Estimating the Timing of Early Simian-Human Immunodeficiency Virus Infections: a Comparison between Poisson Fitter and BEAST.
ABSTRACT: Many HIV prevention strategies are currently under consideration where it is highly informative to know the study participants' times of infection. These can be estimated using viral sequence data sampled early in infection. However, there are several scenarios that, if not addressed, can skew timing estimates. These include multiple transmitted/founder (TF) viruses, APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like)-mediated mutational enrichment, and recombination. Here, we suggest a pipeline to identify these problems and resolve the biases that they introduce. We then compare two modeling strategies to obtain timing estimates from sequence data. The first, Poisson Fitter (PF), is based on a Poisson model of random accumulation of mutations relative to the TF virus (or viruses) that established the infection. The second uses a coalescence-based phylogenetic strategy as implemented in BEAST. The comparison is based on timing predictions using plasma viral RNA (cDNA) sequence data from 28 simian-human immunodeficiency virus (SHIV)-infected animals for which the exact day of infection is known. In this particular setting, based on nucleotide sequences from samples obtained in early infection, the Poisson method yielded more accurate, more precise, and unbiased estimates for the time of infection than did the explored implementations of BEAST.IMPORTANCE The inference of the time of infection is a critical parameter in testing the efficacy of clinical interventions in protecting against HIV-1 infection. For example, in clinical trials evaluating the efficacy of passively delivered antibodies (Abs) for preventing infections, accurate time of infection data are essential for discerning levels of the Abs required to confer protection, given the natural Ab decay rate in the human body. In such trials, genetic sequences from early in the infection are regularly sampled from study participants, generally prior to immune selection, when the viral population is still expanding and genetic diversity is low. In this particular setting of early viral growth, the Poisson method is superior to the alternative approach based on coalescent methods. This approach can also be applied in human vaccine trials, where accurate estimates of infection times help ascertain if vaccine-elicited immune protection wanes over time.
Project description:Knowledge of the time of HIV-1 infection and the multiplicity of viruses that establish HIV-1 infection is crucial for the in-depth analysis of clinical prevention efficacy trial outcomes. Better estimation methods would improve the ability to characterize immunological and genetic sequence correlates of efficacy within preventive efficacy trials of HIV-1 vaccines and monoclonal antibodies. We developed new methods for infection timing and multiplicity estimation using maximum likelihood estimators that shift and scale (calibrate) estimates by fitting true infection times and founder virus multiplicities to a linear regression model with independent variables defined by data on HIV-1 sequences, viral load, diagnostics, and sequence alignment statistics. Using Poisson models of measured mutation counts and phylogenetic trees, we analyzed longitudinal HIV-1 sequence data together with diagnostic and viral load data from the RV217 and CAPRISA 002 acute HIV-1 infection cohort studies. We used leave-one-out cross validation to evaluate the prediction error of these calibrated estimators versus that of existing estimators and found that both infection time and founder multiplicity can be estimated with improved accuracy and precision by calibration. Calibration considerably improved all estimators of time since HIV-1 infection, in terms of reducing bias to near zero and reducing root mean squared error (RMSE) to 5-10 days for sequences collected 1-2 months after infection. The calibration of multiplicity assessments yielded strong improvements with accurate predictions (ROC-AUC above 0.85) in all cases. These results have not yet been validated on external data, and the best-fitting models are likely to be less robust than simpler models to variation in sequencing conditions. For all evaluated models, these results demonstrate the value of calibration for improved estimation of founder multiplicity and of time since HIV-1 infection.
