Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling.
Carboxyfluorescein diacetate succinimidyl ester (CFSE) labelling has been widely used to track and study cell proliferation. Here we use mathematical modelling to describe the kinetics of immune cell proliferation after an in vitro polyclonal stimulation tracked with CFSE. This approach allows us to...
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doaj-cf8aeb38b7f7425d94db0d57e65b92542020-11-25T02:36:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-01126e017976810.1371/journal.pone.0179768Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling.Pauline MazzoccoSamuel BernardLaurent Pujo-MenjouetCarboxyfluorescein diacetate succinimidyl ester (CFSE) labelling has been widely used to track and study cell proliferation. Here we use mathematical modelling to describe the kinetics of immune cell proliferation after an in vitro polyclonal stimulation tracked with CFSE. This approach allows us to estimate a set of key parameters, including ones related to cell death and proliferation. We develop a three-phase model that distinguishes a latency phase, accounting for non-divided cell behaviour, a resting phase and the active phase of the division process. Parameter estimates are derived from model results, and numerical simulations are then compared to the dynamics of in vitro experiments, with different biological assumptions tested. Our model allows us to compare the dynamics of CD4+ and CD8+ cells, and to highlight their kinetic differences. Finally we perform a sensitivity analysis to quantify the impact of each parameter on proliferation kinetics. Interestingly, we find that parameter sensitivity varies with time and with cell generation. Our approach can help biologists to understand cell proliferation mechanisms and to identify potential pathological division processes.http://europepmc.org/articles/PMC5473582?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Pauline Mazzocco Samuel Bernard Laurent Pujo-Menjouet |
spellingShingle |
Pauline Mazzocco Samuel Bernard Laurent Pujo-Menjouet Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling. PLoS ONE |
author_facet |
Pauline Mazzocco Samuel Bernard Laurent Pujo-Menjouet |
author_sort |
Pauline Mazzocco |
title |
Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling. |
title_short |
Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling. |
title_full |
Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling. |
title_fullStr |
Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling. |
title_full_unstemmed |
Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling. |
title_sort |
estimates and impact of lymphocyte division parameters from cfse data using mathematical modelling. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2017-01-01 |
description |
Carboxyfluorescein diacetate succinimidyl ester (CFSE) labelling has been widely used to track and study cell proliferation. Here we use mathematical modelling to describe the kinetics of immune cell proliferation after an in vitro polyclonal stimulation tracked with CFSE. This approach allows us to estimate a set of key parameters, including ones related to cell death and proliferation. We develop a three-phase model that distinguishes a latency phase, accounting for non-divided cell behaviour, a resting phase and the active phase of the division process. Parameter estimates are derived from model results, and numerical simulations are then compared to the dynamics of in vitro experiments, with different biological assumptions tested. Our model allows us to compare the dynamics of CD4+ and CD8+ cells, and to highlight their kinetic differences. Finally we perform a sensitivity analysis to quantify the impact of each parameter on proliferation kinetics. Interestingly, we find that parameter sensitivity varies with time and with cell generation. Our approach can help biologists to understand cell proliferation mechanisms and to identify potential pathological division processes. |
url |
http://europepmc.org/articles/PMC5473582?pdf=render |
work_keys_str_mv |
AT paulinemazzocco estimatesandimpactoflymphocytedivisionparametersfromcfsedatausingmathematicalmodelling AT samuelbernard estimatesandimpactoflymphocytedivisionparametersfromcfsedatausingmathematicalmodelling AT laurentpujomenjouet estimatesandimpactoflymphocytedivisionparametersfromcfsedatausingmathematicalmodelling |
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