Maximum entropy and population heterogeneity in continuous cell cultures

TL;DR

This paper models heterogeneity in continuous cell cultures using maximum entropy, revealing how cell-to-cell variability influences system dynamics, stability, and byproduct accumulation, with applications to CHO cell bioreactors.

Contribution

It introduces a maximum entropy-based framework to incorporate phenotypic heterogeneity into chemostat models, extending traditional homogeneous assumptions.

Findings

Heterogeneity causes qualitative changes in system dynamics.

Increased byproduct accumulation due to heterogeneity.

Larger population sizes in heterogeneous models.

Abstract

Continuous cultures of mammalian cells are complex systems displaying hallmark phenomena of nonlinear dynamics, such as multi-stability, hysteresis, as well as sharp transitions between different metabolic states. In this context mathematical models may suggest control strategies to steer the system towards desired states. Although even clonal populations are known to exhibit cell-to-cell variability, most of the currently studied models assume that the population is homogeneous. To overcome this limitation, we use the maximum entropy principle to model the phenotypic distribution of cells in a chemostat as a function of the dilution rate. We consider the coupling between cell metabolism and extracellular variables describing the state of the bioreactor and take into account the impact of toxic byproduct accumulation on cell viability. We present a formal solution for the stationary state of the chemostat and show how to apply it in two examples. First, a simplified model of cell metabolism where the exact solution is tractable, and then a genome-scale metabolic network of the Chinese hamster ovary (CHO) cell line. Along the way we discuss several consequences of heterogeneity, such as: qualitative changes in the dynamical landscape of the system, increasing concentrations of byproducts that vanish in the homogeneous case, and larger population sizes.