PT  - JOURNAL ARTICLE
AU  - Philipp Thomas
AU  - Vahid Shahrezaei
TI  - Coordination of gene expression noise with cell size: analytical results for agent-based models of growing cell populations
AID  - 10.1101/2020.10.23.352856
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2020.10.23.352856
4099  - http://biorxiv.org/content/early/2021/05/25/2020.10.23.352856.short
4100  - http://biorxiv.org/content/early/2021/05/25/2020.10.23.352856.full
AB  - The chemical master equation and the Gillespie algorithm are widely used to model the reaction kinetics inside living cells. It is thereby assumed that cell growth and division can be modelled through effective dilution reactions and extrinsic noise sources. We here re-examine these paradigms through developing an analytical agent-based framework of growing and dividing cells accompanied by an exact simulation algorithm, which allows us to quantify the dynamics of virtually any intracellular reaction network affected by stochastic cell size control and division noise. We find that the solution of the chemical master equation – including static extrinsic noise – exactly agrees with the agent-based formulation when the network under study exhibits stochastic concentration homeostasis, a novel condition that generalises concentration homeostasis in deterministic systems to higher order moments and distributions. We illustrate stochastic concentration homeostasis for a range of common gene expression networks. When this condition is not met, we demonstrate by extending the linear noise approximation to agent-based models that the dependence of gene expression noise on cell size can qualitatively deviate from the chemical master equation. Surprisingly, the total noise of the agent-based approach can still be well approximated by extrinsic noise models.Competing Interest StatementThe authors have declared no competing interest.