Abstract
Single-cell measurements of mRNA copy numbers inform our understanding of stochastic gene expression, but these measurements coarse-grain over the individual copies of the gene, where transcription and its regulation take place stochastically. We recently combined single-molecule quantification of mRNA and gene loci to measure the transcriptional activity of an endogenous gene in individual Escherichia coli bacteria. When interpreted using a theoretical model for mRNA dynamics, the single-cell data allowed us to obtain the probabilistic rates of promoter switching, transcription initiation and elongation, mRNA release and degradation. Unexpectedly, we found that gene activity is strongly coupled to the transcriptional state of another copy of the same gene present in the cell, and to the progression of the bacterial cell cycle. These gene-copy and cell-cycle correlations demonstrate the limits of mapping whole-cell mRNA numbers to the underlying stochastic gene activity and highlight the contribution of previously hidden variables to the observed population heterogeneity.
Event Details
Date/Time:
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Date:Thursday, May 12, 2022 - 10:00am to 11:00am
Location:
https://gatech.zoom.us/j/97880808617?pwd=Ry9FaGR2Tm1qS2hIbzlxWlFmdnl6QT09 Marcus Nanotechnology Blg. 1116 -1118
For More Information Contact
Prof. JC Gumbart