molbev/masa095) that dogs are a likely intermediate host of a SARS-CoV-2 ancestor. We highlight major flaws in Xia’s inference process and his analysis of CpG deficiencies, and conclude that there is no direct evidence for the role of dogs as intermediate hosts. Bats and pangolins currently have the greatest support as ancestral hosts of SARS-CoV-2, with the strong caveat that sampling of wildlife species for coronaviruses has been limited.

Concurrent sexually transmitted infections (STI) can increase the probability of HIV-1 transmission primarily by increasing the viral load present in semen. In this study, we explored the relationship of HIV-1 in blood and seminal plasma in the presence and absence of urethritis and after treatment of the concurrent STI. Primer ID deep sequencing of the V1/V3 region of the HIV-1 env gene was done for paired blood and semen samples from antiretroviral therapy (ART)-naive men living in Malawi with (n = 19) and without (n = 5) STI-associated urethritis; for a subset of samples, full-length env genes were generated for sequence analysis and to test entry phenotype. Cytokine concentrations in the blood and semen were also measured, and a reduction in the levels of proinflammatory cytokines was observed following STI treatment. We observed no difference in the prevalence of diverse compartmentalized semen-derived lineages in men with or without STI-associated urethritis, and these viral populations were largely stable during STI treatment. Clonal amplification of one or a few viral sequences accounted for nearly 50% of the viral population, indicating a recent bottleneck followed by limited viral replication. We conclude that the male genital tract is a site where virus can be brought in from the blood, where localized sustained replication can occur, and where specific genotypes can be amplified, perhaps initially by cellular proliferation but further by limited viral replication. IMPORTANCE HIV-1 infection is a sexually transmitted infection that coexists with other STI. Here, we examined the impact of a concurrent STI resulting in urethritis on the HIV-1 population within the male genital tract. We found that viral populations remain largely stable even with treatment of the STI. These results show that viral populations within the male genital tract are defined by factors beyond transient inflammation associated with a concurrent STI.

The current state of much of the Wuhan pneumonia virus (COVID-19) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies, and requires unimpeded access to data, analysis tools, and computational infrastructure. Here we show that community efforts in developing open analytical software tools over the past ten years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all COVID-19 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and to (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.

Concurrent sexually transmitted infections (STI) can increase the probability of HIV-1 transmission primarily by increasing the viral load present in semen. In this study, we explored the relationship of HIV-1 in blood and seminal plasma in the presence and absence of urethritis and after treatment of the concurrent STI. Primer ID deep sequencing of the V1/V3 region of the HIV-1envgene was done for paired blood and semen samples from ART-naïve men living in Malawi with (n = 19) and without (n = 5) STI-associated urethritis; for a subset of samples full lengthenvgenes were generated for sequence analysis and to test entry phenotype. Cytokine concentrations in the blood and semen were also measured, and a reduction in the levels of pro-inflammatory cytokines was observed following STI treatment. We observed no difference in the prevalence of diverse compartmentalized semen-derived lineages in men with or without STI-associated urethritis, and these viral populations were largely stable during STI treatment. Clonal amplification of one or a few viral sequences accounted for nearly 50% of the viral population indicating a recent bottleneck followed by limited viral replication. We documented a case of superinfection where the new strain was restricted to the genital tract. We conclude that the male genital tract is a site where virus can be brought in from the blood, where localized sustained replication can occur, where a superinfecting strain can persist, and where specific genotypes can be amplified perhaps initially by cellular proliferation but further by limited viral replication.ImportanceHIV-1 is a sexually transmitted infection that co-exists with other STIs. Here we examine the impact of a concurrent STI resulting in urethritis on the HIV-1 population within the male genital tract. We found that viral populations remain largely stable even with treatment of the STI. These results show that viral populations within the male genital tract are defined by factors beyond transient inflammation associated with a concurrent STI.

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., Author summary 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).

It is standard practice to model site-to-site variability of substitution rates by discretizing a continuous distribution into a small number, K, of equiprobable rate categories. We demonstrate that the variance of this discretized distribution has an upper bound determined solely by the choice of K and the mean of the distribution. This bound can introduce biases into statistical inference, especially when estimating parameters governing site-to-site variability of substitution rates. Applications to two large collections of sequence alignments demonstrate that this upper bound is often reached in analyses of real data. When parameter estimation is of primary interest, additional rate categories or more flexible modeling methods should be considered.

The current state of much of the Wuhan pneumonia virus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) research shows a regrettable lack of data sharing and considerable analytical obfuscation. This impedes global research cooperation, which is essential for tackling public health emergencies and requires unimpeded access to data, analysis tools, and computational infrastructure. Here, we show that community efforts in developing open analytical software tools over the past 10 years, combined with national investments into scientific computational infrastructure, can overcome these deficiencies and provide an accessible platform for tackling global health emergencies in an open and transparent manner. Specifically, we use all SARS-CoV-2 genomic data available in the public domain so far to (1) underscore the importance of access to raw data and (2) demonstrate that existing community efforts in curation and deployment of biomedical software can reliably support rapid, reproducible research during global health crises. All our analyses are fully documented at https://github.com/galaxyproject/SARS-CoV-2.

Human immunodeficiency virus (HIV) is a rapidly evolving virus, allowing its genetic sequence to act as a fingerprint for epidemiological processes among, as well as within, individual infected hosts. Though primarily infecting the CD4+ T-cell population, HIV can also be found in monocytes, an immune cell population that differs in several aspects from the canonical T-cell viral target. Using single genome viral sequencing and statistical phylogenetic inference, we investigated the viral RNA diversity and relative contribution of each of these immune cell types to the viral population within the peripheral blood. Results provide evidence of an increased prevalence of circulating monocytes harboring virus in individuals with high viral load in the absence of suppressive antiretroviral therapy. Bayesian phyloanatomic analysis of three of these individuals demonstrated a measurable role for these cells, but not the circulating T-cell population, as a source of cell-free virus in the plasma, supporting the hypothesis that these cells can act as an additional conduit of virus spread.

