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Metabolomic profiles are increasingly being used to identify responders to dietary interventions. Advances using this approach are particularly needed to personalize and enhance the effectiveness of dietary weight loss interventions. Using obese Diversity Outbred (DO) mice that model genetic and phenotypic heterogeneity of human populations, we aimed to identify urinary metabolite signatures associated with responsiveness to calorie restriction (CR)-mediated weight loss. DO mice (150 males, 150 females) were fed a high-fat diet for 12 weeks to induce obesity, then urine was collected and an 8-week CR regimen (30% decrease in energy intake) initiated. At study completion, mice were rank-ordered according to their percent body weight change, with mice in the extreme quartiles deemed CR responders (n = 67) versus nonresponders (n = 67). Targeted semi-quantitative metabolomics identified elevated glutamic acid and hydroxyproline as key urinary metabolites that distinguish CR responders from CR nonresponders, independent of sex. Three urinary metabolites (glutamic acid, hydroxyproline, and putrescine) distinguished male CR responders from nonresponders. Six metabolites (glutamic acid, hydroxyproline, dopamine, histamine, lysine, and spermine) distinguished female CR responders from nonresponders. Multivariate receiver operating characteristic analyses integrated these metabolites to reveal potential sex specific and sex-independent associations of CR-mediated weight loss. Further, pathway analysis identified several metabolic pathways, including arginine and proline metabolism, and alanine, aspartate, and glutamate biosynthesis, that distinguished CR responders from nonresponders and could be indicative of metabolic reprogramming to enhance insulin sensitivity and energy metabolism.

We evaluated associations among exposure to prenatal phthalate metabolites, perturbations of the newborn metabolome, and infant neurobehavioral functioning in mother-newborn pairs enrolled in the Atlanta African American Maternal-Child Cohort during 2016–2018. We quantified eight phthalate metabolites in prenatal urine samples collected between 8- and 14-weeks’ (visit 1; n  = 216) and 24- and 30-weeks’ gestation (visit 2; n  = 145) and metabolite features in newborn dried-blood spot samples collected at delivery. Associations between phthalate metabolite concentrations and metabolic feature intensities at both visits were examined using adjusted generalized linear models (MWAS). Then, an exploratory meet-in-the-middle (MITM) analysis was conducted in a subset with NICU Neonatal Neurobehavioral Scale (NNNS) scores (visit 1 n  = 81; visit 2 n  = 71). In both the MWAS and MITM, many of the confirmed metabolites are involved in tyrosine and tryptophan metabolism, including tryptophan, tyrosine, thyroxine, and serine. This analysis elucidates how prenatal phthalate exposure disrupts the newborn metabolome and infant neurobehavioral outcomes. Prenatal exposure to phthalates has been linked to metabolic and neurodevelopmental disruptions but the mechanisms remain unclear. Here, the authors show that prenatal phthalate exposure alters newborn metabolite profiles, particularly in tyrosine and tryptophan pathways, which are associated with infant neurobehavioral outcomes.

Heterotrimeric G proteins were originally discovered through efforts to understand the effects of hormones, such as glucagon and epinephrine, on glucose metabolism. On the other hand, many cellular metabolites, including glucose, serve as ligands for G protein-coupled receptors. Here we investigate the consequences of glucose-mediated receptor signaling, and in particular the role of a Gα subunit Gpa2 and a non-canonical Gβ subunit, known as Asc1 in yeast and RACK1 in animals. Asc1/RACK1 is of particular interest because it has multiple, seemingly unrelated, functions in the cell. The existence of such “moonlighting” operations has complicated the determination of phenotype from genotype. Through a comparative analysis of individual gene deletion mutants, and by integrating transcriptomics and metabolomics measurements, we have determined the relative contributions of the Gα and Gβ protein subunits to glucose-initiated processes in yeast. We determined that Gpa2 is primarily involved in regulating carbohydrate metabolism while Asc1 is primarily involved in amino acid metabolism. Both proteins are involved in regulating purine metabolism. Of the two subunits, Gpa2 regulates a greater number of gene transcripts and was particularly important in determining the amplitude of response to glucose addition. We conclude that the two G protein subunits regulate distinct but complementary processes downstream of the glucose-sensing receptor, as well as processes that lead ultimately to changes in cell growth and metabolism.

