Stochastic expression dynamics of a transcription factor revealed by single-molecule noise analysis

• Published in: Nature structural & molecular biology Vol. 19; no. 8; pp. 797 - 802
• Main Authors: Hensel, Zach, Feng, Haidong, Han, Bo, Hatem, Christine, Wang, Jin, Xiao, Jie
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.08.2012; Nature Publishing Group
• Subjects: 631/1647/1513; 631/208/200; 631/337/572; 631/45/612/822; Bacteriophage lambda - genetics; Bacteriophage lambda - metabolism; Biochemistry; Biological Microscopy; Biomedical and Life Sciences; Escherichia coli K12 - virology; Fluctuations; Gene Expression; Genes, Viral; Genetic aspects; Heterogeneity; Homeostasis; Life Sciences; Membrane Biology; Models, Biological; Molecular genetics; Molecules; Noise; Physiological aspects; Protein Biosynthesis; Protein Structure; Quantitative research; Recombinant Fusion Proteins - genetics; Recombinant Fusion Proteins - metabolism; Repressor Proteins - genetics; Repressor Proteins - metabolism; Stochastic analysis; Stochastic models; Stochastic Processes; Transcription factors; Transcription Factors - genetics; Transcription Factors - metabolism; Viral Regulatory and Accessory Proteins - genetics; Viral Regulatory and Accessory Proteins - metabolism; United States
• ISSN: 1545-9993; 1545-9985
• DOI: 10.1038/nsmb.2336

How intrinsic stochasticity of gene expression is controlled is not well understood. A quantitative single-molecule analysis of transcription factor expression dynamics based on a new strategy (cotranslational activation by cleavage, or CoTrAC), sheds light on the mechanisms that cells use to control noise in gene regulatory networks. Gene expression is inherently stochastic; precise gene regulation by transcription factors is important for cell-fate determination. Many transcription factors regulate their own expression, suggesting that autoregulation counters intrinsic stochasticity in gene expression. Using a new strategy, cotranslational activation by cleavage (CoTrAC), we probed the stochastic expression dynamics of cI , which encodes the bacteriophage λ repressor CI, a fate-determining transcription factor. CI concentration fluctuations influence both lysogenic stability and induction of bacteriophage λ. We found that the intrinsic stochasticity in cI expression was largely determined by CI expression level irrespective of autoregulation. Furthermore, extrinsic, cell-to-cell variation was primarily responsible for CI concentration fluctuations, and negative autoregulation minimized CI concentration heterogeneity by counteracting extrinsic noise and introducing memory. This quantitative study of transcription factor expression dynamics sheds light on the mechanisms cells use to control noise in gene regulatory networks.