Project description:If viruses or other pathogens infect a single host, the outcome of infection may depend on the initial basic reproduction number R0, the expected number of host cells infected by a single infected cell. This article shows that sometimes, phylogenetic models can estimate the initial R0, using only sequences sampled from the pathogenic population during its exponential growth or shortly thereafter. When evaluated by simulations mimicking the bursting viral reproduction of HIV and simultaneous sampling of HIV gp120 sequences during early viremia, the estimated R0 displayed useful accuracies in achievable experimental designs. Estimates of R0 have several potential applications to investigators interested in the progress of infection in single hosts, including: (1) timing a pathogen's movement through different microenvironments; (2) timing the change points in a pathogen's mode of spread (e.g., timing the change from cell-free spread to cell-to-cell spread, or vice versa, in an HIV infection); (3) quantifying the impact different initial microenvironments have on pathogens (e.g., in mucosal challenge with HIV, quantifying the impact that the presence or absence of mucosal infection has on R0); (4) quantifying subtle changes in infectability in therapeutic trials (either human or animal), even when therapies do not produce total sterilizing immunity; and (5) providing a variable predictive of the clinical efficacy of prophylactic therapies.
Project description:Stochastic transmission dynamic models are especially useful for studying the early emergence of novel pathogens given the importance of chance events when the number of infectious individuals is small. However, methods for parameter estimation and prediction for these types of stochastic models remain limited. In this manuscript, we describe a calibration and prediction framework for stochastic compartmental transmission models of epidemics. The proposed method, Multiple Shooting for Stochastic systems (MSS), applies a linear noise approximation to describe the size of the fluctuations, and uses each new surveillance observation to update the belief about the true epidemic state. Using simulated outbreaks of a novel viral pathogen, we evaluate the accuracy of MSS for real-time parameter estimation and prediction during epidemics. We assume that weekly counts for the number of new diagnosed cases are available and serve as an imperfect proxy of incidence. We show that MSS produces accurate estimates of key epidemic parameters (i.e. mean duration of infectiousness, R0, and Reff) and can provide an accurate estimate of the unobserved number of infectious individuals during the course of an epidemic. MSS also allows for accurate prediction of the number and timing of future hospitalizations and the overall attack rate. We compare the performance of MSS to three state-of-the-art benchmark methods: 1) a likelihood approximation with an assumption of independent Poisson observations; 2) a particle filtering method; and 3) an ensemble Kalman filter method. We find that MSS significantly outperforms each of these three benchmark methods in the majority of epidemic scenarios tested. In summary, MSS is a promising method that may improve on current approaches for calibration and prediction using stochastic models of epidemics.
Project description:Acute viral infections pose many practical challenges for the accurate assessment of the impact of novel therapies on viral growth and decay. Using the example of influenza A, we illustrate how the measurement of infection-related quantities that determine the dynamics of viral load within the human host, can inform investigators on the course and severity of infection and the efficacy of a novel treatment. We estimated the values of key infection-related quantities that determine the course of natural infection from viral load data, using Markov Chain Monte Carlo methods. The data were placebo group viral load measurements collected during volunteer challenge studies, conducted by Roche, as part of the oseltamivir trials. We calculated the values of the quantities for each patient and the correlations between the quantities, symptom severity and body temperature. The greatest variation among individuals occurred in the viral load peak and area under the viral load curve. Total symptom severity correlated positively with the basic reproductive number. The most sensitive endpoint for therapeutic trials with the goal to cure patients is the duration of infection. We suggest laboratory experiments to obtain more precise estimates of virological quantities that can supplement clinical endpoint measurements.
Project description:Most HIV-1 infected individuals do not know their infection dates. Precise infection timing is crucial information for studies that document transmission networks or drug levels at infection. To improve infection timing, we used the prospective RV217 cohort where the window when plasma viremia becomes detectable is narrow: the last negative visit occurred a median of four days before the first detectable HIV-1 viremia with an RNA test, referred below as diagnosis. We sequenced 1,280 HIV-1 genomes from 39 participants at a median of 4, 32 and 170 days post-diagnosis. HIV-1 infections were dated by using sequence-based methods and a viral load regression method. Bayesian coalescent and viral load regression estimated that infections occurred a median of 6 days prior to diagnosis (IQR: 9-3 and 11-4 days prior, respectively). Poisson-Fitter, which analyzes the distribution of hamming distances among sequences, estimated a median of 7 days prior to diagnosis (IQR: 15-4 days) based on sequences sampled 4 days post-diagnosis, but it did not yield plausible results using sequences sampled at 32 days. Fourteen participants reported a high-risk exposure event at a median of 8 days prior to diagnosis (IQR: 12 to 6 days prior). These different methods concurred that HIV-1 infection occurred about a week before detectable viremia, corresponding to 20 days (IQR: 34-15 days) before peak viral load. Together, our methods comparison helps define a framework for future dating studies in early HIV-1 infection.
