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The urine metabolome constitutes a rich source of functional information reflecting physiological states that are influenced by distinct conditions and biological stresses, such as responses to drug treatments or disease manifestations. Although global liquid chromatography-mass spectrometry (MS) profiling provides the most comprehensive measurement of metabolites in complex biological samples, annotation remains a challenge, and computational approaches are necessary to translate the molecular composition into biological knowledge. Here, we investigated the use of tandem MS-based enhanced molecular networks (MolNetEnhancer) to improve the metabolite annotation of urine extracts. The samples (n = 10) were analyzed by hydrophilic interaction chromatography-quadrupole time-of-flight mass spectrometry in both electrospray ionization (ESI) modes. Consistent with other common data preprocessing software, the use of Progenesis QI led to the annotation of up to 20 metabolites based on MS2 library searches, showing a high fragmentation score (cosine similarity ≥ 0.7), that is, ∼2% of mass features containing MS2 spectra. Molecular networking based on library matching resulted in the annotation of up to 62 urinary compounds. Using a combination of unsupervised substructure discovery (MS2LDA), the in silico tool network annotation propagation (NAP), and ClassyFire chemical ontology, embedded in a multilayered molecular network by MolNetEnhancer, we were able to expand the chemical characterization to ∼50% of the data set. The integrative approach led to the annotation of 275 compounds at the metabolomics standards initiative (MSI) confidence level 2, as well as 459 and 578 urinary metabolites (MSI level 3) in both negative and positive ESI modes, respectively. The exhaustive MS2-based annotation outperformed similar studies applied to larger cohorts while offering the discovery of metabolites not identified by the MS2 library search. This is the first work that effectively integrates orthogonal annotation methods and MS2-based fragmentation studies to improve metabolite annotation in urine samples.

Inorganic polyphosphate (polyP) is a linear polymer composed of up to a few hundred orthophosphates linked together by high-energy phosphoanhydride bonds, identical with those found in ATP. In mammalian mitochondria, polyP has been implicated in multiple processes, including energy metabolism, ion channels function, and the regulation of calcium signaling. However, the specific mechanisms of all these effects of polyP within the organelle remain poorly understood. The central goal of this study was to investigate how mitochondrial polyP participates in the regulation of the mammalian cellular energy metabolism. To accomplish this, we created HEK293 cells depleted of mitochondrial polyP, through the stable expression of the polyP hydrolyzing enzyme (scPPX). We found that these cells have significantly reduced rates of oxidative phosphorylation (OXPHOS), while their rates of glycolysis were elevated. Consistent with this, metabolomics assays confirmed increased levels of metabolites involved in glycolysis in these cells, compared with the wild-type samples. At the same time, key respiratory parameters of the isolated mitochondria were unchanged, suggesting that respiratory chain activity is not affected by the lack of mitochondrial polyP. However, we detected that mitochondria from cells that lack mitochondrial polyP are more fragmented when compared with those from wild-type cells. Based on these results, we propose that mitochondrial polyP plays an important role as a regulator of the metabolic switch between OXPHOS and glycolysis.

Significant advances have been made in unknown metabolite identification and expansion of the number of quantifiable metabolites in human plasma, serum, and whole blood using NMR spectroscopy. However, reliable quantitation of metabolites is still a challenge. A major bottleneck is the lack of a suitable internal standard that does not interact with the complex blood sample matrix and also does not overlap with metabolite peaks apart from exhibiting other favorable characteristics. With the goal of addressing this challenge, a comprehensive investigation of fumaric and maleic acids as potential internal standards was made along with a comparison with the conventional standards, TSP (trimethylsilylpropionic acid) and DSS (trimethylsilylpropanesulfonic acid). Both fumaric acid and maleic acid exhibited a surprisingly high performance with a quantitation error

Data quality in global metabolomics is of great importance for biomarker discovery and system biology studies. However, comprehensive metrics and methods to evaluate and compare the data quality of global metabolomics data sets are lacking. In this work, we combine newly developed metrics, along with well-known measures, to comprehensively and quantitatively characterize the data quality across two similar liquid chromatography coupled with mass spectrometry (LC-MS) platforms, with the goal of providing an efficient and improved ability to evaluate the data quality in global metabolite profiling experiments. A pooled human serum sample was run 50 times on two high-resolution LC-QTOF-MS platforms to provide profile and centroid MS data. These data were processed using Progenesis QI software and then analyzed using five important data quality measures, including retention time drift, the number of compounds detected, missing values, and MS reproducibility (2 measures). The detected compounds were fit to a γ distribution versus compound abundance, which was normalized to allow comparison of different platforms. To evaluate missing values, characteristic curves were obtained by plotting the compound detection percentage versus extraction frequency. To characterize reproducibility, the accumulative coefficient of variation (CV) versus the percentage of total compounds detected and intraclass correlation coefficient (ICC) versus compound abundance were investigated. Key findings include significantly better performance using profile mode data compared to centroid mode as well quantitatively better performance from the newer, higher resolution instrument. A summary table of results gives a snapshot of the experimental results and provides a template to evaluate the global metabolite profiling workflow. In total, these measures give a good overall view of data quality in global profiling and allow comparisons of data acquisition strategies and platforms as well as optimization of parameters.

In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics' technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950-Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231-Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings (COVs) within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)classes. Lastly, we demonstrate that the SLA performs isotope correction; a feature that was absent from the original software.

Glutathione is a ubiquitous cellular antioxidant, which is critically required to protect cells from oxidative damage and free radical injury. It is practically impossible to analyze glutathione in its native form after isolation from biological mixtures since the active form (reduced glutathione, GSH) spontaneously gets converted to the oxidized form (oxidized glutathione, GSSG). To address this challenge, numerous highly sensitive detection methods, including mass spectrometry, have been used in conjunction with derivatization to block the oxidation of GSH. Efforts so far to quantitate GSH and GSSG using the nuclear magnetic resonance (NMR) spectroscopy method have remained unsuccessful. With a focus on addressing this challenge, in this study, we describe an extension to our recent whole blood analysis method [ Anal. Chem. 2017, 89, 4620-4627] that includes the important antioxidants GSH and GSSG. Fresh and frozen human whole blood specimens as well as standard GSH and GSSG were comprehensively investigated using NMR without and with derivatization using N-ethylmaleimide (NEM). NMR experiments detect two diastereomers, distinctly, for the derivatized GSH and enable the analysis of both GSH and GSSG in human whole blood with an accuracy of >99%. Interestingly, the excess (unreacted) NEM used for blocking the GSH can be removed from the samples during a drying step after extraction, with no need for additional processing. This is an important characteristic that offers an added advantage for simultaneous analysis of the antioxidants (GSH and GSSG), redox coenzymes (oxidized nicotinamide adenine dinucleotide (NAD+), reduced nicotinamide adenine dinucleotide (NADH), oxidized nicotinamide adenine dinucleotide phosphate (NADP+), reduced nicotinamide adenine dinucleotide phosphate (NADPH)), energy coenzymes (adenosine 5'-triphosphate (ATP), adenosine 5'-diphosphate (ADP), adenosine 5'-monophosphate (AMP)), and a large number of other blood metabolites using the same one-dimensional (1D) NMR spectrum. The presented method broadens the scope of global metabolite profiling and adds a new dimension to NMR-based blood metabolomics. Further, the method demonstrated here for human blood can be extended to virtually any biological specimen.

