4.6 Article

Time-resolved analysis of transcription kinetics in single live mammalian cells

期刊

FRONTIERS IN PHYSICS
卷 10, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fphy.2022.977125

关键词

transcription; live-cell imaging; single-cell analysis; transcription elongation; transcription termination

资金

  1. Creative-Pioneering Researchers Program through Seoul National University, Howard Hughes Medical Institute (HHMI)-Wellcome International Research Scholar Award from the Wellcome Trust [208468/Z/17/Z]
  2. Basic Science Research Program through the National Research Foundation of Korea (NRF) grant - Korean government [2020R1A2C2007285]
  3. Wellcome Trust [208468/Z/17/Z] Funding Source: Wellcome Trust
  4. National Research Foundation of Korea [2020R1A2C2007285] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

In this study, a new method was proposed to measure the kinetic rates of transcription in live cells, providing a better understanding of transcriptional regulation. By monitoring fluorescently labeled mRNA in time-lapse imaging data, the transcription rates of initiation, elongation, and termination steps were extracted and validated using a mathematical model. This method will be useful for studying the regulation mechanisms of elongation and termination steps in transcriptional processes.
In eukaryotic cells, RNA polymerase II synthesizes mRNA in three stages, initiation, elongation, and termination, and numerous factors determine how quickly a gene is transcribed to produce mRNA molecules through these steps. However, there are few techniques available to measure the rate of each step in living cells, which prevents a better understanding of transcriptional regulation. Here, we present a quantitative analysis method to extract kinetic rates of transcription from time-lapse imaging data of fluorescently labeled mRNA in live cells. Using embryonic fibroblasts cultured from two knock-in mouse models, we monitored transcription of beta-actin and Arc mRNA labeled with MS2 and PP7 stem-loop systems, respectively. After inhibiting transcription initiation, we measured the elongation rate and the termination time by fitting the time trace of transcription intensity with a mathematical model function. We validated our results by comparing them with those from an autocorrelation analysis and stochastic simulations. This live-cell transcription analysis method will be useful for studying the regulation of elongation and termination steps, providing insight into the diverse mechanisms of transcriptional processes.

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