Cargando…

Population mechanics: A mathematical framework to study T cell homeostasis

Unlike other cell types, T cells do not form spatially arranged tissues, but move independently throughout the body. Accordingly, the number of T cells in the organism does not depend on physical constraints imposed by the shape or size of specific organs. Instead, it is determined by competition fo...

Descripción completa

Detalles Bibliográficos
Autores principales: Arias, Clemente F., Herrero, Miguel A., Acosta, Francisco J., Fernandez-Arias, Cristina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573381/
https://www.ncbi.nlm.nih.gov/pubmed/28842645
http://dx.doi.org/10.1038/s41598-017-09949-w
_version_ 1783259649766588416
author Arias, Clemente F.
Herrero, Miguel A.
Acosta, Francisco J.
Fernandez-Arias, Cristina
author_facet Arias, Clemente F.
Herrero, Miguel A.
Acosta, Francisco J.
Fernandez-Arias, Cristina
author_sort Arias, Clemente F.
collection PubMed
description Unlike other cell types, T cells do not form spatially arranged tissues, but move independently throughout the body. Accordingly, the number of T cells in the organism does not depend on physical constraints imposed by the shape or size of specific organs. Instead, it is determined by competition for interleukins. From the perspective of classical population dynamics, competition for resources seems to be at odds with the observed high clone diversity, leading to the so-called diversity paradox. In this work we make use of population mechanics, a non-standard theoretical approach to T cell homeostasis that accounts for clone diversity as arising from competition for interleukins. The proposed models show that carrying capacities of T cell populations naturally emerge from the balance between interleukins production and consumption. These models also suggest remarkable functional differences in the maintenance of diversity in naïve and memory pools. In particular, the distribution of memory clones would be biased towards clones activated more recently, or responding to more aggressive pathogenic threats. In contrast, permanence of naïve T cell clones would be determined by their affinity for cognate antigens. From this viewpoint, positive and negative selection can be understood as mechanisms to maximize naïve T cell diversity.
format Online
Article
Text
id pubmed-5573381
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-55733812017-09-01 Population mechanics: A mathematical framework to study T cell homeostasis Arias, Clemente F. Herrero, Miguel A. Acosta, Francisco J. Fernandez-Arias, Cristina Sci Rep Article Unlike other cell types, T cells do not form spatially arranged tissues, but move independently throughout the body. Accordingly, the number of T cells in the organism does not depend on physical constraints imposed by the shape or size of specific organs. Instead, it is determined by competition for interleukins. From the perspective of classical population dynamics, competition for resources seems to be at odds with the observed high clone diversity, leading to the so-called diversity paradox. In this work we make use of population mechanics, a non-standard theoretical approach to T cell homeostasis that accounts for clone diversity as arising from competition for interleukins. The proposed models show that carrying capacities of T cell populations naturally emerge from the balance between interleukins production and consumption. These models also suggest remarkable functional differences in the maintenance of diversity in naïve and memory pools. In particular, the distribution of memory clones would be biased towards clones activated more recently, or responding to more aggressive pathogenic threats. In contrast, permanence of naïve T cell clones would be determined by their affinity for cognate antigens. From this viewpoint, positive and negative selection can be understood as mechanisms to maximize naïve T cell diversity. Nature Publishing Group UK 2017-08-25 /pmc/articles/PMC5573381/ /pubmed/28842645 http://dx.doi.org/10.1038/s41598-017-09949-w Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Arias, Clemente F.
Herrero, Miguel A.
Acosta, Francisco J.
Fernandez-Arias, Cristina
Population mechanics: A mathematical framework to study T cell homeostasis
title Population mechanics: A mathematical framework to study T cell homeostasis
title_full Population mechanics: A mathematical framework to study T cell homeostasis
title_fullStr Population mechanics: A mathematical framework to study T cell homeostasis
title_full_unstemmed Population mechanics: A mathematical framework to study T cell homeostasis
title_short Population mechanics: A mathematical framework to study T cell homeostasis
title_sort population mechanics: a mathematical framework to study t cell homeostasis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573381/
https://www.ncbi.nlm.nih.gov/pubmed/28842645
http://dx.doi.org/10.1038/s41598-017-09949-w
work_keys_str_mv AT ariasclementef populationmechanicsamathematicalframeworktostudytcellhomeostasis
AT herreromiguela populationmechanicsamathematicalframeworktostudytcellhomeostasis
AT acostafranciscoj populationmechanicsamathematicalframeworktostudytcellhomeostasis
AT fernandezariascristina populationmechanicsamathematicalframeworktostudytcellhomeostasis