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Dynamic models of viral replication and latency

PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus–host interactions that drive these dynamic changes is impo...

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Autores principales: Mohammadi, Pejman, Ciuffi, Angela, Beerenwinkel, Niko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4323573/
https://www.ncbi.nlm.nih.gov/pubmed/25565177
http://dx.doi.org/10.1097/COH.0000000000000136
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author Mohammadi, Pejman
Ciuffi, Angela
Beerenwinkel, Niko
author_facet Mohammadi, Pejman
Ciuffi, Angela
Beerenwinkel, Niko
author_sort Mohammadi, Pejman
collection PubMed
description PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus–host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir.
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spelling pubmed-43235732015-02-17 Dynamic models of viral replication and latency Mohammadi, Pejman Ciuffi, Angela Beerenwinkel, Niko Curr Opin HIV AIDS GENOMICS IN HIV INFECTION: Edited by Amalio Telenti PURPOSE OF REVIEW: HIV targets primary CD4(+) T cells. The virus depends on the physiological state of its target cells for efficient replication, and, in turn, viral infection perturbs the cellular state significantly. Identifying the virus–host interactions that drive these dynamic changes is important for a better understanding of viral pathogenesis and persistence. The present review focuses on experimental and computational approaches to study the dynamics of viral replication and latency. RECENT FINDINGS: It was recently shown that only a fraction of the inducible latently infected reservoirs are successfully induced upon stimulation in ex-vivo models while additional rounds of stimulation make allowance for reactivation of more latently infected cells. This highlights the potential role of treatment duration and timing as important factors for successful reactivation of latently infected cells. The dynamics of HIV productive infection and latency have been investigated using transcriptome and proteome data. The cellular activation state has shown to be a major determinant of viral reactivation success. Mathematical models of latency have been used to explore the dynamics of the latent viral reservoir decay. SUMMARY: Timing is an important component of biological interactions. Temporal analyses covering aspects of viral life cycle are essential for gathering a comprehensive picture of HIV interaction with the host cell and untangling the complexity of latency. Understanding the dynamic changes tipping the balance between success and failure of HIV particle production might be key to eradicate the viral reservoir. Lippincott Williams & Wilkins 2015-03 2015-02-05 /pmc/articles/PMC4323573/ /pubmed/25565177 http://dx.doi.org/10.1097/COH.0000000000000136 Text en Copyright © 2015 Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License, where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle GENOMICS IN HIV INFECTION: Edited by Amalio Telenti
Mohammadi, Pejman
Ciuffi, Angela
Beerenwinkel, Niko
Dynamic models of viral replication and latency
title Dynamic models of viral replication and latency
title_full Dynamic models of viral replication and latency
title_fullStr Dynamic models of viral replication and latency
title_full_unstemmed Dynamic models of viral replication and latency
title_short Dynamic models of viral replication and latency
title_sort dynamic models of viral replication and latency
topic GENOMICS IN HIV INFECTION: Edited by Amalio Telenti
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4323573/
https://www.ncbi.nlm.nih.gov/pubmed/25565177
http://dx.doi.org/10.1097/COH.0000000000000136
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