Project description:Severe dengue virus (DENV)-associated diseases can occur in patients who have preexisting DENV antibodies (Abs) through antibody-dependent enhancement (ADE) of infection. It is well established that during ADE, DENV-antibody immune complexes (ICs) infect Fcγ receptor-bearing cells and increase the systemic viral burden that can be measured in the blood. For protection against infection with DENV serotypes 1 to 4, strongly neutralizing Abs must be elicited to overcome the effect of ADE. Clinical observations in infants who have maternal DENV Abs or recent phase II/III clinical trials with a leading tetravalent dengue vaccine suggested a lack of correlation between Ab neutralization and in vivo disease prevention. In addressing this gap in knowledge, we found that inoculation of ICs formed with serotype cross-reactive Abs that are more than 98% neutralized in vitro promotes high mortality in AG129 mice even though peak viremia was lower than that in direct virus infection. This suggests that the serum viremia level is not always correlated with disease severity. We further demonstrated that infection with the ICs resulted in increased vascular permeability, specifically in the small intestine, accompanied with increased tissue viral load and cytokine production, which can be suppressed by anti-tumor necrosis factor alpha (anti-TNF-α) Abs. Flow cytometric analysis identified increased infection in CD11b(int) CD11c(int/hi) CD103(-) antigen-presenting cells by IC inoculation, suggesting that these infected cells may be responsible for the increase in TNF-α production and vascular permeability in the small intestine that lead to mortality in mice. Our findings may have important implications for the development of dengue therapeutics.We examined the relationship between the neutralizing level of Abs at the time of infection and subsequent disease progression in a mouse model in order to understand why patients who are shown to have a neutralizing quantity of Abs still allow sufficient DENV replication to induce severe dengue manifestations, which sometimes do not correlate with viremia level. Strikingly, we found that high mortality was induced in AG129 mice by the increase in TNF-α-induced vascular permeability accompanied by an increased viral load, specifically in the small intestine, even when the initial infection level is suppressed to less than 5% and the peak viremia level is not enhanced. This suggests that ADE overcomes the protective efficacy of Abs in a tissue-dependent manner that leads to severe small intestinal pathology. Our findings may serve to address the pathogenic role of Abs on severe dengue disease and also help to develop safe Ab-based therapeutic strategies.
Project description:Viral load (VL) rebound timing and set point were analyzed in 235 participants undergoing analytic treatment interruption (ATI) in 6 AIDS Clinical Trials Group studies. There was no significant association between rebound timing and ATI VL set point for those who rebounded ?12 weeks. VL set points were lower in participants with rebound >12 weeks (P < 0.001) and participants treated during early infection (P < 0.001). Pre-antiretroviral therapy VL correlated with set point, though 68% of participants had a set point lower than pre-antiretroviral therapy VL. These results illustrate complex relationships between post-ATI virologic outcomes and the potential presence of biological factors mediating rebound timing and set point.
