Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell

Igor Sazonov, Dmitry Grebennikov, Andreas Meyerhans and Gennady Bocharov
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Igor Sazonov: College of Engineering, Swansea University, Bay Campus, Fabian Way SA1 8EN, UK
Dmitry Grebennikov: Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia
Andreas Meyerhans: ICREA, Pg. Lluis Companys 23, 08010 Barcelona, Spain
Gennady Bocharov: Marchuk Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), 119333 Moscow, Russia

Mathematics, 2021, vol. 9, issue 17, 1-19

Abstract: Replication of Human Immunodeficiency Virus type 1 (HIV) in infected CD4 + T cells represents a key driver of HIV infection. The HIV life cycle is characterised by the heterogeneity of infected cells with respect to multiplicity of infection and the variability in viral progeny. This heterogeneity can result from the phenotypic diversity of infected cells as well as from random effects and fluctuations in the kinetics of biochemical reactions underlying the virus replication cycle. To quantify the contribution of stochastic effects to the variability of HIV life cycle kinetics, we propose a high-resolution mathematical model formulated as a Markov chain jump process. The model is applied to generate the statistical characteristics of the (i) cell infection multiplicity, (ii) cooperative nature of viral replication, and (iii) variability in virus secretion by phenotypically identical cells. We show that the infection with a fixed number of viruses per CD4 + T cell leads to some heterogeneity of infected cells with respect to the number of integrated proviral genomes. The bottleneck factors in the virus production are identified, including the Gag-Pol proteins. Sensitivity analysis enables ranking of the model parameters with respect to the strength of their impact on the size of viral progeny. The first three globally influential parameters are the transport of genomic mRNA to membrane, the tolerance of transcription activation to Tat-mediated regulation, and the degradation of free and mature virions. These can be considered as potential therapeutical targets.

Keywords: HIV life cycle; mathematical model; stochastic processes; Markov chain; heterogeneity; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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