Bat pluripotent stem cells reveal unusual entanglement between host and viruses.

Bats are distinctive among mammals due to their ability to fly, use laryngeal echolocation, and tolerate viruses. However, there are currently no reliable cellular models for studying bat biology or their response to viral infections. Here, we created induced pluripotent stem cells (iPSCs) from two species of bats: the wild greater horseshoe bat (Rhinolophus ferrumequinum) and the greater mouse-eared bat (Myotis myotis). The iPSCs from both bat species showed similar characteristics and had a gene expression profile resembling that of cells attacked by viruses. They also had a high number of endogenous viral sequences, particularly retroviruses. These results suggest that bats have evolved mechanisms to tolerate a large load of viral sequences and may have a more intertwined relationship with viruses than previously thought. Further study of bat iPSCs and their differentiated progeny will provide insights into bat biology, virus host relationships, and the molecular basis of bats' special traits.

Differences in epidemiology of enteropathogens in children pre- and post-rotavirus vaccine introduction in Kilifi, coastal Kenya.

BACKGROUND: Kenya introduced Rotarix® (GlaxoSmithKline Biologicals, Rixensart, Belgium) vaccination into its national immunization programme beginning July 2014. The impact of this vaccination program on the local epidemiology of various known enteropathogens is not fully understood. METHODS: We used a custom TaqMan Array Card (TAC) to screen for 28 different enteropathogens in 718 stools from children aged less than 13 years admitted to Kilifi County Hospital, coastal Kenya, following presentation with diarrhea in 2013 (before vaccine introduction) and in 2016-2018 (after vaccine introduction). Pathogen positivity rate differences between pre- and post-Rotarix® vaccination introduction were examined using both univariate and multivariable logistic regression models. RESULTS: In 665 specimens (92.6%), one or more enteropathogen was detected, while in 323 specimens (48.6%) three or more enteropathogens were detected. The top six detected enteropathogens were: enteroaggregative Escherichia coli (EAggEC; 42.1%), enteropathogenic Escherichia coli (EPEC; 30.2%), enterovirus (26.9%), rotavirus group A (RVA; 24.8%), parechovirus (16.6%) and norovirus GI/GII (14.4%). Post-rotavirus vaccine introduction, there was a significant increase in the proportion of samples testing positive for EAggEC (35.7% vs. 45.3%, p = 0.014), cytomegalovirus (4.2% vs. 9.9%, p = 0.008), Vibrio cholerae (0.0% vs. 2.3%, p = 0.019), Strongyloides species (0.8% vs. 3.6%, p = 0.048) and Dientamoeba fragilis (2.1% vs. 7.8%, p = 0.004). Although not reaching statistical significance, the positivity rate of adenovirus 40/41 (5.8% vs. 7.3%, p = 0.444), norovirus GI/GII (11.2% vs. 15.9%, p = 0.089), Shigella species (8.7% vs. 13.0%, p = 0.092) and Cryptosporidium spp. (11.6% vs. 14.7%, p = 0.261) appeared to increase post-vaccine introduction. Conversely, the positivity rate of sapovirus decreased significantly post-vaccine introduction (7.8% vs. 4.0%, p = 0.030) while that of RVA appeared not to change (27.4% vs. 23.5%, p = 0.253). More enteropathogen coinfections were detected per child post-vaccine introduction compared to before (mean: 2.7 vs. 2.3; p = 0.0025). CONCLUSIONS: In this rural Coastal Kenya setting, childhood enteropathogen infection burden was high both pre- and post-rotavirus vaccination introduction. Children who had diarrheal admissions post-vaccination showed an increase in coinfections and changes in specific enteropathogen positivity rates. This study highlights the utility of multipathogen detection platforms such as TAC in understanding etiology of childhood acute gastroenteritis in resource-limited regions.

Intersection of Syphilis and Human Immunodeficiency Virus (HIV) Networks to Identify Opportunities to Enhance HIV Prevention.

