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Immunomodulatory (IM) metabolic reprogramming in macrophages (Mϕs) is fundamental to immune function. However, limited information is available for human Mϕs, particularly in response plasticity, which is critical to understanding the variable efficacy of immunotherapies in cancer patients. We carried out an in-depth analysis by combining multiplex stable isotope-resolved metabolomics with reversed phase protein array to map the dynamic changes of the IM metabolic network and key protein regulators in four human donors’ Mϕs in response to differential polarization and M1 repolarizer β-glucan (whole glucan particles [WGPs]). These responses were compared with those of WGP-treated ex vivo organotypic tissue cultures (OTCs) of human non-small cell lung cancer. We found consistently enhanced tryptophan catabolism with blocked NAD+ and UTP synthesis in M1-type Mϕs (M1-Mϕs), which was associated with immune activation evidenced by increased release of IL-1β/CXCL10/IFN-γ/TNF-α and reduced phagocytosis. In M2a-Mϕs, WGP treatment of M2a-Mϕs robustly increased glucose utilization via the glycolysis/oxidative branch of the pentose phosphate pathway while enhancing UDP-N-acetyl-glucosamine turnover and glutamine-fueled gluconeogenesis, which was accompanied by the release of proinflammatory IL-1β/TNF-α to above M1-Mϕ’s levels, anti-inflammatory IL-10 to above M2a-Mϕ’s levels, and attenuated phagocytosis. These IM metabolic responses could underlie the opposing effects of WGP, i.e., reverting M2- to M1-type immune functions but also boosting anti-inflammation. Variable reprogrammed Krebs cycle and glutamine-fueled synthesis of UTP in WGP-treated OTCs of human non-small cell lung cancer were observed, reflecting variable M1 repolarization of tumor-associated Mϕs. This was supported by correlation with IL-1β/TNF-α release and compromised tumor status, making patient-derived OTCs unique models for studying variable immunotherapeutic efficacy in cancer patients.

γ-Aminobutyrate (GAB), the biochemical form of (GABA) γ-aminobutyric acid, participates in shaping physiological processes, including the immune response. How GAB metabolism is controlled to mediate such functions remains elusive. Here we show that GAB is one of the most abundant metabolites in CD4+ T helper 17 (TH17) and induced T regulatory (iTreg) cells. GAB functions as a bioenergetic and signalling gatekeeper by reciprocally controlling pro-inflammatory TH17 cell and anti-inflammatory iTreg cell differentiation through distinct mechanisms. 4-Aminobutyrate aminotransferase (ABAT) funnels GAB into the tricarboxylic acid (TCA) cycle to maximize carbon allocation in promoting TH17 cell differentiation. By contrast, the absence of ABAT activity in iTreg cells enables GAB to be exported to the extracellular environment where it acts as an autocrine signalling metabolite that promotes iTreg cell differentiation. Accordingly, ablation of ABAT activity in T cells protects against experimental autoimmune encephalomyelitis (EAE) progression. Conversely, ablation of GABAA receptor in T cells worsens EAE. Our results suggest that the cell-autonomous control of GAB on CD4+ T cells is bimodal and consists of the sequential action of two processes, ABAT-dependent mitochondrial anaplerosis and the receptor-dependent signalling response, both of which are required for T cell-mediated inflammation.

NMR is a very powerful tool for identifying and quantifying compounds within complex mixtures without the need for individual standards or chromatographic separation. Stable Isotope Resolved Metabolomics (or SIRM) is an approach to following the fate of individual atoms from precursors through metabolic transformation, producing an atom-resolved metabolic fate map. However, extracts of cells or tissue give rise to very complex NMR spectra. While multidimensional NMR experiments may partially overcome the spectral overlap problem, additional tools may be needed to determine site-specific isotopomer distributions. NMR is especially powerful by virtue of its isotope editing capabilities using NMR active nuclei such as (13)C, (15)N, (19)F and (31)P to select molecules containing just these atoms in a complex mixture, and provide direct information about which atoms are present in identified compounds and their relative abundances. The isotope-editing capability of NMR can also be employed to select for those compounds that have been selectively derivatized with an NMR-active stable isotope at particular functional groups, leading to considerable spectral simplification. Here we review isotope analysis by NMR, and methods of chemoselection both for spectral simplification, and for enhanced isotopomer analysis.

Past chemopreventive human trials on dietary selenium supplements produced controversial outcomes. They largely employed selenomethionine (SeM)-based diets. SeM was less toxic than selenite or methylseleninic acid (MSeA) to lung cancer cells. We thus investigated the toxic action of these Se agents in two non-small cell lung cancer (NSCLC) cell lines and ex vivo organotypic cultures (OTC) of NSCLC patient lung tissues. Stable isotope-resolved metabolomics (SIRM) using 13C6-glucose and 13C5,15N2-glutamine tracers with gene knockdowns were employed to examine metabolic dysregulations associated with cell type- and treatment-dependent phenotypic changes. Inhibition of key anaplerotic processes, pyruvate carboxylation (PyC) and glutaminolysis were elicited by exposure to MSeA and selenite but not by SeM. They were accompanied by distinct anabolic dysregulation and reflected cell type-dependent changes in proliferation/death/cell cycle arrest. NSCLC OTC showed similar responses of PyC and/or glutaminolysis to the three agents, which correlated with tissue damages. Altogether, we found differential perturbations in anaplerosis-fueled anabolic pathways to underlie the distinct anti-cancer actions of the three Se agents, which could also explain the failure of SeM-based chemoprevention trials.

