Circulating N-lactoyl-amino acids and N-formyl-methionine reflect mitochondrial dysfunction and predict mortality in septic shock.

INTRODUCTION: Sepsis is a highly morbid condition characterized by multi-organ dysfunction resulting from dysregulated inflammation in response to acute infection. Mitochondrial dysfunction may contribute to sepsis pathogenesis, but quantifying mitochondrial dysfunction remains challenging. OBJECTIVE: To assess the extent to which circulating markers of mitochondrial dysfunction are increased in septic shock, and their relationship to severity and mortality. METHODS: We performed both full-scan and targeted (known markers of genetic mitochondrial disease) metabolomics on plasma to determine markers of mitochondrial dysfunction which distinguish subjects with septic shock (n = 42) from cardiogenic shock without infection (n = 19), bacteremia without sepsis (n = 18), and ambulatory controls (n = 19) - the latter three being conditions in which mitochondrial function, proxied by peripheral oxygen consumption, is presumed intact. RESULTS: Nine metabolites were significantly increased in septic shock compared to all three comparator groups. This list includes N-formyl-L-methionine (f-Met), a marker of dysregulated mitochondrial protein translation, and N-lactoyl-phenylalanine (lac-Phe), representative of the N-lactoyl-amino acids (lac-AAs), which are elevated in plasma of patients with monogenic mitochondrial disease. Compared to lactate, the clinical biomarker used to define septic shock, there was greater separation between survivors and non-survivors of septic shock for both f-Met and the lac-AAs measured within 24 h of ICU admission. Additionally, tryptophan was the one metabolite significantly decreased in septic shock compared to all other groups, while its breakdown product kynurenate was one of the 9 significantly increased. CONCLUSION: Future studies which validate the measurement of lac-AAs and f-Met in conjunction with lactate could define a sepsis subtype characterized by mitochondrial dysfunction.

Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers.

BACKGROUND: Quantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality. METHODS: In 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography-mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini-Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst. RESULTS: We found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways. CONCLUSIONS: Metabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.

Identification and targeting of microbial putrescine acetylation in bloodstream infections.

The growth of antimicrobial resistance (AMR) has highlighted an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe bacterial infections profoundly alter host metabolism, prior studies have largely ignored alterations in microbial metabolism in this context. Performing metabolomics on patient and mouse plasma samples, we identify elevated levels of bacterially-derived N-acetylputrescine during gram-negative bloodstream infections (BSI), with higher levels associated with worse clinical outcomes. We discover that SpeG is the bacterial enzyme responsible for acetylating putrescine and show that blocking its activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity enhances bacterial membrane permeability and results in increased intracellular accumulation of antibiotics, allowing us to overcome AMR of clinical isolates both in culture and in vivo. This study highlights how studying pathogen metabolism in the natural context of infection can reveal new therapeutic strategies for addressing challenging infections.

Gut microbial metabolism of 5-ASA diminishes its clinical efficacy in inflammatory bowel disease.

For decades, variability in clinical efficacy of the widely used inflammatory bowel disease (IBD) drug 5-aminosalicylic acid (5-ASA) has been attributed, in part, to its acetylation and inactivation by gut microbes. Identification of the responsible microbes and enzyme(s), however, has proved elusive. To uncover the source of this metabolism, we developed a multi-omics workflow combining gut microbiome metagenomics, metatranscriptomics and metabolomics from the longitudinal IBDMDB cohort of 132 controls and patients with IBD. This associated 12 previously uncharacterized microbial acetyltransferases with 5-ASA inactivation, belonging to two protein superfamilies: thiolases and acyl-CoA N-acyltransferases. In vitro characterization of representatives from both families confirmed the ability of these enzymes to acetylate 5-ASA. A cross-sectional analysis within the discovery cohort and subsequent prospective validation within the independent SPARC IBD cohort (n = 208) found three of these microbial thiolases and one acyl-CoA N-acyltransferase to be epidemiologically associated with an increased risk of treatment failure among 5-ASA users. Together, these data address a longstanding challenge in IBD management, outline a method for the discovery of previously uncharacterized gut microbial activities and advance the possibility of microbiome-based personalized medicine.

Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival.