BACKGROUND: Human immunodeficiency virus (HIV) and syphilis infection continue at disproportionate rates among minority men who have sex with men (MSM) in the United States. The integration of HIV genetic clustering with partner services can provide important insight into local epidemic trends to guide interventions and control efforts. METHODS: We evaluated contact networks of index persons defined as minority men and transgender women diagnosed with early syphilis and/or HIV infection between 2018 and 2020 in 2 North Carolina regions. HIV clusters were constructed from pol sequences collected through statewide surveillance. A combined "HIV-risk" network, which included persons with any links (genetic or sexual contact) to HIV-positive persons, was evaluated by component size, demographic factors, and HIV viral suppression. RESULTS: In total, 1289 index persons were identified and 55% named 1153 contacts. Most index persons were Black (88%) and young (median age 30 years); 70% had early syphilis and 43% had prevalent HIV infection. Most people with HIV (65%) appeared in an HIV cluster. The combined HIV-risk network (1590 contact network and 1500 cluster members) included 287 distinct components; however, 1586 (51%) were in a single component. Fifty-five percent of network members with HIV had no evidence of viral suppression. Overall, fewer index persons needed to be interviewed to identify 1 HIV-positive member without viral suppression (1.3 vs 4.0 for contact tracing). CONCLUSIONS: Integration of HIV clusters and viral loads illuminate networks with high HIV prevalence, indicating recent and ongoing transmission. Interventions intensified toward these networks may efficiently reach persons for HIV prevention and care re-engagement.

Phylodynamics of infectious disease epidemics.

We present a formalism for unifying the inference of population size from genetic sequences and mathematical models of infectious disease in populations. Virus phylogenies have been used in many recent studies to infer properties of epidemics. These approaches rely on coalescent models that may not be appropriate for infectious diseases. We account for phylogenetic patterns of viruses in susceptible-infected (SI), susceptible-infected-susceptible (SIS), and susceptible-infected-recovered (SIR) models of infectious disease, and our approach may be a viable alternative to demographic models used to reconstruct epidemic dynamics. The method allows epidemiological parameters, such as the reproductive number, to be estimated directly from viral sequence data. We also describe patterns of phylogenetic clustering that are often construed as arising from a short chain of transmissions. Our model reproduces the moments of the distribution of phylogenetic cluster sizes and may therefore serve as a null hypothesis for cluster sizes under simple epidemiological models. We examine a small cross-sectional sample of human immunodeficiency (HIV)-1 sequences collected in the United States and compare our results to standard estimates of effective population size. Estimated prevalence is consistent with estimates of effective population size and the known history of the HIV epidemic. While our model accurately estimates prevalence during exponential growth, we find that periods of decline are harder to identify.

Immune-driven recombination and loss of control after HIV superinfection.

After acute HIV infection, CD8(+) T cells are able to control viral replication to a set point. This control is often lost after superinfection, although the mechanism behind this remains unclear. In this study, we illustrate in an HLA-B27(+) subject that loss of viral control after HIV superinfection coincides with rapid recombination events within two narrow regions of Gag and Env. Screening for CD8(+) T cell responses revealed that each of these recombination sites (approximately 50 aa) encompassed distinct regions containing two immunodominant CD8 epitopes (B27-KK10 in Gag and Cw1-CL9 in Env). Viral escape and the subsequent development of variant-specific de novo CD8(+) T cell responses against both epitopes were illustrative of the significant immune selection pressures exerted by both responses. Comprehensive analysis of the kinetics of CD8 responses and viral evolution indicated that the recombination events quickly facilitated viral escape from both dominant WT- and variant-specific responses. These data suggest that the ability of a superinfecting strain of HIV to overcome preexisting immune control may be related to its ability to rapidly recombine in critical regions under immune selection pressure. These data also support a role for cellular immune pressures in driving the selection of new recombinant forms of HIV.

Persistence of transmitted drug resistance among subjects with primary human immunodeficiency virus infection.

Following interruption of antiretroviral therapy among individuals with acquired drug resistance, preexisting drug-sensitive virus emerges relatively rapidly. In contrast, wild-type virus is not archived in individuals infected with drug-resistant human immunodeficiency virus (HIV) and thus cannot emerge rapidly in the absence of selective drug pressure. Fourteen recently HIV-infected patients with transmitted drug-resistant virus were followed for a median of 2.1 years after the estimated date of infection (EDI) without receiving antiretroviral therapy. HIV drug resistance and pol replication capacity (RC) in longitudinal plasma samples were assayed. Resistance mutations were characterized as pure populations or mixtures. The mean time to first detection of a mixture of wild-type and drug-resistant viruses was 96 weeks (1.8 years) (95% confidence interval, 48 to 192 weeks) after the EDI. The median time to loss of detectable drug resistance using population-based assays ranged from 4.1 years (conservative estimate) to longer than the lifetime of the individual (less conservative estimate). The transmission of drug-resistant virus was not associated with virus with reduced RC. Sexual transmission of HIV selects for highly fit drug-resistant variants that persist for years. The prolonged persistence of transmitted drug resistance strongly supports the routine use of HIV resistance genotyping for all newly diagnosed individuals.

