Homeostasis of the biosynthetic E. coli metabolome.

Metabolite concentrations vary across conditions and such metabolome changes are relevant for metabolic and gene regulation. Here, we used LC-MS/MS to explore metabolite concentration changes in Escherichia coli. We measured 101 primary metabolites in 19 experimental conditions that include various nutrients and stresses. Many metabolites showed little variation across conditions and only few metabolites correlated with the growth rate. The least varying metabolites were nucleotides (e.g. UTP had 10% variation) and amino acids (e.g. methionine had 13% variation). These results show that E. coli maintains protein and RNA building blocks within narrow concentration ranges, thus indicating that many feedback mechanisms in biosynthetic pathways contribute to end-product homeostasis.

Spatial alanine metabolism determines local growth dynamics of Escherichia coli colonies.

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.

Metabolome and proteome analyses reveal transcriptional misregulation in glycolysis of engineered E. coli.

Synthetic metabolic pathways are a burden for engineered bacteria, but the underlying mechanisms often remain elusive. Here we show that the misregulated activity of the transcription factor Cra is responsible for the growth burden of glycerol overproducing E. coli. Glycerol production decreases the concentration of fructose-1,6-bisphoshate (FBP), which then activates Cra resulting in the downregulation of glycolytic enzymes and upregulation of gluconeogenesis enzymes. Because cells grow on glucose, the improper activation of gluconeogenesis and the concomitant inhibition of glycolysis likely impairs growth at higher induction of the glycerol pathway. We solve this misregulation by engineering a Cra-binding site in the promoter controlling the expression of the rate limiting enzyme of the glycerol pathway to maintain FBP levels sufficiently high. We show the broad applicability of this approach by engineering Cra-dependent regulation into a set of constitutive and inducible promoters, and use one of them to overproduce carotenoids in E. coli.

Metabolism of non-growing bacteria.

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.

High-throughput enrichment of temperature-sensitive argininosuccinate synthetase for two-stage citrulline production in E. coli.

Controlling metabolism of engineered microbes is important to modulate cell growth and production during a bioprocess. For example, external parameters such as light, chemical inducers, or temperature can act on metabolism of production strains by changing the abundance or activity of enzymes. Here, we created temperature-sensitive variants of an essential enzyme in arginine biosynthesis of Escherichia coli (argininosuccinate synthetase, ArgG) and used them to dynamically control citrulline overproduction and growth of E. coli. We show a method for high-throughput enrichment of temperature-sensitive ArgG variants with a fluorescent TIMER protein and flow cytometry. With 90 of the thus derived ArgG variants, we complemented an ArgG deletion strain showing that 90% of the strains exhibit temperature-sensitive growth and 69% of the strains are auxotrophic for arginine at 42 °C and prototrophic at 30 °C. The best temperature-sensitive ArgG variant enabled precise and tunable control of cell growth by temperature changes. Expressing this variant in a feedback-dysregulated E. coli strain allowed us to realize a two-stage bioprocess: a 33 °C growth-phase for biomass accumulation and a 39 °C stationary-phase for citrulline production. With this two-stage strategy, we produced 3 g/L citrulline during 45 h cultivation in a 1-L bioreactor. These results show that temperature-sensitive enzymes can be created en masse and that they may function as metabolic valves in engineered bacteria.

Breakdown of Vibrio cholerae biofilm architecture induced by antibiotics disrupts community barrier function.

Bacterial cells in nature are frequently exposed to changes in their chemical environment1,2. The response mechanisms of isolated cells to such stimuli have been investigated in great detail. By contrast, little is known about the emergent multicellular responses to environmental changes, such as antibiotic exposure3-7, which may hold the key to understanding the structure and functions of the most common type of bacterial communities: biofilms. Here, by monitoring all individual cells in Vibrio cholerae biofilms during exposure to antibiotics that are commonly administered for cholera infections, we found that translational inhibitors cause strong effects on cell size and shape, as well as biofilm architectural properties. We identified that single-cell-level responses result from the metabolic consequences of inhibition of protein synthesis and that the community-level responses result from an interplay of matrix composition, matrix dissociation and mechanical interactions between cells. We further observed that the antibiotic-induced changes in biofilm architecture have substantial effects on biofilm population dynamics and community assembly by enabling invasion of biofilms by bacteriophages and intruder cells of different species. These mechanistic causes and ecological consequences of biofilm exposure to antibiotics are an important step towards understanding collective bacterial responses to environmental changes, with implications for the effects of antimicrobial therapy on the ecological succession of biofilm communities.

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

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.