Biologically important 2-hydroxy carboxylates such as lactate, malate, and 2-hydroxyglutarate exist in two enantiomeric forms that cannot be distinguished under achiral conditions. The D and L (or R, S) enantiomers have different biological origins and functions, and therefore, there is a need for a simple method for resolving, identifying, and quantifying these enantiomers. We have adapted and improved a chiral derivatization technique for nuclear magnetic resonance (NMR), which needs no chromatography for enantiomer resolution, with greater than 90% overall recovery. This method was developed for 2-hydroxyglutarate (2HG) to produce diastereomers resolvable by column chromatography. We have applied the method to lactate, malate, and 2HG. The limit of quantification was determined to be about 1 nmol for 2HG with coefficients of variation of less than 5%. We also demonstrated the method on an extract of a renal carcinoma bearing an isocitrate dehydrogenase-2 (IDH2) variant that produces copious quantities of 2HG and showed that it is the D enantiomer that was exclusively produced. We also demonstrated in the same experiment that the lactate produced in the same sample was the L enantiomer.

Background Stable Isotope Resolved Metabolomics (SIRM) is a new biological approach that uses stable isotope tracers such as uniformly $$^{13}C$$ 13 C -enriched glucose ($$^{13}C_6$$ 13 C 6 -Glc) to trace metabolic pathways or networks at the atomic level in complex biological systems. Non-steady-state kinetic modeling based on SIRM data uses sets of simultaneous ordinary differential equations (ODEs) to quantitatively characterize the dynamic behavior of metabolic networks. It has been increasingly used to understand the regulation of normal metabolism and dysregulation in the development of diseases. However, fitting a kinetic model is challenging because there are usually multiple sets of parameter values that fit the data equally well, especially for large-scale kinetic models. In addition, there is a lack of statistically rigorous methods to compare kinetic model parameters between different experimental groups. Results We propose a new Bayesian statistical framework to enhance parameter estimation and hypothesis testing for non-steady-state kinetic modeling of SIRM data. For estimating kinetic model parameters, we leverage the prior distribution not only to allow incorporation of experts’ knowledge but also to provide robust parameter estimation. We also introduce a shrinkage approach for borrowing information across the ensemble of metabolites to stably estimate the variance of an individual isotopomer. In addition, we use a component-wise adaptive Metropolis algorithm with delayed rejection to perform efficient Monte Carlo sampling of the posterior distribution over high-dimensional parameter space. For comparing kinetic model parameters between experimental groups, we propose a new reparameterization method that converts the complex hypothesis testing problem into a more tractable parameter estimation problem. We also propose an inference procedure based on credible interval and credible value. Our method is freely available for academic use at https://github.com/xuzhang0131/MCMCFlux. Conclusions Our new Bayesian framework provides robust estimation of kinetic model parameters and enables rigorous comparison of model parameters between experimental groups. Simulation studies and application to a lung cancer study demonstrate that our framework performs well for non-steady-state kinetic modeling of SIRM data.

TP53 is the most commonly mutated gene in cancer, and gain-of-function mutations have wide-ranging effects. Efforts to reactivate wild-type p53 function and inhibit mutant functions have been complicated by the variety of TP53 mutations. Identified from a screen, the NSC59984 compound has been shown to restore activity to mutant p53 in colorectal cancer cells. Here, we investigated its effects on esophageal adenocarcinoma cells with specific p53 hot-spot mutations. NSC59984 treatment of cells reactivated p53 transcriptional regulation, inducing mitochondrial intrinsic apoptosis. Analysis of its effects on cellular metabolism demonstrated increased utilization of the pentose phosphate pathway and inhibition of glycolysis at the fructose-1,6-bisphosphate to fructose 6-phosphate junction. Furthermore, treatment of cells with NSC59984 increased reactive oxygen species production and decreased glutathione levels; these effects were enhanced by the addition of buthionine sulfoximine and inhibited by N-acetyl cysteine. We found that the effects of NSC59984 were substantially greater in cells harboring the p53 R248W mutation. Overall, these findings demonstrate p53-dependent effects of NSC59984 on cellular metabolism, with increased activity in cells harboring the p53 R248W mutation. This research highlights the importance of defining the mutational status of a particular cancer to create a patient-centric strategy for the treatment of p53-driven cancers.

Glucose metabolism comprises numerous amphibolic metabolites that provide precursors for not only the synthesis of cellular building blocks but also for ATP production. In this study, we tested how phosphofructokinase-1 (PFK1) activity controls the fate of glucose-derived carbon in murine hearts in vivo. PFK1 activity was regulated by cardiac-specific overexpression of kinase- or phosphatase-deficient 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase transgenes in mice (termed GlycoLo or GlycoHi mice, respectively). Dietary delivery of 13C6-glucose to these mice, followed by deep network metabolic tracing, revealed that low rates of PFK1 activity promote selective routing of glucose-derived carbon to the purine synthesis pathway to form 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR). Consistent with a mechanism of physical channeling, we found multimeric protein complexes that contained phosphoribosylaminoimidazole carboxylase (PAICS)—an enzyme important for AICAR biosynthesis, as well as chaperone proteins such as Hsp90 and other metabolic enzymes. We also observed that PFK1 influenced glucose-derived carbon deposition in glycogen, but did not affect hexosamine biosynthetic pathway activity. These studies demonstrate the utility of deep network tracing to identify metabolic channeling and changes in biosynthetic pathway activity in the heart in vivo and present new potential mechanisms by which metabolic branchpoint reactions modulate biosynthetic pathways., Graphical Abstract

