In order to inform the rational design of HIV-1 preventive and cure interventions it is critical to understand the events occurring during acute HIV-1 infection (AHI). Using viral deep sequencing on six participants from the early capture acute infection RV217 cohort, we have studied HIV-1 evolution in plasma collected twice weekly during the first weeks following the advent of viremia. The analysis of infections established by multiple transmitted/founder (T/F) viruses revealed novel viral profiles that included: a) the low-level persistence of minor T/F variants, b) the rapid replacement of the major T/F by a minor T/F, and c) an initial expansion of the minor T/F followed by a quick collapse of the same minor T/F to low frequency. In most participants, cytotoxic T-lymphocyte (CTL) escape was first detected at the end of peak viremia downslope, proceeded at higher rates than previously measured in HIV-1 infection, and usually occurred through the exploration of multiple mutational pathways within an epitope. The rapid emergence of CTL escape variants suggests a strong and early CTL response. Minor T/F viral strains can contribute to rapid and varied profiles of HIV-1 quasispecies evolution during AHI. Overall, our results demonstrate that early, deep, and frequent sampling is needed to investigate viral/host interaction during AHI, which could help identify prerequisites for prevention and cure of HIV-1 infection.

Recent studies have highlighted the ability of HIV to escape from cytotoxic T lymphocyte (CTL) responses that concurrently target multiple viral epitopes. Yet, the viral dynamics involved in such escape are incompletely understood. Previous analyses have made several strong assumptions regarding HIV escape from CTL responses such as independent or non-concurrent escape from individual CTL responses. Using experimental data from evolution of HIV half genomes in four patients we observe concurrent viral escape from multiple CTL responses during early infection (first 100 days of infection), providing confirmation of a recent result found in a study of one HIV-infected patient. We show that current methods of estimating CTL escape rates, based on the assumption of independent escapes, are biased and perform poorly when CTL escape proceeds concurrently at multiple epitopes. We propose a new method for analyzing longitudinal sequence data to estimate the rate of CTL escape across multiple epitopes; this method involves few parameters and performs well in simulation studies. By applying our novel method to experimental data, we find that concurrent multiple escapes occur at rates between 0.03 and 0.4 day−1, a relatively broad range that reflects uncertainty due to sparse sampling and wide ranges of parameter values. However, we show that concurrent escape at rates 0.1–0.2 day−1 across multiple epitopes is consistent with our patient datasets.

During the first weeks of human immunodeficiency virus-1 (HIV-1) infection, cytotoxic T-lymphocytes (CTLs) select for multiple escape mutations in the infecting HIV population. In recent years, methods that use escape mutation data to estimate rates of HIV escape have been developed, thereby providing a quantitative framework for exploring HIV escape from CTL response. Current methods for escape-rate inference focus on a specific HIV mutant selected by a single CTL response. However, recent studies have shown that during the first weeks of infection, CTL responses occur at one to three epitopes and HIV escape occurs through complex mutation pathways. Consequently, HIV escape from CTL response forms a complex, selective sweep that is difficult to analyze. In this work, we develop a model of initial infection, based on the well-known standard model, that allows for a description of multi-epitope response and the complex mutation pathways of HIV escape. Under this model, we develop Bayesian and hypothesis-test inference methods that allow us to analyze and estimate HIV escape rates. The methods are applied to two HIV patient data sets, concretely demonstrating the utility of our approach.A CUTE HIV-1 infection is marked by an initial period of 2-4 weeks in which the viral population expands from one to five infected cells to 10 9 infected cells. Following this expansion period, in the subsequent 1-2 months, the viral load drops and reaches a setpoint (Fiebig et al. 2003;Mehandru et al. 2004Mehandru et al. , 2007Keele et al. 2008). Cytotoxic T lymphocytes (CTLs) are thought to play an important role in shaping acute infection (Goulder and Watkins 2004;Cohen et al. 2011). The onset of CTL response is temporally correlated with the end of the expansion period, suggesting a role for CTLs in controlling viral load. Numerous studies have shown that during acute infection, specific HIV mutations on CTL targeted epitopes sweep to fixation, providing more direct evidence that CTL response shapes the infecting HIV population; see Goulder and Watkins (2004) for a review.In recent years, full-genome sequencing studies have provided an increasingly detailed description of CTL response during acute infection, e.g., Fernandez et al. Recent deep-sequencing data sets have provided a picture of HIV escape at the CTL targeted epitopes, e.g., Fisher et al. (2010), Henn et al. (2012), Bimber et al. (2009). HIV escape mutations at the first CTL targeted epitope rise to significant proportions 1-3 weeks after peak viral load. Escape mutations at the next series of epitopes targeted rise to significant proportion within roughly 4-6 weeks of peak viral load. Importantly, deep-sequencing studies have shown that HIV escape at a targeted epitope often occurs along multiple mutation pathways. The different mutation pathways are simply different nucleotide substitutions in the targeted epitope. During an HIV escape, these different mutations sweep to significant frequencies simultaneously, thereby replacing an HIV population typically ...

https://github.com/SLeviyang/RegressHaplo.

Secretion of type I interferons (IFN) by infected cells mediates protection against many viruses, but prolonged or excessive type I IFN secretion can lead to immune pathology. A proper type I IFN response must therefore maintain a balance between protection and excessive IFN secretion. It has been widely noted that the type I IFN response is driven by positive feedback and is heterogeneous, with only a fraction of infected cells upregulating IFN expression even in clonal cell lines, but the functional roles of feedback and heterogeneity in balancing protection and excessive IFN secretion are not clear. To investigate the functional roles for feedback and heterogeneity, we constructed a mathematical model coupling IFN and viral dynamics that extends existing mathematical models by accounting for feedback and heterogeneity. We fit our model to five existing datasets, reflecting different experimental systems. Fitting across datasets allowed us to compare the IFN response across the systems and suggested different signatures of feedback and heterogeneity in the different systems. Further, through numerical experiments, we generated hypotheses of functional roles for IFN feedback and heterogeneity consistent with our mathematical model. We hypothesize an inherent tradeoff in the IFN response: a positive feedback loop prevents excessive IFN secretion, but also makes the IFN response vulnerable to viral antagonism. We hypothesize that cellular heterogeneity of the IFN response functions to protect the feedback loop from viral antagonism. Verification of our hypotheses will require further experimental studies. Our work provides a basis for analyzing the type I IFN response across systems.