Ciliates, a eukaryotic clade that is over 1 billion years old, are defined by division of genome function between transcriptionally inactive germline micronuclei and functional somatic macronuclei. To date, most analyses of gene family evolution have been limited to cultivable model lineages (e.g., Tetrahymena, Paramecium, Oxytricha, and Stylonychia). Here, we focus on the uncultivable Karyorelictea and its understudied sister class Heterotrichea, which represent two extremes in genome architecture., Ciliates, a eukaryotic clade that is over 1 billion years old, are defined by division of genome function between transcriptionally inactive germline micronuclei and functional somatic macronuclei. To date, most analyses of gene family evolution have been limited to cultivable model lineages (e.g., Tetrahymena, Paramecium, Oxytricha, and Stylonychia). Here, we focus on the uncultivable Karyorelictea and its understudied sister class Heterotrichea, which represent two extremes in genome architecture. Somatic macronuclei within the Karyorelictea are described as nearly diploid, while the Heterotrichea have hyperpolyploid somatic genomes. Previous analyses indicate that genome architecture impacts ciliate gene family evolution as the most diverse and largest gene families are found in lineages with extensively processed somatic genomes (i.e., possessing thousands of gene-sized chromosomes). To further assess ciliate gene family evolution, we analyzed 43 single-cell transcriptomes from 33 ciliate species representing 10 classes. Focusing on conserved eukaryotic genes, we use estimates of transcript diversity as a proxy for the number of paralogs in gene families among four focal clades: Karyorelictea, Heterotrichea, extensive fragmenters (with gene-size somatic chromosomes), and non-extensive fragmenters (with more traditional somatic chromosomes), the latter two within the subphylum Intramacronucleata. Our results show that (i) the Karyorelictea have the lowest average transcript diversity, while Heterotrichea are highest among the four groups; (ii) proteins in Karyorelictea are under the highest functional constraints, and the patterns of selection in ciliates may reflect genome architecture; and (iii) stop codon reassignments vary among members of the Heterotrichea and Spirotrichea but are conserved in other classes.

Between 2003 and 2016, transmitted HIV-1 drug resistance has increased in a large California clinic population. However, the most commonly transmitted drug-resistance mutations reduce susceptibility primarily to drugs that are no longer frequently used., Background There are few large studies of transmitted drug resistance (TDR) prevalence and the drug resistance mutations (DRMs) responsible for TDR in the United States. Methods Human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) and protease sequences were obtained from 4253 antiretroviral therapy (ART)–naive individuals in a California clinic population from 2003 to 2016. Phylogenetic analyses were performed to study linkages between TDR strains and selection pressure on TDR-associated DRMs. Results From 2003 to 2016, there was a significant increase in overall (odds ratio [OR], 1.05 per year [95% confidence interval {CI}, 1.03–1.08]; P < .001) and nonnucleoside RT inhibitor (NNRTI)–associated TDR (OR, 1.11 per year [95% CI, 1.08–1.15]; P < .001). Between 2012 and 2016, TDR rates to any drug class ranged from 15.7% to 19.2%, and class-specific rates ranged from 10.0% to 12.8% for NNRTIs, 4.1% to 8.1% for nucleoside RT inhibitors (NRTIs), and 3.6% to 5.2% for protease inhibitors. The thymidine analogue mutations, M184V/I and the tenofovir-associated DRMs K65R and K70E/Q/G/N/T accounted for 82.9%, 7.3%, and 1.4% of NRTI-associated TDR, respectively. Thirty-seven percent of TDR strains clustered with other TDR strains sharing the same DRMs. Conclusions Although TDR has increased significantly in this large cohort, many TDR strains are unlikely to influence the activity of currently preferred first-line ART regimens. The high proportion of DRMs associated with infrequently used regimens combined with the clustering of TDR strains suggest that some TDR strains are being transmitted between ART-naive individuals.

Author(s): Choi, Jun Yong; Pond, Sergei L Kosakovsky; Anderson, Christy M; Richman, Douglas D; Smith, Davey M | Abstract: BackgroundInvestigations into which human immunodeficiency virus type 1 (HIV-1) sequence features may be selected for transmission during sexual exposure have been hampered by the small number of characterized transmission pairs in individual studies.MethodsTo boost statistical power to detect differences in glycosylation, length, and electrical charge in the HIV-1 V1-V4 coding region, we reanalyzed all available 2485 env sequences derived from 114 subjects representing 58 transmission pairs from previous studies using mixed-effects linear regression and an approach to approximate the unobserved transmitted virus.ResultsThe recipient partner had a shorter V1-V4 region and fewer potential N-linked glycosylation sites (PNGS) than sequences from the source partner. We also detected a trend toward more PNGS and lower isoelectric points in transmitted sequences with source partner and the evolutionary tendency to shorten V1-V4 sequences, reduce the number of PNGS, and lower isoelectric points in the recipient following transmission.ConclusionsBy using all available well-characterized env sequences from transmission pairs via sexual exposure, we were able to identify several important virologic factors that may be important in the development of biomedical preventive interventions.

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 the relative rate framework underlying the RelTime approach. RTDT does not require many of the priors demanded by Bayesian approaches, and it has light computing requirements. We found RTDT to be accurate on simulated datasets evolved under a variety of branch rates models. Interestingly, we found two non-Bayesian methods (RTDT and Least Squares Dating [LSD]) to perform similar to or better than the Bayesian approaches available in BEAST and MCMCTree programs. RTDT method was found to generally outperform all other methods for phylogenies in with autocorrelated evolutionary rates. In analyses of empirical datasets, RTDT produced dates that were similar to those from Bayesian analyses. Speed and accuracy of the new method, as compared to the alternatives, makes it appealing for analyzing growing datasets of pathogenic strains. Cross-platform MEGA X software, freely available from http://www.megasoftware.net, now contains the new method for use through a friendly graphical user interface and in high-throughput settings.AUTHOR SUMMARYPathogen 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 timetrees for phylogenies with tip dates, which improves on widely-used Bayesian methods (e.g., BEAST) in computational efficiency and does not require prior specification of population parameters, branch rate model, or clock model. We performed extensive computer simulation and found that RTDT performed better than the other methods for the estimation of divergence times at deep node in phylogenies where evolutionary rates were autocorrelated. The new method is available in the cross-platform MEGA software package that provides a graphical user interface, and allows use via a command line in scripting and high throughput analysis (www.megasoftware.net).

