Stochastic gene expression
Gene expression is inherently stochastic. How cells battle noise in gene expression in order to achieve robust growth and development has been the subject of intense studies. In the past decade, majority of studies focused on the intrinsic noise of gene expression, which are fluctuations caused by the intrinsic properties of biochemical reactions in gene expression at the low-copy number regime. To find out how cells repress intrinsic noise using autoregulatory transcription factors, we developed a single-molecule gene expression reporter to monitor the stochastic expression of a transcription factor and its autoregulatory actions. We discovered that intrinsic noise has negligible effect on the overall gene expression noise. Instead, extrinsic noise, or fluctuations caused by different compositions of cellular factors in different cells, dominates noise in gene expression. Consequently, cells use negative autoregulation to counteract extrinsic noise in order to achieve a homogenous gene expression level. We recently further developed a new strategy to monitor simultaneously the correlative expression dynamics of two transcription factors in live cells, both at the single molecule level. This ability has not been possible before. The new, dual single-molecule reporter system allowed her to uncover two new cell fate potentials that were hidden in a classic bistable switch, which is a common building block of gene regulatory networks, and traditionally is viewed as only capable of directing two mutually exclusive cell fates. We experimentally mapped the corresponding potential landscape and switching kinetics between four different gene expression states, offering first-of-its-kind insight of how cells could encode multiple cell fates even with a limited circuitry to allow a high degree of adaptation and differentiation. These new findings significantly advance our understanding of the operational principle of gene regulatory networks.
Publications
Fang X, Liu Q, Bohrer C, Hensel Z, Han W, Wang J, Xiao J. Cell fate potentials and switching kinetics uncovered in a classic bistable genetic switch. Nat Commun. 2018 Jul 17;9(1):2787
Feng H, Hensel Z, Xiao J, Wang J. Analytical calculation of protein production distributions in models of clustered protein expression. Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Mar;85(3 Pt 1):031904.
Hensel Z, Feng H, Han B, Hatem C, Wang J, Xiao J. Stochastic expression dynamics of a transcription factor revealed by single-molecule noise analysis. Nat Struct Mol Biol. 2012 Aug;19(8):797-802.