Hepatic glutamine synthetase controls N5-methylglutamine in homeostasis and cancer.

Glutamine synthetase (GS) activity is conserved from prokaryotes to humans, where the ATP-dependent production of glutamine from glutamate and ammonia is essential for neurotransmission and ammonia detoxification. Here, we show that mammalian GS uses glutamate and methylamine to produce a methylated glutamine analog, N5-methylglutamine. Untargeted metabolomics revealed that liver-specific GS deletion and its pharmacological inhibition in mice suppress hepatic and circulating levels of N5-methylglutamine. This alternative activity of GS was confirmed in human recombinant enzyme and cells, where a pathogenic mutation in the active site (R324C) promoted the synthesis of N5-methylglutamine over glutamine. N5-methylglutamine is detected in the circulation, and its levels are sustained by the microbiome, as demonstrated by using germ-free mice. Finally, we show that urine levels of N5-methylglutamine correlate with tumor burden and GS expression in a ß-catenin-driven model of liver cancer, highlighting the translational potential of this uncharacterized metabolite.

Redox activation of ATM enhances GSNOR translation to sustain mitophagy and tolerance to oxidative stress.

The denitrosylase S-nitrosoglutathione reductase (GSNOR) has been suggested to sustain mitochondrial removal by autophagy (mitophagy), functionally linking S-nitrosylation to cell senescence and aging. In this study, we provide evidence that GSNOR is induced at the translational level in response to hydrogen peroxide and mitochondrial ROS. The use of selective pharmacological inhibitors and siRNA demonstrates that GSNOR induction is an event downstream of the redox-mediated activation of ATM, which in turn phosphorylates and activates CHK2 and p53 as intermediate players of this signaling cascade. The modulation of ATM/GSNOR axis, or the expression of a redox-insensitive ATM mutant influences cell sensitivity to nitrosative and oxidative stress, impairs mitophagy and affects cell survival. Remarkably, this interplay modulates T-cell activation, supporting the conclusion that GSNOR is a key molecular effector of the antioxidant function of ATM and providing new clues to comprehend the pleiotropic effects of ATM in the context of immune function.

Aspartate metabolism in endothelial cells activates the mTORC1 pathway to initiate translation during angiogenesis.

Angiogenesis, the active formation of new blood vessels from pre-existing ones, is a complex and demanding biological process that plays an important role in physiological as well as pathological settings. Recent evidence supports cell metabolism as a critical regulator of angiogenesis. However, whether and how cell metabolism regulates endothelial growth factor receptor levels and nucleotide synthesis remains elusive. We here shown in both human cell lines and mouse models that during developmental and pathological angiogenesis, endothelial cells (ECs) use glutaminolysis-derived glutamate to produce aspartate (Asp) via aspartate aminotransferase (AST/GOT). Asp leads to mTORC1 activation which, in turn, regulates endothelial translation machinery for VEGFR2 and FGFR1 synthesis. Asp-dependent mTORC1 pathway activation also regulates de novo pyrimidine synthesis in angiogenic ECs. These findings identify glutaminolysis-derived Asp as a regulator of mTORC1-dependent endothelial translation and pyrimidine synthesis. Our studies may help overcome anti-VEGF therapy resistance by targeting endothelial growth factor receptor translation.

A map of the altered glioma metabolism.

The frequent occurrence of neomorphic isocitrate dehydrogenase 1 (IDH1) mutations in low-grade glioma led to an IDH-centric classification of these tumors. However, exploiting metabolic alterations of glioma for diagnostic imaging and treatment has marginally improved patients' prognosis. Here we discuss the nutritional microenvironment of glioma, shaped by the distinctive dependence of the brain on glucose and ketone bodies for energy, and on amino acids for neurotransmission. We highlight the progress in metabolic applications for glioma diagnosis and therapy, and present a map that streamlines the rewired glioma metabolism. The map illustrates the altered reactions in central carbon and nitrogen metabolism that drive glioma biology, and represent metabolic vulnerabilities with translational potential.

Cystathionine-γ-lyase drives antioxidant defense in cysteine-restricted IDH1-mutant astrocytomas.