Background Recent advances in high-throughput molecular epidemiology are transforming the analysis of viral infections. Methods Human immunodeficiency virus (HIV)-1 pol sequences from a Northern Californian cohort (NCC) of 4553 antiretroviral-naive individuals sampled between 1998 and 2016 were analyzed together with 140 000 previously published global pol sequences. The HIV-TRAnsmission Cluster Engine (HIV-TRACE) was used to infer a transmission network comprising links between NCC and previously published sequences having a genetic distance ≤1.5%. Results Twenty-five percent of NCC sequences were included in 264 clusters linked to a published sequence, and approximately one third of these (8.0% of the total) were linked to 1 or more non-US sequences. The largest cluster, containing 512 NCC sequences (11.2% of the total), comprised the subtype B lineage that traced its origin to the earliest North American sequences. Approximately 5 percent of NCC sequences belonged to a non-B subtype, and these were more likely to cluster with a non-US sequence. Twenty-two NCC sequences belonged to 1 of 4 large clusters containing sequences from rapidly growing regional epidemics: CRF07_BC (East Asia), subtype A6 (former Soviet Union), a Japanese subtype B lineage, and an East/Southeast Asian CRF01_AE lineage. Bayesian phylogenetics suggested that most non-B sequences resulted from separate introductions but that local spread within the largest CRF01_AE cluster occurred twice. Conclusions The NCC contains national and international links to previously published sequences including many to the subtype B strain that originated in North America and several to rapidly growing Asian epidemics. Despite their rapid regional growth, the Asian epidemic strains demonstrated limited NCC spread.

Although antiretroviral therapy (ART) is highly effective at suppressing HIV-1 replication, the virus persists as a latent reservoir in resting CD4+ T cells during therapy. Little is known about the dynamics of reservoir formation and this reservoir forms even when ART is initiated early after infection. The reservoir of individuals who initiate therapy in chronic infection is generally larger and genetically more diverse than that of individuals who initiate in acute infection, suggesting the reservoir is formed continuously throughout untreated infection. To determine when viruses enter the latent reservoir, we compared sequences of replication-competent viruses from resting CD4+ T cells from nine women on therapy to viral sequences circulating in blood collected longitudinally prior to therapy. We found that 78% of viruses from the latent reservoir were most genetically similar to viruses replicating just prior to therapy initiation. This proportion is far greater than expected if the reservoir forms continuously and is always long-lived. Thus, therapy alters the host environment in a way that allows the formation of a majority of the long-lived latent HIV-1 reservoir.One Sentence SummaryMost of the long-lived, replication-competent HIV-1 reservoir is formed at the time of therapy initiation.

Human immunodeficiency virus (HIV) RNA and DNA have been isolated from patient monocytes, an immune cell population that is quite different in several aspects from the canonical T-cell viral target. Because monocytes are migratory and resilient to both natural and synthetic antiviral defenses, knowledge of the contribution of monocyte infection to ongoing viral evolution and spread \textit{in vivo} is of significant interest for drug development and treatment strategies. Using single viral genome sequencing from different peripheral blood compartments and phyloanatomic statistical inference, we demonstrate that productively infected monocytes follow an evolutionary trajectory that is distinct from peripheral T cells during multiple stages of disease progression. Gene flow and selection analysis reveal plasticity in the source of monocyte infection and in the region of the HIV envelope glycoprotein that experiences selection pressure across individuals. The findings, thus, point to a potential reservoir showing a range of infection and transmission dynamics, for which the current universal, T cell-targeted treatment strategies would be inadequate.

The HIV epidemic in San Mateo County is sustained by multiple overlapping risk groups and is an important hub for HIV transmission in northern California. Limited access to care has led historically to delayed clinical presentation, higher rates of opportunistic infections, and an increased prevalence of antiretroviral drug resistance. The virologic and clinical consequences of treatment within these multiple ethnic and behavioral groups are poorly understood, highlighting the need for efficient surveillance strategies that are able to elucidate transmission networks and drug resistance patterns. We obtained sequence data from a group of 316 HIV-positive individuals in the San Mateo AIDS Program over a 14-year period and integrated epidemiologic, phylogenetic, and network approaches to characterize transmission clusters, risk factors and drug resistance. Drug resistance mutations were identified using the Stanford HIV Drug Resistance Database. A maximum likelihood tree was inferred in RAxML and subjected to clustering analysis in Cluster Picker. Network analysis using pairwise genetic distances was performed in HIV-TRACE. Participants were primarily male (60%), white Hispanics and non-Hispanics (32%) and African American (20.6%). The most frequent behavior risk factor was male-male sex (33.5%), followed by heterosexual (23.4%) and injection drug use (9.5%). Nearly all sequences were subtype B (96%) with subtypes A, C, and CRF01_AE also observed. Sequences from 65% of participants had at least one drug resistance mutation. Clustered transmissions included a higher number of women when compared to non-clustered individuals and were more likely to include heterosexual or people who inject drugs (PWID). Detailed analysis of the largest network (N = 47) suggested that PWID played a central role in overall transmission of HIV-1 as well as bridging men who have sex with men (MSM) transmission with heterosexual/PWID among primarily African American men. Combined phylogenetic and network analysis of HIV sequence data identified several overlapping risk factors in the epidemic, including MSM, heterosexual and PWID transmission with a disproportionate impact on African Americans and a high prevalence of drug resistance.

Author(s): Mehta, Sanjay R; Murrell, Ben; Anderson, Christy M; Kosakovsky Pond, Sergei L; Wertheim, Joel O; Young, Jason A; Freitas, Lorri; Richman, Douglas D; Mathews, W Chris; Scheffler, Konrad; Little, Susan J; Smith, Davey M | Abstract: BackgroundBecause recently infected individuals disproportionately contribute to the spread of human immunodeficiency virus (HIV), we evaluated the impact of a primary HIV screening program (the Early Test) implemented in San Diego.MethodsThe Early Test program used combined nucleic acid and serology testing to screen for primary infection targeting local high-risk individuals. Epidemiologic, HIV sequence, and geographic data were obtained from the San Diego County Department of Public Health and the Early Test program. Poisson regression analysis was performed to determine whether the Early Test program was temporally and geographically associated with changes in incident HIV diagnoses. Transmission chains were inferred by phylogenetic analysis of sequence data.ResultsOver time, a decrease in incident HIV diagnoses was observed proportional to the number primary HIV infections diagnosed in each San Diego region (P l .001). Molecular network analyses also showed that transmission chains were more likely to terminate in regions where the program was marketed (P = .002). Although, individuals in these zip codes had infection diagnosed earlier (P = .08), they were not treated earlier (P = .83).ConclusionsThese findings suggests that early HIV diagnoses by this primary infection screening program probably contributed to the observed decrease in new HIV diagnoses in San Diego, and they support the expansion and evaluation of similar programs.

