Gene expression is controlled by the joint effect of (i) the global physiological state of the cell, in particular the activity of the gene expression machinery, and (ii) DNA-binding transcription factors and other specific regulators. We present a model-based approach to distinguish between these two effects using time-resolved measurements of promoter activities. We demonstrate the strength of the approach by analyzing a circuit involved in the regulation of carbon metabolism in E. coli. Our results show that the transcriptional response of the network is controlled by the physiological state of the cell and the signaling metabolite cyclic AMP (cAMP). The absence of a strong regulatory effect of transcription factors suggests that they ar...
International audienceThe inference of regulatory interactions and quantitative models of gene regul...
In bacterial adaptation to the dynamic environment, metabolic genes are typically thought to be the ...
International audienceThe inference of regulatory interactions and quantitative models of gene regul...
International audienceGene expression is controlled by the joint effect of (i) the global physiologi...
International audienceGene expression is controlled by the joint effect of (i) the global physiologi...
Transcription networks consist of hundreds of transcription factors with thousands of often overlapp...
Metabolism controls gene expression through allosteric interactions between metabolites and transcri...
Gene expression is regulated by specific transcriptional circuits but also by the global expression ...
Gene expression is regulated by specific transcriptional circuits but also by the global expression ...
Gene expression is regulated by specific transcriptional circuits but also by the global expression ...
<div><p>The inference of regulatory interactions and quantitative models of gene regulation from tim...
Cells adjust gene expression profiles in response to environmental and physiological changes through...
Cells adjust gene expression profiles in response to environmental and physiological changes through...
International audienceGene regulatory networks consist of direct interactions, but also include indi...
In bacterial adaptation to the dynamic environment, metabolic genes are typically thought to be the ...
International audienceThe inference of regulatory interactions and quantitative models of gene regul...
In bacterial adaptation to the dynamic environment, metabolic genes are typically thought to be the ...
International audienceThe inference of regulatory interactions and quantitative models of gene regul...
International audienceGene expression is controlled by the joint effect of (i) the global physiologi...
International audienceGene expression is controlled by the joint effect of (i) the global physiologi...
Transcription networks consist of hundreds of transcription factors with thousands of often overlapp...
Metabolism controls gene expression through allosteric interactions between metabolites and transcri...
Gene expression is regulated by specific transcriptional circuits but also by the global expression ...
Gene expression is regulated by specific transcriptional circuits but also by the global expression ...
Gene expression is regulated by specific transcriptional circuits but also by the global expression ...
<div><p>The inference of regulatory interactions and quantitative models of gene regulation from tim...
Cells adjust gene expression profiles in response to environmental and physiological changes through...
Cells adjust gene expression profiles in response to environmental and physiological changes through...
International audienceGene regulatory networks consist of direct interactions, but also include indi...
In bacterial adaptation to the dynamic environment, metabolic genes are typically thought to be the ...
International audienceThe inference of regulatory interactions and quantitative models of gene regul...
In bacterial adaptation to the dynamic environment, metabolic genes are typically thought to be the ...
International audienceThe inference of regulatory interactions and quantitative models of gene regul...