Herpes simplex virus type 2 acquisition during recent HIV infection does not influence plasma HIV levels.

We assessed the effect of herpes simplex virus type 2 (HSV-2) acquisition on the plasma HIV RNA and CD4 cell levels among individuals with primary HIV infection using a retrospective cohort analysis. We studied 119 adult, antiretroviral-naive, recently HIV-infected men with a negative HSV-2-specific enzyme immunoassay (EIA) result at enrollment. HSV-2 acquisition was determined by seroconversion on HSV-2 EIA, confirmed by Western blot analysis. Ten men acquired HSV-2 infection a median of 1.3 years after HIV infection (HSV-2 incidence rate of 7.4 per 100 person-years of follow-up). The median time of follow-up after acquiring HSV-2 infection was 303 days. All men except 1 were asymptomatic during HSV-2 acquisition, and only 1 HSV-2 seroconverter, who was asymptomatic, had a transient increase in blood HIV load (0.5 log10 copies/mL over 11 days). The HSV-2 incidence rate was high in our cohort of recently HIV-infected individuals; however, HSV-2 acquisition did not significantly change the plasma HIV dynamics and CD4 cell levels.

An evolutionary-network model reveals stratified interactions in the V3 loop of the HIV-1 envelope.

The third variable loop (V3) of the human immunodeficiency virus type 1 (HIV-1) envelope is a principal determinant of antibody neutralization and progression to AIDS. Although it is undoubtedly an important target for vaccine research, extensive genetic variation in V3 remains an obstacle to the development of an effective vaccine. Comparative methods that exploit the abundance of sequence data can detect interactions between residues of rapidly evolving proteins such as the HIV-1 envelope, revealing biological constraints on their variability. However, previous studies have relied implicitly on two biologically unrealistic assumptions: (1) that founder effects in the evolutionary history of the sequences can be ignored, and; (2) that statistical associations between residues occur exclusively in pairs. We show that comparative methods that neglect the evolutionary history of extant sequences are susceptible to a high rate of false positives (20%-40%). Therefore, we propose a new method to detect interactions that relaxes both of these assumptions. First, we reconstruct the evolutionary history of extant sequences by maximum likelihood, shifting focus from extant sequence variation to the underlying substitution events. Second, we analyze the joint distribution of substitution events among positions in the sequence as a Bayesian graphical model, in which each branch in the phylogeny is a unit of observation. We perform extensive validation of our models using both simulations and a control case of known interactions in HIV-1 protease, and apply this method to detect interactions within V3 from a sample of 1,154 HIV-1 envelope sequences. Our method greatly reduces the number of false positives due to founder effects, while capturing several higher-order interactions among V3 residues. By mapping these interactions to a structural model of the V3 loop, we find that the loop is stratified into distinct evolutionary clusters. We extend our model to detect interactions between the V3 and C4 domains of the HIV-1 envelope, and account for the uncertainty in mapping substitutions to the tree with a parametric bootstrap.

Computational analysis and identification of amino acid sites in dengue E proteins relevant to development of diagnostics and vaccines.

We have identified 72 completely conserved amino acid residues in the E protein of major groups of the Flavivirus genus by computational analyses. In the dengue species we have identified 12 highly conserved sequence regions, 186 negatively selected sites, and many dengue serotype-specific negatively selected sites. The flavivirus-conserved sites included residues involved in forming six disulfide bonds crucial for the structural integrity of the protein, the fusion motif involved in viral infectivity, and the interface residues of the oligomers. The structural analysis of the E protein showed 19 surface-exposed non-conserved residues, 128 dimer or trimer interface residues, and regions, which undergo major conformational change during trimerization. Eleven consensus T(h)-cell epitopes common to all four dengue serotypes were predicted. Most of these corresponded to dengue-conserved regions or negatively selected sites. Of special interest are six singular sites (N(37), Q(211), D(215), P(217), H(244), K(246)) in dengue E protein that are conserved, are part of the predicted consensus T(h)-cell epitopes and are exposed in the dimer or trimer. We propose these sites and corresponding epitopic regions as potential candidates for prioritization by experimental biologists for development of diagnostics and vaccines that may be difficult to circumvent by natural or man-made alteration of dengue virus.

