CD8 lymphocyte depletion enhances the latency reversal activity of the SMAC mimetic AZD5582 in ART-suppressed SIV-infected rhesus macaques.

Inducing latency reversal to reveal infected cells to the host immune system represents a potential strategy to cure HIV infection. In separate studies, we have previously shown that CD8+ T cells may contribute to the maintenance of viral latency and identified a novel SMAC mimetic/IAP inhibitor (AZD5582) capable of reversing HIV/SIV latency in vivo by activating the non-canonical (nc) NF-κB pathway. Here, we use AZD5582 in combination with antibody-mediated depletion of CD8α+ cells to further evaluate the role of CD8+ T cells in viral latency maintenance. Six rhesus macaques (RM) were infected with SIVmac239 and treated with ART starting at week 8 post-infection. After 84-85 weeks of ART, all animals received a single dose of the anti-CD8α depleting antibody (Ab), MT807R1 (50mg/kg, s.c.), followed by 5 weekly doses of AZD5582 (0.1 mg/kg, i.v.). Following CD8α depletion + AZD5582 combined treatment, 100% of RMs experienced on-ART viremia above 60 copies per ml of plasma. In comparator groups of ART-suppressed SIV-infected RMs treated with AZD5582 only or CD8α depletion only, on-ART viremia was experienced by 56% and 57% of the animals respectively. Furthermore, the frequency of increased viremic episodes during the treatment period was greater in the CD8α depletion + AZD5582 group as compared to other groups. Mathematical modeling of virus reactivation suggested that, in addition to viral dynamics during acute infection, CD8α depletion influenced the response to AZD5582. This work suggests that the latency reversal induced by activation of the ncNF-κB signaling pathway with AZD5582 can be enhanced by CD8α+ cell depletion.

Quantification of Ebola virus replication kinetics in vitro.

Mathematical modelling has successfully been used to provide quantitative descriptions of many viral infections, but for the Ebola virus, which requires biosafety level 4 facilities for experimentation, modelling can play a crucial role. Ebola virus modelling efforts have primarily focused on in vivo virus kinetics, e.g., in animal models, to aid the development of antivirals and vaccines. But, thus far, these studies have not yielded a detailed specification of the infection cycle, which could provide a foundational description of the virus kinetics and thus a deeper understanding of their clinical manifestation. Here, we obtain a diverse experimental data set of the Ebola virus infection in vitro, and then make use of Bayesian inference methods to fully identify parameters in a mathematical model of the infection. Our results provide insights into the distribution of time an infected cell spends in the eclipse phase (the period between infection and the start of virus production), as well as the rate at which infectious virions lose infectivity. We suggest how these results can be used in future models to describe co-infection with defective interfering particles, which are an emerging alternative therapeutic.

Fc-mediated effector function contributes to the in vivo antiviral effect of an HIV neutralizing antibody.

Treatment of HIV infection with either antiretroviral (ARV) therapy or neutralizing monoclonal antibodies (NAbs) leads to a reduction in HIV plasma virus. Both ARVs and NAbs prevent new rounds of viral infection, but NAbs may have the additional capacity to accelerate the loss of virus-infected cells through Fc gamma receptor (FcγR)-mediated effector functions, which should affect the kinetics of plasma-virus decline. Here, we formally test the role of effector function in vivo by comparing the rate and timing of plasma-virus clearance in response to a single-dose treatment with either unmodified NAb or those with either reduced or augmented Fc function. When infused into viremic simian HIV (SHIV)-infected rhesus macaques, there was a 21% difference in slope of plasma-virus decline between NAb and NAb with reduced Fc function. NAb engineered to increase FcγRIII binding and improve antibody-dependent cellular cytotoxicity (ADCC) in vitro resulted in arming of effector cells in vivo, yet led to viral-decay kinetics similar to NAbs with reduced Fc function. These studies show that the predominant mechanism of antiviral activity of HIV NAbs is through inhibition of viral entry, but that Fc function can contribute to the overall antiviral activity, making them distinct from standard ARVs.

Quantifying the contribution of Fc-mediated effector functions to the antiviral activity of anti-HIV-1 IgG1 antibodies in vivo.

In combating viral infections, the Fab portion of an antibody could mediate virus neutralization, whereas Fc engagement of Fc-γ receptors (FcγRs) could mediate an array of effector functions. Evidence abounds that effector functions are important in controlling infections by influenza, Ebola, or HIV-1 in animal models. However, the relative contribution of virus neutralization versus effector functions to the overall antiviral activity of an antibody remains unknown. To address this fundamental question in immunology, we utilized our knowledge of HIV-1 dynamics to compare the kinetics of the viral load decline (ΔVL) in infected animals given a wild-type (WT) anti-HIV-1 immunoglobulin G1 (IgG1) versus those given a Fc-Null variant of the same antibody. In three independent experiments in HIV-1-infected humanized mice and one pivotal experiment in simian-human immunodeficiency virus (SHIV)-infected rhesus macaques, an earlier and sharper decline in viral load was consistently detected for the WT antibody. Quantifications of the observed differences indicate that Fc-mediated effector functions accounted for 25-45% of the total antiviral activity in these separate experiments. In this study, Fc-mediated effector functions have been quantified in vivo relative to the contribution of virus neutralization mediated by the Fab.

Within-host mathematical models of hepatitis B virus infection: Past, present, and future.

