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.

Bacterial cells in nature are frequently exposed to changes in their chemical environment 1,2. For such stimuli, the response mechanisms of isolated cells have been investigated in great detail. By contrast, little is known about the emergent multicellular responses to environmental changes, such as antibiotic exposure 3-7 , which may hold the key to understanding the structure and functions of the most common bacterial communities: biofilms. Here, by monitoring all individual cells in Vibrio cholerae biofilms during exposure to commonly administered antibiotics for cholera infections, we discovered that translational inhibitors cause strong effects on cell size and shape, Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:

Bacteria commonly live in spatially structured biofilm assemblages, which are encased by an extracellular matrix. Metabolic activity of the cells inside biofilms causes gradients in local environmental conditions, which leads to the emergence of physiologically differentiated subpopulations. Information about the properties and spatial arrangement of such metabolic subpopulations, as well as their interaction strength and interaction length scales are lacking, even for model systems like Escherichia coli colony biofilms grown on agar-solidified media. Here, we use an unbiased approach, based on temporal and spatial transcriptome and metabolome data acquired during E. coli colony biofilm growth, to study the spatial organization of metabolism. We discovered that alanine displays a unique pattern among amino acids and that alanine metabolism is spatially and temporally heterogeneous. At the anoxic base of the colony, where carbon and nitrogen sources are abundant, cells secrete alanine via the transporter AlaE. In contrast, cells utilize alanine as a carbon and nitrogen source in the oxic nutrient-deprived region at the colony mid-height, via the enzymes DadA and DadX. This spatially structured alanine cross-feeding influences cellular viability and growth in the cross-feeding-dependent region, which shapes the overall colony morphology. More generally, our results on this precisely controllable biofilm model system demonstrate a remarkable spatiotemporal complexity of metabolism in biofilms. A better characterization of the spatiotemporal metabolic heterogeneities and dependencies is essential for understanding the physiology, architecture, and function of biofilms.

A main function of bacterial metabolism is to supply biomass building blocks and energy for growth. This seems to imply that metabolism is idle in non-growing bacteria. But how relevant is metabolism for the physiology of non-growing bacteria and how active is their metabolism? Here, we reviewed literature describing metabolism of non-growing bacteria in their natural environment, as well as in biotechnological and medical applications. We found that metabolism does play an important role during dormancy and that especially the demand for ATP determines metabolic activity of non-growing bacteria.