Dataset Information

Systematic identification of metabolites controlling gene expression in E. coli

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.

INSTRUMENT(S): Liquid Chromatography MS - Alternating (LC-MS (Alternating))

SUBMITTER: Hannes Link

PROVIDER: MTBLS1044 | MetaboLights | 2019-08-23

REPOSITORIES: MetaboLights

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Systematic identification of metabolites controlling gene expression in E. coli.

Lempp Martin M Farke Niklas N Kuntz Michelle M Freibert Sven Andreas SA Lill Roland R Link Hannes H

Nature communications 20191002 1

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 expr ...[more]

PMID: 31578326

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Project description:Guanosine 3 ,5 -bispyrophosphate (ppGpp), also known as ‘‘magic spot,’’ has been shown to bind prokaryotic RNA polymerase to down-regulate ribosome production and increase transcription of amino acid biosynthesis genes during the stringent response to amino acid starvation. Because many environmental growth perturbations cause ppGpp to accumulate, we hypothesize ppGpp to have an overarching role in regulating the genetic program that coordinates transitions between logarithmic growth (feast) and growth arrest (famine). We used the classic glucose-lactose diauxie as an experimental system to investigate the temporal changes in transcription that accompany growth arrest and recovery in wildtype Escherichia coli and in mutants that lack RelA (ppGpp synthetase) and other global regulators, i.e., RpoS and Crp. When cultured on a mixture of glucose and lactose, E. coli grows preferentially on glucose until it is exhausted, resulting in growth arrest while the cells adjust to growth on lactose, i.e., diauxie. Diauxie was delayed in the relA mutant and was accompanied by a 15% decrease in the number of carbon sources used and a 3-fold overall decrease in the induction of RpoS and Crp regulon genes. Thus the data significantly expand the previously known role of ppGpp and support a model wherein the ppGpp-dependent redistribution of RNA polymerase across the genome is the driving force behind control of the stringent response, general stress response, and starvation-induced carbon scavenging. Our conceptual model of diauxie describes these global control circuits as dynamic, interconnected, and dependent upon ppGpp for the efficient temporal coordination of gene expression that programs the cell for transitions between feast and famine. E. coli MG1655 and isogenic mutants were cultured in a 2 l Biostat B fermentor (B. Braun Biotech International) containing 1 liter of Morpholinepropanesulfonic acid (MOPS) minimal medium with 0.5 g/l of glucose and 1.5 g/l of lactose. The temperature was maintained at 37 ºC and pH was kept constant at 7.2 by the addition of 2 M NaOH. The dissolved oxygen level was maintained above 20% of saturation by adjusting the agitation speeds in the range of 270-500 rpm with fixed 1 l/min air flow.

			Action	DRS
	MTBLS1044	Other
	FILES	Other
	a_MTBLS1044_BEH_mass_spectrometry.txt	Txt
	a_MTBLS1044_iHILIC_mass_spectrometry.txt	Txt
	i_Investigation.txt	Txt