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

Igor Sazonov Orcid Logo, Dmitry Grebennikov, Andreas Meyerhans, Gennady Bocharov

Mathematics, Volume: 9, Issue: 17, Start page: 2025

Swansea University Author: Igor Sazonov Orcid Logo

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DOI (Published version): 10.3390/math9172025

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 ca...

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Published in: Mathematics
ISSN: 2227-7390
Published: MDPI AG 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa58057
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spelling 2021-10-21T16:52:45.2613895 v2 58057 2021-09-23 Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell 05a507952e26462561085fb6f62c8897 0000-0001-6685-2351 Igor Sazonov Igor Sazonov true false 2021-09-23 AERO 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. Journal Article Mathematics 9 17 2025 MDPI AG 2227-7390 HIV life cycle; mathematical model; stochastic processes; Markov chain; heterogeneity; sensitivity analysis 24 8 2021 2021-08-24 10.3390/math9172025 COLLEGE NANME Aerospace Engineering COLLEGE CODE AERO Swansea University The reported study was funded by the Russian Science Foundation (grant number 18-11-00171), the Russian Foundation for Basic Research (grant number 20-01-00352) and the Moscow Center for Fundamental and Applied Mathematics at INM RAS (agreement with the Ministry of Education and Science of the Russian Federation No. 075-15-2019-1624). AM is also supported by the Spanish Ministry of Science and Innovation grant no. PID2019-106323RB-I00(AEI/MINEICO/FEDER, UE), and “Unidad de Excelencia María de Maeztu”, funded by the AEI (CEX2018-000792-M). 2021-10-21T16:52:45.2613895 2021-09-23T16:15:40.6324672 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering Igor Sazonov 0000-0001-6685-2351 1 Dmitry Grebennikov 2 Andreas Meyerhans 3 Gennady Bocharov 4 58057__20986__baf9ceabed4748d0a25ec851b95ccb2c.pdf 58057.pdf 2021-09-23T16:17:04.8804034 Output 4212721 application/pdf Version of Record true © 2021 by the authors. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license true eng https://creativecommons.org/licenses/by/4.0/
title Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
spellingShingle Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
Igor Sazonov
title_short Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
title_full Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
title_fullStr Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
title_full_unstemmed Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
title_sort Markov Chain-Based Stochastic Modelling of HIV-1 Life Cycle in a CD4 T Cell
author_id_str_mv 05a507952e26462561085fb6f62c8897
author_id_fullname_str_mv 05a507952e26462561085fb6f62c8897_***_Igor Sazonov
author Igor Sazonov
author2 Igor Sazonov
Dmitry Grebennikov
Andreas Meyerhans
Gennady Bocharov
format Journal article
container_title Mathematics
container_volume 9
container_issue 17
container_start_page 2025
publishDate 2021
institution Swansea University
issn 2227-7390
doi_str_mv 10.3390/math9172025
publisher MDPI AG
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Aerospace Engineering
document_store_str 1
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description 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.
published_date 2021-08-24T04:14:16Z
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