Altered lipid metabolism has emerged as an important feature of ovarian cancer (OC), yet the translational potential of lipid metabolites to aid in diagnosis and triage remains unproven. We conducted a multi-level interrogation of lipid metabolic phenotypes in patients with adnexal masses, integrating quantitative lipidomics profiling of plasma and ascites with publicly-available tumor transcriptome data. Using Sciex Lipidyzer, we assessed concentrations of > 500 plasma lipids in two patient cohorts—(i) a pilot set of 100 women with OC (50) or benign tumor (50), and (ii) an independent set of 118 women with malignant (60) or benign (58) adnexal mass. 249 lipid species and several lipid classes were significantly reduced in cases versus controls in both cohorts (FDR –5). Certain lipids exhibited greater alterations in early- (diacylglycerols) or late-stage (lysophospholipids) cases, and multiple lipids in plasma and ascites were positively correlated. Lipoprotein receptor gene expression differed markedly in OC versus benign tumors. Importantly, several plasma lipid species, such as DAG(16:1/18:1), improved the accuracy of CA125 in differentiating early-stage OC cases from benign controls, and conferred a 15–20% increase in specificity at 90% sensitivity in multivariate models adjusted for age and BMI. This study provides novel insight into systemic and local lipid metabolic differences between OC and benign disease, further implicating altered lipid uptake in OC biology, and advancing plasma lipid metabolites as a complementary class of circulating biomarkers for OC diagnosis and triage.

Consumption of dietary lignans has been associated with reduced risk of chronic diseases, although the underlying mechanisms are unclear. We sought to determine if urinary excretion of ENL, the predominant microbial metabolite of dietary lignans, was associated with plasma protein abundance using a cross-sectional design based on data and plasma collected from 80 healthy participants in a randomized crossover, controlled feeding study. Proteomic analysis was performed on plasma samples collected at the end of each of two diet periods (160 samples total) using a customized antibody array corresponding to 2072 unique proteins. GC-MS was used to measure ENL excretion in 24-h urine samples collected in tandem with plasma. Linear mixed models tested the association between urinary enterolignan excretion and plasma protein abundance. Subsequently, over-representation analysis was conducted considering 17 a priori pathways with putative associations with enterolignan bioactivity in an exploratory approach. Controlling the false discovery rate at 10%, ENL excretion was inversely associated with seven proteins (FCRL5, PSCA, GAB1, LAPTM5, CCS, REG4, CEACAM1), and positively associated with two proteins (WAS and FBLN5). Over-representation analysis revealed associations of ENL excretion with estrogen and TNF signaling pathways, which were not significant after adjustment for false discovery. These ENL-associated proteins and pathways have potential implications in cancer prevention.

In metabolomics, pathway analysis normally refers to analysis of a pre-defined sets of metabolites (metabolite set) associated to the metabolic pathways. The metabolite set analysis is useful to facilitate biological interpretation of metabolomics data. The currently available methods may be divided into three generations: over-representation analysis, functional class scoring, and network topology analysis. Among the three generations of tools, the network topology methods have been shown to have lower false discovery rates and better biological interpretability than the other two earlier generations of tools. However, most of the current network topology methods focus the analysis only at the metabolite-level network. The interaction between pathways are not taken into consideration. To address this issue, we propose a new metabolite sets association network (MSAN) modelling scheme. In the developed method, the metabolite sets are defined based on the KEGG databases. By using the metabolite sets as vertexes, the MSAN network evaluated the relationships between pairs of metabolite sets based on their mutual information. The impact of a single metabolite set on the overall network was evaluated by the MSAN network, which may help to uncover differential metabolite sets relevant to the underlying biology mechanism of the study. A metabolomic dataset from a published colorectal cancer (CRC) study is used to evaluate the performance of MSAN network to identify perturbed metabolite sets in colorectal cancer patients. The current results are compared to that of two commonly used methods, NetGSA and MetaboAnalyst, which are based on the metabolite-level network approach. The current method highlights a number of metabolites sets consistent with recent published CRC reports. Taken together, the proposed method may provide an alternative tool for the identification of dysregulated pathways and facilitate biological interpretation of metabolomics data.

Background/Aims Patients with irritable bowel syndrome (IBS) often report poor sleep quality. Whether poor sleep is associated with tryptophan (Trp) metabolites is unknown. We compared serum Trp metabolites in women with IBS and healthy controls (HCs) using targeted liquid chromatography mass spectrometry (LC-MS)-based profiling. In IBS only, we explored whether Trp metabolites are associated with IBS symptoms and subjective and objective sleep indices, serum cortisol, plasma adrenocorticotropic hormone (ACTH), and cortisol/ACTH levels. Methods Blood samples were obtained every 80 minutes in 21 HCs and 38 IBS subjects following an anticipation-of-public-speaking stressor during a sleep laboratory protocol. Subjects completed symptom diaries for 28 days. Adjacent values of metabolites were averaged to represent 4 time-periods: awake, early sleep, mid-sleep, and mid-to-late sleep. Thirteen of 20 targeted Trp metabolites were identified. Results Ten of 13 Trp metabolites decreased across the night, while nicotinamide increased in both groups. A MANOVA omnibus test performed after principal component analysis showed a significant difference in these 13 principal component (P = 0.014) between groups. Compared to HCs, nicotinamide levels were higher and indole-3-lactic acid levels lower in the IBS group. Melatonin and indole-3-acetic acid levels were associated with several subjective/objective sleep measures; decreased stool consistency/frequency and abdominal pain were positively associated with melatonin and serotonin in the IBS group. The kynurenine and kynurenic acid were associated with ACTH (positively) and cortisol/ACTH (negatively). Conclusions Nighttime Trp metabolites may provide clues to poor sleep and stress with IBS. Further study of the mechanism of metabolite action is warranted.

BACKGROUND: Low–glycemic load dietary patterns, characterized by consumption of whole grains, legumes, fruits, and vegetables, are associated with reduced risk of several chronic diseases. METHODS: Using samples from a randomized, controlled, crossover feeding trial, we evaluated the effects on metabolic profiles of a low-glycemic whole-grain dietary pattern (WG) compared with a dietary pattern high in refined grains and added sugars (RG) for 28 d. LC-MS-based targeted metabolomics analysis was performed on fasting plasma samples from 80 healthy participants (n = 40 men, n = 40 women) aged 18–45 y. Linear mixed models were used to evaluate differences in response between diets for individual metabolites. Kyoto Encyclopedia of Genes and Genomes (KEGG)–defined pathways and 2 novel data-driven analyses were conducted to consider differences at the pathway level. RESULTS: There were 121 metabolites with detectable signal in >98% of all plasma samples. Eighteen metabolites were significantly different between diets at day 28 [false discovery rate (FDR)

Mitochondrial trifunctional protein deficiency, due to mutations in hydratase subunit A (HADHA), results in sudden infant death syndrome with no cure. To reveal the disease etiology, we generated stem cell-derived cardiomyocytes from HADHA-deficient hiPSCs and accelerated their maturation via an engineered microRNA maturation cocktail that upregulated the epigenetic regulator, HOPX. Here we report, matured HADHA mutant cardiomyocytes treated with an endogenous mixture of fatty acids manifest the disease phenotype: defective calcium dynamics and repolarization kinetics which results in a pro-arrhythmic state. Single cell RNA-seq reveals a cardiomyocyte developmental intermediate, based on metabolic gene expression. This intermediate gives rise to mature-like cardiomyocytes in control cells but, mutant cells transition to a pathological state with reduced fatty acid beta-oxidation, reduced mitochondrial proton gradient, disrupted cristae structure and defective cardiolipin remodeling. This study reveals that HADHA (tri-functional protein alpha), a monolysocardiolipin acyltransferase-like enzyme, is required for fatty acid beta-oxidation and cardiolipin remodeling, essential for functional mitochondria in human cardiomyocytes.

