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:	Kenneth Y Wertheim, Bhanwar Lal Puniya, Alyssa La Fleur, Ab Rauf Shah, Matteo Barberis, Tomáš Helikar
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/dcbf566f061e4a15be98e38f97a531fe
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spelling	oai:doaj.org-article:dcbf566f061e4a15be98e38f97a531fe2021-12-02T19:58:08ZA multi-approach and multi-scale platform to model CD4+ T cells responding to infections.1553-734X1553-735810.1371/journal.pcbi.1009209https://doaj.org/article/dcbf566f061e4a15be98e38f97a531fe2021-08-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009209https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Immune 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.Kenneth Y WertheimBhanwar Lal PuniyaAlyssa La FleurAb Rauf ShahMatteo BarberisTomáš HelikarPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 8, p e1009209 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Kenneth Y Wertheim Bhanwar Lal Puniya Alyssa La Fleur Ab Rauf Shah Matteo Barberis Tomáš Helikar A multi-approach and multi-scale platform to model CD4+ T cells responding to infections.
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.
format	article
author	Kenneth Y Wertheim Bhanwar Lal Puniya Alyssa La Fleur Ab Rauf Shah Matteo Barberis Tomáš Helikar
author_facet	Kenneth Y Wertheim Bhanwar Lal Puniya Alyssa La Fleur Ab Rauf Shah Matteo Barberis Tomáš Helikar
author_sort	Kenneth Y Wertheim
title	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_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_sort	multi-approach and multi-scale platform to model cd4+ t cells responding to infections.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/dcbf566f061e4a15be98e38f97a531fe
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A multi-approach and multi-scale platform to model CD4+ T cells responding to infections.

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