BACKGROUND: Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and whether these methods improved upon conventional statistical approaches. METHODS: Plasma gas chromatography-liquid chromatography mass spectrometry quantified 411 metabolites measured ≤ 72 h of ICU admission in 60 patients with sepsis at a single center (Brigham and Women's Hospital, Boston, USA). Seven ML approaches were trained to differentiate survivors from non-survivors. Model performance predicting 28 day mortality was assessed through internal cross-validation, and innate top-feature (metabolite) selection and rankings were compared across the 7 ML approaches and with conventional statistical methods (logistic regression). Metabolites were consensus ranked by a summary, ensemble ML ranking procedure weighing their contribution to mortality risk prediction across multiple ML models. RESULTS: Median (IQR) patient age was 58 (47, 62) years, 45% were women, and median (IQR) SOFA score was 9 (6, 12). Mortality at 28 days was 42%. The models' specificity ranged from 0.619 to 0.821. Partial least squares regression-discriminant analysis and nearest shrunken centroids prioritized the greatest number of metabolites identified by at least one other method. Penalized logistic regression demonstrated top-feature results that were consistent with many ML methods. Across the plasma metabolome, the 13 metabolites with the strongest linkage to mortality defined through an ensemble ML importance score included lactate, bilirubin, kynurenine, glycochenodeoxycholate, phenylalanine, and others. Four of these top 13 metabolites (3-hydroxyisobutyrate, indoleacetate, fucose, and glycolithocholate sulfate) have not been previously associated with sepsis survival. Many of the prioritized metabolites are constituents of the tryptophan, pyruvate, phenylalanine, pentose phosphate, and bile acid pathways. CONCLUSIONS: We identified metabolites linked with sepsis survival, some confirming prior observations, and others representing new associations. The application of ensemble ML feature-ranking tools to metabolomic data may represent a promising statistical platform to support biologic target discovery.

Ketogenic HMG-CoA lyase and its product ß-hydroxybutyrate promote pancreatic cancer progression.

Pancreatic ductal adenocarcinoma (PDA) tumor cells are deprived of oxygen and nutrients and therefore must adapt their metabolism to ensure proliferation. In some physiological states, cells rely on ketone bodies to satisfy their metabolic needs, especially during nutrient stress. Here, we show that PDA cells can activate ketone body metabolism and that ß-hydroxybutyrate (ßOHB) is an alternative cell-intrinsic or systemic fuel that can promote PDA growth and progression. PDA cells activate enzymes required for ketogenesis, utilizing various nutrients as carbon sources for ketone body formation. By assessing metabolic gene expression from spontaneously arising PDA tumors in mice, we find HMG-CoA lyase (HMGCL), involved in ketogenesis, to be among the most deregulated metabolic enzymes in PDA compared to normal pancreas. In vitro depletion of HMGCL impedes migration, tumor cell invasiveness, and anchorage-independent tumor sphere compaction. Moreover, disrupting HMGCL drastically decreases PDA tumor growth in vivo, while ßOHB stimulates metastatic dissemination to the liver. These findings suggest that ßOHB increases PDA aggressiveness and identify HMGCL and ketogenesis as metabolic targets for limiting PDA progression.

Model Systems to Study the Chronic, Polymicrobial Infections in Cystic Fibrosis: Current Approaches and Exploring Future Directions.

A recent workshop titled "Developing Models to Study Polymicrobial Infections," sponsored by the Dartmouth Cystic Fibrosis Center (DartCF), explored the development of new models to study the polymicrobial infections associated with the airways of persons with cystic fibrosis (CF). The workshop gathered 35+ investigators over two virtual sessions. Here, we present the findings of this workshop, summarize some of the challenges involved with developing such models, and suggest three frameworks to tackle this complex problem. The frameworks proposed here, we believe, could be generally useful in developing new model systems for other infectious diseases. Developing and validating new approaches to study the complex polymicrobial communities in the CF airway could open windows to new therapeutics to treat these recalcitrant infections, as well as uncovering organizing principles applicable to chronic polymicrobial infections more generally.

Dissecting cell-type-specific metabolism in pancreatic ductal adenocarcinoma.

Tumors are composed of many different cell types including cancer cells, fibroblasts, and immune cells. Dissecting functional metabolic differences between cell types within a mixed population can be challenging due to the rapid turnover of metabolites relative to the time needed to isolate cells. To overcome this challenge, we traced isotope-labeled nutrients into macromolecules that turn over more slowly than metabolites. This approach was used to assess differences between cancer cell and fibroblast metabolism in murine pancreatic cancer organoid-fibroblast co-cultures and tumors. Pancreatic cancer cells exhibited increased pyruvate carboxylation relative to fibroblasts, and this flux depended on both pyruvate carboxylase and malic enzyme 1 activity. Consequently, expression of both enzymes in cancer cells was necessary for organoid and tumor growth, demonstrating that dissecting the metabolism of specific cell populations within heterogeneous systems can identify dependencies that may not be evident from studying isolated cells in culture or bulk tissue.

