title: Signatures of gene expression noise in cellular systems.
abstract: Noise in gene expression, either due to inherent stochasticity or to varying inter- and intracellular environment, can generate significant cell-to-cell variability of protein levels in clonal populations. To quantify the different sources of gene expression noise, several theoretical studies have been performed using either a quasi-stationary approximation for the emerging master equation or employing a time-dependent description, when cell division is taken explicitly into account. Here, we give an overview of the different origins of gene expression noise which were found experimentally and introduce the basic stochastic modeling approaches. We extend, and apply a time-dependent description of gene expression noise to experimental data. The analysis shows that the induction level of the transcription factor can be employed to discriminate the noise profiles and their characteristic signatures. On the basis of experimentally measured cell distributions, our simulations suggest that transcription factor binding and promoter activation can be modeled independently of each other with sufficient accuracy.
authors.affiliation: Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104 Freiburg, Germany. juhe@fdm.uni-freiburg.de
authors.forename: Julia
authors.initials: J
authors.lastname: Rausenberger
authors.forename: Christian
authors.initials: C
authors.lastname: Fleck
authors.forename: Jens
authors.initials: J
authors.lastname: Timmer
authors.forename: Markus
authors.initials: M
authors.lastname: Kollmann
mesh_terms: D000818:Animals; D002477:Cells / Q000378:metabolism*; D004926:Escherichia coli / Q000166:cytology / Q000235:genetics / Q000378:metabolism; D005786:Gene Expression Regulation; D006801:Humans; D008957:Models, Genetic; D013269:Stochastic Processes; D013997:Time Factors; D014157:Transcription Factors / Q000378:metabolism
chemical_list: D014157:Transcription Factors