Imperial College London
Portrait Picture

DrPhilippThomas

Faculty of Natural Sciences, Department of Mathematics

Senior Lecturer in Biomathematics
 
 
 
//

Contact

 

+44 (0)20 7594 2647p.thomas

 
 
//

Location

 

626Huxley BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Thomas:2014:10.1073/pnas.1400049111,
author = {Thomas, P and Popovic, N and Grima, R},
doi = {10.1073/pnas.1400049111},
journal = {Proceedings of the National Academy of Sciences of the United States of America},
pages = {6994--6999},
title = {Phenotypic switching in gene regulatory networks},
url = {http://dx.doi.org/10.1073/pnas.1400049111},
volume = {111},
year = {2014}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Noise in gene expression can lead to reversible phenotypic switching. Several experimental studies have shown that the abundance distributions of proteins in a population of isogenic cells may display multiple distinct maxima. Each of these maxima may be associated with a subpopulation of a particular phenotype, the quantification of which is important for understanding cellular decision-making. Here, we devise a methodology which allows us to quantify multimodal gene expression distributions and single-cell power spectra in gene regulatory networks. Extending the commonly used linear noise approximation, we rigorously show that, in the limit of slow promoter dynamics, these distributions can be systematically approximated as a mixture of Gaussian components in a wide class of networks. The resulting closed-form approximation provides a practical tool for studying complex nonlinear gene regulatory networks that have thus far been amenable only to stochastic simulation. We demonstrate the applicability of our approach in a number of genetic networks, uncovering previously unidentified dynamical characteristics associated with phenotypic switching. Specifically, we elucidate how the interplay of transcriptional and translational regulation can be exploited to control the multimodality of gene expression distributions in two-promoter networks. We demonstrate how phenotypic switching leads to birhythmical expression in a genetic oscillator, and to hysteresis in phenotypic induction, thus highlighting the ability of regulatory networks to retain memory.
AU  - Thomas,P
AU  - Popovic,N
AU  - Grima,R
DO  - 10.1073/pnas.1400049111
EP  - 6999
PY  - 2014///
SN  - 0027-8424
SP  - 6994
TI  - Phenotypic switching in gene regulatory networks
T2  - Proceedings of the National Academy of Sciences of the United States of America
UR  - http://dx.doi.org/10.1073/pnas.1400049111
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000335798000061&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - https://www.pnas.org/content/111/19/6994/
VL  - 111
ER  -
Download