title: Determining the stability of genetic switches: explicitly accounting for mRNA noise.
abstract: Cells use genetic switches to shift between alternate gene-expression states, e.g., to adapt to new environments or to follow a developmental pathway. Here, we study the dynamics of switching in a generic-feedback on-off switch. Unlike protein-only models, we explicitly account for stochastic fluctuations of mRNA, which have a dramatic impact on switch dynamics. Employing the WKB theory to treat the underlying chemical master equations, we obtain accurate results for the quasistationary distributions of mRNA and protein copy numbers and for the mean switching time, starting from either state. Our analytical results agree well with Monte Carlo simulations. Importantly, one can use the approach to study the effect of varying biological parameters on switch stability.
authors.affiliation: Departments of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
authors.forename: Michael
authors.initials: M
authors.lastname: Assaf
authors.forename: Elijah
authors.initials: E
authors.lastname: Roberts
authors.forename: Zaida
authors.initials: Z
authors.lastname: Luthey-Schulten
mesh_terms: D003198:Computer Simulation; D025461:Feedback, Physiological; D005812:Genes, Switch / Q000235:genetics*; D008957:Models, Genetic; D009010:Monte Carlo Method; D011336:Probability; D011506:Proteins / Q000235:genetics / Q000378:metabolism; D012333:RNA, Messenger / Q000235:genetics* / Q000378:metabolism; D013997:Time Factors
chemical_list: D011506:Proteins; D012333:RNA, Messenger