Background While several JavaScript packages for visualizing phylogenetic trees exist, most are best characterized as frameworks that are designed with a specific set of tasks in mind. Extending such packages to use cases that are not available as features often ends up being difficult. Moreover, existing packages tend to produce standalone widgets that are not designed to serve as middleware, as opposed to flexible tools that can integrate with other components of an application. Results phylotree.js is a library that extends the popular data visualization framework d3.js, and is suitable for building JavaScript applications where users can view and interact with phylogenetic trees. The effects of such interactions can be captured and communicated to other package components, making it possible to engineer complex and responsive applications that include phylogenetic trees. phylotree.js implements several abstractions in addition to features, and comes with a documented application programming interface, thus promoting interoperability and extensibility. Example applications include a tool to visualize and annotate phylogenetic trees, a web application for comparative sequence analysis, a structural viewer that interacts with a large phylogenetic tree, and an interactive tanglegram. Conclusions phylotree.js is a useful tool and application module for a variety of computational biology software applications. The code is available on Github and is released under the MIT license. Electronic supplementary material The online version of this article (10.1186/s12859-018-2283-2) contains supplementary material, which is available to authorized users.

Most HIV-1-infected individuals with virological failure on a pharmacologically-boosted protease inhibitor (PI) regimen do not develop PI-resistance protease mutations. One proposed explanation is that HIV-1 gag or gp41 cytoplasmic domain mutations might also reduce PI susceptibility. In a recent study of paired gag and gp41 sequences from individuals with virological failure on a PI regimen, we did not identify PI-selected mutations and concluded that if such mutations existed, larger numbers of paired sequences from multiple studies would be needed for their identification. In this study, we generated site-specific amino acid profiles using gag and gp41 published sequences from 5,338 and 4,242 ART-naïve individuals, respectively, to assist researchers identify unusual mutations arising during therapy and to provide scripts for performing established and novel maximal likelihood estimates of dN/dS substitution rates in paired sequences. The pipelines used to generate the curated sequences, amino acid profiles, and dN/dS analyses will facilitate the application of consistent methods to paired gag and gp41 sequence datasets and expedite the identification of potential sites under PI-selection pressure.

Author(s): Wertheim, Joel O; Murrell, Ben; Mehta, Sanjay R; Forgione, Lisa A; Kosakovsky Pond, Sergei L; Smith, Davey M; Torian, Lucia V | Abstract: BackgroundHIV-1 genetic sequences can be used to infer viral transmission history and dynamics. Throughout the United States, HIV-1 sequences from drug resistance testing are reported to local public health departments.MethodsWe investigated whether inferred HIV transmission network dynamics can identify individuals and clusters of individuals most likely to give rise to future HIV cases in a surveillance setting. We used HIV-TRACE, a genetic distance-based clustering tool, to infer molecular transmission clusters from HIV-1 pro/RT sequences from 65736 people in the New York City surveillance registry. Logistic and LASSO regression analyses were used to identify correlates of clustering and cluster growth, respectively. We performed retrospective transmission network analyses to evaluate individual- and cluster-level prioritization schemes for identifying parts of the network most likely to give rise to new cases in the subsequent year.ResultsIndividual-level prioritization schemes predicted network growth better than random targeting. Across the 3600 inferred molecular transmission clusters, previous growth dynamics were superior predictors of future transmission cluster growth compared to individual-level prediction schemes. Cluster-level prioritization schemes considering previous cluster growth relative to cluster size further improved network growth predictions.ConclusionsPrevention efforts based on HIV molecular epidemiology may improve public health outcomes in a US surveillance setting.

The evolution of viral pathogens is shaped by strong selective forces that are exerted during jumps to new hosts, confrontations with host immune responses and antiviral drugs, and numerous other processes. However, while undeniably strong and frequent, adaptive evolution is largely confined to small parts of information-packed viral genomes, and the majority of observed variation is effectively neutral. The predictions and implications of the neutral theory have proven immensely useful in this context, with applications spanning understanding within-host population structure, tracing the origins and spread of viral pathogens, predicting evolutionary dynamics, and modeling the emergence of drug resistance. We highlight the multiple ways in which the neutral theory has had an impact, which has been accelerated in the age of high-throughput, high-resolution genomics.

The relative evolutionary rates at individual sites in proteins are informative measures of conservation or adaptation. Often used as evolutionarily-aware conservation scores, relative rates reveal key functional or strongly-selected residues. Estimating rates in a phylogenetic context requires specifying a protein substitution model, which is typically a phenomenological model trained on a large empirical dataset. A strong emphasis has traditionally been placed on selecting the “best-fit” model, with the implicit understanding that suboptimal or otherwise ill-fitting models can potentially bias inferences. However, the pervasiveness and degree of such bias has not been systematically examined. We investigated how model choice impacts site-wise relative rates from a large set of empirical protein alignments. We compared models designed for use on any general protein, models designed for specific domains of life, and the simple equal-rates Jukes Cantor-style model (JC). As expected, information theoretic measures showed overwhelming evidence that some models fit the data decidedly better than others. By contrast, estimates of site-specific evolutionary rates were impressively insensitive to the substitution model used, revealing an unexpected degree of robustness to potential model misspecification. A deeper examination of the fewer than 5% of sites for which model inferences differed in a meaningful way showed that the JC model can uniquely identify rapidly-evolving sites that models with empirically-derived exchangeabilities fail to detect. We conclude that relative protein rates appear robust to the applied substitution model, and any sensible model of protein evolution, regardless of its fit to the data, should produce broadly consistent evolutionary rates.

We introduce LEISR (Likehood Estimation of Individual Site Rates, pronounced “laser”), a tool to infer relative evolutionary rates from protein and nucleotide data, implemented in HyPhy. LEISR is based on the popular Rate4Site (Pupko et al., 2002) approach for inferring relative site-wise evolutionary rates, primarily from protein data. We extend the original method for more general use in several key ways: (i) we increase the support for nucleotide data with additional models, (ii) we allow for datasets of arbitrary size, (iii) we support analysis of site-partitioned datasets to correct for the presence of recombination breakpoints, (iv) we produce rate estimates at all sites rather than at just a subset of sites, and (v) we implemented LEISR as MPI-enabled to support rapid, high-throughput analysis. LEISR is available in HyPhy starting with version 2.3.8, and it is accessible as an option in the HyPhy analysis menu (“Relative evolutionary rate inference”), which calls the HyPhy batchfile LEISR.bf.

