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A multi-approach and multi-scale platform to model CD4+ T cells responding to infections

Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells, which uses four modeling approaches to integrate processes at three spatial scales in different tissues. In eac...

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Autores principales: Wertheim, Kenneth Y., Puniya, Bhanwar Lal, La Fleur, Alyssa, Shah, Ab Rauf, Barberis, Matteo, Helikar, Tomáš
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376204/
https://www.ncbi.nlm.nih.gov/pubmed/34343169
http://dx.doi.org/10.1371/journal.pcbi.1009209
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author Wertheim, Kenneth Y.
Puniya, Bhanwar Lal
La Fleur, Alyssa
Shah, Ab Rauf
Barberis, Matteo
Helikar, Tomáš
author_facet Wertheim, Kenneth Y.
Puniya, Bhanwar Lal
La Fleur, Alyssa
Shah, Ab Rauf
Barberis, Matteo
Helikar, Tomáš
author_sort Wertheim, Kenneth Y.
collection PubMed
description Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells, which uses four modeling approaches to integrate processes at three spatial scales in different tissues. In each cell, signal transduction and gene regulation are described by a logical model, metabolism by constraint-based models. Cell population dynamics are described by an agent-based model and systemic cytokine concentrations by ordinary differential equations. A Monte Carlo simulation algorithm allows information to flow efficiently between the four modules by separating the time scales. Such modularity improves computational performance and versatility and facilitates data integration. We validated our technology by reproducing known experimental results, including differentiation patterns of CD4+ T cells triggered by different combinations of cytokines, metabolic regulation by IL2 in these cells, and their response to influenza infection. In doing so, we added multi-scale insights to single-scale studies and demonstrated its predictive power by discovering switch-like and oscillatory behaviors of CD4+ T cells that arise from nonlinear dynamics interwoven across three scales. We identified the inflamed lymph node’s ability to retain naive CD4+ T cells as a key mechanism in generating these emergent behaviors. We envision our model and the generic framework encompassing it to serve as a tool for understanding cellular and molecular immunological problems through the lens of systems immunology.
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spelling pubmed-83762042021-08-20 A multi-approach and multi-scale platform to model CD4+ T cells responding to infections Wertheim, Kenneth Y. Puniya, Bhanwar Lal La Fleur, Alyssa Shah, Ab Rauf Barberis, Matteo Helikar, Tomáš PLoS Comput Biol Research Article Immune responses rely on a complex adaptive system in which the body and infections interact at multiple scales and in different compartments. We developed a modular model of CD4+ T cells, which uses four modeling approaches to integrate processes at three spatial scales in different tissues. In each cell, signal transduction and gene regulation are described by a logical model, metabolism by constraint-based models. Cell population dynamics are described by an agent-based model and systemic cytokine concentrations by ordinary differential equations. A Monte Carlo simulation algorithm allows information to flow efficiently between the four modules by separating the time scales. Such modularity improves computational performance and versatility and facilitates data integration. We validated our technology by reproducing known experimental results, including differentiation patterns of CD4+ T cells triggered by different combinations of cytokines, metabolic regulation by IL2 in these cells, and their response to influenza infection. In doing so, we added multi-scale insights to single-scale studies and demonstrated its predictive power by discovering switch-like and oscillatory behaviors of CD4+ T cells that arise from nonlinear dynamics interwoven across three scales. We identified the inflamed lymph node’s ability to retain naive CD4+ T cells as a key mechanism in generating these emergent behaviors. We envision our model and the generic framework encompassing it to serve as a tool for understanding cellular and molecular immunological problems through the lens of systems immunology. Public Library of Science 2021-08-03 /pmc/articles/PMC8376204/ /pubmed/34343169 http://dx.doi.org/10.1371/journal.pcbi.1009209 Text en © 2021 Wertheim et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Wertheim, Kenneth Y.
Puniya, Bhanwar Lal
La Fleur, Alyssa
Shah, Ab Rauf
Barberis, Matteo
Helikar, Tomáš
A multi-approach and multi-scale platform to model CD4+ T cells responding to infections
title A multi-approach and multi-scale platform to model CD4+ T cells responding to infections
title_full A multi-approach and multi-scale platform to model CD4+ T cells responding to infections
title_fullStr A multi-approach and multi-scale platform to model CD4+ T cells responding to infections
title_full_unstemmed A multi-approach and multi-scale platform to model CD4+ T cells responding to infections
title_short A multi-approach and multi-scale platform to model CD4+ T cells responding to infections
title_sort multi-approach and multi-scale platform to model cd4+ t cells responding to infections
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8376204/
https://www.ncbi.nlm.nih.gov/pubmed/34343169
http://dx.doi.org/10.1371/journal.pcbi.1009209
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