Tumors contain a mixture of many different types of cells, including cancer cells and non-cancer cells. The interactions between these two groups of cells affect how the cancer cells use nutrients, which, in turn, affects how fast these cells grow and divide. Furthermore, different cell types may use nutrients in diverse ways to make other molecules ­ known as metabolites ­ that the cell needs to survive. Fibroblasts are a subset of non-cancer cells that are typically found in tumors and can help them form. Separating fibroblasts from cancer cells in a tumor takes a lot longer than the chemical reactions in each cell of the tumor that produce and use up nutrients, also known as the cell's metabolism. Therefore, measuring the levels of glucose (the sugar that is the main energy source for cells) and other metabolites in each tumor cell after separating them does not necessarily provide accurate information about the tumor cell's metabolism. This makes it difficult to study how cancer cells and fibroblasts use nutrients differently. Lau et al. have developed a strategy to study the metabolism of cancer cells and fibroblasts in tumors. Mice with tumors in their pancreas were provided glucose that had been labelled using biochemical techniques. As expected, when the cell processed the glucose, the label was transferred into metabolites that got used up very quickly. But the label also became incorporated into larger, more stable molecules, such as proteins. Unlike the small metabolites, these larger molecules do not change in the time it takes to separate the cancer cells from the fibroblasts. Lau et al. sorted cells from whole pancreatic tumors and analyzed large, stable molecules that can incorporate the label from glucose in cancer cells and fibroblasts. The experiments showed that, in cancer cells, these molecules were more likely to have labeling patterns that are characteristic of two specific enzymes called pyruvate carboxylase and malic enzyme 1. This suggests that these enzymes are more active in cancer cells. Lau et al. also found that pancreatic cancer cells needed these two enzymes to metabolize glucose and to grow into large tumors. Pancreatic cancer is one of the most lethal cancers and current therapies offer limited benefit to many patients. Therefore, it is important to develop new drugs to treat this disease. Understanding how cancer cells and non-cancer cells in pancreatic tumors use nutrients differently is important for developing drugs that only target cancer cells.

Transaminase Inhibition by 2-Hydroxyglutarate Impairs Glutamate Biosynthesis and Redox Homeostasis in Glioma.

IDH1 mutations are common in low-grade gliomas and secondary glioblastomas and cause overproduction of (R)-2HG. (R)-2HG modulates the activity of many enzymes, including some that are linked to transformation and some that are probably bystanders. Although prior work on (R)-2HG targets focused on 2OG-dependent dioxygenases, we found that (R)-2HG potently inhibits the 2OG-dependent transaminases BCAT1 and BCAT2, likely as a bystander effect, thereby decreasing glutamate levels and increasing dependence on glutaminase for the biosynthesis of glutamate and one of its products, glutathione. Inhibiting glutaminase specifically sensitized IDH mutant glioma cells to oxidative stress in vitro and to radiation in vitro and in vivo. These findings highlight the complementary roles for BCATs and glutaminase in glutamate biosynthesis, explain the sensitivity of IDH mutant cells to glutaminase inhibitors, and suggest a strategy for maximizing the effectiveness of such inhibitors against IDH mutant gliomas.

Altered exocrine function can drive adipose wasting in early pancreatic cancer.

Malignancy is accompanied by changes in the metabolism of both cells and the organism1,2. Pancreatic ductal adenocarcinoma (PDAC) is associated with wasting of peripheral tissues, a metabolic syndrome that lowers quality of life and has been proposed to decrease survival of patients with cancer3,4. Tissue wasting is a multifactorial disease and targeting specific circulating factors to reverse this syndrome has been mostly ineffective in the clinic5,6. Here we show that loss of both adipose and muscle tissue occurs early in the development of pancreatic cancer. Using mouse models of PDAC, we show that tumour growth in the pancreas but not in other sites leads to adipose tissue wasting, suggesting that tumour growth within the pancreatic environment contributes to this wasting phenotype. We find that decreased exocrine pancreatic function is a driver of adipose tissue loss and that replacement of pancreatic enzymes attenuates PDAC-associated wasting of peripheral tissues. Paradoxically, reversal of adipose tissue loss impairs survival in mice with PDAC. When analysing patients with PDAC, we find that depletion of adipose and skeletal muscle tissues at the time of diagnosis is common, but is not associated with worse survival. Taken together, these results provide an explanation for wasting of adipose tissue in early PDAC and suggest that early loss of peripheral tissue associated with pancreatic cancer may not impair survival.

Collagen-derived proline promotes pancreatic ductal adenocarcinoma cell survival under nutrient limited conditions.