In modern applications of molecular epidemiology, genetic sequence data are routinely used to identify clusters of transmission in rapidly evolving pathogens, most notably HIV-1. Traditional 'shoe-leather' epidemiology infers transmission clusters by tracing chains of partners sharing epidemiological connections (e.g., sexual contact). Here, we present a computational tool for identifying a molecular transmission analog of such clusters: HIV-TRACE (TRAnsmission Cluster Engine). HIV-TRACE implements an approach inspired by traditional epidemiology, by identifying chains of partners whose viral genetic relatedness imply direct or indirect epidemiological connections. Molecular transmission clusters are constructed using codon-aware pairwise alignment to a reference sequence followed by pairwise genetic distance estimation among all sequences. This approach is computationally tractable and is capable of identifying HIV-1 transmission clusters in large surveillance databases comprising tens or hundreds of thousands of sequences in near real time, that is, on the order of minutes to hours. HIV-TRACE is available at www.hivtrace.org and from www.github.com/veg/hivtrace, along with the accompanying result visualization module from www.github.com/veg/hivtrace-viz. Importantly, the approach underlying HIV-TRACE is not limited to the study of HIV-1 and can be applied to study outbreaks and epidemics of other rapidly evolving pathogens.

Next generation sequencing of viral populations has advanced our understanding of viral population dynamics, the development of drug resistance, and escape from host immune responses. Many applications require complete gene sequences, which can be impossible to reconstruct from short reads. HIV env, the protein of interest for HIV vaccine studies, is exceptionally challenging for long-read sequencing and analysis due to its length, high substitution rate, and extensive indel variation. While long-read sequencing is attractive in this setting, the analysis of such data is not well handled by existing methods. To address this, we introduce FLEA (Full-Length Envelope Analyzer), which performs end-to-end analysis and visualization of long-read sequencing data. FLEA consists of both a pipeline (optionally run on a high-performance cluster), and a client-side web application that provides interactive results. The pipeline transforms FASTQ reads into high-quality consensus sequences (HQCSs) and uses them to build a codon-aware multiple sequence alignment. The resulting alignment is then used to infer phylogenies, selection pressure, and evolutionary dynamics. The web application provides publication-quality plots and interactive visualizations, including an annotated viral alignment browser, time series plots of evolutionary dynamics, visualizations of gene-wide selective pressures (such as dN/dS) across time and across protein structure, and a phylogenetic tree browser. We demonstrate how FLEA may be used to process Pacific Biosciences HIV env data and describe recent examples of its use. Simulations show how FLEA dramatically reduces the error rate of this sequencing platform, providing an accurate portrait of complex and variable HIV env populations. A public instance of FLEA is hosted at http://flea.datamonkey.org. The Python source code for the FLEA pipeline can be found at https://github.com/veg/flea-pipeline. The client-side application is available at https://github.com/veg/flea-web-app. A live demo of the P018 results can be found at http://flea.murrell.group/view/P018., Author summary Viral populations constantly evolve and diversify. In this article we introduce a method, FLEA, for reconstructing and visualizing the details of evolutionary changes. FLEA specifically processes data from sequencing platforms that generate reads that are long, but error-prone. To study the evolutionary dynamics of entire genes during viral infection, data is collected via long-read sequencing at discrete time points, allowing us to understand how the virus changes over time. However, the experimental and sequencing process is imperfect, so the resulting data contain not only real evolutionary changes, but also mutations and other genetic artifacts caused by sequencing errors. Our method corrects most of these errors by combining thousands of erroneous sequences into a much smaller number of unique consensus sequences that represent biologically meaningful variation. The resulting high-quality sequences are used for further analysis, such as building an evolutionary tree that tracks and interprets the genetic changes in the viral population over time. FLEA is open source, and is freely available online.

Inference of how evolutionary forces have shaped extant genetic diversity is a cornerstone of modern comparative sequence analysis. Advances in sequence generation and increased statistical sophistication of relevant methods now allow researchers to extract ever more evolutionary signal from the data, albeit at an increased computational cost. Here, we announce the release of Datamonkey 2.0, a completely re-engineered version of the Datamonkey web-server for analyzing evolutionary signatures in sequence data. For this endeavor, we leveraged recent developments in open-source libraries that facilitate interactive, robust, and scalable web application development. Datamonkey 2.0 provides a carefully curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application. To complement Datamonkey 2.0, we additionally release HyPhy Vision, an accompanying JavaScript application for visualizing analysis results. HyPhy Vision can also be used separately from Datamonkey 2.0 to visualize locally executed HyPhy analyses. Together, Datamonkey 2.0 and HyPhy Vision showcase how scientific software development can benefit from general-purpose open-source frameworks. Datamonkey 2.0 is freely and publicly available at http://www.datamonkey.org, and the underlying codebase is available from https://github.com/veg/datamonkey-js.

Lentiviral RNA genomes contain structural elements that play critical roles in viral replication. Although structural features of 5′-untranslated regions have been well characterized, attempts to identify important structures in other genomic regions by Selective 2′-Hydroxyl Acylation analyzed by Primer Extension (SHAPE) have led to conflicting structural and mechanistic conclusions. Previous approaches accounted neither for sequence heterogeneity that is ubiquitous in viral populations, nor for selective constraints operating at the protein level. We developed an approach that augments SHAPE with phylogenetic analyses and applied it to investigate structure in coding regions (cRNA) within the HIV and SIV envelope genes. Analysis of single-genome SHAPE data with phylogenetic information from diverse lentiviral sequences argues against the conservation of a putative global gp120 RNA structure but points to the existence of core RNA sub-structures. Our findings establish a framework for considering sequence heterogeneity and protein function in de novo RNA structure inference approaches.