Polybrominated diphenyl ethers (PBDEs) are persistent environmental toxicants associated with increased risk for metabolic syndrome. Intermediary metabolism is influenced by the intestinal microbiome. To test the hypothesis that PBDEs reduce host-beneficial intermediary metabolites in an intestinal microbiome–dependent manner, 9-week old male conventional (CV) and germ-free (GF) C57BL/6 mice were orally gavaged once daily with vehicle, BDE-47, or BDE-99 (100 μmol/kg) for 4 days. Intestinal microbiome (16S rDNA sequencing), liver transcriptome (RNA-Seq), and intermediary metabolites in serum, liver, as well as small and large intestinal contents (SIC and LIC; LC-MS) were examined. Changes in intermediary metabolite abundances in serum, liver, and SIC, were observed under basal conditions (CV vs. GF mice) and by PBDE exposure. PBDEs altered the largest number of metabolites in the LIC; most were regulated by PBDEs in GF conditions. Importantly, intestinal microbiome was necessary for PBDE-mediated decreases in branched-chain and aromatic amino acid metabolites, including 3-indolepropionic acid, a tryptophan metabolite recently shown to be protective against inflammation and diabetes. Gene-metabolite networks revealed a positive association between the hepatic glycan synthesis gene α-1,6-mannosyltransferase (Alg12) mRNA and mannose, which are important for protein glycosylation. Glycome changes have been observed in patients with metabolic syndrome. In LIC of CV mice, 23 bacterial taxa were regulated by PBDEs. Correlations of certain taxa with distinct serum metabolites further highlight a modulatory role of the microbiome in mediating PBDE effects. In summary, PBDEs impact intermediary metabolism in an intestinal microbiome–dependent manner, suggesting that dysbiosis may contribute to PBDE-mediated toxicities that include metabolic syndrome.

Objectives: Despite the widespread use of manganese (Mn) in industrial settings and its association with adverse neurological outcomes, a validated and reliable biomarker for Mn exposure is still elusive. Here, we utilize targeted metabolomics to investigate metabolic differences between Mn-exposed and -unexposed workers, which could inform a putative biomarker for Mn and lead to increased understanding of Mn toxicity.Methods: End of shift spot urine samples collected from Mn exposed (n = 17) and unexposed (n = 15) workers underwent a targeted assay of 362 metabolites using LC-MS/MS; 224 were quantified and retained for analysis. Differences in metabolite abundances between exposed and unexposed workers were tested with a Benjamini-Hochberg adjusted Wilcoxon Rank-Sum test. We explored perturbed pathways related to exposure using a pathway analysis.Results: Seven metabolites were significantly differentially abundant between exposed and unexposed workers (FDR ≤ 0.1), including n-isobutyrylglycine, cholic acid, anserine, beta-alanine, methionine, n-isovalerylglycine, and threonine. Three pathways were significantly perturbed in exposed workers and had an impact score >0.5: beta-alanine metabolism, histidine metabolism, and glycine, serine, and threonine metabolism.Conclusion: This is one of few studies utilizing targeted metabolomics to explore differences between Mn-exposed and -unexposed workers. Metabolite and pathway analysis showed amino acid metabolism was perturbed in these Mn-exposed workers. Amino acids have also been shown to be perturbed in other occupational cohorts exposed to Mn. Additional research is needed to characterize the biological importance of amino acids in the Mn exposure-disease continuum, and to determine how to appropriately utilize and interpret metabolomics data collected from occupational cohorts.

BACKGROUND: Following trauma, persistent inflammation, immunosuppression, and catabolism may characterize delayed recovery or failure to recover. Understanding the metabolic response associated with these adverse outcomes may facilitate earlier identification and intervention. We characterized the metabolic profiles of trauma victims who died or developed chronic critical illness (CCI) and hypothesized that differences would be evident within 1-week postinjury. METHODS: Venous blood samples from trauma victims with shock who survived at least 7 days were analyzed using mass spectrometry. Subjects who died or developed CCI (intensive care unit length of stay of ≥14 days with persistent organ dysfunction) were compared with subjects who recovered rapidly (intensive care unit length of stay, ≤7 days) and uninjured controls. We used partial least squares discriminant analysis, t tests, linear mixed effects regression, and pathway enrichment analyses to make broad comparisons and identify differences in metabolite concentrations and pathways. RESULTS: We identified 27 patients who died or developed CCI and 33 who recovered rapidly. Subjects were predominantly male (65%) with a median age of 53 years and Injury Severity Score of 36. Healthy controls (n = 48) had similar age and sex distributions. Overall, from the 163 metabolites detected in the samples, 56 metabolites and 21 pathways differed between injury outcome groups, and partial least squares discriminant analysis models distinguished injury outcome groups as early as 1-day postinjury. Differences were observed in tryptophan, phenylalanine, and tyrosine metabolism; metabolites associated with oxidative stress via methionine metabolism; inflammatory mediators including kynurenine, arachidonate, and glucuronic acid; and products of the gut microbiome including indole-3-propionate. CONCLUSIONS: The metabolic profiles in subjects who ultimately die or develop CCI differ from those who have recovered. In particular, we have identified differences in markers of inflammation, oxidative stress, amino acid metabolism, and alterations in the gut microbiome. Targeted metabolomics has the potential to identify important metabolic changes postinjury to improve early diagnosis and targeted intervention. LEVEL OF EVIDENCE: Prognostic/epidemiologic, level III.

Background Heart disease is a frequent cause of hospitalization and mortality for elderly patients. A common feature of both heart disease and aging itself is the involvement of metabolic organ alterations ultimately leading to changes in circulating metabolite levels. However, the specific contribution of aging and ischemic injury to the metabolic dysregulation occurring in older adults with ischemic heart disease is still unknown. Aim To evaluate the effects of aging and ischemia/reperfusion (I/R) injury on plasma metabolomic profiling in mice. Methods Young and aged mice were subjected to a minimally invasive model of I/R injury or sham operation. Complete evaluation of cardiac function and untargeted plasma metabolomics analysis were performed. Results We confirmed that aged mice from the sham group had impaired cardiac function and augmented left ventricular (LV) dimensions compared to young sham‐operated mice. Further, we found that ischemic injury did not drastically reduce LV systolic/diastolic function and dyssynchrony in aged compared to young mice. Using an untargeted metabolomics approach focused on aqueous metabolites, we found that ischemic injury does not affect the plasma metabolomic profile either in young or old mice. Our data also demonstrate that age significantly affects circulating metabolite levels (predominantly amino acids, phospholipids and organic acids) and perturbs several pathways involved in amino acid, glucid and nucleic acid metabolism as well as pyridoxal‐5′‐phosphate salvage pathway in both sham and ischemic mice. Conclusions Our approach increases our understanding of age‐associated plasma metabolomic signatures in mice with and without heart disease excluding confounding factors related to metabolic comorbidities., Studying the intersection between aging and heart disease is a key research area as cardiac dysfunction is a common cause of death in older adults. In our study, we evaluated plasma metabolomic profiling in young and old mice subjected to myocardial ischemia/reperfusion or sham operation. Our results confirmed unique metabolomic features of aging and showed that ischemic injury did not affect plasma metabolomic profile neither in young nor old mice.

Cells culturing on different synthetic biomaterials would reprogram cell metabolism for adaption to their living conditions because such alterations in cell metabolism were necessary for cellular functions on them. Here we used metabolomics to uncover metabolic changes when liver cells were cultured on IGF/TNF-α and chargeable polymers co-modified biomaterials with the aim to explain their modulating effects on cell metabolism. The results showed that cell metabolism on IGF-1/TNF-α co-immobilized conjugates was significantly regulated according to their scatterings on the score plot of principal component analysis (PCA). Specifically, cell metabolisms were reprogrammed to the higher level of pyrimidine metabolism, β-alanine metabolism and pantothenate and CoA biosynthesis and the lower level of methionine salvage pathway in order to promote cell growth on IGF/TNF-α co-modified surface. Furthermore, cell senescence on PSt-PAAm-IGF/TNF-α surface was delayed through the regulation of branch amino acid metabolism and AMPK signal pathway. The research showed that metabolomics had great potentials to uncover the molecular interaction between biomaterials and seeded cells and provide the insights about cell metabolic reprogramming on IGF/TNF-α co-modified conjugates for cell growth. This article is protected by copyright. All rights reserved.

