Cell population heterogeneity driven by stochastic partition and growth optimality

Fernandez-de-Cossio-Diaz, J., Mulet, R. and Vazquez, A. (2019) Cell population heterogeneity driven by stochastic partition and growth optimality. Scientific Reports, 9, 9406. (doi: 10.1038/s41598-019-45882-w) (PMID:31253860) (PMCID:PMC6599024)

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Abstract

A fundamental question in biology is how cell populations evolve into different subtypes based on homogeneous processes at the single cell level. Here we show that population bimodality can emerge even when biological processes are homogenous at the cell level and the environment is kept constant. Our model is based on the stochastic partitioning of a cell component with an optimal copy number. We show that the existence of unimodal or bimodal distributions depends on the variance of partition errors and the growth rate tolerance around the optimal copy number. In particular, our theory provides a consistent explanation for the maintenance of aneuploid states in a population. The proposed model can also be relevant for other cell components such as mitochondria and plasmids, whose abundances affect the growth rate and are subject to stochastic partition at cell division.

Item Type:Articles
Additional Information:This project has received funding from the European Unions Horizon 2020 research and innovation programme MSCA-RISE-2016 under grant agreement No. 734439 INFERNET.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vazquez, Alexei
Authors: Fernandez-de-Cossio-Diaz, J., Mulet, R., and Vazquez, A.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cancer Sciences
Journal Name:Scientific Reports
Publisher:Nature Research
ISSN:2045-2322
ISSN (Online):2045-2322
Copyright Holders:Copyright © The Authors 2019
First Published:First published in Scientific Reports 9:9406
Publisher Policy:Reproduced under a Creative Commons license

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