Several groups have proposed that genotypic determinants in gag and the gp41 cytoplasmic domain (gp41-CD) reduce protease inhibitor (PI) susceptibility without PI-resistance mutations in protease. However, no gag and gp41-CD mutations definitively responsible for reduced PI susceptibility have been identified in individuals with virological failure (VF) while receiving a boosted PI (PI/r)-containing regimen. To identify gag and gp41 mutations under selective PI pressure, we sequenced gag and/or gp41 in 61 individuals with VF on a PI/r (n = 40) or NNRTI (n = 20) containing regimen. We quantified nonsynonymous and synonymous changes in both genes and identified sites exhibiting signal for directional or diversifying selection. We also used published gag and gp41 polymorphism data to highlight mutations displaying a high selection index, defined as changing from a conserved to an uncommon amino acid. Many amino acid mutations developed in gag and in gp41-CD in both the PI- and NNRTI-treated groups. However, in neither gene, were there discernable differences between the two groups in overall numbers of mutations, mutations displaying evidence of diversifying or directional selection, or mutations with a high selection index. If gag and/or gp41 encode PI-resistance mutations, they may not be confined to consistent mutations at a few sites.

Understanding whether the neutralizing antibody (NAb) response impacts HIV-1 superinfection and how superinfection subsequently modulates the NAb response can help clarify correlates of protection from HIV exposures and better delineate pathways of NAb development. We examined associations between the development of NAb and the occurrence of superinfection in a well-characterized, antiretroviral therapy (ART)-naive, primary infection cohort of men who have sex with men. Deep sequencing was applied to blood plasma samples from the cohort to detect cases of superinfection. We compared the NAb activity against autologous and heterologous viruses between 10 participants with intrasubtype B superinfection and 19 monoinfected controls, matched to duration of infection and risk behavior. Three to 6 months after primary infection, individuals who would later become superinfected had significantly weaker NAb activity against tier 1 subtype B viruses ( P = 0.003 for SF-162 and P = 0.017 for NL4-3) and marginally against autologous virus ( P = 0.054). Lower presuperinfection NAb responses correlated with weaker gp120 binding and lower plasma total IgG titers. Soon after superinfection, the NAb response remained lower, but between 2 and 3 years after primary infection, NAb levels strengthened and reached those of controls. Superinfecting viruses were typically not susceptible to neutralization by presuperinfection plasma. These observations suggest that recently infected individuals with a delayed NAb response against primary infecting and tier 1 subtype B viruses are more susceptible to superinfection. IMPORTANCE Our findings suggest that within the first year after HIV infection, a relatively weak neutralizing antibody response against primary and subtype-specific neutralization-sensitive viruses increases susceptibility to superinfection in the face of repeated exposures. As natural infection progresses, the immune response strengthens significantly in some superinfected individuals. These findings will inform HIV vaccine design by providing testable correlates of protection from initial HIV infection.

Venezuelan equine encephalitis (VEE) complex alphaviruses are important re-emerging arboviruses that cause life-threatening disease in equids during epizootics as well as spillover human infections. We conducted a comprehensive analysis of VEE complex alphaviruses by sequencing the genomes of 94 strains and performing phylogenetic analyses of 130 isolates using complete open reading frames for the nonstructural and structural polyproteins. Our analyses confirmed purifying selection as a major mechanism influencing the evolution of these viruses as well as a confounding factor in molecular clock dating of ancestors. Times to most recent common ancestors (tMRCAs) could be robustly estimated only for the more recently diverged subtypes; the tMRCA of the ID/IAB/IC/II and IE clades of VEE virus (VEEV) were estimated at ca. 149–973 years ago. Evolution of the IE subtype has been characterized by a significant evolutionary shift from the rest of the VEEV complex, with an increase in structural protein substitutions that are unique to this group, possibly reflecting adaptation to its unique enzootic mosquito vector Culex (Melanoconion) taeniopus. Our inferred tree topologies suggest that VEEV is maintained primarily in situ, with only occasional spread to neighboring countries, probably reflecting the limited mobility of rodent hosts and mosquito vectors., Author summary The Venezuelan equine encephalitis (VEE) complex comprises a broadly distributed group of alphaviruses in the Americas that have the potential to emerge and cause severe disease. Historically, VEE complex viruses have caused recurring outbreaks of human and equine encephalitis in Central and South America as well as Mexico, with at least one outbreak resulting in movement of the virus to the southern United States. We present the most comprehensive phylogenetic analysis of complete genomic sequences of the most prominent member of the VEE complex, VEE virus (VEEV). We were able to identify the major forces influencing VEEV evolution, and using the inferred phylogenies we determined that VEEV evolves in geographically segregated lineages with enzootic transmission between rodents and mosquitoes apparently limiting its spread.

Hepatitis E virus (HEV) is the most common cause of acute viral hepatitis globally. HEV comprises four genotypes with different geographic distributions and host ranges. We utilize this natural case-control study for investigating the evolution of zoonotic viruses compared to single-host viruses, using 244 near-full-length HEV genomes. Genome-wide estimates of the ratio of nonsynonymous to synonymous evolutionary changes ( dN / dS ratio) located a region of overlapping reading frames, which is subject to positive selection in genotypes 3 and 4. The open reading frames (ORFs) involved have functions related to host-pathogen interaction, so genotype-specific evolution of these regions may reflect their fitness. Bayesian inference of evolutionary rates shows that genotypes 3 and 4 have significantly higher rates than genotype 1 across all ORFs. Reconstruction of the phylogenies of zoonotic genotypes demonstrates significant intermingling of isolates between hosts. We speculate that the genotype-specific differences may result from cyclical adaptation to different hosts in genotypes 3 and 4. IMPORTANCE Hepatitis E virus (HEV) is increasingly recognized as a pathogen that affects both the developing and the developed world. While most often clinically mild, HEV can be severe or fatal in certain demographics, such as expectant mothers. Like many other viral pathogens, HEV has been classified into several distinct genotypes. We show that most of the HEV genome is evolutionarily constrained. One locus of positive selection is unusual in that it encodes two distinct protein products. We are the first to detect positive selection in this overlap region. Genotype 1, which infects humans only, appears to be evolving differently from genotypes 3 and 4, which infect multiple species, possibly because genotypes 3 and 4 are unable to achieve the same fitness due to repeated host jumps.