PURPOSE: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-hour urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). METHODS: A 2-week controlled feeding study mimicking the participants’ habitual diets was conducted among 153 postmenopausal women from the Women’s Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct injection based quantitative lipidomics platform. Urinary metabolites were analyzed using (1)H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R(2)) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3% and 37.1% respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R(2) reached 55.5% for energy (kcal/d), 52.0% and 45.0% for protein (g/d, %E), 55.9% and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, gives a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disorder. High bile acid (BA) profiles have been associated with abdominal pain symptoms, mucosal inflammation, and diarrhea in a subgroup of those with IBS. The purpose of this study was to compare: 1) fecal primary and secondary BAs in women with and without IBS; and 2) symptoms, gut microbiome, and diet between women with high and normal BAs (i.e., similar to healthy [HC] women). Women (ages 18–45) with IBS and HCs were recruited from healthcare providers or the community. Participants kept a 28-day symptom diary, completed a 3-day food journal, and collected a stool sample for microbiome analysis (16 S rRNA gene sequencing). Primary and secondary BA levels were determined by mass spectrometry. Primary BAs did not differ between IBS (n = 45) and HC (n = 28) groups; women with IBS had significantly increased conjugated secondary BAs (glycodeoxycholic acid [ p = 0.006], taurodeoxycholic acid [ p = 0.006], and glycolithocholic acid [ p = 0.01]). Sixty percent of women with IBS had normal BAs whereas 40% had high BAs. Women with high fecal BAs were predominantly IBS-Diarrhea or IBS-Mixed and consumed less fiber and vegetable protein and more animal protein compared to women with IBS whose fecal BAs levels were comparable to HCs. Those with high conjugated secondary fecal BAs also had a greater Firmicutes/Bacteroidetes ratio, less abundance of phylum Bacteroidetes and genus Gemmiger, and more abundance of family Erysipelotrichaceae compared to IBS women with normal BAs. Determination of fecal BA levels provides additional insights into pathophysiological links between diet and microbiome in IBS.

Plant lignans and their microbial metabolites, e.g., enterolactone (ENL), may affect bile acid (BA) metabolism through interaction with hepatic receptors. We evaluated the effects of a flaxseed lignan extract (50 mg/day secoisolariciresinol diglucoside) compared to a placebo for 60 days each on plasma BA concentrations in 46 healthy men and women (20&ndash, 45 years) using samples from a completed randomized, crossover intervention. Twenty BA species were measured in fasting plasma using LC-MS. ENL was measured in 24-h urines by GC-MS. We tested for a) effects of the intervention on BA concentrations overall and stratified by ENL excretion, and b) cross-sectional associations between plasma BA and ENL. We also explored the overlap in bacterial metabolism at the genus level and conducted in vitro anaerobic incubations of stool with lignan substrate to identify genes that are enriched in response to lignan metabolism. There were no intervention effects, overall or stratified by ENL at FDR &lt, 0.05. In the cross-sectional analysis, irrespective of treatment, five secondary BAs were associated with ENL excretion (FDR &lt, 0.05). In vitro analyses showed positive associations between ENL production and bacterial gene expression of the bile acid-inducible gene cluster and hydroxysteroid dehydrogenases. These data suggest overlap in community bacterial metabolism of secondary BA and ENL.

Absolute quantitation is a major challenge in metabolomics. Previously, we [ Nagana Gowda et al. Anal. Chem. 2018 , 90 , 2001 - 2009 ] showed that nuclear magnetic resonance (NMR) spectroscopy can guide absolute quantitation using mass spectrometry (MS); however, this method does not account for the matrix effect in MS measurements. To surmount this challenge, we have developed a novel method, qNMR-MS, for the absolute quantitation of metabolites using MS by combining it with NMR and chemical derivatization. Metabolite concentrations are first obtained using NMR for a reference sample. Subsequently, both reference and study samples are chemically derivatized with isotope-labeled and unlabeled reagents, respectively. The derivatized reference sample is then mixed with study samples and measured using MS. Comparison of paired isotope unlabeled and labeled MS peaks enables absolute quantitation with virtually no matrix effects. As a proof of concept, we applied the qNMR-MS method for absolute quantitation of amino acids using propyl-chloroformate (PCF) derivatization. For standards, the observed coefficients of determination ( R2) of most amino acids were greater than 0.99 across concentrations of 0.2 to 20 uM. For human serum, the results of the qNMR-MS method are comparable to the conventional isotope-labeled internal standard (iSTD) method ( R2 ≥ 0.99), with an average median coefficient of variation (CV) of 5.45%. The qNMR-MS method is relatively simple, highly quantitative, has high cost-efficiency (no iSTD required), and offers new avenues for the routine quantitation of amino acids in blood samples; it can, in principle, be extended to a wide variety of metabolites in different biological samples.

OBJECTIVES: Health benefits of high-fiber foods may be attributed, in part, to microbial metabolites of plant compounds. Lignans and their microbial metabolites, the enterolignans [enterolactone (ENL) and enterodiol (END)], reduce serum lipids through a variety of mechanisms, including regulation of bile acid (BA) synthesis. BA, released into the gut lumen in response to dietary fat, undergo microbial metabolism to secondary (2°) BA, which have been positively associated with chronic disease, e.g., liver disease and colorectal cancer. Our aims were to evaluate the effects of a flaxseed lignan supplement on circulating BA and examine associations between enterolignans and 2° BA. METHODS: We conducted a randomized, crossover trial of a flaxseed lignan supplement (50 mg/d secoisolariciresinol diglucoside) compared to placebo in 46 healthy men and women (20-45 y). Each period lasted 60 days, separated by a 60-day washout period. Six primary and fourteen 2° BA species were measured in fasting plasma using LC-MS. ENL and END were measured in 24-h urines by GC-MS. Low- and high-ENL excreters were defined as below and above the median 24-h ENL excretion at the end of the flaxseed lignan intervention (23.4 µmol/24 h). Linear mixed models were used to a) test the effects of the intervention on individual BA concentrations, overall and stratified by low and high ENL excreters; and b) to cross-sectionally determine the association between plasma 2(o) BA and ENL and END. RESULTS: There was no significant effect of the flaxseed lignan intervention compared to placebo on BA concentrations overall, or by ENL-excreter status, after FDR adjustment. In the cross-sectional analysis, irrespective of treatment, six 2° BA were statistically significantly associated with ENL (FDR

Abnormal protein aggregation within neurons is a key pathologic feature of Parkinson’s disease (PD). The spread of brain protein aggregates is associated with clinical disease progression, but how this occurs remains unclear. Mutations in glucosidase, beta acid 1 (GBA), which encodes glucocerebrosidase (GCase), are the most penetrant common genetic risk factor for PD and dementia with Lewy bodies and associate with faster disease progression. To explore how GBA mutations influence pathogenesis, we previously created a Drosophila model of GBA deficiency (Gba1b) that manifests neurodegeneration and accelerated protein aggregation. Proteomic analysis of Gba1b mutants revealed dysregulation of proteins involved in extracellular vesicle (EV) biology, and we found altered protein composition of EVs from Gba1b mutants. Accordingly, we hypothesized that GBA may influence pathogenic protein aggregate spread via EVs. We found that accumulation of ubiquitinated proteins and Ref(2)P, Drosophila homologue of mammalian p62, were reduced in muscle and brain tissue of Gba1b flies by ectopic expression of wildtype GCase in muscle. Neuronal GCase expression also rescued protein aggregation both cell-autonomously in brain and non-cell-autonomously in muscle. Muscle-specific GBA expression reduced the elevated levels of EV-intrinsic proteins and Ref(2)P found in EVs from Gba1b flies. Perturbing EV biogenesis through neutral sphingomyelinase (nSMase), an enzyme important for EV release and ceramide metabolism, enhanced protein aggregation when knocked down in muscle, but did not modify Gba1b mutant protein aggregation when knocked down in neurons. Lipidomic analysis of nSMase knockdown on ceramide and glucosylceramide levels suggested that Gba1b mutant protein aggregation may depend on relative depletion of specific ceramide species often enriched in EVs. Finally, we identified ectopically expressed GCase within isolated EVs. Together, our findings suggest that GCase deficiency promotes accelerated protein aggregate spread between cells and tissues via dysregulated EVs, and EV-mediated trafficking of GCase may partially account for the reduction in aggregate spread., Author summary Parkinson’s disease (PD) is a common neurodegenerative disease characterized by abnormal clumps of proteins (aggregates) within the brain and other tissues which can lead to cellular dysfunction and death. Mutations in the gene GBA, which encodes glucocerebrosidase (GCase), are the strongest genetic risk factor for PD, and are associated with faster disease progression. GCase-deficient mutant flies display features suggestive of PD including increased protein aggregation in brain and muscle. We found that restoring GCase protein in the muscle of mutant flies reduced protein aggregation in muscle and the brain, suggesting a mechanism involving interaction between tissues. Previous work indicated that GBA influences extracellular vesicles (EVs)–small membrane-bound structures released by cells to communicate and/or transport cargo from cell to cell. Here, we found increased aggregated proteins within EVs of mutant flies, which was reduced by restoring GCase in muscle. In addition, we found GCase within the EVs, possibly explaining how GCase in one tissue such as muscle could reduce protein aggregation in a distant tissue like the brain. Our findings suggest that GCase influences proteins within EVs, affecting the spread of protein aggregation. This may be important to understanding PD progression and could uncover new targets to slow neurodegeneration.