Robust and effective T cell immune surveillance and cancer immunotherapy require properly allocating metabolic resources to sustain energetically costly processes, including growth and cytokine production. Amino acids are major cellular constituents that serve as protein building blocks, energy sources, and signaling molecules. Although T cells can synthesize all nonessential amino acids, including asparagine (Asn), activated CD8 T cells still consume considerable quantities of exogenous Asn. Unexpectedly, Asn restriction on CD8 T cells induced a biphasic response, consisting of sequential actions with opposing effects at two conceptually separated phases after activation. Asn restriction suppressed activation and cell cycle entry in the early phase by depleting the intracellular Asn pool while rapidly engaging an ATF4/NRF2-dependent stress response, conferring robust proliferation and effector function of CD8 T cells in the late phase. Mechanistically, ATF4 and NRF2 activation rendered CD8 T cells to utilize de novo biosynthesis of Asn, consuming less glucose and glutamine but producing more intracellular nucleotides for proliferation. Moreover, NRF2 activation promoted the expression of inflammatory and effector genes to enhance effector functions in CD8 T cells. Accordingly, Asn restriction or overexpression of ATF4 or NRF2 potentiated T cell-mediated antitumoral response in the metabolically restricted tumor microenvironment. Our studies revealed Asn as a critical metabolic node in directing the stress signaling to shape T cell metabolic fitness and effector functions. Asn restriction is a promising and clinically relevant strategy to enhance cancer immunotherapy.

Effective T cell-mediated immune responses require the proper allocation of metabolic resources to sustain growth, proliferation, and cytokine production. Epigenetic control of the genome also governs T cell transcriptome and T cell lineage commitment and maintenance. Cellular metabolic programs interact with epigenetic regulation by providing substrates for covalent modifications of chromatin. By using complementary genetic, epigenetic, and metabolic approaches, we revealed that tricarboxylic acid (TCA) cycle flux fueled biosynthetic processes while controlling the ratio of succinate/α-ketoglutarate (α-KG) to modulate the activities of dioxygenases that are critical for driving T cell inflammation. In contrast to cancer cells, where succinate dehydrogenase (SDH)/complex II inactivation drives cell transformation and growth, SDH/complex II deficiency in T cells caused proliferation and survival defects when the TCA cycle was truncated, blocking carbon flux to support nucleoside biosynthesis. Replenishing the intracellular nucleoside pool partially relieved the dependence of T cells on SDH/complex II for proliferation and survival. SDH deficiency induced a proinflammatory gene signature in T cells and promoted T helper 1 and T helper 17 lineage differentiation. An increasing succinate/α-KG ratio in SDH-deficient T cells promoted inflammation by changing the pattern of the transcriptional and chromatin accessibility signatures and consequentially increasing the expression of the transcription factor, PR domain zinc finger protein 1. Collectively, our studies revealed a role of SDH/complex II in allocating carbon resources for anabolic processes and epigenetic regulation in T cell proliferation and inflammation.

T cells undergo metabolic rewiring to meet their bioenergetic, biosynthetic and redox demands following antigen stimulation. To fulfil these needs, effector T cells must adapt to fluctuations in environmental nutrient levels at sites of infection and inflammation. Here, we show that effector T cells can utilize inosine, as an alternative substrate, to support cell growth and function in the absence of glucose in vitro. T cells metabolize inosine into hypoxanthine and phosphorylated ribose by purine nucleoside phosphorylase. We demonstrate that the ribose subunit of inosine can enter into central metabolic pathways to provide ATP and biosynthetic precursors, and that cancer cells display diverse capacities to utilize inosine as a carbon source. Moreover, the supplementation with inosine enhances the anti-tumour efficacy of immune checkpoint blockade and adoptive T-cell transfer in solid tumours that are defective in metabolizing inosine, reflecting the capability of inosine to relieve tumour-imposed metabolic restrictions on T cells.

The genetic alterations associated with cell transformation are in large measure expressed in the metabolic phenotype as cancer cells proliferate and change their local environment, and prepare for metastasis. Qualitatively, the fundamental biochemistry of cancer cells is generally the same as in the untransformed cells, but the cancer cells produce a local environment, the TME, that is hostile to the stromal cells, and compete for nutrients. In order to proliferate, cells need sufficient nutrients, either those that cannot be made by the cells themselves, or must be made from simpler precursors. However, in solid tumors, the nutrient supply is often limiting given the potential for rapid proliferation, and the poor quality of the vasculature. Thus, cancer cells may employ a variety of strategies to obtain nutrients for survival, growth and metastasis. Although much has been learned using established cell lines in standard culture conditions, it is becoming clear from in vivo metabolic studies that this can also be misleading, and which nutrients are used for energy production versus building blocks for synthesis of macromolecules can vary greatly from tumor to tumor, and even within the same tumor. Here we review the operation of metabolic networks, and how recent understanding of nutrient supply in the TME and utilization are being revealed using stable isotope tracers in vivo as well as in vitro. Keywords: Cancer metabolism, Nutrient supply, Stable isotope resolved metabolomics, Tumor microenvironment, Metabolic flux

Metabolic reprogramming is a hallmark of cancer. In cancer cells, transcription factors (TFs) govern metabolic reprogramming through abnormally increasing or decreasing the transcription rate of metabolic enzymes, which provides cancer cells growth advantages and concurrently leads to the altered metabolic phenotypes observed in many cancers. Consequently, targeting TFs that govern metabolic reprogramming can be highly effective for novel cancer therapeutics. In this work, we present TFmeta, a machine learning approach to uncover TFs that govern reprogramming of cancer metabolism. Our approach achieves state-of-the-art performance in reconstructing relations between TFs and their target genes on public benchmark data sets. Leveraging TF binding profiles inferred from genome-wide ChIP-seq experiments and 150 RNA-seq samples from 75 paired cancerous (CA) and non-cancerous (NC) human lung tissues, our approach predicted 19 key TFs that may be the major regulators of the gene expression changes of metabolic enzymes of the central metabolic pathway glycolysis, which may underlie the dysregulation of glycolysis in non-small-cell lung cancer patients.

