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Abstract:
HIV infection leads to two cell fates, the viral productive state or viral latency (a reversible non-productive state). HIV latency is relevant because infected active CD4+ T-lymphocytes can reach a resting memory state in which the provirus remains silent for long periods of time. Despite experimental and theoretical efforts, the causal molecular mechanisms responsible for HIV latency are only partially understood. Studies have determined that HIV latency is influenced by the innate immune response carried out by cell restriction factors that inhibit the postintegration steps in the virus replication cycle. In this study, we present a mathematical study that combines deterministic and stochastic approaches to analyze the interactions between HIV proteins and the innate immune response. Using wide ranges of parameter values, we observed the following: (1) a phenomenological description of the viral productive and latent cell phenotypes is obtained by bistable and bimodal dynamics, (2) biochemical noise reduces the probability that an infected cell adopts the latent state, (3) the effects of the innate immune response enhance the HIV latency state, (4) the conditions of the cell before infection affect the latent phenotype, i.e., the existing expression of cell restriction factors propitiates HIV latency, and existing expression of HIV proteins reduces HIV latency.
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Studying HIV latency by modeling the interaction between HIV proteins and the innate immune response.
- Aguilera LU, Jesús Rodríguez-González
- Journal of theoretical biology , 11/ 2014 , Volume 360 , pages: 67-77 , PubMed ID: 24997239
Submitter of this revision: Lucian Smith
Curator: Lucian Smith
Modellers: administrator, Luis Ubaldo Aguilera de Lira
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Mathematical Modelling Ontology Ordinary differential equation model
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