Markov chain-based stochastic modelling of HIV-1 life cycle in a CD4 T cell

Mostra el registre complet Registre parcial de l'ítem

• dc.contributor.author Sazonov, Igor
• dc.contributor.author Grebennikov, Dmitry
• dc.contributor.author Meyerhans, Andreas
• dc.contributor.author Bocharov, Gennady A.
• dc.date.accessioned 2021-10-20T06:29:17Z
• dc.date.available 2021-10-20T06:29:17Z
• dc.date.issued 2021
• dc.description.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.
• dc.format.mimetype application/pdf
• dc.identifier.citation Sazonov I, Grebennikov D, Meyerhans A, Bocharov G. Markov chain-based stochastic modelling of HIV-1 life cycle in a CD4 T cell. Mathematics. 2021;9(17):2025. DOI: 10.3390/math9172025
• dc.identifier.doi http://dx.doi.org/10.3390/math9172025
• dc.identifier.issn 2227-7390
• dc.identifier.uri http://hdl.handle.net/10230/48711
• dc.language.iso eng
• dc.publisher MDPI
• dc.relation.ispartof Mathematics. 2021;9(17):2025
• dc.rights © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by/4.0/
• dc.subject.keyword HIV life cycle
• dc.subject.keyword Mathematical model
• dc.subject.keyword Stochastic processes
• dc.subject.keyword Markov chain
• dc.subject.keyword Heterogeneity
• dc.subject.keyword Sensitivity analysis
• dc.title Markov chain-based stochastic modelling of HIV-1 life cycle in a CD4 T cell
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion