Greedy reduction of Bacillus subtilis genome yields emergent phenotypes of high resistance to a DNA damaging agent and low evolvability.

Genome-scale engineering enables rational removal of dispensable genes in chassis genomes. Deviating from this approach, we applied greedy accumulation of deletions of large dispensable regions in the Bacillus subtilis genome, yielding a library of 298 strains with genomes reduced up to 1.48 Mb in size. High-throughput physiological phenotyping of these strains confirmed that genome reduction is associated with substantial loss of cell fitness and accumulation of synthetic-sick interactions. Transcriptome analysis indicated that <15% of the genes conserved in our genome-reduced strains exhibited a twofold or higher differential expression and revealed a thiol-oxidative stress response. Most transcriptional changes can be explained by loss of known functions and by aberrant transcription at deletion boundaries. Genome-reduced strains exhibited striking new phenotypes relative to wild type, including a very high resistance (increased >300-fold) to the DNA-damaging agent mitomycin C and a very low spontaneous mutagenesis (reduced 100-fold). Adaptive laboratory evolution failed to restore cell fitness, except when coupled with a synthetic increase of the mutation rate, confirming low evolvability. Although mechanisms underlying this emergent phenotype are not understood, we propose that low evolvability can be leveraged in an engineering strategy coupling reductive cycles with evolutive cycles under induced mutagenesis.

Itaconate confers tolerance to late NLRP3 inflammasome activation.

Itaconate is a unique regulatory metabolite that is induced upon Toll-like receptor (TLR) stimulation in myeloid cells. Here, we demonstrate major inflammatory tolerance and cell death phenotypes associated with itaconate production in activated macrophages. We show that endogenous itaconate is a key regulator of the signal 2 of NLR family pyrin domain containing 3 (NLRP3) inflammasome activation after long lipopolysaccharide (LPS) priming, which establishes tolerance to late NLRP3 inflammasome activation. We show that itaconate acts synergistically with inducible nitric oxide synthase (iNOS) and that the ability of various TLR ligands to establish NLRP3 inflammasome tolerance depends on the pattern of co-expression of IRG1 and iNOS. Mechanistically, itaconate accumulation upon prolonged inflammatory stimulation prevents full caspase-1 activation and processing of gasdermin D, which we demonstrate to be post-translationally modified by endogenous itaconate. Altogether, our data demonstrate that metabolic rewiring in inflammatory macrophages establishes tolerance to NLRP3 inflammasome activation that, if uncontrolled, can result in pyroptotic cell death and tissue damage.

AG-348 (Mitapivat), an allosteric activator of red blood cell pyruvate kinase, increases enzymatic activity, protein stability, and ATP levels over a broad range of PKLR genotypes.

Pyruvate kinase (PK) deficiency is a rare hereditary disorder affecting red cell (RBC) glycolysis, causing changes in metabolism including a deficiency in ATP. This affects red cell homeostasis, promoting premature removal of RBCs from the circulation. In this study we characterized and evaluated the effect of AG-348, an allosteric activator of PK that is currently in clinical trials for treatment of PK deficiency, on RBCs and erythroid precursors from PK-deficient patients. In 15 patients ex vivo treatment with AG-348 resulted in increased enzymatic activity in all patient cells after 24 hours (mean increase 1.8-fold, range 1.2-3.4). ATP levels increased (mean increase 1.5-fold, range 1.0-2.2) similar to control cells (mean increase 1.6-fold, range, 1.4-1.8). Generally, PK thermostability was strongly reduced in PK-deficient RBCs. Ex vivo treatment with AG-348 increased residual activity 1.4 to >10-fold than residual activity of vehicle-treated samples. Protein analyses suggests that a sufficient level of PK protein is required for cells to respond to AG-348 treatment ex-vivo, as treatment effects were minimal in patient cells with very low or undetectable levels of PK-R. In half of the patients, ex vivo treatment with AG-348 was associated with an increase in RBC deformability. These data support the hypothesis that drug intervention with AG-348 effectively upregulates PK enzymatic activity and increases stability in PK-deficient RBCs over a broad range of PKLR genotypes. The concomitant increase in ATP levels suggests that glycolytic pathway activity may be restored. AG-348 treatment may represent an attractive way to correct the underlying pathologies of PK deficiency. (AG-348 is currently in clinical trials for the treatment of PK deficiency. ClinicalTrials.gov: NCT02476916, NCT03853798, NCT03548220, NCT03559699).

