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...
Autores principales: | , , , |
---|---|
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 |