Breast cancer (BC) is a major cause of human morbidity and mortality, especially among women. Despite the important role of metabolism in the molecular pathogenesis of cancer, robust metabolic markers to enable enhanced screening and disease monitoring of BC are still critically needed. In this study, a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolic profiling approach is presented for the identification of metabolic marker candidates that could enable highly sensitive and specific detection of all-stage as well as early-stage BC. In this targeted approach, 105 metabolites from >35 metabolic pathways of potential biological relevance were reliably detected in 201 plasma samples taken from two groups of subjects (102 BC patients and 99 healthy controls). The results of our general linear model and partial least squares-discriminant analysis (PLS-DA) informed the construction of a novel 6-metabolite panel of potential biomarkers. A receiver operating characteristic (ROC) curve generated based on an improved PLS-DA model showed relatively high sensitivity (0.80), specificity (0.75), and area under the receiver-operating characteristic curve (AUROC = 0.89). Similar classification performance of the model was observed for detection of early-stage BC (AUROC = 0.87, sensitivity: 0.86, specificity: 0.75). Bioinformatics analyses revealed significant disturbances in arginine/proline metabolism, tryptophan metabolism, and fatty acid biosynthesis. Our univariate and multivariate results indicate the effectiveness of this metabolomics approach for all-stage as well as early-stage BC diagnosis; our bioinformatics results indicate affected pathways related to tumor growth, metastasis, and immune escape mechanisms. Future studies should validate these results using more samples from different locations.

Nonalcoholic fatty liver disease (NAFLD) is categorized based on histological severity into nonalcoholic fatty liver (NAFL) or nonalcoholic steatohepatitis (NASH). We used a multiplatform metabolomics approach to identify metabolite markers and metabolic pathways that distinguish NAFL from early NASH and advanced NASH. We analyzed fasting serum samples from 57 prospectively-recruited patients with histologically-proven NAFLD, including 12 with NAFL, 31 with early NASH and 14 with advanced NASH. Metabolite profiling was performed using a combination of liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy analyzed with multivariate statistical and pathway analysis tools. We targeted 237 metabolites of which 158 were quantified. Multivariate analysis uncovered metabolite profile clusters for patients with NAFL, early NASH, and advanced NASH. Also, multiple individual metabolites were associated with histological severity, most notably spermidine which was more than 2-fold lower in advanced fibrosis vs. early fibrosis, in advanced NASH vs. NAFL and in advanced NASH vs. early NASH, suggesting that spermidine exercises a protective effect against development of fibrosing NASH. Furthermore, the results also showed metabolic pathway perturbations between early-NASH and advanced-NASH. In conclusion, using a combination of two reliable analytical platforms (LC-MS and NMR spectroscopy) we identified individual metabolites, metabolite clusters and metabolic pathways that were significantly different between NAFL, early-NASH, and advanced-NASH. These differences provide mechanistic insights as well as potentially important metabolic biomarker candidates that may noninvasively distinguish patients with NAFL, early-NASH, and advanced-NASH. The associations of spermidine levels with less advanced histology merit further assessment of the potential protective effects of spermidine in NAFLD.

Leigh Syndrome (LS) is a mitochondrial disorder defined by progressive focal neurodegenerative lesions in specific regions of the brain. Defects in NDUFS4, a subunit of complex I of the mitochondrial electron transport chain, cause LS in humans; the Ndufs4 knockout mouse (Ndufs4(KO)) closely resembles the human disease. Here, we probed brain region-specific molecular signatures in pre-symptomatic Ndufs4(KO) to identify factors which underlie focal neurodegeneration. Metabolomics revealed that free amino acid concentrations are broadly different by region, and glucose metabolites are increased in a manner dependent on both region and genotype. We then tested the impact of the mTOR inhibitor rapamycin, which dramatically attenuates LS in Ndufs4(KO), on region specific metabolism. Our data revealed that loss of Ndufs4 drives pathogenic changes to CNS glutamine/glutamate/α-ketoglutarate metabolism which are rescued by mTOR inhibition Finally, restriction of the Ndufs4 deletion to pre-synaptic glutamatergic neurons recapitulated the whole-body knockout. Together, our findings are consistent with mTOR inhibition alleviating disease by increasing availability of α-ketoglutarate, which is both an efficient mitochondrial complex I substrate in Ndufs4(KO) and an important metabolite related to neurotransmitter metabolism in glutamatergic neurons.

Although the gut microbiome has been associated with dietary patterns linked to health, microbial metabolism is not well characterized. This ancillary study was a proof of principle analysis for a novel application of metaproteomics to study microbial protein expression in a controlled dietary intervention. We measured the response of the microbiome to diet in a randomized crossover dietary intervention of a whole-grain, low glycemic load diet (WG) and a refined-grain, high glycemic load diet (RG). Total proteins in stools from 9 participants at the end of each diet period (n = 18) were analyzed by LC MS/MS and proteins were identified using the Human Microbiome Project (HMP) human gut microbiome database and UniProt human protein databases. T-tests, controlling for false discovery rate (FDR) &lt, 10%, were used to compare the Gene Ontology (GO) biological processes and bacterial enzymes between the two interventions. Using shotgun proteomics, more than 53,000 unique peptides were identified including microbial (89%) and human peptides (11%). Forty-eight bacterial enzymes were statistically different between the diets, including those implicated in SCFA production and degradation of fatty acids. Enzymes associated with degradation of human mucin were significantly enriched in the RG diet. These results illustrate that the metaproteomic approach is a valuable tool to study the microbial metabolism of diets that may influence host health.

The gut microbiome regulates important host metabolic pathways including xenobiotic metabolism and intermediary metabolism, such as the conversion of primary bile acids (BAs) into secondary BAs. The nuclear receptors pregnane X receptor (PXR) and constitutive androstane receptor (CAR) are well-known regulators for xenobiotic biotransformation in liver. However, little is known regarding the potential effects of PXR and CAR on the composition and function of the gut microbiome. To test our hypothesis that activation of PXR and CAR regulates gut microbiota and secondary BA synthesis, 9-week-old male conventional and germ-free mice were orally gavaged with corn oil, PXR agonist PCN (75 mg/kg), or CAR agonist TCPOBOP (3 mg/kg) once daily for 4 days. PCN and TCPOBOP decreased two taxa in the Bifidobacterium genus, which corresponded with decreased gene abundance of the BA-deconjugating enzyme bile salt hydrolase. In liver and small intestinal content of germ-free mice, there was a TCPOBOP-mediated increase in total, primary, and conjugated BAs corresponding with increased Cyp7a1 mRNA. Bifidobacterium, Dorea, Peptociccaceae, Anaeroplasma, and Ruminococcus positively correlated with T-UDCA in LIC, but negatively correlated with T-CDCA in serum. In conclusion, PXR and CAR activation downregulates BA-metabolizing bacteria in the intestine and modulates BA homeostasis in a gut microbiota-dependent manner.

Glucose and branched-chain amino acids (BCAAs) are essential nutrients and key determinants of cell growth and stress responses. High BCAA level inhibits glucose metabolism but reciprocal regulation of BCAA metabolism by glucose has not been demonstrated. Here we show that glucose suppresses BCAA catabolism in cardiomyocytes to promote hypertrophic response. High glucose inhibits CREB stimulated KLF15 transcription resulting in downregulation of enzymes in the BCAA catabolism pathway. Accumulation of BCAA through the glucose-KLF15-BCAA degradation axis is required for the activation of mTOR signaling during the hypertrophic growth of cardiomyocytes. Restoration of KLF15 prevents cardiac hypertrophy in response to pressure overload in wildtype mice but not in mutant mice deficient of BCAA degradation gene. Thus, regulation of KLF15 transcription by glucose is critical for the glucose-BCAA circuit which controls a cascade of obligatory metabolic responses previously unrecognized for cell growth., Hypertrophic cardiomyocytes switch their metabolism from fatty acid oxidation to glucose use, but the functional role of this change is unclear. Here the authors show that high intracellular glucose inhibits the degradation of branched-chain amino acids, which is required for the activation of pro-growth mTOR signaling.

Obesity is fast becoming a serious health problem worldwide. Of the many possible antiobesity strategies, one interesting approach focuses on blocking adipocyte differentiation and lipid accumulation to counteract the rise in fat storage. However, there is currently no drug available for the treatment of obesity that works by inhibiting adipocyte differentiation. Here we use a broad-based metabolomics approach to interrogate and better understand metabolic changes that occur during adipocyte differentiation. In particular, we focus on changes induced by the antiadipogenic diarylheptanoid, which was isolated from a traditional Chinese medicine Dioscorea zingiberensis and identified as (3 R,5 R)-3,5-dihydroxy-1-(3,4-dihydroxyphenyl)-7-(4-hydroxyphenyl)-heptane (1). Targeted aqueous metabolic profiling indicated that a total of 14 metabolites involved in the TCA cycle, glycolysis, amino acid metabolism, and purine catabolism participate in regulating energy metabolism, lipogenesis, and lipolysis in adipocyte differentiation and can be modulated by diarylheptanoid 1. As indicated by lipidomics analysis, diarylheptanoid 1 restored the quantity and degree of unsaturation of long-chain free fatty acids and restored the levels of 171 lipids mainly from 10 lipid classes in adipocytes. In addition, carbohydrate metabolism in diarylheptanoid-1-treated adipocytes further demonstrated the delayed differentiation process by flux analysis. Our results provide valuable information for further understanding the metabolic adjustment in adipocytes subjected to diarylheptanoid 1 treatment. Moreover, this study offers new insight into developing antiadipogenic leading compounds based on metabolomics.

Broad-based, targeted metabolite profiling using mass spectrometry (MS) has become a major platform used in the field of metabolomics for a variety of applications. However, quantitative MS analysis is challenging owing to numerous factors including (1) the need for, ideally, isotope-labeled internal standards for each metabolite, (2) the fact that such standards may be unavailable or prohibitively costly, (3) the need to maintain the standards' concentrations close to those of the target metabolites, and (4) the alternative use of time-consuming calibration curves for each target metabolite. Here, we introduce a new method in which metabolites from a single serum specimen are quantified on the basis of a recently developed NMR method [ Nagana Gowda et al. Anal. Chem. 2015 , 87 , 706 ] and then used as references for absolute metabolite quantitation using MS. The MS concentrations of 30 metabolites thus derived for test serum samples exhibited excellent correlations with the NMR ones (R2 > 0.99) with a median CV of 3.2%. This NMR-guided-MS quantitation approach is simple and easy to implement and offers new avenues for the routine quantification of blood metabolites using MS. The demonstration that NMR and MS data can be compared and correlated when using identical sample preparations allows improved opportunities to exploit their combined strengths for biomarker discovery and unknown-metabolite identification. Intriguingly, however, metabolites including glutamine, pyroglutamic acid, glucose, and sarcosine correlated poorly with NMR data because of stability issues in their MS analyses or weak or overlapping signals. Such information is potentially important for improving biomarker discovery and biological interpretations. Further, the new quantitation method demonstrated here for human blood serum can in principle be extended to a variety of biological mixtures.

Artificial nutrition support is central to the care of critically ill patients and is primarily provided enterally (EN). There are circumstances when parenteral nutrition (PN) is considered necessary. We are uncertain how each of these approaches confer clinical benefits beyond simply providing calories. We sought to better understand how each of these techniques influence metabolism in critically ill patients using a broad-based metabolomics approach. Metabolic responses to EN and PN may differ in ways that could help us understand how to optimize use of these therapies.We prospectively enrolled subjects over 7 months in 2015 at an urban, Level I trauma center. Subjects were included before starting either EN or PN during their inpatient admission. Plasma samples were obtained between 1 and 12 hours before initiation of artificial nutrition, and 3 and 7 days later. All samples were analyzed with liquid chromatography/mass spectrometry-based metabolomics. Differences in metabolite concentrations were assessed via principal component analyses and multiple linear regression.We enrolled 30 subjects. Among the critically ill subjects, 10 received EN and 10 received PN. In subjects receiving EN, amino acid and urea cycle metabolites (citrulline, p = 0.04; ornithine, p = 0.05) increased, as did ribonucleic acid metabolites (uridine, p = 0.04; cysteine, 0 = 0.05; oxypurinol, p = 0.04). Oxidative stress decreased over time (increased betaine, p = 0.05; decreased 4-pyridoxic acid, p = 0.04). In subjects receiving PN, amino acid concentrations increased over time (taurine, p = 0.04; phenylalanine, p = 0.05); omega 6 and omega 3 fatty acid concentrations decreased over time (p = 0.05 and 0.03, respectively).EN was associated with amino acid repletion, urea cycle upregulation, restoration of antioxidants, and increasing ribonucleic acid synthesis. Parenteral nutrition was associated with increased amino acid concentrations, but did not influence protein metabolism or antioxidant repletion. This suggests that parenteral amino acids are used less effectively than those given enterally. The biomarkers reported in this study may be useful in guiding nutrition therapy for critically ill patients.Therapeutic study, level III; prognostic study, level II.

Conventional human blood metabolomics employs serum or plasma and provides a wealth of metabolic information therein. However, this approach lacks the ability to measure and evaluate important metabolites such as coenzymes and antioxidants that are present at high concentrations in red blood cells. As an important alternative to serum/plasma metabolomics, we show here that a simple 1H NMR experiment can simultaneously measure coenzymes and antioxidants in extracts of whole human blood, in addition to the nearly 70 metabolites that were shown to be quantitated in serum/plasma recently [ Anal. Chem. 2015 , 87 , 706 - 715 ]. Coenzymes of redox reactions: oxidized/reduced nicotinamide adenine dinucleotide (NAD+ and NADH) and nicotinamide adenine dinucleotide phosphate (NADP+ and NADPH); coenzymes of energy including adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP); and antioxidants, the sum of oxidized and reduced glutathione (GSSG and GSH) can be measured with essentially no additional effort. A new method was developed for detecting many of these unstable species without affecting other blood/blood plasma metabolites. The identities of coenzymes and antioxidants in blood NMR spectra were established combining 1D/2D NMR techniques, chemical shift databases, pH measurements and, finally, spiking with authentic compounds. This is the first study to report identification of major coenzymes and antioxidants and quantify them, simultaneously, with the large pool of other metabolites in human blood using NMR spectroscopy. Considering that the levels of coenzymes and antioxidants represent a sensitive measure of cellular functions in health and numerous diseases, the NMR method presented here potentially opens a new chapter in the metabolomics of blood.