Author(s): Green, Nella; Hoenigl, Martin; Chaillon, Antoine; Anderson, Christy M; Kosakovsky Pond, Sergei L; Smith, Davey M; Little, Susan J | Abstract: BackgroundTo examine the yield of HIV partner services provided to persons newly diagnosed with acute and early HIV infection (AEH) in San Diego, United States.DesignObservational cohort study.MethodsThe study investigated the yield (i.e. number of new HIV and AEH diagnoses, genetically linked partnerships and high-risk uninfected partners) of partner services (confidential contact tracing) for individuals with AEH enrolled in the San Diego Primary Infection Resource Consortium 1996-2014.ResultsA total of 107 of 574 persons with AEH (19%; i.e. index cases) provided sufficient information to recruit 119 sex partners. Fifty-seven percent of the 119 recruited partners were HIV infected, and 33% of the 119 were newly HIV diagnosed. Among those newly HIV diagnosed, 36% were diagnosed during AEH. There were no significant demographic or behavioral risk differences between HIV-infected and HIV-uninfected recruited partners. Genetic sequences were available for both index cases and partners in 62 partnerships, of which 61% were genetically linked. Partnerships in which both index case and partner enrolled within 30 days were more likely to yield a new HIV diagnosis (P = 0.01) and to be genetically linked (P l 0.01).ConclusionPartner services for persons with AEH within 30 days of diagnosis represents an effective tool to find HIV-unaware persons, including those with AEH who are at greatest risk of HIV transmission.

For investigations of human B-cell receptor (BCR) repertoires, we have developed a protocol for large-scale surveys of human antibody heavy chain (VH) rearrangements. Here we study IgA repertoires, as more IgA antibodies are synthesized in the human body on a daily level than all other isotypes combined. In fact, IgA is secreted at all mucosal surfaces, and it is also secreted in the perspiration that coats our cutaneous surfaces. In these studies we can characterize the IgA clonal diversity of B-cell populations obtained from any donor. To recover representative repertoire libraries, we make our libraries from antibody gene transcript templates (i.e., cDNA), as these are closer reflections of the immune repertoire expressed at the antibody protein level. To avoid biases potentially introduced by upstream oligonucleotide primers that hybridize to variable region framework regions, our approach also uses rapid amplification of cDNA ends (RACE) of antibody transcripts. For exploration of human IgA responses, we have designed a duplexing antisense constant region primer that efficiently amplifies, side-by-side, heavy chain transcripts of both the IgA1 and IgA2 subclasses. By these methods we have begun to define the molecular differences in the IgA1 and IgA2 responses occurring simultaneously in different donors. These methods will be used to investigate the effects of microbial virulence factors on host defenses, during autoimmune responses, and in B-cell malignancies.

Author(s): Wagner, Gabriel A; Chaillon, Antoine; Liu, Siqi; Franklin, Donald R; Caballero, Gemma; Kosakovsky Pond, Sergei L; Vaida, Florin; Heaton, Robert K; Letendre, Scott L; Grant, Igor; Richman, Douglas D; Smith, Davey M | Abstract: ObjectiveCompared with HIV monoinfection, HIV dual infection has been associated with decreased CD4 T-cell counts and increased viral loads. The same markers are also associated with the development of HIV-associated neurocognitive disorder (HAND), which continues to be a prevalent problem in the era of combination antiretroviral therapy (ART). We sought to determine the relationship between dual infection and HAND.MethodsParticipants on ART (N = 38) underwent deep sequencing of four PCR-amplified HIV coding regions derived from peripheral blood mononuclear cell DNA samples. Phylogenetic analyses were performed to evaluate whether two distinct viral lineages, that is, dual infection, were present in the same individual. All study participants underwent neurocognitive, substance use, and neuromedical assessments at each study visit.ResultsOf 38 participants, nine (23.7%) had evidence of dual infection. Using clinical ratings, global neurocognitive impairment was identified in 21 (55%) participants, and multivariate analysis demonstrated a significant association between dual infection and impairment; odds ratio (95% confidence interval) = 18.3 (1.9, 414.2), P = 0.028. Neurocognitive impairment was also associated with lower current (P = 0.028) and nadir (P = 0.043) CD4 T-cell counts.ConclusionsDeep sequencing of HIV DNA populations in blood mononuclear cell identified dual infection in nearly a quarter of HIV-infected adults receiving ART, and dual infection was associated with HAND. Dual infection may contribute to the development of HAND, perhaps because of increased viral diversity. Further investigation is needed to determine how dual infection results in worse neurocognitive performance.

To design effective eradication strategies, it may be necessary to target HIV reservoirs in anatomic compartments other than blood. This study examined HIV RNA rebound following interruption of antiretroviral therapy (ART) in blood and cerebrospinal fluid (CSF) to determine whether the central nervous system (CNS) might serve as an independent source of resurgent viral replication. Paired blood and CSF samples were collected longitudinally from 14 chronically HIV-infected individuals undergoing ART interruption. HIV env (C2-V3), gag (p24) and pol (reverse transcriptase) were sequenced from cell-free HIV RNA and cell-associated HIV DNA in blood and CSF using the Roche 454 FLX Titanium platform. Comprehensive sequence and phylogenetic analyses were performed to search for evidence of unique or differentially represented viral subpopulations emerging in CSF supernatant as compared with blood plasma. Using a conservative definition of compartmentalization based on four distinct statistical tests, nine participants presented a compartmentalized HIV RNA rebound within the CSF after interruption of ART, even when sampled within 2 weeks from viral rebound. The degree and duration of viral compartmentalization varied considerably between subjects and between time-points within a subject. In 10 cases, we identified viral populations within the CSF supernatant at the first sampled time-point after ART interruption, which were phylogenetically distinct from those present in the paired blood plasma and mostly persisted over time (when longitudinal time-points were available). Our data suggest that an independent source of HIV RNA contributes to viral rebound within the CSF after treatment interruption. The most likely source of compartmentalized HIV RNA is a CNS reservoir that would need to be targeted to achieve complete HIV eradication.

International audience; The high-mannose patch on HIV Env is a preferred target for broadly neutralizing antibodies (bnAbs), but to date, no vaccination regimen has elicited bnAbs against this region. Here, we present the development of a bnAb lineage targeting the high-mannose patch in an HIV-1 subtype-C-infected donor from sub-Saharan Africa. The Abs first acquired autologous neutralization, then gradually matured to achieve breadth. One Ab neutralized >47% of HIV-1 strains with only ∼11% somatic hypermutation and no insertions or deletions. By sequencing autologous env, we determined key residues that triggered the lineage and participated in Ab-Env coevolution. Next-generation sequencing of the Ab repertoire showed an early expansive diversification of the lineage followed by independent maturation of individual limbs, several of them developing notable breadth and potency. Overall, the findings are encouraging from a vaccine standpoint and suggest immunization strategies mimicking the evolution of the entire high-mannose patch and promoting maturation of multiple diverse Ab pathways.