Selective Vulnerability to Pyrimidine Starvation in Hematologic Malignancies Revealed by AG-636, a Novel Clinical-Stage Inhibitor of Dihydroorotate Dehydrogenase.

Agents targeting metabolic pathways form the backbone of standard oncology treatments, though a better understanding of differential metabolic dependencies could instruct more rationale-based therapeutic approaches. We performed a chemical biology screen that revealed a strong enrichment in sensitivity to a novel dihydroorotate dehydrogenase (DHODH) inhibitor, AG-636, in cancer cell lines of hematologic versus solid tumor origin. Differential AG-636 activity translated to the in vivo setting, with complete tumor regression observed in a lymphoma model. Dissection of the relationship between uridine availability and response to AG-636 revealed a divergent ability of lymphoma and solid tumor cell lines to survive and grow in the setting of depleted extracellular uridine and DHODH inhibition. Metabolic characterization paired with unbiased functional genomic and proteomic screens pointed to adaptive mechanisms to cope with nucleotide stress as contributing to response to AG-636. These findings support targeting of DHODH in lymphoma and other hematologic malignancies and suggest combination strategies aimed at interfering with DNA-damage response pathways.

Comparative evaluation of itaconate and its derivatives reveals divergent inflammasome and type I interferon regulation in macrophages.

Following activation, macrophages undergo extensive metabolic rewiring1,2. Production of itaconate through the inducible enzyme IRG1 is a key hallmark of this process3. Itaconate inhibits succinate dehydrogenase4,5, has electrophilic properties6 and is associated with a change in cytokine production4. 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, 4-octyl itaconate nor 4-monoethyl itaconate are converted to intracellular itaconate, while exogenous itaconic acid readily enters macrophages. We find that only dimethyl itaconate and 4-octyl itaconate induce a strong electrophilic stress response, in contrast to itaconate and 4-monoethyl itaconate. This correlates with their immunosuppressive phenotype: dimethyl itaconate and 4-octyl itaconate inhibited IκBζ and pro-interleukin (IL)-1ß induction, as well as IL-6, IL-10 and interferon-ß secretion, in an NRF2-independent manner. In contrast, itaconate treatment suppressed IL-1ß secretion but not pro-IL-1ß levels and, surprisingly, strongly enhanced lipopolysaccharide-induced interferon-ß 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.

Methionine Metabolism Shapes T Helper Cell Responses through Regulation of Epigenetic Reprogramming.

Epigenetic modifications on DNA and histones regulate gene expression by modulating chromatin accessibility to transcription machinery. Here we identify methionine as a key nutrient affecting epigenetic reprogramming in CD4+ T helper (Th) cells. Using metabolomics, we showed that methionine is rapidly taken up by activated T cells and serves as the major substrate for biosynthesis of the universal methyl donor S-adenosyl-L-methionine (SAM). Methionine was required to maintain intracellular SAM pools in T cells. Methionine restriction reduced histone H3K4 methylation (H3K4me3) at the promoter regions of key genes involved in Th17 cell proliferation and cytokine production. Applied to the mouse model of multiple sclerosis (experimental autoimmune encephalomyelitis), dietary methionine restriction reduced the expansion of pathogenic Th17 cells in vivo, leading to reduced T cell-mediated neuroinflammation and disease onset. Our data identify methionine as a key nutritional factor shaping Th cell proliferation and function in part through regulation of histone methylation.

Metabolic Profiling Using Stable Isotope Tracing Reveals Distinct Patterns of Glucose Utilization by Physiologically Activated CD8+ T Cells.

Naive CD8+ T cells differentiating into effector T cells increase glucose uptake and shift from quiescent to anabolic metabolism. Although much is known about the metabolism of cultured T cells, how T cells use nutrients during immune responses in vivo is less well defined. Here, we combined bioenergetic profiling and 13C-glucose infusion techniques to investigate the metabolism of CD8+ T cells responding to Listeria infection. In contrast to in vitro-activated T cells, which display hallmarks of Warburg metabolism, physiologically activated CD8+ T cells displayed greater rates of oxidative metabolism, higher bioenergetic capacity, differential use of pyruvate, and prominent flow of 13C-glucose carbon to anabolic pathways, including nucleotide and serine biosynthesis. Glucose-dependent serine biosynthesis mediated by the enzyme Phgdh was essential for CD8+ T cell expansion in vivo. Our data highlight fundamental differences in glucose use by pathogen-specific T cells in vivo, illustrating the impact of environment on T cell metabolic phenotypes.

