Literature DB >> 30129198

Some deterministic and stochastic mathematical models of naïve T-cell homeostasis.

Grant Lythe1, Carmen Molina-París1.   

Abstract

Humans live for decades, whereas mice live for months. Over these long timescales, naïve T cells die or divide infrequently enough that it makes sense to approximate death and division as instantaneous events. The population of T cells in the body is naturally divided into clonotypes; a clonotype is the set of cells that have identical T-cell receptors. While total numbers of cells, such as naïve CD4+ T cells, are large enough that ordinary differential equations are an appropriate starting point for mathematical models, the numbers of cells per clonotype are not. Here, we review a number of basic mathematical models of the maintenance of clonal diversity. As well as deterministic models, we discuss stochastic models that explicitly track the integer number of naïve T cells in many competing clonotypes over the lifetime of a mouse or human, including the effect of waning thymic production. Experimental evaluation of clonal diversity by bulk high-throughput sequencing has many difficulties, but the use of single-cell sequencing is restricted to numbers of cells many orders of magnitude smaller than the total number of T cells in the body. Mathematical questions associated with extrapolating from small samples are therefore key to advances in understanding the diversity of the repertoire of T cells. We conclude with some mathematical models on how to advance in this area.
© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  aging; competition; computational models; extinction; sampling; single-cell sequencing; stochastic

Mesh:

Substances:

Year:  2018        PMID: 30129198     DOI: 10.1111/imr.12696

Source DB:  PubMed          Journal:  Immunol Rev        ISSN: 0105-2896            Impact factor:   12.988


  8 in total

1.  Selected before selection: A case for inherent antigen bias in the T cell receptor repertoire.

Authors:  Paul G Thomas; Jeremy Chase Crawford
Journal:  Curr Opin Syst Biol       Date:  2019-11-06

2.  Introduction to modeling viral infections and immunity.

Authors:  Alan S Perelson; Ruy M Ribeiro
Journal:  Immunol Rev       Date:  2018-09       Impact factor: 12.988

Review 3.  Molecular characterization of hypoxanthine guanine phosphoribosyltransferase mutant T cells in human blood: The concept of surrogate selection for immunologically relevant cells.

Authors:  Noah A Kaitz; Cindy L Zuleger; Peng Yu; Michael A Newton; Richard J Albertini; Mark R Albertini
Journal:  Mutat Res Rev Mutat Res       Date:  2022-03-11       Impact factor: 7.015

4.  Diversity in biology: definitions, quantification and models.

Authors:  Song Xu; Lucas Böttcher; Tom Chou
Journal:  Phys Biol       Date:  2020-03-19       Impact factor: 2.583

5.  Quantifying the Role of Stochasticity in the Development of Autoimmune Disease.

Authors:  Lindsay B Nicholson; Konstantin B Blyuss; Farzad Fatehi
Journal:  Cells       Date:  2020-04-02       Impact factor: 6.600

6.  Mathematical Modeling of Proliferative Immune Response Initiated by Interactions Between Classical Antigen-Presenting Cells Under Joint Antagonistic IL-2 and IL-4 Signaling.

Authors:  Komlan Atitey; Benedict Anchang
Journal:  Front Mol Biosci       Date:  2022-01-28

7.  How Naive T-Cell Clone Counts Are Shaped By Heterogeneous Thymic Output and Homeostatic Proliferation.

Authors:  Renaud Dessalles; Yunbei Pan; Mingtao Xia; Davide Maestrini; Maria R D'Orsogna; Tom Chou
Journal:  Front Immunol       Date:  2022-02-17       Impact factor: 7.561

Review 8.  Quantifying T Cell Cross-Reactivity: Influenza and Coronaviruses.

Authors:  Jessica Ann Gaevert; Daniel Luque Duque; Grant Lythe; Carmen Molina-París; Paul Glyndwr Thomas
Journal:  Viruses       Date:  2021-09-07       Impact factor: 5.048

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.