Objective It is well established that the liver-specific miR-122, a bona fide tumor suppressor, plays a critical role in lipid homeostasis. However, its role, if any, in amino acid metabolism has not been explored. Since glutamine (Gln) is a critical energy and anaplerotic source for mammalian cells, we assessed Gln metabolism in control wild type (WT) mice and miR-122 knockout (KO) mice by stable isotope resolved metabolomics (SIRM) studies. Methods Six-to eight-week-old WT and KO mice and 12- to 15-month-old liver tumor-bearing mice were injected with [U–13C5,15N2]-L-Gln, and polar metabolites from the liver tissues were analyzed by nuclear magnetic resonance (NMR) imaging and ion chromatography-mass spectrometry (IC-MS). Gln-metabolism was also assessed in a Gln-dependent hepatocellular carcinoma (HCC) cell line (EC4). Expressions of glutaminases (Gls and Gls2) were analyzed in mouse livers and human primary HCC samples. Results The results showed that loss of miR-122 promoted glutaminolysis but suppressed gluconeogenesis in mouse livers as evident from the buildup of 13C- and/or 15N-Glu and decrease in glucose-6-phosphate (G6P) levels, respectively, in KO livers. Enhanced glutaminolysis is consistent with the upregulation of expressions of Gls (kidney-type glutaminase) and Slc1a5, a neutral amino acid transporter in KO livers. Both Gls and Slc1a5 were confirmed as direct miR-122 targets by the respective 3′-UTR-driven luciferase assays. Importantly, expressions of Gls and Slc1a5 as well as glutaminase activity were suppressed in a Gln-dependent HCC (EC4) cell line transfected with miR-122 mimic that resulted in decreased 13C-Gln, 13C-á-ketoglutarate, 13C-isocitrate, and 13C-citrate levels. In contrast, 13C-phosphoenolpyruvate and 13C-G6P levels were elevated in cells expressing ectopic miR-122, suggesting enhanced gluconeogenesis. Finally, The Cancer Genome Atlas—Liver Hepatocellular Carcinoma (TCGA-LIHC) database analysis showed that expression of GLS is negatively correlated with miR-122 in primary human HCCs, and the upregulation of GLS RNA is associated with higher tumor grade. More importantly, patients with higher expressions of GLS or SLC1A5 in tumors exhibited poor survival compared with those expressing lower levels of these proteins. Conclusions Collectively, these results show that miR-122 modulates Gln metabolism both in vitro and in vivo, implicating the therapeutic potential of miR-122 in HCCs that exhibit relatively high GLS levels., Highlights • miR-122, the most abundant liver specific microRNA and a potent tumor suppressor, regulates glutamine metabolism. • SIRM analysis showed enhanced glutaminolysis and impeded gluconeogenesis in the livers of miR-122 KO mice. • Gls, a key enzyme involved in glutaminolysis and a miR-122 target is upregulated in miR-122 KO livers. • Ectopic miR-122 expression suppressed glutaminolysis but enhanced gluconeogenesis in a glutamine dependent HCC cell line. • Expression of MIR-122 negatively correlated with that of GLS in human primary HCCs.

γ-Aminobutyrate (GAB) is the biochemical form of γ-aminobutyric acid (GABA) at physiological pH and functions as an essential neurotransmitter in the vertebrate’s central nervous system (CNS). Growing evidence suggests that GAB may also mediate intercellular communications to shape various physiological processes, including immune response. Beyond acting as a paracrine signaling molecule, how GAB metabolism is controlled to exert many distinct functions remains elusive. By an integrated analysis of the extracellular metabolome, stable isotope traced metabolic pathway analysis, and metabolic transcriptome, we revealed that GAB is one of the most abundant metabolites produced through glutamine and arginine catabolism in CD4+ T help 17 (TH17) and induced T regulatory (iTreg) cells. GAB functions as a bioenergetic and signaling gatekeeper by reciprocally controlling pro-inflammatory TH17 cell and anti-inflammatory iTreg cell differentiation through distinct mechanisms. The expression of 4-aminobutyrate aminotransferase (ABAT) funnels GAB, as an anaplerotic substrate, into the TCA cycle to maximize carbon allocation in promoting TH17 cell differentiation. By contrast, the absence of ABAT activities in iTreg cells enables GAB exporting to the extracellular environment and acting as an autocrine signaling metabolite to promote iTreg cell differentiation. Accordingly, genetic or pharmacological ablation of ABAT activity in T cells confers protection against experimental autoimmune encephalomyelitis (EAE) pathogenic progression. Conversely, genetic ablation of GABA(A) receptor in T cells deteriorates EAE pathogenic progression. Collectively, our results suggest that the cell-autonomous control exerted by GAB on CD4+ T cell is bimodal and consists of the sequential action of two discrete processes, ABAT–dependent mitochondrial anaplerosis and the receptor-dependent autocrine signaling response, both of which are required for a properly controlled T cell-mediated inflammation.

Cellular metabolism has key roles in T cells differentiation and function. CD4+ T helper-1 (Th1), Th2, and Th17 subsets are highly glycolytic while regulatory T cells (Tregs) use glucose during expansion but rely on fatty acid oxidation for function. Upon uptake, glucose can enter pentose phosphate pathway (PPP) or be used in glycolysis. Here, we showed that blocking 6-phosphogluconate dehydrogenase (6PGD) in the oxidative PPP resulted in substantial reduction of Tregs suppressive function and shifts toward Th1, Th2, and Th17 phenotypes which led to the development of fetal inflammatory disorder in mice model. These in turn improved anti-tumor responses and worsened the outcomes of colitis model. Metabolically, 6PGD blocked Tregs showed improved glycolysis and enhanced non-oxidative PPP to support nucleotide biosynthesis. These results uncover critical role of 6PGD in modulating Tregs plasticity and function, which qualifies it as a novel metabolic checkpoint for immunotherapy applications.

