Making sense of snapshot data: ergodic principle for clonal cell populations

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Title: Making sense of snapshot data: ergodic principle for clonal cell populations
Authors: Thomas, P
Item Type: Journal Article
Abstract: Population growth is often ignored when quantifying gene expression levels across clonal cell populations. We develop a framework for obtaining the molecule number distributions in an exponentially growing cell population taking into account its age structure. In the presence of generation time variability, the average acquired across a population snapshot does not obey the average of a dividing cell over time, apparently contradicting ergodicity between single cells and the population. Instead, we show that the variation observed across snapshots with known cell age is captured by cell histories, a single-cell measure obtained from tracking an arbitrary cell of the population back to the ancestor from which it originated. The correspondence between cells of known age in a population with their histories represents an ergodic principle that provides a new interpretation of population snapshot data. We illustrate the principle using analytical solutions of stochastic gene expression models in cell populations with arbitrary generation time distributions. We further elucidate that the principle breaks down for biochemical reactions that are under selection, such as the expression of genes conveying antibiotic resistance, which gives rise to an experimental criterion with which to probe selection on gene expression fluctuations.
Issue Date: 29-Nov-2017
Date of Acceptance: 30-Oct-2017
ISSN: 1742-5662
Publisher: Royal Society, The
Journal / Book Title: Journal of the Royal Society Interface
Volume: 14
Copyright Statement: © 2017 The Author(s). Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Royal Commission for the Exhibition of 1851
Funder's Grant Number: EP/N014529/1
Keywords: population dynamics
population snapshots
stochastic gene expression
MD Multidisciplinary
General Science & Technology
Publication Status: Published
Article Number: 20170467
Appears in Collections:Mathematics
Applied Mathematics and Mathematical Physics
Faculty of Natural Sciences

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