(636c) Multiscale Model of HIV Infection at Intra and Extracellular Levels with Detailed Simulation of Reverse Transcription as the Critical Part of the Infection Cycle

Khalili, S. - Presenter, The Pennsylvania State University
Armaou, A. - Presenter, Pennsylvania State University

The focus of this work is developing a multiscale of HIV infection dynamics at both intracellular and extracellular level. This model is helpful in predicting the dynamics of infection progress at different stages of infection as well as investigating the effects of treatment on viral clearance and repair of the immune system in order to optimize the outcome of treatment for patients.

At the extracellular level, we are looking at populations of wild type and mutant type virus which interact with T cells and generate actively and latently infected populations [1]. Quantification of these populations is necessary to determine infection progression at the animal level and to enumerate parameters such as virus count per milliliter of blood which is used in medical contexts. However, the successful attachment of virus to a T cell is the first step of series of complex events at the intracellular level necessary to successful production of new virus particles. Consequently, modeling intracellular events (attachment of virus to the host T cell, reverse transcription, DNA integration, RNA transcription and translation, modification and budding) is necessary to achieve an accurate prediction of the overall disease dynamics.

The interaction dynamics of intracellular components are extremely complicated. Furthermore, quantitative information from experimental studies does not include all parts of the cycle. We have used available empirical data to develop a stochastic description model of the intracellular events. Among these intracellular events, the reverse transcription of the viral RNA to a double strand DNA is the most important part of the cycle since the generated DNA can be integrated into the host DNA which results in transfer of viral genetic information to the next generation. This critical step is the target by one of the most commonly used HIV drugs called nucleoside reverse transcription inhibitors, NRTIs. NRTIs are congeners of natural nucleotides and function by competing with natural nucleotides for incorporation into the HIV genome during its reverse transcription. The probability of an NRTI inclusion instead of its natural nucleotide can be expressed in terms of intracellular drug concentrations, natural nucleotide concentrations, and relevant rate constants derived from reverse transcriptase's mechanism of nucleotide addition. With each NRTI incorporation, some probability of permanently terminating the developing HIV genome can be assumed. Consequently, two major factors contribute to time delay or termination of the reverse transcription process: the ability of the NRTI to be incorporated into the growing HIV genome and the stability of the terminated complex. Based on the available data [2,3,4], the time delay and the overall probability of developing terminated HIV genome was calculated for four different kinds of NRTIs (AZT, d4T, ddC, and 3TC) and sensitivity analysis was performed regarding drug concentration and administration time.

Following the development of the stochastic extracellular and intracellular models, a multiscale model of HIV infection to incorporate both extra and intracellular dynamics is developed. The developed model enhances the understanding of infection cycle and is useful in predicting the overall infection dynamics. The time scale of intracellular events inside the infected host is a few orders of magnitude smaller than the time scale of cell population interactions at the extracellular level. The basic intracellular/extracellular (multiscale) model is developed in a sequential manner. First the extracellular, atomistic component is derived and subsequently a stochastic, also atomistic, intracellular component is developed. In the extracellular model an ?atom? denotes either a virus particle or a T-cell, while in the intracellular model, an ?atom? denotes a protein, an RNA or a DNA. Due exactly to the atomistic nature of both models the development of the multiscale model is conceptually possible. The multiscale model simulation is initiated at the extracellular level. During the simulation, an extracellular event (e.g., binding of a virus particle to a T-cell) initiates the intracellular model. The intracellular model is then simulated for a period of time and all the intracellular events that took place within this time horizon are represented as one ?coarse? event at the extracellular level. The flow of information between the two different description levels is critical to the accuracy and stability of the multiscale model.