BACKGROUND: Mutations in isocitrate dehydrogenase 1 or 2 (IDH1/2) define glioma subtypes and are considered primary events in gliomagenesis, impacting tumor epigenetics and metabolism. IDH enzyme activity is crucial for the generation of reducing potential in normal cells, yet the impact of the mutation on the cellular antioxidant system in glioma is not understood. The aim of this study was to determine how glutathione (GSH), the main antioxidant in the brain, is maintained in IDH1-mutant gliomas, despite an altered NADPH/NADP balance. METHODS: Proteomics, metabolomics, metabolic tracer studies, genetic silencing, and drug targeting approaches in vitro and in vivo were applied. Analyses were done in clinical specimen of different glioma subtypes, in glioma patient-derived cell lines carrying the endogenous IDH1 mutation and corresponding orthotopic xenografts in mice. RESULTS: We find that cystathionine-γ-lyase (CSE), the enzyme responsible for cysteine production upstream of GSH biosynthesis, is specifically upregulated in IDH1-mutant astrocytomas. CSE inhibition sensitized these cells to cysteine depletion, an effect not observed in IDH1 wild-type gliomas. This correlated with an increase in reactive oxygen species and reduced GSH synthesis. Propargylglycine (PAG), a brain-penetrant drug specifically targeting CSE, led to delayed tumor growth in mice. CONCLUSIONS: We show that IDH1-mutant astrocytic gliomas critically rely on NADPH-independent de novo GSH synthesis via CSE to maintain the antioxidant defense, which highlights a novel metabolic vulnerability that may be therapeutically exploited.

S-nitrosylation affects TRAP1 structure and ATPase activity and modulates cell response to apoptotic stimuli.

The mitochondrial chaperone TRAP1 has been involved in several mitochondrial functions, and modulation of its expression/activity has been suggested to play a role in the metabolic reprogramming distinctive of cancer cells. TRAP1 posttranslational modifications, i.e. phosphorylation, can modify its capability to bind to different client proteins and modulate its oncogenic activity. Recently, it has been also demonstrated that TRAP1 is S-nitrosylated at Cys501, a redox modification associated with its degradation via the proteasome. Here we report molecular dynamics simulations of TRAP1, together with analysis of long-range structural communication, providing a model according to which Cys501 S-nitrosylation induces conformational changes to distal sites in the structure of the protein. The modification is also predicted to alter open and closing motions for the chaperone function. By means of colorimetric assays and site directed mutagenesis aimed at generating C501S variant, we also experimentally confirmed that selective S-nitrosylation of Cys501 decreases ATPase activity of recombinant TRAP1. Coherently, C501S mutant was more active and conferred protection to cell death induced by staurosporine. Overall, our results provide the first in silico, in vitro and cellular evidence of the relevance of Cys501 S-nitrosylation in TRAP1 biology.

Analyzing Biomolecular Ensembles.

Several techniques are available to generate conformational ensembles of proteins and other biomolecules either experimentally or computationally. These methods produce a large amount of data that need to be analyzed to identify structure-dynamics-function relationship. In this chapter, we will cover different tools to unveil the information hidden in conformational ensemble data and to guide toward the rationalization of the data. We included routinely used approaches such as dimensionality reduction, as well as new methods inspired by high-order statistics and graph theory.

Computational Structural Biology of S-nitrosylation of Cancer Targets.

Nitric oxide (NO) plays an essential role in redox signaling in normal and pathological cellular conditions. In particular, it is well known to react in vivo with cysteines by the so-called S-nitrosylation reaction. S-nitrosylation is a selective and reversible post-translational modification that exerts a myriad of different effects, such as the modulation of protein conformation, activity, stability, and biological interaction networks. We have appreciated, over the last years, the role of S-nitrosylation in normal and disease conditions. In this context, structural and computational studies can help to dissect the complex and multifaceted role of this redox post-translational modification. In this review article, we summarized the current state-of-the-art on the mechanism of S-nitrosylation, along with the structural and computational studies that have helped to unveil its effects and biological roles. We also discussed the need to move new steps forward especially in the direction of employing computational structural biology to address the molecular and atomistic details of S-nitrosylation. Indeed, this redox modification has been so far an underappreciated redox post-translational modification by the computational biochemistry community. In our review, we primarily focus on S-nitrosylated proteins that are attractive cancer targets due to the emerging relevance of this redox modification in a cancer setting.

An optimal distance cutoff for contact-based Protein Structure Networks using side-chain centers of mass.

Proteins are highly dynamic entities attaining a myriad of different conformations. Protein side chains change their states during dynamics, causing clashes that are propagated at distal sites. A convenient formalism to analyze protein dynamics is based on network theory using Protein Structure Networks (PSNs). Despite their broad applicability, few efforts have been devoted to benchmarking PSN methods and to provide the community with best practices. In many applications, it is convenient to use the centers of mass of the side chains as nodes. It becomes thus critical to evaluate the minimal distance cutoff between the centers of mass which will provide stable network properties. Moreover, when the PSN is derived from a structural ensemble collected by molecular dynamics (MD), the impact of the MD force field has to be evaluated. We selected a dataset of proteins with different fold and size and assessed the two fundamental properties of the PSN, i.e. hubs and connected components. We identified an optimal cutoff of 5 Å that is robust to changes in the force field and the proteins. Our study builds solid foundations for the harmonization and standardization of the PSN approach.