Search

Studying the early events that occur after viral infection in humans is difficult unless one intentionally infects volunteers in a human challenge study. Here, we use data about severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in such a study in combination with mathematical modeling to gain insights into the relationship between the amount of virus in the upper respiratory tract and the immune response it generates. We propose a set of dynamic models of increasing complexity to dissect the roles of target cell limitation, innate immunity, and adaptive immunity in determining the observed viral kinetics. We introduce an approach for modeling the effect of humoral immunity that describes a decline in infectious virus after immune activation. We fit our models to viral load and infectious titer data from all the untreated infected participants in the study simultaneously. We found that a power-law with a power h < 1 describes the relationship between infectious virus and viral load. Viral replication at the early stage of infection is rapid, with a doubling time of ~2 h for viral RNA and ~3 h for infectious virus. We estimate that adaptive immunity is initiated ~7 to 10 d postinfection and appears to contribute to a multiphasic viral decline experienced by some participants; the viral rebound experienced by other participants is consistent with a decline in the interferon response. Altogether, we quantified the kinetics of SARS-CoV-2 infection, shedding light on the early dynamics of the virus and the potential role of innate and adaptive immunity in promoting viral decline during infection., Competing Interests: Competing interests statement:The authors declare no competing interest.

The latent reservoir for HIV-1 in resting CD4 + T cells persists despite antiretroviral therapy (ART) and precludes cure. Reservoir-targeting interventions are evaluated in ART-treated macaques infected with simian immunodeficiency virus (SIV) or simian-human immunodeficiency virus (SHIV). Efficacy is determined by reservoir measurements before and after the intervention. However, most proviruses persisting in the setting of ART are defective. In addition, intact HIV-1 and SIV genomes undergo complex, multiphasic decay observable when new infection events are blocked by ART. Intervention-induced elimination of latently infected cells must be distinguished from natural decay. Here, we address these issues for SHIV. We describe an intact proviral DNA assay that allows digital counting of SHIV genomes lacking common fatal defects. We show that intact SHIV genomes in circulating CD4 + T cells undergo biphasic decay during the first year of ART, with a rapid first phase (t 1/2 = 30.1 d) and a slower second phase (t 1/2 = 8.1 mo) that is still more rapid that the slow decay observed in people with HIV-1 on long-term ART (t 1/2 = 3.7 y). In SHIV models, most interventions are tested during 2nd phase decay. Natural 2nd phase decay must be considered in evaluating interventions as most infected cells present at this time do not become part of the stable reservoir. In addition, for interventions tested during 2nd phase decay, a caveat is that the intervention may not be equally effective in people with HIV on long-term ART whose reservoirs are dominated by latently infected cells with a slower decay rate.

In persons living with HIV-1 (PLWH) who start antiretroviral therapy (ART), plasma virus decays in a biphasic fashion to below the detection limit. The first phase reflects the short half-life (<1 d) of cells that produce most of the plasma virus. The second phase represents the slower turnover ( t 1/2 = 14 d) of another infected cell population, whose identity is unclear. Using the intact proviral DNA assay (IPDA) to distinguish intact and defective proviruses, we analyzed viral decay in 17 PLWH initiating ART. Circulating CD4 + T cells with intact proviruses include few of the rapidly decaying first-phase cells. Instead, this population initially decays more slowly ( t 1/2 = 12.9 d) in a process that largely represents death or exit from the circulation rather than transition to latency. This more protracted decay potentially allows for immune selection. After ∼3 mo, the decay slope changes, and CD4 + T cells with intact proviruses decay with a half-life of 19 mo, which is still shorter than that of the latently infected cells that persist on long-term ART. Two-long-terminal repeat (2LTR) circles decay with fast and slow phases paralleling intact proviruses, a finding that precludes their use as a simple marker of ongoing viral replication. Proviruses with defects at the 5' or 3' end of the genome show equivalent monophasic decay at rates that vary among individuals. Understanding these complex early decay processes is important for correct use of reservoir assays and may provide insights into properties of surviving cells that can constitute the stable latent reservoir., Competing Interests: Competing interest statement: Aspects of the IPDA are the subject of patent application PCT/US16/28822 filed by Johns Hopkins University with R.F.S. as an inventor and licensed to AccelevirDx. R.F.S. holds no equity interest in AccelevirDx., (Copyright © 2022 the Author(s). Published by PNAS.)

The within-host viral kinetics of SARS-CoV-2 infection and how they relate to a person's infectiousness are not well understood. This limits our ability to quantify the impact of interventions on viral transmission. Here, we develop viral dynamic models of SARS-CoV-2 infection and fit them to data to estimate key within-host parameters such as the infected cell half-life and the within-host reproductive number. We then develop a model linking viral load (VL) to infectiousness and show a person's infectiousness increases sublinearly with VL and that the logarithm of the VL in the upper respiratory tract is a better surrogate of infectiousness than the VL itself. Using data on VL and the predicted infectiousness, we further incorporated data on antigen and RT-PCR tests and compared their usefulness in detecting infection and preventing transmission. We found that RT-PCR tests perform better than antigen tests assuming equal testing frequency; however, more frequent antigen testing may perform equally well with RT-PCR tests at a lower cost but with many more false-negative tests. Overall, our models provide a quantitative framework for inferring the impact of therapeutics and vaccines that lower VL on the infectiousness of individuals and for evaluating rapid testing strategies., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

