title: What Population Reveals about Individual Cell Identity: Single-Cell Parameter Estimation of Models of Gene Expression in Yeast.
abstract: Significant cell-to-cell heterogeneity is ubiquitously observed in isogenic cell populations. Consequently, parameters of models of intracellular processes, usually fitted to population-averaged data, should rather be fitted to individual cells to obtain a population of models of similar but non-identical individuals. Here, we propose a quantitative modeling framework that attributes specific parameter values to single cells for a standard model of gene expression. We combine high quality single-cell measurements of the response of yeast cells to repeated hyperosmotic shocks and state-of-the-art statistical inference approaches for mixed-effects models to infer multidimensional parameter distributions describing the population, and then derive specific parameters for individual cells. The analysis of single-cell parameters shows that single-cell identity (e.g. gene expression dynamics, cell size, growth rate, mother-daughter relationships) is, at least partially, captured by the parameter values of gene expression models (e.g. rates of transcription, translation and degradation). Our approach shows how to use the rich information contained into longitudinal single-cell data to infer parameters that can faithfully represent single-cell identity.
authors: Inria Saclay - Ile-de-France, Palaiseau, France.|Laboratoire Matière et Systèmes Complexes, UMR 7057, Université Paris Diderot & CNRS, Paris, France.
authors: Artémis
authors: A
authors: Llamosi
authors: Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Pavia, Italy.
authors: Andres M
authors: AM
authors: Gonzalez-Vargas
authors: Laboratoire d'Informatique Fondamentale de Lille, UMR 8022, Université de Lille 1 & CNRS, Villeneuve d'Ascq Cedex, France.
authors: Cristian
authors: C
authors: Versari
authors: INRIA Grenoble - Rhône-Alpes, Montbonnot, France.
authors: Eugenio
authors: E
authors: Cinquemani
authors: Dipartimento di Ingegneria Industriale e dell'Informazione, Università degli Studi di Pavia, Pavia, Italy.
authors: Giancarlo
authors: G
authors: Ferrari-Trecate
authors: Laboratoire Matière et Systèmes Complexes, UMR 7057, Université Paris Diderot & CNRS, Paris, France.
authors: Pascal
authors: P
authors: Hersen
authors: Inria Saclay - Ile-de-France, Palaiseau, France.
authors: Gregory
authors: G
authors: Batt
mesh_terms: D019295:Computational Biology; D015870:Gene Expression / Q000235:genetics / Q000502:physiology*; D046210:Microfluidic Analytical Techniques; D008954:Models, Biological; D012441:Saccharomyces cerevisiae / Q000166:cytology* / Q000235:genetics / Q000378:metabolism / Q000502:physiology*; D059010:Single-Cell Analysis