Abstract
BackgroundGene expression is an inherently stochastic process, owing to its dynamic molecular nature. Protein amount distributions, which can be acquired by cytometry using a reporter gene, can inform about the mechanisms of the underlying microscopic molecular system.ResultsBy using different clones of chicken erythroid progenitor cells harboring different integration sites of a CMV-driven mCherry protein, we investigated the dynamical behavior of such distributions. We show that, on short term, clone distributions can be quickly regenerated from small population samples with a high accuracy. On longer term, on the contrary, we show variations manifested by correlated fluctuation in the Mean Fluorescence Intensity. In search for a possible cause of this correlation, we demonstrate that in response to small temperature variations cells are able to adjust their gene expression rate: a modest (2 °C) increase in external temperature induces a significant down regulation of mean expression values, with a reverse effect observed when the temperature is decreased. Using a two-state model of gene expression we further demonstrate that temperature acts by modifying the size of transcription bursts, while the burst frequency of the investigated promoter is less systematically affected.ConclusionsFor the first time, we report that transcription burst size is a key parameter for gene expression that metazoan cells from homeotherm animals can modify in response to an external thermal stimulus.Electronic supplementary materialThe online version of this article (doi:10.1186/s12867-015-0048-2) contains supplementary material, which is available to authorized users.
Highlights
Gene expression is an inherently stochastic process, owing to its dynamic molecular nature
By fitting a two-state model on the fluorescence distributions measured under different temperature conditions, we demonstrated that this effect was related to a modification of the burst size, while their frequency was less systematically altered
The normalized variances were not significantly correlated (Fig. 2d, e). These results suggest that the mean fluorescence intensity (MFI) varies quite significantly during very long periods, whereas the NV value is more constant for a clone
Summary
Gene expression is an inherently stochastic process, owing to its dynamic molecular nature. In the classical “two-state model” [13, 14], a gene switches from a closed to an open state with constant rates Simplified, this description is relevant enough to allow reproducing many features of stochastic expression data, and to infer the underlying chromatin dynamics. It is able to describe the eukaryotic bursty transcription regime, where the gene is mostly closed and opens only for brief periods of times. This model is simple enough to be fitted on high-throughput data such as fluorescence distributions measured by cytometry.
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