A chemical biology screen identifies a vulnerability of neuroendocrine cancer cells to SQLE inhibition.

Aberrant metabolism of cancer cells is well appreciated, but the identification of cancer subsets with specific metabolic vulnerabilities remains challenging. We conducted a chemical biology screen and identified a subset of neuroendocrine tumors displaying a striking pattern of sensitivity to inhibition of the cholesterol biosynthetic pathway enzyme squalene epoxidase (SQLE). Using a variety of orthogonal approaches, we demonstrate that sensitivity to SQLE inhibition results not from cholesterol biosynthesis pathway inhibition, but rather surprisingly from the specific and toxic accumulation of the SQLE substrate, squalene. These findings highlight SQLE as a potential therapeutic target in a subset of neuroendocrine tumors, particularly small cell lung cancers.

Improving membrane protein expression and function using genomic edits.

Expression of membrane proteins often leads to growth inhibition and perturbs central metabolism and this burden varies with the protein being overexpressed. There are also known strain backgrounds that allow greater expression of membrane proteins but that differ in efficacy across proteins. We hypothesized that for any membrane protein, it may be possible to identify a modified strain background where its expression can be accommodated with less burden. To directly test this hypothesis, we used a bar-coded transposon insertion library in tandem with cell sorting to assess genome-wide impact of gene deletions on membrane protein expression. The expression of five membrane proteins (CyoB, CydB, MdlB, YidC, and LepI) and one soluble protein (GST), each fused to GFP, was examined. We identified Escherichia coli mutants that demonstrated increased membrane protein expression relative to that in wild type. For two of the proteins (CyoB and CydB), we conducted functional assays to confirm that the increase in protein expression also led to phenotypic improvement in function. This study represents a systematic approach to broadly identify genetic loci that can be used to improve membrane protein expression, and our method can be used to improve expression of any protein that poses a cellular burden.

Engineering glucose metabolism of Escherichia coli under nitrogen starvation.

A major aspect of microbial metabolic engineering is the development of chassis hosts that have favorable global metabolic phenotypes, and can be further engineered to produce a variety of compounds. In this work, we focus on the problem of decoupling growth and production in the model bacterium Escherichia coli, and in particular on the maintenance of active metabolism during nitrogen-limited stationary phase. We find that by overexpressing the enzyme PtsI, a component of the glucose uptake system that is inhibited by α-ketoglutarate during nitrogen limitation, we are able to achieve a fourfold increase in metabolic rates. Alternative systems were also tested: chimeric PtsI proteins hypothesized to be insensitive to α-ketoglutarate did not improve metabolic rates under the conditions tested, whereas systems based on the galactose permease GalP suffered from energy stress and extreme sensitivity to expression level. Overexpression of PtsI is likely to be a useful arrow in the metabolic engineer's quiver as productivity of engineered pathways becomes limited by central metabolic rates during stationary phase production processes.

Metabolic constraints on the evolution of antibiotic resistance.

Despite our continuous improvement in understanding antibiotic resistance, the interplay between natural selection of resistance mutations and the environment remains unclear. To investigate the role of bacterial metabolism in constraining the evolution of antibiotic resistance, we evolved Escherichia coli growing on glycolytic or gluconeogenic carbon sources to the selective pressure of three different antibiotics. Profiling more than 500 intracellular and extracellular putative metabolites in 190 evolved populations revealed that carbon and energy metabolism strongly constrained the evolutionary trajectories, both in terms of speed and mode of resistance acquisition. To interpret and explore the space of metabolome changes, we developed a novel constraint-based modeling approach using the concept of shadow prices. This analysis, together with genome resequencing of resistant populations, identified condition-dependent compensatory mechanisms of antibiotic resistance, such as the shift from respiratory to fermentative metabolism of glucose upon overexpression of efflux pumps. Moreover, metabolome-based predictions revealed emerging weaknesses in resistant strains, such as the hypersensitivity to fosfomycin of ampicillin-resistant strains. Overall, resolving metabolic adaptation throughout antibiotic-driven evolutionary trajectories opens new perspectives in the fight against emerging antibiotic resistance.

Synthetic and systems biology for microbial production of commodity chemicals.

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Quantitative prediction of genome-wide resource allocation in bacteria.

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.

A Method to Constrain Genome-Scale Models with 13C Labeling Data.

Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA). This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13C labeling data. A comparison shows that the results of this new method are similar to those found through 13C Metabolic Flux Analysis (13C MFA) for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA) flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems.