We have implemented a linear ion trap (LIT)-based SIM-stitching method for ultra-high-resolution Fourier transform mass spectrometry (FTMS) that increases the S/N over a wide m/z range compared to non-segmented wide full-scan (WFS) spectra. Here we described an improved segmented spectral scan stitching method that was based on quadrupole mass filter (QMF)-SIM, which overcame previous limitations of ion signal loss in LIT. This allowed for accurate representation of isotopologue distributions, both at natural abundance and in stable isotope-resolved metabolomics (SIRM)-based experiments. We also introduced a new spectral binning method that provided more precise and resolution-independent bins for irreversibly noise-suppressed FTMS spectra. We demonstrated a substantial improvement in S/N and sensitivity (typically > 10-fold) for 13C labeled lipid extracts of human macrophages grown as three-dimensional (3D) cell culture, with detection of an increased number of 13C isotopologue ions. The method also enabled analysis of extracts from very limited biological samples.

Background Identifying differentially abundant features between different experimental groups is a common goal for many metabolomics and proteomics studies. However, analyzing data from mass spectrometry (MS) is difficult because the data may not be normally distributed and there is often a large fraction of zero values. Although several statistical methods have been proposed, they either require the data normality assumption or are inefficient. Results We propose a new semi-parametric differential abundance analysis (SDA) method for metabolomics and proteomics data from MS. The method considers a two-part model, a logistic regression for the zero proportion and a semi-parametric log-linear model for the possibly non-normally distributed non-zero values, to characterize data from each feature. A kernel-smoothed likelihood method is developed to estimate model coefficients and a likelihood ratio test is constructed for differential abundant analysis. The method has been implemented into an R package, SDAMS, which is available at https://www.bioconductor.org/packages/release/bioc/html/SDAMS.html. Conclusion By introducing the two-part semi-parametric model, SDA is able to handle both non-normally distributed data and large fraction of zero values in a MS dataset. It also allows for adjustment of covariates. Simulations and real data analyses demonstrate that SDA outperforms existing methods.

Nucleotide synthesis is essential to proliferating cells, but the preferred precursors for de novo biosynthesis are not defined in human cancer tissues. We have employed multiplexed stable isotope-resolved metabolomics to track the metabolism of [(13)C(6)]glucose, D(2)-glycine, [(13)C(2)]glycine, and D(3)-serine into purine nucleotides in freshly resected cancerous and matched noncancerous lung tissues from nonsmall cell lung cancer (NSCLC) patients, and we compared the metabolism with established NSCLC PC9 and A549 cell lines in vitro. Surprisingly, [(13)C(6)]glucose was the best carbon source for purine synthesis in human NSCLC tissues, in contrast to the noncancerous lung tissues from the same patient, which showed lower mitotic indices and MYC expression. We also observed that D(3)-Ser was preferentially incorporated into purine rings over D(2)-glycine in both tissues and cell lines. MYC suppression attenuated [(13)C(6)]glucose, D(3)-serine, and [(13)C(2)]glycine incorporation into purines and reduced proliferation in PC9 but not in A549 cells. Using detailed kinetic modeling, we showed that the preferred use of glucose as a carbon source for purine ring synthesis in NSCLC tissues involves cytoplasmic activation/compartmentation of the glucose–to–serine pathway and enhanced reversed one-carbon fluxes that attenuate exogenous serine incorporation into purines. Our findings also indicate that the substrate for de novo nucleotide synthesis differs profoundly between cancer cell lines and fresh human lung cancer tissues; the latter preferred glucose to exogenous serine or glycine but not the former. This distinction in substrate utilization in purine synthesis in human cancer tissues should be considered when targeting one-carbon metabolism for cancer therapy.

We combined multiplex Stable Isotope-Resolved Metabolomics (mSIRM) with Reverse Phase Protein Array (RPPA) to map the time course changes of IM metabolic network and key protein regulators in four human donors’ MΦ’s in response to differential polarization and whole glucan particulates (WGP) treatments. We found consistent and plastic network responses to polarization durations and WGP treatments compared to those of the mouse counterparts. Consistent responses included enhanced 15N2-tryptophan catabolism to quinolinate, 2H2-glucose oxidation to ribose/ribulose-5-phosphate, and conversion of 13C5-glutamine to itaconate in response to pro-inflammatory (M1) versus anti-inflammatory (M2) stimuli. WGP robustly induced the buildup of 2H2-glucose-derived 6-phosphogluconate, -lactate, and -IMP, 13C5-glutamine-derived fructose-1,6-bisphosphate, and increased enrichment of 2H-labeled UDP-N-acetylglucosamine in M2-MΦ’s. However, the Krebs cycle activity was variably enhanced by M2 stimuli or WGP treatment. The consistent effects were related to increased release of proinflammatory IM effectors IL-1β/CXCL10/IFNγ/TNFα by M1-MΦ’s and enhanced release of IL-1β/TNFα to above M1-MΦ’s levels in WGP-treated M2-MΦ’s while boosting the latter in anti-inflammatory IL-10 release and maintenance of NAD+ synthesis. They were also related to lower phagocytosis in M1-MΦ’s and WGP-treated M2-MΦ’s versus M2-MΦ’s. Together with the expression changes of key protein regulators, we suggest enhanced tryptophan catabolism with blocked NAD+ and UTP synthesis to be key to the consistent changes in immune functions in response to M1 stimuli. Likewise, increased glucose utilization via glycolysis and the oxidative branch of the pentose phosphate pathway, and blockade of glutamine-fueled N-linked glycosylation could be linked to reversion of M2 to M1-type immune functions. Reprogrammed Krebs cycle and glutamine conversion to UTP occurred variably in WGP-treated ex vivo organotypic tissue cultures (OTCs) of human non-small cell lung cancer (NSCLC), which could reflect variable M1 repolarization of tumor associated MΦ’s. This in turn correlated with IL-1β/TNFα releases and compromised tumor status, making patient-derived OTCs a unique model for studying variable immunotherapeutic efficacy in cancer patients. In conclusion, consistent and variable IM metabolic responses were evident in four human donors’ MΦ’s. WGP repolarized some M2 to M1-type responses while boosting other M2-type responses. NSCLC OTCs from six patients showed variable M1 repolarization in response to WGP. Citation Format: Teresa W. M. Fan, Saeed Daneshmandi, Teresa A. Cassel, Mohammad B. Uddin, James Sledziona, Patrick T. Thompson, Penghui Lin, Richard M. Higashi, Andrew N. Lane. Beta-glucan reprograms immunomodulatory metabolism in human macrophage and ex vivo in lung cancer tissues [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2537.

