Measurement of gene regulation in individual cells reveals rapid switching between promoter states

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Science  11 Mar 2016:
Vol. 351, Issue 6278, pp. 1218-1222
DOI: 10.1126/science.aad0635

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Stochastic properties of phage promoter

Full understanding of regulated gene expression requires characterization of stochastic variation in the activity of individual promoters. To avoid cell-to-cell variability and variation between the activity of specific gene copies, Sepúlveda et al. investigated the behavior of the lysogeny maintenance promoter of phage lambda in individual Escherichia coli cells. They measured the concentration of transcription factor and the actual number of mRNAs produced, and used mathematical modeling to discern the stochastic activity of the regulated promoter. The promoter underwent switching between configurations that occurred more rapidly than the lifetime of mRNA molecules produced, and individual copies of the same gene functioned independently in the same cell. Such studies can reveal new aspects of systems that have been well studied by more conventional techniques.

Science, this issue p. 1218


In vivo mapping of transcription-factor binding to the transcriptional output of the regulated gene is hindered by probabilistic promoter occupancy, the presence of multiple gene copies, and cell-to-cell variability. We demonstrate how to overcome these obstacles in the lysogeny maintenance promoter of bacteriophage lambda, PRM. We simultaneously measured the concentration of the lambda repressor CI and the number of messenger RNAs (mRNAs) from PRM in individual Escherichia coli cells, and used a theoretical model to identify the stochastic activity corresponding to different CI binding configurations. We found that switching between promoter configurations is faster than mRNA lifetime and that individual gene copies within the same cell act independently. The simultaneous quantification of transcription factor and promoter activity, followed by stochastic theoretical analysis, provides a tool that can be applied to other genetic circuits.

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