Single-cell gene-switching networks and heterogeneous cell population phenotypes

Cell populations are heterogeneous systems in the sense that cellular properties are unevenly distributed amongst the cells of the population. In this work, we present a novel methodological and computational framework for the quantitative assessment of the effects of cell population heterogeneity on the dynamics of cell populations. It combines the cell population balance modeling approach which accounts for cell population heterogeneity with the continuum modeling approach, which does not. We focus on populations of cells carrying an artificial genetic network, known as the genetic toggle, consisting of a system of two promoter-repressor pairs. Detailed numerical simulations indicate that taking into account cell population heterogeneity leads to agreement with experimental data, while neglecting it results in significant qualitative and quantitative differences both transiently and at balanced growth. Furthermore, the simulations revealed the effect of systemic parameters on both the transient and balanced growth behavior, leading us to the formulation of specific hypotheses to interpret experimental results. Thus, cell population balance modeling when used in conjunction with mechanistic single-cell models constitutes a powerful predictive tool which can provide invaluable quantitative insights into the biological system under consideration.