Introduction: Glycogen is a readily deployed intracellular energy storage macromolecule composed of branched chains of glucose. Although glycogen primarily occurs in the liver and muscle, it can be found in most tissues throughout the body, and its metabolism has been shown to be important in cancers and immune cells. Robust analysis of glycogen turnover requires stable isotope tracing plus a reliable means of quantifying total and labeled glycogen derived from precursors such as 13C6-glucose. Current methods for analyzing glycogen are time- and sample-consuming, at best semi-quantitative, and unable to measure stable isotope enrichment. Methods: We have developed a microscale method for quantifying both intact and acid-hydrolyzed glycogen by ultra-high-resolution Fourier transform mass spectrometric (UHR-FTMS) and/or NMR analysis in stable isotope resolved metabolomics (SIRM) studies. Polar metabolites, including intact glycogen and their 13C positional isotopomer distributions were first measured in crude biological extracts by high resolution NMR, followed by rapid and efficient acid hydrolysis to glucose in 1 N HCl for 10 minutes at 110 °C under a N2 atmosphere in a microwave-assisted synthesis reactor. The resulting glucose and its 13C isotopologues were then analyzed by UHR-FTMS and/or NMR. Results: We optimized the microwave digestion time, temperature, and oxygen purging in terms of recovery versus degradation and found 10 minutes at 110-115 °C to give > 90% recovery. The method was applied to track the fate of 13C6-glucose in primary human lung BEAS-2B cells, human macrophages, murine liver and patient-derived tumor xenograft (PDTX) in vivo, and the fate of 2H7-glucose in ex vivo lung organotypic tissue cultures of a lung cancer patient. We showed the incorporation of 13C6-glucose into glycogen and its metabolic intermediates, UDP-Glucose and glucose-1-phosphate, both in terms of the 13C levels and fractional enrichment, thereby demonstrating the utility of the method in tracing glycogen turnover in cells and tissues. Conclusions: The method offers a quantitative, sensitive, and convenient means to analyze glycogen turnover in mg amounts of complex biological materials. Keywords: glycogen turnover; 13C6-glucose, stable isotope resolved metabolomics (SIRM); microwave-assisted hydrolysis. Citation Format: Andrew N. Lane, Timothy L. Scott, Juan Zhu, Teresa A. Cassel, Sara Vicente-Munoz, Penghui Lin, Richard M. Higashi, Teresa W-M Fan. Small-scale microwave-assisted acid hydrolysis method for glycogen determination and turnover in tumors using Stable Isotope Resolved Metabolomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2324.

Dysregulated metabolism can fuel cancer by altering the production of bioenergetic building blocks and directly stimulating oncogenic gene expression programs. However, relatively few optical methods for the direct study of metabolites in cells exist. To address this need and facilitate new approaches to cancer treatment and diagnosis, here we report an optimized chemical approach to detect the oncometabolite fumarate. Our strategy employs diaryl tetrazoles as cell-permeable photoinducible precursors to nitrileimines. Uncaging these species in cells and cell extracts enables them to undergo 1,3-dipolar cycloaddition reactions with endogenous dipolarophile metabolites such as fumarate, forming pyrazoline cycloadducts that can be readily detected by their intrinsic fluorescence. The ability to photolytically uncage diaryl tetrazoles provides greatly improved sensitivity relative to previous methods, and enables the facile detection of dysregulated fumarate metabolism via biochemical activity assays, intracellular imaging, and flow cytometry. Our studies showcase a novel intersection of bioorthogonal chemistry and metabolite reactivity that can be applied for biological profiling, imaging, and diagnostic applications.

A substantial fraction of common metabolites contains carboxyl functional groups. Their 13C isotopomer analysis by nuclear magnetic resonance (NMR) is hampered by the low sensitivity of the 13C nucleus, the slow longitudinal relaxation for the lack of an attached proton, and the relatively low chemical shift dispersion of carboxylates. Chemoselective (CS) derivatization is a means of tagging compounds in a complex mixture via a specific functional group. 15N1-cholamine has been shown to be a useful CS agent for carboxylates, producing a peptide bond that can be detected via 15N-attached H with high sensitivity in heteronuclear single quantum coherence experiments. Here, we report an improved method of derivatization and show how 13C-enrichment at the carboxylate and/or the adjacent carbon can be determined via one- and two-bond coupling of the carbons adjacent to the cholamine 15N atom in the derivatives. We have applied this method for the determination of 13C isotopomer distribution in the extracts of A549 cell culture and liver tissue from a patient-derived xenograft mouse.