Mathematical modeling has been instrumental in enhancing our understanding of the viral dynamics of hepatitis B virus (HBV) infection. We give a primer on HBV infection in humans and a brief overview of the development of within-host mathematical models of HBV infection. In the last decade, models have advanced from considering chronic HBV infections under therapy to the pathogenesis of infection. We also summarize estimates of key viral dynamic parameters that have varied greatly among studies, and show that they impact model predictions. Future directions for mathematical modeling of HBV infection are proposed to better understand emerging therapies, the HBV life cycle, predicting cure, and the mechanisms involved in the immune response to HBV infection.

Exploring virus release as a bottleneck for the spread of influenza A virus infection in vitro and the implications for antiviral therapy with neuraminidase inhibitors.

Mathematical models (MMs) have been used to study the kinetics of influenza A virus infections under antiviral therapy, and to characterize the efficacy of antivirals such as neuraminidase inhibitors (NAIs). NAIs prevent viral neuraminidase from cleaving sialic acid receptors that bind virus progeny to the surface of infected cells, thereby inhibiting their release, suppressing infection spread. When used to study treatment with NAIs, MMs represent viral release implicitly as part of viral replication. Consequently, NAIs in such MMs do not act specifically and exclusively on virus release. We compared a MM with an explicit representation of viral release (i.e., distinct from virus production) to a simple MM without explicit release, and investigated whether parameter estimation and the estimation of NAI efficacy were affected by the use of a simple MM. Since the release rate of influenza A virus is not well-known, a broad range of release rates were considered. If the virus release rate is greater than ∼0.1 h-1, the simple MM provides accurate estimates of infection parameters, but underestimates NAI efficacy, which could lead to underdosing and the emergence of NAI resistance. In contrast, when release is slower than ∼0.1 h-1, the simple MM accurately estimates NAI efficacy, but it can significantly overestimate the infectious lifespan (i.e., the time a cell remains infectious and producing free virus), and it will significantly underestimate the total virus yield and thus the likelihood of resistance emergence. We discuss the properties of, and a possible lower bound for, the influenza A virus release rate.

(In)validating experimentally derived knowledge about influenza A defective interfering particles.

A defective interfering particle (DIP) in the context of influenza A virus is a virion with a significantly shortened RNA segment substituting one of eight full-length parent RNA segments, such that it is preferentially amplified. Hence, a cell co-infected with DIPs will produce mainly DIPs, suppressing infectious virus yields and affecting infection kinetics. Unfortunately, the quantification of DIPs contained in a sample is difficult because they are indistinguishable from standard virus (STV). Using a mathematical model, we investigated the standard experimental method for counting DIPs based on the reduction in STV yield (Bellett & Cooper, 1959, Journal of General Microbiology 21, 498-509 (doi:10.1099/00221287-21-3-498)). We found the method is valid for counting DIPs provided that: (i) an STV-infected cell's co-infection window is approximately half its eclipse phase (it blocks infection by other virions before it begins producing progeny virions), (ii) a cell co-infected by STV and DIP produces less than 1 STV per 1000 DIPs and (iii) a high MOI of STV stock (more than 4 PFU per cell) is added to perform the assay. Prior work makes no mention of these criteria such that the method has been applied incorrectly in several publications discussed herein. We determined influenza A virus meets these criteria, making the method suitable for counting influenza A DIPs.

Assessing the in vitro fitness of an oseltamivir-resistant seasonal A/H1N1 influenza strain using a mathematical model.

In 2007, the A/Brisbane/59/2007 (H1N1) seasonal influenza virus strain acquired the oseltamivir-resistance mutation H275Y in its neuraminidase (NA) gene. Although previous studies had demonstrated that this mutation impaired the replication capacity of the influenza virus in vitro and in vivo, the A/Brisbane/59/2007 H275Y oseltamivir-resistant mutant completely out-competed the wild-type (WT) strain and was, in the 2008-2009 influenza season, the primary A/H1N1 circulating strain. Using a combination of plaque and viral yield assays, and a simple mathematical model, approximate values were extracted for two basic viral kinetics parameters of the in vitro infection. In the ST6GalI-MDCK cell line, the latent infection period (i.e., the time for a newly infected cell to start releasing virions) was found to be 1-3 h for the WT strain and more than 7 h for the H275Y mutant. The infecting time (i.e., the time for a single infectious cell to cause the infection of another one) was between 30 and 80 min for the WT, and less than 5 min for the H275Y mutant. Single-cycle viral yield experiments have provided qualitative confirmation of these findings. These results, though preliminary, suggest that the increased fitness success of the A/Brisbane/59/2007 H275Y mutant may be due to increased infectivity compensating for an impaired or delayed viral release, and are consistent with recent evidence for the mechanistic origins of fitness reduction and recovery in NA expression. The method applied here can reconcile seemingly contradictory results from the plaque and yield assays as two complementary views of replication kinetics, with both required to fully capture a strain's fitness.

Design considerations in building in silico equivalents of common experimental influenza virus assays.

Experimentation in vitro is a vital part of the process by which the clinical and epidemiological characteristics of a particular influenza virus strain are determined. We detail the considerations which must be made in designing appropriate theoretical/mathematical models of these experiments and show how modeling can increase the information output of such experiments. Starting from a traditional system of ordinary differential equations, common to infectious disease modeling, we broaden the approach by using an agent-based model, applicable to more general experimental geometries and assumptions about the biological properties of viruses, cell and their interaction. Within this framework, we explore the limits of the assumptions made by more traditional models and the conditions under which these assumptions begin to break down, requiring the use of more sophisticated models. We apply the agent-based model to experimental plaque growth of two influenza strains, one resistant to the antiviral oseltamivir, and extract the values of key infection parameters specific to each strain.