Literature DB >> 23311419

A division-dependent compartmental model for computing cell numbers in CFSE-based lymphocyte proliferation assays.

H T Banks1, W Clayton Thompson, Cristina Peligero, Sandra Giest, Jordi Argilaguet, Andreas Meyerhans.   

Abstract

Some key features of a mathematical description of an immune response are an estimate of the number of responding cells and the manner in which those cells divide, differentiate, and die. The intracellular dye CFSE is a powerful experimental tool for the analysis of a population of dividing cells, and numerous mathematical treatments have been aimed at using CFSE data to describe an immune response [30,31,32,37,38,42,48,49]. Recently, partial differential equation structured population models, with measured CFSE fluorescence intensity as the structure variable, have been shown to accurately fit histogram data obtained from CFSE flow cytometry experiments [18,19,52,54]. In this report, the population of cells is mathematically organized into compartments, with all cells in a single compartment having undergone the same number of divisions. A system of structured partial differential equations is derived which can be fit directly to CFSE histogram data. From such a model, cell counts (in terms of the number of divisions undergone) can be directly computed and thus key biological parameters such as population doubling time and precursor viability can be determined. Mathematical aspects of this compartmental model are discussed, and the model is fit to a data set. As in [18,19], we find temporal and division dependence in the rates of proliferation and death to be essential features of a structured population model for CFSE data. Variability in cellular autofluorescence is found to play a significant role in the data, as well. Finally, the compartmental model is compared to previous work, and statistical aspects of the experimental data are discussed.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 23311419     DOI: 10.3934/mbe.2012.9.699

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  10 in total

1.  Mathematical models for CFSE labelled lymphocyte dynamics: asymmetry and time-lag in division.

Authors:  Tatyana Luzyanina; Jovana Cupovic; Burkhard Ludewig; Gennady Bocharov
Journal:  J Math Biol       Date:  2013-12-13       Impact factor: 2.259

2.  Estimating intratumoral heterogeneity from spatiotemporal data.

Authors:  E M Rutter; H T Banks; K B Flores
Journal:  J Math Biol       Date:  2018-05-08       Impact factor: 2.259

3.  A structured population modeling framework for quantifying and predicting gene expression noise in flow cytometry data.

Authors:  Kevin B Flores
Journal:  Appl Math Lett       Date:  2013-07       Impact factor: 4.055

4.  Quantifying CFSE Label Decay in Flow Cytometry Data.

Authors:  H T Banks; A Choi; T Huffman; J Nardini; L Poag; W C Thompson
Journal:  Appl Math Lett       Date:  2013-01-03       Impact factor: 4.055

5.  Quantifying T lymphocyte turnover.

Authors:  Rob J De Boer; Alan S Perelson
Journal:  J Theor Biol       Date:  2013-01-09       Impact factor: 2.691

6.  A novel statistical analysis and interpretation of flow cytometry data.

Authors:  H T Banks; D F Kapraun; W Clayton Thompson; Cristina Peligero; Jordi Argilaguet; Andreas Meyerhans
Journal:  J Biol Dyn       Date:  2013       Impact factor: 2.179

7.  Estimates and impact of lymphocyte division parameters from CFSE data using mathematical modelling.

Authors:  Pauline Mazzocco; Samuel Bernard; Laurent Pujo-Menjouet
Journal:  PLoS One       Date:  2017-06-16       Impact factor: 3.240

8.  A novel and efficient method to induce allospecific CD8+ memory T lymphocytes.

Authors:  Lei Yang; Qingyun Huang; Jianping Fu; Zhimin Lin; Qiqi Mao; Lili Zhao; Xingxin Gao; Songlin Chen; Guangzong Hua; Sheng Li
Journal:  J Clin Lab Anal       Date:  2021-08-31       Impact factor: 2.352

Review 9.  Asymmetry of Cell Division in CFSE-Based Lymphocyte Proliferation Analysis.

Authors:  Gennady Bocharov; Tatyana Luzyanina; Jovana Cupovic; Burkhard Ludewig
Journal:  Front Immunol       Date:  2013-09-02       Impact factor: 7.561

10.  Infected hematopoietic stem cells and with integrated HBV DNA generate defective T cells in chronic HBV infection patients.

Authors:  Y Shi; Y Lan; F Cao; Y Teng; L Li; F Wang; J Li; J Zhou; Y Li
Journal:  J Viral Hepat       Date:  2014-03-12       Impact factor: 3.728

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.