The reservoir of HIV latently infected cells is the major obstacle for eradication of HIV infection. The "shock-and-kill" strategy proposed earlier aims to reduce the reservoir by activating cells out of latency. While the intracellular HIV Tat gene circuit is known to play important roles in controlling latency and its transactivation in HIV-infected cells, the detailed control mechanisms are not well understood. Here we study the mechanism of probabilistic control of the latent and the transactivated cell phenotypes of HIV-infected cells. We reconstructed the probability landscape, which is the probability distribution of the Tat gene circuit states, by directly computing the exact solution of the underlying chemical master equation. Results show that the Tat circuit exhibits a clear bimodal probability landscape (i.e., there are two distinct probability peaks, one associated with the latent cell phenotype and the other with the transactivated cell phenotype). We explore potential modifications to reactions in the Tat gene circuit for more effective transactivation of latent cells (i.e., the shock-and-kill strategy). Our results suggest that enhancing Tat acetylation can dramatically increase Tat and viral production, while increasing the Tat-transactivation response binding affinity can transactivate latent cells more rapidly than other manipulations. Our results further explored the "block and lock" strategy toward a functional cure for HIV. Overall, our study demonstrates a general approach toward discovery of effective therapeutic strategies and druggable targets by examining control mechanisms of cell phenotype switching via exactly computed probability landscapes of reaction networks., Competing Interests: The authors declare no conflict of interest.

RNA viruses exist as a genetically diverse quasispecies with extraordinary ability to adapt to abrupt changes in the host environment. However, the molecular mechanisms that contribute to their rapid adaptation and persistence in vivo are not well studied. Here, we probe hepatitis C virus (HCV) persistence by analyzing clinical samples taken from subjects who were treated with a second-generation HCV protease inhibitor. Frequent longitudinal viral load determinations and large-scale single-genome sequence analyses revealed rapid antiviral resistance development, and surprisingly, dynamic turnover of dominant drug-resistant mutant populations long after treatment cessation. We fitted mathematical models to both the viral load and the viral sequencing data, and the results provided strong support for the critical roles that superinfection and cure of infected cells play in facilitating the rapid turnover and persistence of viral populations. More broadly, our results highlight the importance of considering viral dynamics and competition at the intracellular level in understanding rapid viral adaptation. Thus, we propose a theoretical framework integrating viral and molecular mechanisms to explain rapid viral evolution, resistance, and persistence despite antiviral treatment and host immune responses., Competing Interests: Conflict of interest statement: R.J.O.B. is an employee and shareholder of Merck & Co., Inc. This work was funded by a grant from Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc. (to G.M.S.). A.S.P. consulted for Merck Sharp & Dohme Corp., a subsidiary of Merck & Co., Inc., (Copyright © 2018 the Author(s). Published by PNAS.)

During acute hepatitis B virus (HBV) infection viral loads reach high levels ( approximately 10(10) HBV DNA per ml), and nearly every hepatocyte becomes infected. Nonetheless, approximately 85-95% of infected adults clear the infection. Although the immune response has been implicated in mediating clearance, the precise mechanisms remain to be elucidated. As infection clears, infected cells are replaced by uninfected ones. During much of this process the virus remains plentiful but nonetheless does not rekindle infection. Here, we analyze data from a set of individuals identified during acute HBV infection and develop mathematical models to test the role of immune responses in various stages of early HBV infection. Fitting the models to data we are able to separate the kinetics of the noncytolytic and the cytolytic immune responses, thus explaining the relative contribution of these two processes. We further show that we need to hypothesize that newly generated uninfected cells are refractory to productive infection. Without this assumption, viral resurgence is observed as uninfected cells are regenerated. Such protection, possibly mediated by cytokines, may also be important in resolving other acute viral infections.

Deuterated glucose labeling was used to measure the in vivo turnover of T lymphocytes. A realistic T cell kinetic model, with populations of resting and activated T cells, was fitted to d-glucose labeling data from healthy and HIV-1-infected individuals before and after antiretroviral treatment. Our analysis highlights why HIV-1 infection, which increases the fraction of both CD4(+) and CD8(+) T lymphocytes that are proliferating (Ki67(+)), leads to CD4 but not CD8 depletion. We find that HIV-1 infection tends to increase the rates of death and proliferation of activated CD4(+) T cells, and to increase the rate at which resting CD4 T cells become activated, but does not increase the fraction of activated CD4(+) T cells, consistent with their preferential loss in HIV-1-infected individuals. In contrast, HIV-1 infection does not lead to an increase in proliferation or death rates of activated CD8(+) T cells, but did increase the fraction of activated CD8(+) T cells, consistent with these cells remaining in an activated state longer and undergoing more rounds of proliferation than CD4(+) T cells. Our results also explain why telomeres shorten in CD8(+) cells, but not in CD4(+) cells of HIV-1-infected patients, compared with age-matched controls.

HIV drug therapy often fails because of the appearance of multidrug-resistant virus. There are two possible scenarios for the outgrowth of multidrug-resistant virus in response to therapy. Resistant virus may preexist at low frequencies in drug-naive patients and is rapidly selected in the presence of drugs. Alternatively, resistant virus is absent at the start of therapy but is generated by residual viral replication during therapy. Currently available experimental methods are generally too insensitive to distinguish between these two scenarios. Here we use deterministic and stochastic models to investigate the origin of multidrug resistance. We quantify the probabilities that resistant mutants preexist, and that resistant mutants are generated during therapy. The models suggest that under a wide range of conditions, treatment failure is most likely caused by the preexistence of resistant mutants.