Beyond fuelling cellular activities with building blocks and energy, metabolism also integrates environmental conditions into intracellular signals. The underlying regulatory network is complex and multifaceted: it ranges from slow interactions, such as changing gene expression, to rapid ones, such as the modulation of protein activity via post-translational modification or the allosteric binding of small molecules. In this Review, we outline the coordination of common metabolic tasks, including nutrient uptake, central metabolism, the generation of energy, the supply of amino acids and protein synthesis. Increasingly, a set of key metabolites is recognized to control individual regulatory circuits, which carry out specific functions of information input and regulatory output. Such a modular view of microbial metabolism facilitates an intuitive understanding of the molecular mechanisms that underlie cellular decision making.

Highlights d Developed 13 C-infusion method for studying T cell metabolism in vivo d T cell glucose use and bioenergetics differ between cell culture and mouse models d Glucose metabolism in T cells changes dynamically over an immune response d Glucose-dependent serine biosynthesis supports T cell proliferation in vivo

Upon activation, macrophages undergo extensive metabolic rewiring 1 , 2 . Production of itaconate through the inducible enzyme IRG1 is a key hallmark of this process 3 . Itaconate inhibits succinate dehydrogenase (SDH) 4 , 5 , has electrophilic properties 6 , and is associated with a change in cytokine production 4 . Here, we compare the metabolic, electrophilic, and immunologic profiles of macrophages treated with unmodified itaconate and a panel of commonly used itaconate derivatives to examine its role. Using wild type and Irg1 −/− macrophages, we show that neither dimethyl itaconate (DI), 4-octyl itaconate (4OI), nor 4-monoethyl itaconate (4EI) are converted into intracellular itaconate, while exogenous itaconic acid readily enters macrophages. We find that only DI and 4OI induce a strong electrophilic stress response, in contrast to itaconate and 4EI. This correlates with their immunosuppressive phenotype: DI and 4OI inhibit IκBζ and pro-IL-1β induction, as well as IL-6, IL-10, and IFN-β secretion in an Nrf2-independent manner. In contrast, itaconate treatment only suppressed IL-1β secretion but not pro-IL-1β levels, and, surprisingly, strongly enhanced LPS-induced IFN-β secretion. Consistently, Irg1 −/− macrophages produced lower levels of interferon and reduced transcriptional activation of this pathway. Our work establishes itaconate as an immunoregulatory, rather than strictly immunosuppressive metabolite, and highlights the importance of using unmodified itaconate in future studies.

Regulation of enzyme expression is one key mechanism by which cells control their metabolic programs. In this work, a quantitative analysis of metabolism in a model bacterium under different conditions shows that expression alone cannot explain the majority of the observed metabolic changes.

Predicting resource allocation between cell processes is the primary step towards decoding the evolutionary constraints governing bacterial growth under various conditions. Quantitative prediction at genome-scale remains a computational challenge as current methods are limited by the tractability of the problem or by simplifying hypotheses. Here, we show that the constraint-based modeling method Resource Balance Analysis (RBA), calibrated using genome-wide absolute protein quantification data, accurately predicts resource allocation in the model bacterium Bacillus subtilis for a wide range of growth conditions. The regulation of most cellular processes is consistent with the objective of growth rate maximization except for a few suboptimal processes which likely integrate more complex objectives such as coping with stressful conditions and survival. As a proof of principle by using simulations, we illustrated how calibrated RBA could aid rational design of strains for maximizing protein production, offering new opportunities to investigate design principles in prokaryotes and to exploit them for biotechnological applications.