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Abstract

Metabolism controls gene expression through allosteric interactions
between metabolites and transcription factors. These interactions are
usually measured with in vitro assays, but there are no methods to
identify them at a genome-scale in vivo. Here we show that dynamic
transcriptome and metabolome data identify metabolites that control
transcription factors in E. coli. By switching an E. coli culture
between starvation and growth, we induce strong metabolite concentration
changes and gene expression changes. Using Network Component Analysis we
calculate the activities of 209 transcriptional regulators and correlate
them with metabolites. This approach captures, for instance, the in vivo
kinetics of CRP regulation by cyclic-AMP. By testing correlations
between all pairs of transcription factors and metabolites, we predict
putative effectors of 71 transcription factors, and validate five
interactions in vitro. These results show that combining transcriptomics
and metabolomics generates hypotheses about metabolism-transcription
interactions that drive transitions between physiological states.