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Expression stochastique des gènes chez Bacillus subtilis

Abstract : A population of genetically identical individuals sharing the same environment exhibits some residual phenotypic variability. Such heterogeneity arises from the stochastic, or random, nature of gene expression also referred as noise. This stochasticity results on the one hand from the random encounter of chemical species during both transcription and translation (intrinsic noise), and on the other hand from the fluctuations in the concentration of these chemicals (extrinsic noise). A stochastic model involving only intrinsic noise predicts that phenotypic noise strength varies linearly with translational efficiency but does not depend on transcriptional one. This prediction was shown to be compatible with data on a limited number of strains and conditions but has never been fully tested on a large collection of strains with different transcription and translation efficiencies. We aim to go further in the test of this prediction by using a collection of ~40 strains of the bacterium Bacillus subtilis where GFP is expressed under the control of different Promoters, TSS and RBS. For each strain, cell-to-cell heterogeneity is investigated by quantifying fluorescence signal at the single cell level, based on flow cytometry techniques and epifluorescence microscopy. Our results show that, contrary to expectations, phenotypic noise strength shows a strong positive correlation with transcriptional efficiency. We demonstrated that over a wide range of expression covering most of the proteome of B. subtilis, the expression noise is dominated by external noise sources. Therefore, stochastic models of gene expression are not suitable for quantifying the effects of translation and transcription on gene expression noise.
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Submitted on : Friday, August 28, 2020 - 3:49:46 PM
Last modification on : Thursday, September 3, 2020 - 11:29:31 AM


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  • HAL Id : tel-02924997, version 1


Alexandre Deloupy. Expression stochastique des gènes chez Bacillus subtilis. Biophysique []. Sorbonne Université, 2018. Français. ⟨NNT : 2018SORUS443⟩. ⟨tel-02924997⟩



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