Evolutionary interactions between N-linked glycosylation sites in the HIV-1 envelope.

The addition of asparagine (N)-linked polysaccharide chains (i.e., glycans) to the gp120 and gp41 glycoproteins of human immunodeficiency virus type 1 (HIV-1) envelope is not only required for correct protein folding, but also may provide protection against neutralizing antibodies as a "glycan shield." As a result, strong host-specific selection is frequently associated with codon positions where nonsynonymous substitutions can create or disrupt potential N-linked glycosylation sites (PNGSs). Moreover, empirical data suggest that the individual contribution of PNGSs to the neutralization sensitivity or infectivity of HIV-1 may be critically dependent on the presence or absence of other PNGSs in the envelope sequence. Here we evaluate how glycan-glycan interactions have shaped the evolution of HIV-1 envelope sequences by analyzing the distribution of PNGSs in a large-sequence alignment. Using a "covarion"-type phylogenetic model, we find that the rates at which individual PNGSs are gained or lost vary significantly over time, suggesting that the selective advantage of having a PNGS may depend on the presence or absence of other PNGSs in the sequence. Consequently, we identify specific interactions between PNGSs in the alignment using a new paired-character phylogenetic model of evolution, and a Bayesian graphical model. Despite the fundamental differences between these two methods, several interactions are jointly identified by both. Mapping these interactions onto a structural model of HIV-1 gp120 reveals that negative (exclusive) interactions occur significantly more often between colocalized glycans, while positive (inclusive) interactions are restricted to more distant glycans. Our results imply that the adaptive repertoire of alternative configurations in the HIV-1 glycan shield is limited by functional interactions between the N-linked glycans. This represents a potential vulnerability of rapidly evolving HIV-1 populations that may provide useful glycan-based targets for neutralizing antibodies.

Evolutionary model selection with a genetic algorithm: a case study using stem RNA.

The choice of a probabilistic model to describe sequence evolution can and should be justified. Underfitting the data through the use of overly simplistic models may miss out on interesting phenomena and lead to incorrect inferences. Overfitting the data with models that are too complex may ascribe biological meaning to statistical artifacts and result in falsely significant findings. We describe a likelihood-based approach for evolutionary model selection. The procedure employs a genetic algorithm (GA) to quickly explore a combinatorially large set of all possible time-reversible Markov models with a fixed number of substitution rates. When applied to stem RNA data subject to well-understood evolutionary forces, the models found by the GA 1) capture the expected overall rate patterns a priori; 2) fit the data better than the best available models based on a priori assumptions, suggesting subtle substitution patterns not previously recognized; 3) cannot be rejected in favor of the general reversible model, implying that the evolution of stem RNA sequences can be explained well with only a few substitution rate parameters; and 4) perform well on simulated data, both in terms of goodness of fit and the ability to estimate evolutionary rates. We also investigate the utility of several distance measures for comparing and contrasting inferred evolutionary models. Using widely available small computer clusters, our approach allows, for the first time, to evaluate the performance of existing RNA evolutionary models by comparing them with a large pool of candidate models and to validate common modeling assumptions. In addition, the new method provides the foundation for rigorous selection and comparison of substitution models for other types of sequence data.

Respondent-driven sampling of injection drug users in two U.S.-Mexico border cities: recruitment dynamics and impact on estimates of HIV and syphilis prevalence.