Although Pembrolizumab-based immunotherapy has significantly improved lung cancer patient survival, many patients show variable efficacy and resistance development. A better understanding of the drug’s action is needed to improve patient outcomes. Functional heterogeneity of the tumor microenvironment (TME) is crucial to modulating drug resistance; understanding of individual patients’ TME that impacts drug response is hampered by lack of appropriate models. Lung organotypic tissue slice cultures (OTC) with patients’ native TME procured from primary and brain-metastasized (BM) non-small cell lung cancer (NSCLC) patients were treated with Pembrolizumab and/or beta-glucan (WGP, an innate immune activator). Metabolic tracing with 13C6-Glc/13C5,15N2-Gln, multiplex immunofluorescence, and digital spatial profiling (DSP) were employed to interrogate metabolic and functional responses to Pembrolizumab and/or WGP. Primary and BM PD-1+ lung cancer OTC responded to Pembrolizumab and Pembrolizumab + WGP treatments, respectively. Pembrolizumab activated innate immune metabolism and functions in primary OTC, which were accompanied by tissue damage. DSP analysis indicated an overall decrease in immunosuppressive macrophages and T cells but revealed microheterogeneity in immune responses and tissue damage. Two TMEs with altered cancer cell properties showed resistance. Pembrolizumab or WGP alone had negligible effects on BM-lung cancer OTC but Pembrolizumab + WGP blocked central metabolism with increased pro-inflammatory effector release and tissue damage. In-depth metabolic analysis and multiplex TME imaging of lung cancer OTC demonstrated overall innate immune activation by Pembrolizumab but heterogeneous responses in the native TME of a patient with primary NSCLC. Metabolic and functional analysis also revealed synergistic action of Pembrolizumab and WGP in OTC of metastatic NSCLC.

Lipids comprise diverse classes of compounds that are important for the structure and properties of membranes, as high-energy fuel sources and as signaling molecules. Therefore, the turnover rates of these varied classes of lipids are fundamental to cellular function. However, their enormous chemical diversity and dynamic range in cells makes detailed analysis very complex. Furthermore, although stable isotope tracers enable the determination of synthesis and degradation of complex lipids, the numbers of distinguishable molecules increase enormously, which exacerbates the problem. Although LC-MS-MS (Liquid Chromatography-Tandem Mass Spectrometry) is the standard for lipidomics, NMR can add value in global lipid analysis and isotopomer distributions of intact lipids. Here, we describe new developments in NMR analysis for assessing global lipid content and isotopic enrichment of mixtures of complex lipids for two cell lines (PC3 and UMUC3) using both 13C6 glucose and 13C5 glutamine tracers.

Summary: Although T cell expansion depends on glycolysis, T effector cell differentiation requires signaling via the production of reactive oxygen species (ROS). Because the pentose phosphate pathway (PPP) regulates ROS by generating nicotinamide adenine dinucleotide phosphate (NADPH), we examined how PPP blockade affects T cell differentiation and function. Here, we show that genetic ablation or pharmacologic inhibition of the PPP enzyme 6-phosphogluconate dehydrogenase (6PGD) in the oxidative PPP results in the generation of superior CD8+ T effector cells. These cells have gene signatures and immunogenic markers of effector phenotype and show potent anti-tumor functions both in vitro and in vivo. In these cells, metabolic reprogramming occurs along with increased mitochondrial ROS and activated antioxidation machinery to balance ROS production against oxidative damage. Our findings reveal a role of 6PGD as a checkpoint for T cell effector differentiation/survival and evidence for 6PGD as an attractive metabolic target to improve tumor immunotherapy.

The Metabolome comprises a complex network of interconnecting enzyme-catalyzed reactions that involve transfers of numerous molecular subunits. Thus, reconstruction of metabolic networks requires metabolite substructures to be tracked. Subunit tracking can be achieved by tracing stable isotopes through metabolic transformations using NMR and ultrahigh resolution (UHR) MS. UHR-MS(1) readily resolves and counts isotopic labels in metabolites but requires tandem MS to help identify isotopic enrichment in substructures. However, it is challenging to perform chromatography-based UHR-MS(1) with its long acquisition time, while acquiring MS(2) data on scores of co-eluting labeled isotopologues for each metabolite. We have developed an Ion Chromatography (IC)-UHR-MS(1)/data independent (DI)-HR-MS(2) method, demonstrated on tracing the fate of (13)C atoms from [(13)C(6)]-Glucose ([(13)C(6)]-Glc) in 3D A549 spheroids in response to anti-cancer selenite and simultaneous (13)C/(15)N atoms from [(13)C(5),(15)N(2)]-glutamine ([(13)C(5),(15)N(2)]-Gln) in 2D BEAS-2B cells in response to arsenite transformation. This method retains the complete isotopologue distributions of metabolites via UHR-MS(1) while simultaneously acquiring substructure label information via DI-MS(2). These details in metabolite labeling patterns greatly facilitate rigorous reconstruction of multiple, intersecting metabolic pathways of central metabolism, which are illustrated here for the purine/pyrimidine nucleotide biosynthesis. The pathways reconstructed based on subunit-level isotopologue analysis further reveal specific enzyme catalyzed reactions that are impacted by selenite or arsenite treatments.