Tissue architecture contributes to pancreatic ductal adenocarcinoma (PDAC) phenotypes. Cancer cells within PDAC form gland-like structures embedded in a collagen-rich meshwork where nutrients and oxygen are scarce. Altered metabolism is needed for tumour cells to survive in this environment, but the metabolic modifications that allow PDAC cells to endure these conditions are incompletely understood. Here we demonstrate that collagen serves as a proline reservoir for PDAC cells to use as a nutrient source when other fuels are limited. We show PDAC cells are able to take up collagen fragments, which can promote PDAC cell survival under nutrient limited conditions, and that collagen-derived proline contributes to PDAC cell metabolism. Finally, we show that proline oxidase (PRODH1) is required for PDAC cell proliferation in vitro and in vivo. Collectively, our results indicate that PDAC extracellular matrix represents a nutrient reservoir for tumour cells highlighting the metabolic flexibility of this cancer.

Nature and Nurture: What Determines Tumor Metabolic Phenotypes?

Understanding the genetic basis of cancer has led to therapies that target driver mutations and has helped match patients with more personalized drugs. Oncogenic mutations influence tumor metabolism, but other tumor characteristics can also contribute to their metabolic phenotypes. Comparison of isogenic lung and pancreas tumor models suggests that use of some metabolic pathways is defined by lineage rather than by driver mutation. Lung tumors catabolize circulating branched chain amino acids (BCAA) to extract nitrogen for nonessential amino acid and nucleotide synthesis, whereas pancreatic cancer obtains amino acids from catabolism of extracellular protein. These differences in amino acid metabolism translate into distinct pathway dependencies, as genetic disruption of the enzymes responsible for utilization of BCAA nitrogen limits the growth of lung tumors, but not pancreatic tumors. These data argue that some cancer metabolic phenotypes are defined by cancer tissue-of-origin and environment and that these features constrain the influence of genetic mutations on metabolism. A better understanding of the factors defining tumor nutrient utilization could be exploited to help improve cancer therapy. Cancer Res; 77(12); 3131-4. ©2017 AACR.

Direct evidence for cancer-cell-autonomous extracellular protein catabolism in pancreatic tumors.

Mammalian tissues rely on a variety of nutrients to support their physiological functions. It is known that altered metabolism is involved in the pathogenesis of cancer, but which nutrients support the inappropriate growth of intact malignant tumors is incompletely understood. Amino acids are essential nutrients for many cancer cells that can be obtained through the scavenging and catabolism of extracellular protein via macropinocytosis. In particular, macropinocytosis can be a nutrient source for pancreatic cancer cells, but it is not fully understood how the tumor environment influences metabolic phenotypes and whether macropinocytosis supports the maintenance of amino acid levels within pancreatic tumors. Here we utilize miniaturized plasma exchange to deliver labeled albumin to tissues in live mice, and we demonstrate that breakdown of albumin contributes to the supply of free amino acids in pancreatic tumors. We also deliver albumin directly into tumors using an implantable microdevice, which was adapted and modified from ref. 9. Following implantation, we directly observe protein catabolism and macropinocytosis in situ by pancreatic cancer cells, but not by adjacent, non-cancerous pancreatic tissue. In addition, we find that intratumoral inhibition of macropinocytosis decreases amino acid levels. Taken together, these data suggest that pancreatic cancer cells consume extracellular protein, including albumin, and that this consumption serves as an important source of amino acids for pancreatic cancer cells in vivo.

Tissue of origin dictates branched-chain amino acid metabolism in mutant Kras-driven cancers.

Tumor genetics guides patient selection for many new therapies, and cell culture studies have demonstrated that specific mutations can promote metabolic phenotypes. However, whether tissue context defines cancer dependence on specific metabolic pathways is unknown. Kras activation and Trp53 deletion in the pancreas or the lung result in pancreatic ductal adenocarinoma (PDAC) or non-small cell lung carcinoma (NSCLC), respectively, but despite the same initiating events, these tumors use branched-chain amino acids (BCAAs) differently. NSCLC tumors incorporate free BCAAs into tissue protein and use BCAAs as a nitrogen source, whereas PDAC tumors have decreased BCAA uptake. These differences are reflected in expression levels of BCAA catabolic enzymes in both mice and humans. Loss of Bcat1 and Bcat2, the enzymes responsible for BCAA use, impairs NSCLC tumor formation, but these enzymes are not required for PDAC tumor formation, arguing that tissue of origin is an important determinant of how cancers satisfy their metabolic requirements.