Respondent-driven sampling (RDS), a chain referral sampling approach, is increasingly used to recruit participants from hard-to-reach populations, such as injection drug users (IDUs). Using RDS, we recruited IDUs in Tijuana and Ciudad (Cd.) Juárez, two Mexican cities bordering San Diego, CA and El Paso, TX, respectively, and compared recruitment dynamics, reported network size, and estimates of HIV and syphilis prevalence. Between February and April 2005, we used RDS to recruit IDUs in Tijuana (15 seeds, 207 recruits) and Cd. Juárez (9 seeds, 197 recruits), Mexico for a cross-sectional study of behavioral and contextual factors associated with HIV, HCV and syphilis infections. All subjects provided informed consent, an anonymous interview, and a venous blood sample for serologic testing of HIV, HCV, HBV (Cd. Juárez only) and syphilis antibody. Log-linear models were used to analyze the association between the state of the recruiter and that of the recruitee in the referral chains, and population estimates of the presence of syphilis antibody were obtained, correcting for biased sampling using RDS-based estimators. Sampling of the targeted 200 recruits per city was achieved rapidly (2 months in Tijuana, 2 weeks in Cd. Juárez). After excluding seeds and missing data, the sample prevalence of HCV, HIV and syphilis were 96.6, 1.9 and 13.5% respectively in Tijuana, and 95.3, 4.1, and 2.7% respectively in Cd. Juárez (where HBV prevalence was 84.7%). Syphilis cases were clustered in recruitment trees. RDS-corrected estimates of syphilis antibody prevalence ranged from 12.8 to 26.8% in Tijuana and from 2.9 to 15.6% in Ciudad Juárez, depending on how recruitment patterns were modeled, and assumptions about how network size affected an individual's probability of being included in the sample. RDS was an effective method to rapidly recruit IDUs in these cities. Although the frequency of HIV was low, syphilis prevalence was high, particularly in Tijuana. RDS-corrected estimates of syphilis prevalence were sensitive to model assumptions, suggesting that further validation of RDS is necessary.

Neutralizing antibody responses drive the evolution of human immunodeficiency virus type 1 envelope during recent HIV infection.

HIV type 1 (HIV-1) can rapidly escape from neutralizing antibody responses. The genetic basis of this escape in vivo is poorly understood. We compared the pattern of evolution of the HIV-1 env gene between individuals with recent HIV infection whose virus exhibited either a low or a high rate of escape from neutralizing antibody responses. We demonstrate that the rate of viral escape at a phenotypic level is highly variable among individuals, and is strongly correlated with the rate of amino acid substitutions. We show that dramatic escape from neutralizing antibodies can occur in the relative absence of changes in glycosylation or insertions and deletions ("indels") in the envelope; conversely, changes in glycosylation and indels occur even in the absence of neutralizing antibody responses. Comparison of our data with the predictions of a mathematical model support a mechanism in which escape from neutralizing antibodies occurs via many amino acid substitutions, with low cross-neutralization between closely related viral strains. Our results suggest that autologous neutralizing antibody responses may play a pivotal role in the diversification of HIV-1 envelope during the early stages of infection.

Characterization of human immunodeficiency virus type 1 (HIV-1) envelope variation and neutralizing antibody responses during transmission of HIV-1 subtype B.

We analyzed neutralization sensitivity and genetic variation of transmitted subtype B human immunodeficiency virus type 1 (HIV-1) in eight recently infected men who have sex with men and the virus from the six subjects who infected them. In contrast to reports of heterosexual transmission of subtype C HIV-1, in which the transmitted virus appears to be more neutralization sensitive, we demonstrate that in our study population, relatively few phenotypic changes in neutralization sensitivity or genotypic changes in envelope occurred during transmission of subtype B HIV-1. We suggest that limited genetic variation within the infecting host reduces the likelihood of selective transmission of neutralization-sensitive HIV.

Genetic basis of hypersusceptibility to protease inhibitors and low replicative capacity of human immunodeficiency virus type 1 strains in primary infection.

The initial virus strains from as many as 12% of individuals with primary human immunodeficiency virus (HIV) infection have a 50% inhibitory concentration

Association of antiretroviral resistance genotypes with response to therapy--comparison of three models.

Genotype-based resistance assays are commonly used to aid treatment in HIV-infected individuals failing antiretroviral therapy. The relationship between genotype and antiretroviral therapy comes mostly from in vitro assays of the response to a single drugs although there is a need for a prediction of clinical response to combination therapy. We have compared three different methods of analysing genotype data as a predictor of clinical response in a small clinical cohort of highly antiretroviral-experienced individuals failing therapy. No method performed well beyond 8 weeks into a new therapeutic regimen. A model based on the number of 'primary' mutations was statistically significant, but a multiple regression model, which identified specific mutations explained threefold more variation in response. Optimal prediction in this dataset was given by a model obtained from a classification tree analysis, in which genotype at amino acid sites 135 and 202 were combined with amino acid site 184, which explained over 50% of the deviance in the data and had a classification success of 86%.