Project description:HIV-specific antibodies (Abs) can reduce viral burden by blocking new rounds of infection or by destroying infected cells via activation of effector cells through Fc–FcR interaction. This latter process, referred to as antibody-dependent cellular cytotoxicity (ADCC), has been associated with viral control and improved clinical outcome following both HIV and SIV infections. Here we describe an HIV viral-like particle (VLP)-based sorting strategy that led to identification of HIV-specificmemory B cells encoding Abs that mediate ADCC froma subtype A-infected Kenyan woman at 914 days post-infection. Using this strategy, 12 HIV-envelope-specific monoclonal antibodies (mAbs) were isolated and three mediated potent ADCC activitywhen compared to well-characterized ADCC mAbs. The ADCC-mediating Abs also mediated antibody-dependent cell-mediated virus inhibition (ADCVI), which provides a net measure of Fc receptor-triggered effects against replicating virus. Two of the three ADCC-mediating Abs targeted a CD4-induced (CD4i) epitope also bound by the mAb C11; the third antibody targeted the N-terminus of V3. Both CD4i Abs identified here demonstrated strong cross-clade breadth with activity against 10 of 11 envelopes tested, including those from clades A, B, C, A/D and C/D, whereas the V3-specific antibody showed more limited breadth. Variants of these CD4i, C11-like mAbs engineered to interrupt binding to Fc?Rs inhibited a measurable percentage of the donor's ADCC activity starting as early as 189 days post-infection. C11-like antibodies also accounted for between 18–78% of ADCC activity in 9 chronically infected individuals from the same cohort study. Further, the two CD4i Abs originated from unique B cells, suggesting that antibodies targeting this epitope can be commonly produced. Taken together, these data provide strong evidence that CD4i, C11-like antibodies develop within the first 6 months of infection and they can arise fromunique B-cell lineages in the same individual. Further, thesemAbsmediate potent plasma IgG-specificADCC breadth and potency and contribute to ADCC activity in other HIV-infected individuals.
Project description:Antibodies (Abs) produced during HIV-1 infection rarely neutralize a broad range of viral isolates; only eight broadly-neutralizing (bNt) monoclonal (M)Abs have been isolated. Yet, to be effective, an HIV-1 vaccine may have to elicit the essential features of these MAbs. The V genes of all of these bNt MAbs are highly somatically mutated, and the V(H) genes of five of them encode a long (? 20 aa) third complementarity-determining region (CDR-H3). This led us to question whether long CDR-H3s and high levels of somatic mutation (SM) are a preferred feature of anti-HIV bNt MAbs, or if other adaptive immune responses elicit them in general.We assembled a V(H)-gene sequence database from over 700 human MAbs of known antigen specificity isolated from chronic (viral) infections (ChI), acute (bacterial and viral) infections (AcI), and systemic autoimmune diseases (SAD), and compared their CDR-H3 length, number of SMs and germline V(H)-gene usage. We found that anti-HIV Abs, regardless of their neutralization breadth, tended to have long CDR-H3s and high numbers of SMs. However, these features were also common among Abs associated with other chronic viral infections. In contrast, Abs from acute viral infections (but not bacterial infections) tended to have relatively short CDR-H3s and a low number of SMs, whereas SAD Abs were generally intermediate in CDR-H3 length and number of SMs. Analysis of V(H) gene usage showed that ChI Abs also tended to favor distal germline V(H)-genes (particularly V(H)1-69), especially in Abs bearing long CDR-H3s.The striking difference between the Abs produced during chronic vs. acute viral infection suggests that Abs bearing long CDR-H3s, high levels of SM and V(H)1-69 gene usage may be preferentially selected during persistent infection.
Project description:BACKGROUND:Severe acute respiratory syndrome (SARS) is caused by infection with SARS-associated coronavirus (CoV). Amino acid residues 450-650 of the spike (S) glycoprotein of SARS-CoV (S450-650) contains dominant epitopes for anti-viral antibodies (Abs) in patient sera. OBJECTIVES:To develop and evaluate an ELISA system for detection of anti-S Abs in patient sera. STUDY DESIGN:Express recombinant S450-650 in E. Coli and evaluate the sensitivity and specificity of an ELISA system based on the S450-650 polypeptide. RESULTS:The S450-650-based ELISA detected IgG Abs in 41 out of 51 serum samples from 22 hospitalized patients with probable SARS, a result closely correlated with that obtained with a virus-based ELISA (r = 0.75, k = 0.8). Differential anti-S IgG responses were observed amongst SARS patients. Some of them produced anti-S Abs early during their infection, while others failed to make IgG Abs against the S450-650 polypeptide. None of the serum samples from 100 healthy blood donors was positive in the S450-650-based assay. CONCLUSION:The S450-650-based ELISA can detect anti-S IgG Abs with high sensitivity and specificity.