Circulating Metabolites and Survival Among Patients With Pancreatic Cancer.

BACKGROUND: Pancreatic tumors cause changes in whole-body metabolism, but whether prediagnostic circulating metabolites predict survival is unknown. METHODS: We measured 82 metabolites by liquid chromatography-mass spectrometry in prediagnostic plasma from 484 pancreatic cancer case patients enrolled in four prospective cohort studies. Association of metabolites with survival was evaluated using Cox proportional hazards models adjusted for age, cohort, race/ethnicity, cancer stage, fasting time, and diagnosis year. After multiple-hypothesis testing correction, a P value of .0006 or less (.05/82) was considered statistically significant. Based on the results, we evaluated 33 tagging single-nucleotide polymorphisms (SNPs) in the ACO1 gene, requiring a P value of less than .002 (.05/33) for statistical significance. All statistical tests were two-sided. RESULTS: Two metabolites in the tricarboxylic acid (TCA) cycle--isocitrate and aconitate--were statistically significantly associated with survival. Participants in the highest vs lowest quintile had hazard ratios (HRs) for death of 1.89 (95% confidence interval [CI] = 1.06 to 3.35, Ptrend < .001) for isocitrate and 2.54 (95% CI = 1.42 to 4.54, Ptrend < .001) for aconitate. Isocitrate is interconverted with citrate via the intermediate aconitate in a reaction catalyzed by the enzyme aconitase 1 (ACO1). Therefore, we investigated the citrate to aconitate plus isocitrate ratio and SNPs in the ACO1 gene. The ratio was strongly associated with survival (P trend < .001) as was the SNP rs7874815 in the ACO1 gene (hazard ratio for death per minor allele = 1.37, 95% CI = 1.16 to 1.61, P < .001). Patients had an approximately three-fold hazard for death when possessing one or more minor alleles at rs7874851 and high aconitate or isocitrate. CONCLUSIONS: Prediagnostic circulating levels of TCA cycle intermediates and inherited ACO1 genotypes were associated with survival among patients with pancreatic cancer.

Famine versus feast: understanding the metabolism of tumors in vivo.

To fuel unregulated proliferation, cancer cells alter metabolism to support macromolecule biosynthesis. Cell culture studies have revealed how different oncogenic mutations and nutrients impact metabolism. Glucose and glutamine are the primary fuels used in vitro; however, recent studies have suggested that utilization of other amino acids as well as lipids and protein can also be important to cancer cells. Early investigations of tumor metabolism are translating these findings to the biology of whole tumors and suggest that additional complexity exists beyond nutrient availability alone in vivo. Whole-body metabolism and tumor heterogeneity also influence the metabolism of tumor cells, and successful targeting of metabolism for cancer therapy will require an understanding of tumor metabolism in vivo.

Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development.

Most patients with pancreatic ductal adenocarcinoma (PDAC) are diagnosed with advanced disease and survive less than 12 months. PDAC has been linked with obesity and glucose intolerance, but whether changes in circulating metabolites are associated with early cancer progression is unknown. To better understand metabolic derangements associated with early disease, we profiled metabolites in prediagnostic plasma from individuals with pancreatic cancer (cases) and matched controls from four prospective cohort studies. We find that elevated plasma levels of branched-chain amino acids (BCAAs) are associated with a greater than twofold increased risk of future pancreatic cancer diagnosis. This elevated risk was independent of known predisposing factors, with the strongest association observed among subjects with samples collected 2 to 5 years before diagnosis, when occult disease is probably present. We show that plasma BCAAs are also elevated in mice with early-stage pancreatic cancers driven by mutant Kras expression but not in mice with Kras-driven tumors in other tissues, and that breakdown of tissue protein accounts for the increase in plasma BCAAs that accompanies early-stage disease. Together, these findings suggest that increased whole-body protein breakdown is an early event in development of PDAC.

Reductive glutamine metabolism is a function of the α-ketoglutarate to citrate ratio in cells.

Reductively metabolized glutamine is a major cellular carbon source for fatty acid synthesis during hypoxia or when mitochondrial respiration is impaired. Yet, a mechanistic understanding of what determines reductive metabolism is missing. Here we identify several cellular conditions where the α-ketoglutarate/citrate ratio is changed due to an altered acetyl-CoA to citrate conversion, and demonstrate that reductive glutamine metabolism is initiated in response to perturbations that result in an increase in the α-ketoglutarate/citrate ratio. Thus, targeting reductive glutamine conversion for a therapeutic benefit might require distinct modulations of metabolite concentrations rather than targeting the upstream signalling, which only indirectly affects the process.