Cargando…

Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background

Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and m...

Descripción completa

Detalles Bibliográficos
Autores principales: Vibert, Julien, Thomas-Vaslin, Véronique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367836/
https://www.ncbi.nlm.nih.gov/pubmed/28288157
http://dx.doi.org/10.1371/journal.pcbi.1005417
_version_ 1782517843459309568
author Vibert, Julien
Thomas-Vaslin, Véronique
author_facet Vibert, Julien
Thomas-Vaslin, Véronique
author_sort Vibert, Julien
collection PubMed
description Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and migration of lymphocytes to peripheral tissues, where proliferation also occurs upon antigen recognition. Quantification of cell proliferation dynamics requires specific experimental methods and mathematical modelling. Here, we assess the impact of genetics and aging on the immune system by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Our investigation is based on single-cell multicolour flow cytometry analysis revealing the active incorporation of a thymidine analogue during S phase after pulse-chase-pulse experiments in vivo, versus cell DNA content. A generic mathematical model of state transition simulates through Ordinary Differential Equations (ODEs) the evolution of single cell behaviour during various durations of labelling. It allows us to fit our data, to deduce proliferation rates and estimate cell cycle durations in sub-populations. Our model is simple and flexible and is validated with other durations of pulse/chase experiments. Our results reveal that T cell proliferation is highly heterogeneous but with a specific “signature” that depends upon genetic origins, is specific to cell differentiation stages in thymus and spleen and is altered with age. In conclusion, our model allows us to infer proliferation rates and cell cycle phase durations from complex experimental 5-ethynyl-2'-deoxyuridine (EdU) data, revealing T cell proliferation heterogeneity and specific signatures.
format Online
Article
Text
id pubmed-5367836
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-53678362017-04-06 Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background Vibert, Julien Thomas-Vaslin, Véronique PLoS Comput Biol Research Article Cell proliferation is the common characteristic of all biological systems. The immune system insures the maintenance of body integrity on the basis of a continuous production of diversified T lymphocytes in the thymus. This involves processes of proliferation, differentiation, selection, death and migration of lymphocytes to peripheral tissues, where proliferation also occurs upon antigen recognition. Quantification of cell proliferation dynamics requires specific experimental methods and mathematical modelling. Here, we assess the impact of genetics and aging on the immune system by investigating the dynamics of proliferation of T lymphocytes across their differentiation through thymus and spleen in mice. Our investigation is based on single-cell multicolour flow cytometry analysis revealing the active incorporation of a thymidine analogue during S phase after pulse-chase-pulse experiments in vivo, versus cell DNA content. A generic mathematical model of state transition simulates through Ordinary Differential Equations (ODEs) the evolution of single cell behaviour during various durations of labelling. It allows us to fit our data, to deduce proliferation rates and estimate cell cycle durations in sub-populations. Our model is simple and flexible and is validated with other durations of pulse/chase experiments. Our results reveal that T cell proliferation is highly heterogeneous but with a specific “signature” that depends upon genetic origins, is specific to cell differentiation stages in thymus and spleen and is altered with age. In conclusion, our model allows us to infer proliferation rates and cell cycle phase durations from complex experimental 5-ethynyl-2'-deoxyuridine (EdU) data, revealing T cell proliferation heterogeneity and specific signatures. Public Library of Science 2017-03-13 /pmc/articles/PMC5367836/ /pubmed/28288157 http://dx.doi.org/10.1371/journal.pcbi.1005417 Text en © 2017 Vibert, Thomas-Vaslin http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Vibert, Julien
Thomas-Vaslin, Véronique
Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background
title Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background
title_full Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background
title_fullStr Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background
title_full_unstemmed Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background
title_short Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background
title_sort modelling t cell proliferation: dynamics heterogeneity depending on cell differentiation, age, and genetic background
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5367836/
https://www.ncbi.nlm.nih.gov/pubmed/28288157
http://dx.doi.org/10.1371/journal.pcbi.1005417
work_keys_str_mv AT vibertjulien modellingtcellproliferationdynamicsheterogeneitydependingoncelldifferentiationageandgeneticbackground
AT thomasvaslinveronique modellingtcellproliferationdynamicsheterogeneitydependingoncelldifferentiationageandgeneticbackground