Decline in the skeletal muscle stem cell (MuSC) function is a major contributor to age-associated impairments in muscle regeneration and function. The ability of MuSCs to activate (i.e. exit quiescence, enter the cell cycle, and divide) following injury is a critical step that initiates muscle regeneration. However, the mechanisms that regulate MuSC activation function are poorly understood. Here, we show that the activation function, specifically the speed by which cells progress through G0-G1, declines tremendously with age in mouse MuSCs. Using a number ofin vivomodels andex vivoassays of MuSC activation and muscle regenerative functions, live cell metabolic flux analyses, and metabolomics we present data indicating that changes in MuSC mitochondrial flux underlie age-associated changes in MuSC activation. We show that, in the course of MuSC activation, there is a profound,16-fold, increase in ATP production rates, which is fueled largely by increases in pyruvate flux into mitochondria. We found that MuSCs from aged mice display progressive defects in the ability to increase mitochondrial flux during activation and that this correlates with higher levels of phosphorylated, inactivated, pyruvate dehydrogenase (PDH). Importantly, we demonstrate that pharmacologic and physiologic methods to induce dephosphorylation and activation of PDH in MuSCs are sufficient to rescue the activation and muscle regenerative functions of MuSCs in aged mice. Collectively the data presented show that MuSC mitochondrial function is a central regulator of MuSC activation and muscle regenerative functions. Moreover, our results suggest that approaches to increase MuSC pyruvate oxidation may have therapeutic potential to promote muscle repair and regeneration.

INTRODUCTION: High-fat diets increase risk for Alzheimer’s disease, but individuals with the risk gene APOE ε4 (E4) paradoxically have improved memory soon after high fat feeding. Little is known about how dietary lipids affect CNS lipids, especially in older adults. OBJECTIVES: We analyzed the lipidomic signature of cerebrospinal fluid (CSF) in older adults who underwent both a saline and TG infusion. We further analyzed these data by E4 carrier status. METHODS: Older adults (n = 21, age 67.7 ± 8.6) underwent a 5-h TG and saline infusion on different days in random crossover design; lumbar CSF was collected at the end of the infusion. Lipids were extracted using dichloromethane/methanol and 13 classes of lipids analyzed using the Lipidyzer platform consisting of an AB Sciex 5500 MS/MS QTraps system equipped with a SelexION for differential mobility spectrometry (DMS). Multiple reaction monitoring was used to target and quantify 1070 lipids in positive and negative ionization modes with and without DMS. RESULTS: The TG infusion increased total lipids in the CSF, including the appearance of more lipids at the detection limit in the TG samples compared to saline (Chi square p < 0.0001). The infusion increased the total level of diacylglycerols and lysophosphatidylcholines and reduced dihydroceramides. Of the possible 1070 lipids detectable, we found 348 after saline and 365 after TG infusion. Analysis using MetaboAnalyst revealed 11 specific lipids that changed; five of these lipids decreased after TG infusion, and four of them differed by E4 status, but none differed by cognitive diagnosis or sex. CONCLUSION: These results in older adults show that blood lipids affect lipid profiles in CSF and such profiles are modified by APOE status. This suggests that how the CNS handles lipids may be important in the AD phenotype.

Rationale: Hypertrophied hearts switch from mainly using fatty acids (FAs) to an increased reliance on glucose for energy production. It has been shown that preserving FA oxidation (FAO) prevents the pathological shift of substrate preference, preserves cardiac function and energetics, and reduces cardiomyocyte hypertrophy during cardiac stresses. However, it remains elusive whether substrate metabolism regulates cardiomyocyte hypertrophy directly or via a secondary effect of improving cardiac energetics. Objective: The goal of this study was to determine the mechanisms of how preservation of FAO prevents the hypertrophic growth of cardiomyocytes. Methods and Results: We cultured adult rat cardiomyocytes in a medium containing glucose and mixed-chain FAs and induced pathological hypertrophy by phenylephrine. Phenylephrine-induced hypertrophy was associated with increased glucose consumption and higher intracellular aspartate levels, resulting in increased synthesis of nucleotides, RNA, and proteins. These changes could be prevented by increasing FAO via deletion of ACC2 (acetyl-CoA-carboxylase 2) in phenylephrine-stimulated cardiomyocytes and in pressure overload–induced cardiac hypertrophy in vivo. Furthermore, aspartate supplementation was sufficient to reverse the antihypertrophic effect of ACC2 deletion demonstrating a causal role of elevated aspartate level in cardiomyocyte hypertrophy. 15N and 13C stable isotope tracing revealed that glucose but not glutamine contributed to increased biosynthesis of aspartate, which supplied nitrogen for nucleotide synthesis during cardiomyocyte hypertrophy. Conclusions: Our data show that increased glucose consumption is required to support aspartate synthesis that drives the increase of biomass during cardiac hypertrophy. Preservation of FAO prevents the shift of metabolic flux into the anabolic pathway and maintains catabolic metabolism for energy production, thus preventing cardiac hypertrophy and improving myocardial energetics.

BACKGROUND Acute liver rejection (ALR), a significant complication of liver transplantation, burdens patients, healthcare payers, and the healthcare providers due to an increase in morbidity, cost, and resources. Despite clinical resolution, ALR is associated with an increased risk of graft loss. A unique protocol of delayed immunosuppression used in our institute provided a model to characterize metabolomic profiles in human ALR. MATERIAL AND METHODS Twenty liver allograft biopsies obtained 48 hours after liver transplantation in the absence of immunosuppression were studied. Hepatic metabolites were quantitated in these biopsies by liquid chromatography and mass spectroscopy (LC/MS). Metabolite profiles were compared among: 1) biopsies with reperfusion injury but no histological evidence of rejection (n=7), 2) biopsies with histological evidence of moderate or severe rejection (n=5), and 3) biopsies with histological evidence of mild rejection (n=8). RESULTS There were 133 metabolites consistently detected by LC/MS and these were prioritized using variable importance to projection (VIP) analysis, comparing moderate or severe rejection vs. no rejection or mild rejection using partial least squares discriminant statistical analysis (PLS-DA). Twenty metabolites were identified as progressively different. Further PLS-DA using these metabolites identified 3 metabolites (linoleic acid, γ-linolenic acid, and citrulline) which are associated with either cyclooxygenase or nitric oxide synthase functionality. CONCLUSIONS Hepatic metabolic aberrancies associated with cyclooxygenase and nitric oxide synthase function occur contemporaneous with ALR. Additional studies are required to better characterize the role of these metabolic pathways to enhance utility of the metabolomics approach in diagnosis and outcomes of ALR.

Six strictly anaerobic Gram-negative bacteria representing three novel species were isolated from the female reproductive tract. The proposed type strains for each species were designated UPII 199-6T, KA00182T and BV3C16-1T. Phylogenetic analyses based on 16S rRNA gene sequencing indicated that the bacterial isolates were members of the genus Megasphaera . UPII 199-6T and KA00182T had 16S rRNA gene sequence identities of 99.9 % with 16S rRNA clone sequences previously amplified from the human vagina designated as Megasphaera type 1 and Megasphaera type 2, members of the human vaginal microbiota associated with bacterial vaginosis, preterm birth and HIV acquisition. UPII 199-6T exhibited sequence identities ranging from 92.9 to 93.6 % with validly named Megasphaera isolates and KA00182T had 16S rRNA gene sequence identities ranging from 92.6–94.2 %. BV3C16-1T was most closely related to Megasphaera cerevisiae with a 16S rRNA gene sequence identity of 95.4 %. Cells were coccoid or diplococcoid, non-motile and did not form spores. Genital tract isolates metabolized organic acids but were asaccharolytic. The isolates also metabolized amino acids. The DNA G+C content for the genome sequences of UPII 199-6T, KA00182T and BV3C16-1T were 46.4, 38.9 and 49.8 mol%, respectively. Digital DNA–DNA hybridization and average nucleotide identity between the genital tract isolates and other validly named Megasphaera species suggest that each isolate type represents a new species. The major fatty acid methyl esters include the following: C12 : 0, C16 : 0, C16 : 0 dimethyl acetal (DMA) and summed feature 5 (C15 : 0 DMA and/or C14 : 0 3-OH) in UPII 199-6T; C16 : 0 and C16 : 1 cis 9 in KA00182T; C12 : 0; C14 : 0 3-OH; and summed feature 5 in BV3C16-1T. The isolates produced butyrate, isobutyrate, and isovalerate but there were specific differences including production of formate and propionate. Together, these data indicate that UPII 199-6T, KA00182T and BV3C16-1T represent novel species within the genus Megasphaera . We propose the following names: Megasphaera lornae sp. nov. for UPII 199-6T representing the type strain of this species (=DSM 111201T=ATCC TSD-205T), Megasphaera hutchinsoni sp. nov. for KA00182T representing the type strain of this species (=DSM 111202T=ATCC TSD-206T) and Megasphaera vaginalis sp. nov. for BV3C16-1T representing the type strain of this species (=DSM 111203T=ATCC TSD-207T).

