Vibert2017 - Tcell proliferation model

  public model
Model Identifier
MODEL2003170002
Short description 
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. Model is encoded by Matthew Maire and submitted in BioModels by Krishna Kumar Tiwari.
Format
SBML (L2V4)
Related Publication
  • Modelling T cell proliferation: Dynamics heterogeneity depending on cell differentiation, age, and genetic background.
  • Vibert J, Thomas-Vaslin V
  • PLoS computational biology , 3/ 2017 , Volume 13 , Issue 3 , pages: e1005417 , PubMed ID: 28288157
  • Sorbonne Universités, UPMC Univ Paris 06, INSERM, Immunology-Immunopathology-Immunotherapy (I3) UMRS959; Paris, France.
  • 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.
Contributors
Submitter of the first revision: Krishna Kumar Tiwari
Submitter of this revision: Krishna Kumar Tiwari
Modellers: Krishna Kumar Tiwari

Metadata information

isDescribedBy (1 statement)
PubMed 28288157

hasProperty (1 statement)
Mathematical Modelling Ontology Ordinary differential equation model

Curation status
Non-curated
Modelling approach(es)
ordinary differential equation model
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Model files
Vibert2017.xml SBML L2V4 file for the model 40.57 KB Preview | Download

Additional files
Vibert2017.cps COPASI 4.27(Built417) file for the model 83.12 KB Preview | Download
Vibert2017.sedml SEDML file for the model 4.16 KB Preview | Download

  • Model originally submitted by : Krishna Kumar Tiwari
  • Submitted: Mar 17, 2020 9:28:30 PM
  • Last Modified: Mar 17, 2020 9:28:30 PM
Revisions
  • Version: 1 public model Download this version
    • Submitted on: Mar 17, 2020 9:28:30 PM
    • Submitted by: Krishna Kumar Tiwari
    • With comment: Import of Vibert2017 - Tcell proliferation model