ArticlePLoS computational biology2019
Maximum entropy and population heterogeneity in continuous cell cultures.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed, 27 citations in OpenAlex.
- Article
- A multilevel hierarchical framework for quantification of experimental heterogeneity in population snapshot data.PLoS computational biology · 2026Article
- Sensitivity of endogenous autofluorescence in HeLa cells to the application of external magnetic fields.Scientific reports · 2023Article
- Article
- Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers.ACS nano · 2023Article
- Inference of metabolic fluxes in nutrient-limited continuous cultures: A Maximum Entropy approach with the minimum information.iScience · 2022Article
- Maximum Entropy Technique and Regularization Functional for Determining the Pharmacokinetic Parameters in DCE-MRI.Journal of digital imaging · 2022Article
- Relationship between fitness and heterogeneity in exponentially growing microbial populations.Biophysical journal · 2022Article
- Modified Maximum Entropy Method and Estimating the AIF via DCE-MRI Data Analysis.Entropy (Basel, Switzerland) · 2022Article
- Assessment of the electrical penetration of cell membranes using four-frequency impedance cytometry.Microsystems & nanoengineering · 2022Article
- Addressing uncertainty in genome-scale metabolic model reconstruction and analysis.Genome biology · 2021Review
- Cooperative metabolic resource allocation in spatially-structured systems.Journal of mathematical biology · 2021Article
- Systematically gap-filling the genome-scale metabolic model of CHO cells.Biotechnology letters · 2021Article
- Dynamic metabolic resource allocation based on the maximum entropy principle.Journal of mathematical biology · 2020Article
- Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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