An age-dependent branching process model for the analysis of CFSE-labeling experiments

Springer Science and Business Media LLC - Tập 5 - Trang 1-17 - 2010
Ollivier Hyrien1, Rui Chen1, Martin S Zand2
1Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, USA
2Department of Medicine, Division of Nephrology, University of Rochester Medical Center, Rochester, USA

Tóm tắt

Over the past decade, flow cytometric CFSE-labeling experiments have gained considerable popularity among experimentalists, especially immunologists and hematologists, for studying the processes of cell proliferation and cell death. Several mathematical models have been presented in the literature to describe cell kinetics during these experiments. We propose a multi-type age-dependent branching process to model the temporal development of populations of cells subject to division and death during CFSE-labeling experiments. We discuss practical implementation of the proposed model; we investigate a competing risk version of the process; and we identify the classes of cellular dependencies that may influence the expectation of the process and those that do not. An application is presented where we study the proliferation of human CD8+ T lymphocytes using our model and a competing risk branching process. The proposed model offers a widely applicable approach to the analysis of CFSE-labeling experiments. The model fitted very well our experimental data. It provided reasonable estimates of cell kinetics parameters as well as meaningful insights into the processes of cell division and cell death. In contrast, the competing risk branching process could not describe the kinetics of CD8+ T cells. This suggested that the decision of cell division or cell death may be made early in the cell cycle if not in preceding generations. Also, we show that analyses based on the proposed model are robust with respect to cross-sectional dependencies and to dependencies between fates of linearly filiated cells. This article was reviewed by Marek Kimmel, Wai-Yuan Tan and Peter Olofsson.

Tài liệu tham khảo

Gett AV, Hodgkin PD: Cell division regulates the T cell cytokine repertoire, revealing a mechanism underlying immune class regulation. Proc Natl Acad Sci USA. 1998, 95: 9488-9493. 10.1073/pnas.95.16.9488.

Gett AV, Hodgkin PD: A cellular calculus for signal integration by T cells. Nat Immunol. 2000, 1: 239-244. 10.1038/79782.

Bernard S, Pujo-Menjouet L, Mackey MC: Analysis of cell kinetics using a cell division marker: mathematical modelling of experimental data. Biophys J. 2003, 84: 3414-3424. 10.1016/S0006-3495(03)70063-0.

Ganusov VV, Pilyugin SS, De Boer RJ, Murali-Krishna K, Ahmed R, Antia R: Quantifying cell turnover using CFSE data. J Immunol Methods. 2005, 298: 183-200. 10.1016/j.jim.2005.01.011.

De Boer RJ, Perelson AS: Estimating division and death rates from CFSE data. J Comp Appl Math. 2005, 184: 104-164.

Hawkins ED, Turner ML, Dowling MR, van Gend C, Hodgkin PD: A model of immune regulation as a consequence of randomized lymphocyte division and death times. Proc Natl Acad Sci USA. 2007, 104: 5032-5037. 10.1073/pnas.0700026104.

Hyrien O, Zand MS: A mixture model with dependent observations for the analysis of CFSE-labeling experiments. J Am Stat Assoc. 2008, 103: 222-239. 10.1198/016214507000000194.

Hyrien O, Mayer-Pröschel M, Noble M, Yakovlev A: A stochastic model to analyze clonal data on multi type cell populations. Biometrics. 2005, 61: 199-207. 10.1111/j.0006-341X.2005.031210.x.

Jagers P: Branching Processes with Biological Applications. 1975, John Wiley and Sons, London

Yakovlev AY, Yanev N: Transient Processes in Cell Proliferation Kinetics. 1989, Springer Heidelberg

Kimmel M, Axelrod DE: Branching Processes in Biology. 2002, Springer New York

Hyrien O, Chen R, Mayer-Pröschel M, Noble M: Saddlepoint approximations to the moments of age-dependent branching processes, with applications. Biometrics. 2010, 66: 567-577. 10.1111/j.1541-0420.2009.01281.x.

Waugh WAO'N: Age-dependent branching processes under a condition of ultimate extinction. Biometrika. 1968, 55: 291-296. 10.1093/biomet/55.2.291.

Arnold BC, Beaver RJ, Groeneveld RA, Meeker WQ: The nontruncated marginal of a truncated bivariate normal distribution. Psychometrika. 1993, 58: 471-488. 10.1007/BF02294652.

Collyn d'Hooghe M, Valleron AJ, Malaise EP: Time-lapse cinematography studies of cell cycle and mitosis duration. Experimental Cell Research. 1977, 106: 405-407. 10.1016/0014-4827(77)90190-2.

Huggins RM, Staudte RG: Variance components models for dependent cell populations. J Am Stat Assoc. 1994, 89: 19-29. 10.2307/2291197.

Crump KS, Mode CJ: An age-dependent branching process with correlations among sister cells. J Appl Probab. 1969, 6: 205-210. 10.2307/3212288.

Stivers DD, Kimmel M, Axelrod DE: A discrete-time multi-type generational inheritance branching process model of cell proliferation. Math Biosci. 1996, 137: 25-50. 10.1016/S0025-5564(96)00066-1.

Boucher K, Yakovlev AY, Mayer-Pröschel M, Noble M: A stochastic model of temporarily regulated generation of oligodendrocytes in vitro. Math Biosci. 1999, 159: 47-78. 10.1016/S0025-5564(99)00010-3.

Hyrien O: A pseudo maximum likelihood estimator for discretely observed multitype Bellman-Harris branching processes. J Statist Plan Inf. 2007, 137: 1375-1388. 10.1016/j.jspi.2006.01.014.

Terrano DT, Upreti M, Chambers TC: Cyclin-dependent kinase 1-mediated Bcl-xL/Bcl-2 phosphorylation acts as a functional link coupling mitotic arrest and apoptosis. Mol Cell Biol. 2010, 30 (3): 640-56. 10.1128/MCB.00882-09.

Hawkins ED, Markham JF, McGuinness LP, Hodgkin PD: A single-cell pedigree analysis of alternative stochastic lymphocyte fates. Proc Natl Acad Sci USA. 2009, 106 (32): 13457-62. 10.1073/pnas.0905629106.