The complexity of biological mixtures continues to challenge efforts aimed at unknown metabolite identification in the metabolomics field. To address this challenge, we provide a new method to identify related peaks from individual metabolites in complex NMR spectra. Extractive ratio analysis NMR spectroscopy (E-RANSY) builds on our previously described ratio analysis method [ Wei et al. Anal. Chem. 2011 , 83 , 7616 - 7623 ] and exploits the simplified NMR spectra provided by the extraction of metabolites under varied pH conditions. Under such conditions, metabolites from the same biological specimen are extracted differentially, and the resulting NMR spectra exhibit characteristics favorable for unraveling unknown metabolite peaks using ratio analysis. We demonstrate the utility of the E-RANSY method by extracting carboxylic acid containing metabolites from human urine, one of the highly complex biological mixtures encountered in the metabolomics field. E-RANSY performs better than STOCSY and the original RANSY method and offers new avenues to identify unknown metabolites in complex biological mixtures.

Sepsis‐associated acute kidney injury (AKI) is a significant problem in critically ill children and adults resulting in increased morbidity and mortality. Fundamental mechanisms contributing to sepsis‐associated AKI are poorly understood. Previous research has demonstrated that peroxisome proliferator‐activated receptor α (PPAR α) expression is associated with reduced organ system failure in sepsis. Using an experimental model of polymicrobial sepsis, we demonstrate that mice deficient in PPAR α have worse kidney function, which is likely related to reduced fatty acid oxidation and increased inflammation. Ultrastructural evaluation with electron microscopy reveals that the proximal convoluted tubule is specifically injured in septic PPAR α deficient mice. In this experimental group, serum metabolomic analysis reveals unanticipated metabolic derangements in tryptophan‐kynurenine‐NAD + and pantothenate pathways. We also show that a subgroup of children with sepsis whose genome‐wide expression profiles are characterized by repression of the PPAR α signaling pathway has increased incidence of severe AKI. These findings point toward interesting associations between sepsis‐associated AKI and PPAR α‐driven fatty acid metabolism that merit further investigation.

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.

Background Controlled human feeding studies are necessary for robust nutritional biomarker development and validation. Previous feeding studies have typically evaluated single nutrients and tested relatively few diets. Objectives The objectives were 1) to simultaneously associate dietary intake with a range of potential nutritional biomarkers in postmenopausal women by using a controlled feeding study whereby each participant was provided a diet similar to her usual diet and 2) to evaluate serum concentrations of select nutrients as potential biomarkers with the use of established urinary recovery biomarkers of energy and protein as benchmarks for evaluation. Design Postmenopausal women from the Women's Health Initiative (n = 153) were provided with a 2-wk controlled diet in which each individual's menu approximated her habitual food intake as estimated from her 4-d food record and adjusted for estimated energy requirements. Serum biomarkers, including carotenoids, tocopherols, folate, vitamin B-12, and phospholipid fatty acids, were collected at the beginning and end of the feeding period. Doubly labeled water and urinary nitrogen biomarkers were used to derive estimates of energy and protein consumption, respectively. Results Linear regression of (ln-transformed) consumed nutrients on (ln-transformed) potential biomarkers and participant characteristics led to the following regression (R2) values for serum concentration biomarkers: folate, 0.49; vitamin B-12, 0.51; α-carotene, 0.53; β-carotene, 0.39; lutein + zeaxanthin, 0.46; lycopene, 0.32; and α-tocopherol, 0.47. R2 values for percentage of energy from polyunsaturated fatty acids and urinary recovery biomarkers of energy and protein intakes were 0.27, 0.53, and 0.43, respectively. Phospholipid saturated fatty acids and monounsaturated fatty acids and serum γ-tocopherol were weakly associated with intake (R2 Conclusions Serum concentration biomarkers of several vitamins and carotenoids performed similarly to established energy and protein urinary recovery biomarkers in representing nutrient intake variation in a feeding study, and thus are likely suitable for application in this population of postmenopausal women. Further work is needed to identify objective measures of categories of fatty acid intake. This trial was registered at clinicaltrials.gov as NCT00000611.

The balance between metabolism and biomass is very important in biological systems; however, to date there has been no quantitative method to characterize the balance. In this methodological study, we propose to use the distribution of amino acids in different domains to investigate this balance. It is well known that endogenous or exogenous amino acids in a biological system are either metabolized or incorporated into free amino acids (FAAs) or proteome amino acids (PAAs). Using glycine (Gly) as an example, we demonstrate a novel method to accurately determine the amounts of amino acids in various domains using serum, urine, and cell samples. As expected, serum and urine had very different distributions of FAA- and PAA-Gly. Using Tet21N human neuroblastoma cells, we also found that Myc(oncogene)-induced metabolic reprogramming included a higher rate of metabolizing Gly, which provides additional evidence that the metabolism of proliferating cells is adapted to facilitate producing new cells. It is therefore anticipated that our method will be very valuable for further studies of the metabolism and biomass balance that will lead to a better understanding of human cancers.

Intravenous (IV) busulfan doses are often personalized to a concentration at steady state (Css) using the patient’s clearance, which is estimated with therapeutic drug monitoring. We sought to identify biomarkers of IV busulfan clearance using a targeted pharmacometabonomics approach. A total of 200 metabolites were quantitated in 106 plasma samples, each obtained before IV busulfan administration in hematopoietic cell transplant (HCT) recipients. Both univariate linear regression with false discovery rate (FDR), and pathway enrichment analyses using the Global test were performed. In the univariate analysis, glycine, N-acetylglycine, 2-hydroxyisovaleric acid, creatine, serine, and tyrosine and were statistically significantly associated with IV busulfan clearance at P0.1. Glycine is a component of glutathione, which is conjugated with busulfan via glutathione transferase enzymes. These results demonstrate the potential utility of pharmacometabonomics to inform IV busulfan dosing. Future studies are required to validate these findings.

Coenzymes of cellular redox reactions and cellular energy mediate biochemical reactions fundamental to the functioning of all living cells. Despite their immense interest, no simple method exists to gain insights into their cellular concentrations in a single step. We show that a simple (1)H NMR experiment can simultaneously measure oxidized and reduced forms of nicotinamide adenine dinucleotide (NAD(+) and NADH), oxidized and reduced forms of nicotinamide adenine dinucleotide phosphate (NADP(+) and NADPH), and adenosine triphosphate (ATP) and its precursors, adenosine diphosphate (ADP) and adenosine monophosphate (AMP), using mouse heart, kidney, brain, liver, and skeletal muscle tissue extracts as examples. Combining 1D/2D NMR experiments, chemical shift libraries, and authentic compound data, reliable peak identities for these coenzymes have been established. To assess this methodology, cardiac NADH and NAD(+) ratios/pool sizes were measured using mouse models with a cardiac-specific knockout of the mitochondrial Complex I Ndufs4 gene (cKO) and cardiac-specific overexpression of nicotinamide phosphoribosyltransferase (cNAMPT) as examples. Sensitivity of NAD(+) and NADH to cKO or cNAMPT was observed, as anticipated. Time-dependent investigations showed that the levels of NADH and NADPH diminish by up to ∼50% within 24 h; concomitantly, NAD(+) and NADP(+) increase proportionately; however, degassing the sample and flushing the sample tubes with helium gas halted such changes. The analysis protocol along with the annotated characteristic fingerprints for each coenzyme is provided for easy identification and absolute quantification using a single internal reference for routine use. The ability to visualize the ubiquitous coenzymes fundamental to cellular functions, simultaneously and reliably, offers a new avenue to interrogate the mechanistic details of cellular function in health and disease.