Acute Limonene Toxicity in Escherichia coli Is Caused by Limonene Hydroperoxide and Alleviated by a Point Mutation in Alkyl Hydroperoxidase AhpC.

Limonene, a major component of citrus peel oil, has a number of applications related to microbiology. The antimicrobial properties of limonene make it a popular disinfectant and food preservative, while its potential as a biofuel component has made it the target of renewable production efforts through microbial metabolic engineering. For both applications, an understanding of microbial sensitivity or tolerance to limonene is crucial, but the mechanism of limonene toxicity remains enigmatic. In this study, we characterized a limonene-tolerant strain of Escherichia coli and found a mutation in ahpC, encoding alkyl hydroperoxidase, which alleviated limonene toxicity. We show that the acute toxicity previously attributed to limonene is largely due to the common oxidation product limonene hydroperoxide, which forms spontaneously in aerobic environments. The mutant AhpC protein with an L-to-Q change at position 177 (AhpC(L177Q)) was able to alleviate this toxicity by reducing the hydroperoxide to a more benign compound. We show that the degree of limonene toxicity is a function of its oxidation level and that nonoxidized limonene has relatively little toxicity to wild-type E. coli cells. Our results have implications for both the renewable production of limonene and the applications of limonene as an antimicrobial.

Environmental dependence of stationary-phase metabolism in Bacillus subtilis and Escherichia coli.

When microbes lack the nutrients necessary for growth, they enter stationary phase. In cases when energy sources are still present in the environment, they must decide whether to continue to use their metabolic program to harvest the available energy. Here we characterized the metabolic response to a variety of types of nutrient starvation in Escherichia coli and Bacillus subtilis. We found that E. coli exhibits a range of phenotypes, with the lowest metabolic rates under nitrogen starvation and highest rates under magnesium starvation. In contrast, the phenotype of B. subtilis was dominated by its decision to form metabolically inactive endospores. While its metabolic rates under most conditions were thus lower than those of E. coli, when sporulation was suppressed by a genetic perturbation or an unnatural starvation condition, the situation was reversed. To further probe stationary-phase metabolism, we used quantitative metabolomics to investigate possible small-molecule signals that may regulate the metabolic rate of E. coli and initiate sporulation in B. subtilis. We hypothesize a role for phosphoenolpyruvate (PEP) in regulating E. coli glucose uptake and for the redox cofactors NAD(H) and NADP(H) in initiation of sporulation. Our work is directly relevant to synthetic biology and metabolic engineering, where active metabolism during stationary phase, which uncouples production from growth, remains an elusive goal.

Coordination of microbial metabolism.

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.

Transcriptional regulation is insufficient to explain substrate-induced flux changes in Bacillus subtilis.

One of the key ways in which microbes are thought to regulate their metabolism is by modulating the availability of enzymes through transcriptional regulation. However, the limited success of efforts to manipulate metabolic fluxes by rewiring the transcriptional network has cast doubt on the idea that transcript abundance controls metabolic fluxes. In this study, we investigate control of metabolic flux in the model bacterium Bacillus subtilis by quantifying fluxes, transcripts, and metabolites in eight metabolic states enforced by different environmental conditions. We find that most enzymes whose flux switches between on and off states, such as those involved in substrate uptake, exhibit large corresponding transcriptional changes. However, for the majority of enzymes in central metabolism, enzyme concentrations were insufficient to explain the observed fluxes--only for a number of reactions in the tricarboxylic acid cycle were enzyme changes approximately proportional to flux changes. Surprisingly, substrate changes revealed by metabolomics were also insufficient to explain observed fluxes, leaving a large role for allosteric regulation and enzyme modification in the control of metabolic fluxes.

Somewhat in control--the role of transcription in regulating microbial metabolic fluxes.

The most common way for microbes to control their metabolism is by controlling enzyme levels through transcriptional regulation. Yet recent studies have shown that in many cases, perturbations to the transcriptional regulatory network do not result in altered metabolic phenotypes on the level of the flux distribution. We suggest that this may be a consequence of cells protecting their metabolism against stochastic fluctuations in expression as well as enabling a fast response for those fluxes that may need to be changed quickly. Furthermore, it is impossible for a regulatory program to guarantee optimal expression levels in all conditions. Several studies have found examples of demonstrably suboptimal regulation of gene expression, and improvements to the regulatory network have been investigated in laboratory evolution experiments.