Multi-Scale Modeling of HIV Infection in vitro and APOBEC3G-Based Anti-Retroviral Therapy

Abstract

The human APOBEC3G is an innate restriction factor that, in the absence of Vif, restricts HIV-1 replication by inducing excessive deamination of cytidine residues in nascent reverse transcripts and inhibiting reverse transcription and integration. To shed light on impact of A3G-Vif interactions on HIV replication, we developed a multi-scale computational system consisting of intracellular (single-cell), cellular and extracellular (multicellular) events by using ordinary differential equations. The single-cell model describes molecular-level events within individual cells (such as production and degradation of host and viral proteins, and assembly and release of new virions), whereas the multicellular model describes the viral dynamics and multiple cycles of infection within a population of cells. We estimated the model parameters either directly from previously published experimental data or by running simulations to find the optimum values. We validated our integrated model by reproducing the results of in vitro T cell culture experiments. Crucially, both downstream effects of A3G (hypermutation and reduction of viral burst size) were necessary to replicate the experimental results in silico. We also used the model to study anti-HIV capability of several possible therapeutic strategies including: an antibody to Vif; upregulation of A3G; and mutated forms of A3G. According to our simulations, A3G with a mutated Vif binding site is predicted to be significantly more effective than other molecules at the same dose. Ultimately, we performed sensitivity analysis to identify important model parameters. The results showed that the timing of particle formation and virus release had the highest impacts on HIV replication. The model also predicted that the degradation of A3G by Vif is not a crucial step in HIV pathogenesis.

A multi-scale mathematical modeling framework to investigate anti-viral therapeutic opportunities in targeting HIV-1 accessory proteins

“…In these equations, time τ represents the time post-HIV-1 entry into an uninfected T cell and τ 1 is the time required for viral protein translation to reach half the maximum value (we use τ 1 = 18 hours). Values for these parameters are taken from the literature [20], and we assume that both HIV-1-Vpu and HIV-1-Vif have similar production and degradation rates.…”

“…The intracellular A3G-Vif kinetics are key to controlling the dynamics of two virus populations: A3G positive (A3G+) and A3G negative (A3G−). To model these intracellular interactions we used an existing model of A3G-Vif kinetics [20] and restructured it to fit our requirements. The modified equations are shown below.…”

“…Values for protein production and degradation parameters were taken from the literature [20], and we assume that both HIV-1-Vpu and HIV-1-Vif have similar production and degradation rates.…”

“…However, these age-structured models do not account for the intracellular processes of accessory protein expression and interaction with host proteins. To incorporate the activity of HIV-1 trans-activator of transcription (Tat), that regulates transcription of HIV-1 in infected cells Althaus and De Boer developed a multi-scale model [2], and another recent study examined intracellular A3G Vif reaction kinetics as HIV-1 infection progresses in cell culture [20]. However, this model is not amenable for describing the dynamics of viral loads or T cell counts in HIV-1-infected individuals.…”

Insights into Proteomic Immune Cell Signaling and Communication via Data-Driven Modeling

“…These theory-driven approaches enable crucial hypothesis-testing of system-level properties and evaluation of parameter values in the broad context of an entire signaling network (Benedict et al 2011), both of which are difficult to obtain with experimental work alone. In the field of immunology, a deep body of the experimental literature and broad range of experimental assays for measuring transcriptional and intracellular protein signaling events have allowed for valuable use of theory-driven approaches, including understanding how various IjB proteins affect NFjB signaling dynamics (Hoffmann et al 2002), evaluating APO-BEC3G-and Vif-based therapeutic strategies for HIV infection (Hosseini and Gabhann 2012), elucidating the role of shared receptor components, ligand competition, and feedback loops in IL-7 signaling (Palmer et al 2008), and understanding how Th and Treg IL-2 feedback loops and signaling dynamics shape different cellular microenvironments (Busse et al 2010). …”