Understanding the mechanisms of the Warburg shift to aerobic glycolysis is critical to defining the metabolic basis of cancer. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is an aggressive cancer characterized by biallelic inactivation of the gene encoding the Krebs cycle enzyme fumarate hydratase, an early shift to aerobic glycolysis, and rapid metastasis. We observed impairment of the mitochondrial respiratory chain in tumors from patients with HLRCC. Biochemical and transcriptomic analyses revealed that respiratory chain dysfunction in the tumors was due to loss of expression of mitochondrial DNA (mtDNA)-encoded subunits of respiratory chain complexes, caused by a marked decrease in mtDNA content and increased mtDNA mutations. We demonstrated that accumulation of fumarate in HLRCC tumors inactivated the core factors responsible for replication and proofreading of mtDNA, leading to loss of respiratory chain components, thereby promoting the shift to aerobic glycolysis and disease progression in this prototypic model of glucose-dependent human cancer.

This chapter describes an approach that utilizes the biotransformation activities of aquatic microphytes intrinsic to the Selenium (Se)-laden agricultural evaporation basins for “natural” remediation. It also describes the laboratory studies which involved fractionating the commonly occurring microphyte species from the basin waters, establishing monocultures of these species, measuring their Se volatilization kinetics, and characterizing the biotransformation products of Se. Medium water, the trap, and biomass samples were digested using a microdigestion method described previously, which substantially simplified the procedure and reduced sample requirement compared with reported macrodigestion methods. The relationship between Se depletion from the medium and rates of Se volatilization as a function of selenite concentrations by the filamentous cyanophyte culture was also investigated. Selenium contamination and accumulation in the agricultural drainage evaporation basins of the San Joaquin Valley has been a major concern for California’s multi-billion dollar agriculture.

Hepatocyte nuclear factor 4α (HNF4α) is a master regulator of liver function and a tumor suppressor in hepatocellular carcinoma (HCC). In this study, we explore the reciprocal negative regulation of HNF4α and cyclin D1, a key cell cycle protein in the liver. Transcriptomic analysis of cultured hepatocyte and HCC cells found that cyclin D1 knockdown induced the expression of a large network of HNF4α-regulated genes. Chromatin immunoprecipitation-sequencing (ChIP-seq) demonstrated that cyclin D1 inhibits the binding of HNF4α to thousands of targets in the liver, thereby diminishing the expression of associated genes that regulate diverse metabolic activities. Conversely, acute HNF4α deletion in the liver induces cyclin D1 and hepatocyte cell cycle progression; concurrent cyclin D1 ablation blocked this proliferation, suggesting that HNF4α maintains proliferative quiescence in the liver, at least, in part, via repression of cyclin D1. Acute cyclin D1 deletion in the regenerating liver markedly inhibited hepatocyte proliferation after partial hepatectomy, confirming its pivotal role in cell cycle progression in this in vivo model, and enhanced the expression of HNF4α target proteins. Hepatocyte cyclin D1 gene ablation caused markedly increased postprandial liver glycogen levels (in a HNF4α-dependent fashion), indicating that the cyclin D1-HNF4α axis regulates glucose metabolism in response to feeding. In AML12 hepatocytes, cyclin D1 depletion led to increased glucose uptake, which was negated if HNF4α was depleted simultaneously, and markedly elevated glycogen synthesis. To summarize, mutual repression by cyclin D1 and HNF4α coordinately controls the cell cycle machinery and metabolism in the liver.

SUMMARY Although T cell expansion depends on glycolysis, T effector cell differentiation requires signaling via the production of reactive oxygen species (ROS). Because the pentose phosphate pathway (PPP) regulates ROS by generating nicotinamide adenine dinucleotide phosphate (NADPH), we examined how PPP blockade affects T cell differentiation and function. Here, we show that genetic ablation or pharmacologic inhibition of the PPP enzyme 6-phosphogluconate dehydrogenase (6PGD) in the oxidative PPP results in the generation of superior CD8+ T effector cells. These cells have gene signatures and immunogenic markers of effector phenotype and show potent anti-tumor functions both in vitro and in vivo. In these cells, metabolic reprogramming occurs along with increased mitochondrial ROS and activated antioxidation machinery to balance ROS production against oxidative damage. Our findings reveal a role of 6PGD as a checkpoint for T cell effector differentiation/survival and evidence for 6PGD as an attractive metabolic target to improve tumor immunotherapy., In brief Daneshmandi et al. show that 6-phosphogluconate dehydrogenase (6PGD) in the oxidative pentose phosphate pathway (PPP) is a modulator of CD8+ T cell activation and differentiation. 6PGD blockade reprograms CD8+ T cell metabolism to support superior effector function with higher tumoricidal activity. This metabolic checkpoint represents a key therapeutic target for cancer immunotherapies., Graphical Abstract

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Profound metabolic changes are characteristic of macrophages during classical activation and have been implicated in this phenotype. Here we demonstrate that nitric oxide (NO) produced by murine macrophages is responsible for TCA cycle alterations and citrate accumulation associated with polarization. 13C tracing and mitochondrial respiration experiments map NO-mediated suppression of metabolism to mitochondrial aconitase (ACO2). Moreover, we find that inflammatory macrophages reroute pyruvate away from pyruvate dehydrogenase (PDH) in an NO-dependent and hypoxia-inducible factor 1α (Hif1α)-independent manner, thereby promoting glutamine-based anaplerosis. Ultimately, NO accumulation leads to suppression and loss of mitochondrial electron transport chain (ETC) complexes. Our data reveal that macrophages metabolic rewiring, in vitro and in vivo, is dependent on NO targeting specific pathways, resulting in reduced production of inflammatory mediators. Our findings require modification to current models of macrophage biology and demonstrate that reprogramming of metabolism should be considered a result rather than a mediator of inflammatory polarization., Production of inflammatory mediators by M1-polarized macrophages is thought to rely on suppression of mitochondrial metabolism in favor of glycolysis. Refining this concept, here the authors define metabolic targets of nitric oxide as responsible for the mitochondrial rewiring resulting from polarization.

Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.