Clonal abundance patterns in hematopoiesis: Mathematical modeling and parameter estimation

Frontiers in Systems Biology, vol. 3, pp. 893366

Abstract

methods. Subsequent proliferation and differentiation preserve the tag identity, thus defining a clone of mature cells across multiple cell type or lineages. By tracking the population of clones, measured within samples taken at discrete time points, we infer physiological parameters associated with a hybrid stochastic-deterministic mathematical model of hematopoiesis. We analyze clone population data from Koelle et al. (Koelle et al., 2017) and compare the states of clones (mean and variance of their abundances) and the state-space density of clones with the corresponding quantities predicted from our model. Comparing our model to the tagged granulocyte populations, we find parameters (stem cell carrying capacity, stem cell differentiation rates, and the proliferative potential of progenitor cells, and sample sizes) that provide reasonable fits in three out of four animals. Even though some observed features cannot be quantitatively reproduced by our model, our analyses provides insight into how model parameters influence the underlying mechanisms in hematopoiesis. We discuss additional mechanisms not incorporated in our model.

Authors 5

1. Yunbei Pan

   California State University, Northridge · University of California, Los Angeles

   Affiliation as printed

   Department of Computational Medicine, UCLA, Los Angeles, CA, United States

   Department of Mathematics, California State University at Northridge, Los Angeles, CA, United States

2. Maria Rita D'Orsogna

   California State University, Northridge · University of California, Los Angeles

   Affiliation as printed

   Department of Computational Medicine, UCLA, Los Angeles, CA, United States

   Department of Mathematics, California State University at Northridge, Los Angeles, CA, United States

3. Min Ming Tang corresponding

   Shanghai Jiao Tong University

   Affiliation as printed

   Institute of Natural Sciences, Shanghai Jiaotong University, Shanghai, China

4. Thomas Stiehl Aachen Institute of Computational Biomedicine

   RWTH Aachen University

   Affiliation as printed

   Institute of Computational Biomedicine, RWTH Aachen University, Aachen, Germany

5. Tom Chou corresponding

   University of California, Los Angeles

   Affiliation as printed

   Department of Computational Medicine, UCLA, Los Angeles, CA, United States

   Department of Mathematics, UCLA, Los Angeles, CA, United States