Antiretroviral therapy-naive HIV-1 infected infants experience poor viral containment and rapid disease progression compared to adults. Viral factors (e.g. transmitted cytotoxic T- lymphocyte (CTL) escape mutations) or infant factors (e.g. reduced CTL functional capacity) may explain this observation. We assessed CTL functionality by analysing selection in CTL-targeted HIV-1 epitopes following perinatal infection. HIV-1 gag, pol and nef sequences were generated from a historical repository of longitudinal specimens from 19 vertically infected infants. Evolutionary rate and selection were estimated for each gene and in CTL-restricted and non-restricted epitopes. Evolutionary rate was higher in nef and gag vs. pol, and lower in infants with non-severe immunosuppression vs. severe immunosuppression across gag and nef. Selection pressure was stronger in infants with non-severe immunosuppression vs. severe immunosuppression across gag. The analysis also showed that infants with non-severe immunosuppression had stronger selection in CTL-restricted vs. non-restricted epitopes in gag and nef. Evidence of stronger CTL selection was absent in infants with severe immunosuppression. These data indicate that infant CTLs can exert selection pressure on gag and nef epitopes in early infection and that stronger selection across CTL epitopes is associated with favourable clinical outcomes. These results have implications for the development of paediatric HIV-1 vaccines.

Lymphoid tissue is a key reservoir established by HIV-1 during acute infection. It is a site associated with viral production, storage of viral particles in immune complexes, and viral persistence. Although combinations of antiretroviral drugs usually suppress viral replication and reduce viral RNA to undetectable levels in blood, it is unclear whether treatment fully suppresses viral replication in lymphoid tissue reservoirs. Here we show that virus evolution and trafficking between tissue compartments continues in patients with undetectable levels of virus in their bloodstream. We present a spatial and dynamic model of persistent viral replication and spread that indicates why the development of drug resistance is not a foregone conclusion under conditions in which drug concentrations are insufficient to completely block virus replication. These data provide new insights into the evolutionary and infection dynamics of the virus population within the host, revealing that HIV-1 can continue to replicate and replenish the viral reservoir despite potent antiretroviral therapy.

Broadly neutralizing antibodies (bnAbs) are thought to be a critical component of a protective HIV vaccine. However, designing vaccines immunogens able to elicit bnAbs has proven unsuccessful to date. Understanding the correlates and immunological mechanisms leading to the development of bnAb responses during natural HIV infection is thus critical to the design of a protective vaccine. The IAVI Protocol C program investigates a large longitudinal cohort of primary HIV-1 infection in Eastern and South Africa. Development of neutralization was evaluated in 439 donors using a 6 cross-clade pseudo-virus panel predictive of neutralization breadth on larger panels. About 15% of individuals developed bnAb responses, essentially between year 2 and year 4 of infection. Statistical analyses revealed no influence of gender, age or geographical origin on the development of neutralization breadth. However, cross-clade neutralization strongly correlated with high viral load as well as with low CD4 T cell counts, subtype-C infection and HLA-A*03(-) genotype. A correlation with high overall plasma IgG levels and anti-Env IgG binding titers was also found. The latter appeared not associated with higher affinity, suggesting a greater diversity of the anti-Env responses in broad neutralizers. Broadly neutralizing activity targeting glycan-dependent epitopes, largely the N332-glycan epitope region, was detected in nearly half of the broad neutralizers while CD4bs and gp41-MPER bnAb responses were only detected in very few individuals. Together the findings suggest that both viral and host factors are critical for the development of bnAbs and that the HIV Env N332-glycan supersite may be a favorable target for vaccine design., Author Summary Understanding how HIV-1-broadly neutralizing antibodies (bnAbs) develop during natural infection is essential to the design of an efficient HIV vaccine. We studied kinetics and correlates of neutralization breadth in a large sub-Saharan African longitudinal cohort of 439 participants with primary HIV-1 infection. Broadly nAb responses developed in 15% of individuals, on average three years after infection. Broad neutralization was associated with high viral load, low CD4+ T cell counts, virus subtype C infection and HLA*A3(-) genotype. A correlation with high overall plasma IgG levels and anti-Env binding titers was also found. Specificity mapping of the bnAb responses showed that glycan-dependent epitopes, in particular the N332 region, were most commonly targeted, in contrast to other bnAb epitopes, suggesting that the HIV Env N332-glycan epitope region may be a favorable target for vaccine design.

Transmission of multiple founder variants has been associated with faster HIV disease progression. Many studies have attempted to determine the number of founder variants, mainly by analysis of sequence diversity and/or tree topology from acutely HIV-infected individuals. We hypothesized that adding sequence data collected from source partners might improve resolution and characterization of transmission events. Blood plasma samples were collected from both the source and recipient in thirty epidemiologically- and phylogenetically linked transmission pairs. All were men who have sex with men, sampled on average 70 days (range 11–170) after the recipient’s estimated date of infection. Next generation sequencing (454 FLX, Roche) of HIV-1 env (C2-V3) was performed for all samples. Inspection of sequence alignments, highlighter plots, phylogenetic tree topologies and sequence diversity were used to determine the multiplicity of founder viruses with and without the inclusion of source data. Using only recipient sequence data, we were able to resolve multiplicity in twenty-six of the thirty transmission pairs (87 percent). Among them, five presented with a high viral diversity at baseline (>0.10 subst/site), consistent with multiple founders. By incorporating sequence data collected from the source partner, we were able to characterize all thirty transmission pairs. Overall, sixteen transmission events (53.3 percent) involved multiple founders. Results obtained by combining sequence data from recipient and source were congruent for nineteen of the twenty-six (73 percent) cases where conclusions were made using only recipient sequence data. The multiplicity of founders was associated with significantly higher HIV RNA levels (P = 0.04). To further evaluate the transmission bottleneck, we focused on single founder transmissions (fourteen of the thirty), and identified four recipients (28.6 percent) that had founder variants that were inferred to arise from minority viral populations in the source. These source clades ranged from 1.0 to 5.4 percent of the sampled population. Incorporating sequence data from the source increased of the ability to determine the multiplicity of founder variants, reduced misclassification, and allowed us to infer the transmission of minority variants.