title: Molecular noise can minimize the collective sensitivity of a clonal heterogeneous cell population.
abstract: It is now widely accepted that molecular noise, rather than be always detrimental, introduces in many circumstances the required boost to reach fundamental cellular activities or strategies otherwise unattainable. In threshold-like genetic systems, molecular noise serves to generate heterogeneous responses in a clonal population, also in a tissue, due to cell-to-cell variability. Here, we derived a mathematical framework from which we could study in detail this effect. We focused on a minimal decision-making gene circuit implemented as a transcriptional positive-feedback loop. We evidenced that when the individual responses of each cell within the population are averaged, a sort of collective behavior, the resulting dose-response curve is linearized. In other words, the population is less sensitive than the individuals, which otherwise enhances the information transfer from signal to response. We found that the distance to the ideal linear response of the cell population is minimized for a particular noise level, and also characterized the interplay between intrinsic and extrinsic noise. Overall, our results highlight how cells could, by acting as a collective, entangle their genetic systems with their environments by adjusting the intracellular noise levels.
authors.affiliation: Instituto de Biología Molecular y Celular de Plantas, CSIC - UPV, 46022 Valencia, Spain.
authors.forename: Marzo
authors.initials: M
authors.lastname: Forment
authors.affiliation: Instituto de Biología Molecular y Celular de Plantas, CSIC - UPV, 46022 Valencia, Spain. Electronic address: guillermo.rodrigo@csic.es.
authors.forename: Guillermo
authors.initials: G
authors.lastname: Rodrigo
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D002999:Clone Cells / Q000166:cytology*; D005246:Feedback; D053263:Gene Regulatory Networks; D059647:Gene-Environment Interaction; D006801:Humans; D008954:Models, Biological; D008962:Models, Theoretical; D018401:Sample Size; D012680:Sensitivity and Specificity; D059010:Single-Cell Analysis
keywords: Gene Regulation; Response Linearization; Stochastic Dynamics; Systems Biology