Experimental and theoretical investigation of estrogen dependent transcription in single cells
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Abstract
Heterogeneous gene expression responses to external cues are essential for cellular decision making and environmental adaptation. Heterogeneity arises at each gene from random switching between transcriptionally active and inactive intervals, causing transcriptional bursting. Furthermore, the internal state of the cell influences gene expression leading to cell-to-cell variability in transcript copy numbers. We investigated how external stimuli interplay with the cellular state to modulate the kinetics of bursting.
To this end, we use reporter cell lines carrying multimerised PP7 RNA stem loops into the genome of estrogen sensitive MCF-7 breast cancer cells allowing to image transcription in single cells over time and under various experimental conditions. Utilizing a likelihood free bayesian algorithm we fitted stochastic models of varying complexity to transcription time course data. We found that small models stochastically switching between active and inactive states of transcription are sufficient to explain our experimental data. Moreover, the estrogen stimulus modulates the frequency of transcriptional bursting. Our model fitting indicated that the cellular state globally affects transcriptional dynamics by altering initiation and elongation kinetics.
Taken together, we propose a quantitative framework to characterize intrinsic and extrinsic variability of stimulus dependent gene transcription in single cells.