The yeast Saccharomyces cerevisiae has long been used to produce alcohol from glucose and other sugars. While much is known about glucose metabolism, relatively little is known about the receptors and signaling pathways that indicate glucose availability. Here, we compare the two glucose receptor systems in S. cerevisiae. The first is a heterodimer of transporter-like proteins (transceptors), while the second is a seven-transmembrane receptor coupled to a large G protein (Gpa2) that acts in coordination with two small G proteins (Ras1 and Ras2). Through comprehensive measurements of glucose-dependent transcription and metabolism, we demonstrate that the two receptor systems have distinct roles in glucose signaling: the G-protein-coupled receptor directs carbohydrate and energy metabolism, while the transceptors regulate ancillary processes such as ribosome, amino acids, cofactor and vitamin metabolism. The large G-protein transmits the signal from its cognate receptor, while the small G-protein Ras2 (but not Ras1) integrates responses from both receptor pathways. Collectively, our analysis reveals the molecular basis for glucose detection and the earliest events of glucose-dependent signal transduction in yeast.

Breast carcinogenesis is a multistep process accompanied by widespread molecular and genomic alterations, both in tumor and in surrounding microenvironment. It is known that tumors have altered metabolism, but the metabolic changes in normal or cancer-adjacent, nonmalignant normal tissues and how these changes relate to alterations in gene expression and histological composition are not well understood. Normal or cancer-adjacent normal breast tissues from 99 women of the Normal Breast Study (NBS) were evaluated. Data of metabolomics, gene expression and histological composition was collected by mass spectrometry, whole genome microarray, and digital image, respectively. Unsupervised clustering analysis determined metabolomics-derived subtypes. Their association with genomic and histological features, as well as other breast cancer risk factors, genomic and histological features were evaluated using logistic regression. Unsupervised clustering of metabolites resulted in two main clusters. The metabolite differences between the two clusters suggested enrichment of pathways involved in lipid metabolism, cell growth and proliferation, and migration. Compared with Cluster 1, subjects in Cluster 2 were more likely to be obese (body mass index ≥30 kg/m2, p<0.05), have increased adipose proportion (p<0.01) and associated with a previously defined Active genomic subtype (p<0.01). By the integrated analyses of histological, metabolomics and transcriptional data, we characterized two distinct subtypes of non-malignant breast tissue. Further research is needed to validate our findings, and understand the potential role of these alternations in breast cancer initiation, progression and recurrence.

ALDH1L1 (10-formyltetrahydrofolate dehydrogenase), an enzyme of folate metabolism, is highly expressed in the liver. It regulates the overall flux of folate-bound one-carbon groups by converting 10-formyltetrahydrofolate to tetrahydrofolate and CO2 in a NADP+-dependent reaction. Our previous study revealed that Aldh1l1 knockout (KO) mice have an altered liver metabotype with metabolic symptoms of folate deficiency when fed a standard chow diet containing 2 ppm folic acid. Here we performed untargeted metabolomic analysis of liver and plasma of KO and wild-type (WT) male and female mice fed for 16 weeks either standard or folate-deficient diet. OPLS-DA, a supervised multivariate technique that was applied to 6595 and 10,678 features for the liver and plasma datasets, respectively, indicated that genotype and diet, alone or in combination, gave distinct metabolic profiles in both types of biospecimens. A more detailed analysis of affected metabolic pathways based on most confidently identified metabolites in the liver and plasma (OL1 and OL2a ontology level) indicated that the dietary folate restriction itself does not fully recapitulate the metabolic effect of the KO. Of note, dietary folate withdrawal enhanced the metabolic perturbations linked to the ALDH1L1 loss only for a subset of metabolites. Importantly, both the ALDH1L1 loss and dietary folate deficiency produced sex-specific metabolic effects.

Purpose. To conduct an exploratory study to identify mechanisms that differentiate Luminal A (BT474 and MCF-7) and triple-negative (MDA-MB-231 and MDA-MB-468) breast cancer (BCa) cell lines to potentially provide novel therapeutic targets based on differences in energy utilization. Methods. Cells were cultured in media containing either [U-13C]-glucose or [U-13C]-glutamine for 48 hours. Conditioned media and cellular extracts were analyzed by 1H and 13C NMR spectroscopy. Results. MCF-7 cells consumed the most glucose, producing the most lactate, demonstrating the greatest Warburg effect-associated energy utilization. BT474 cells had the highest tricarboxylic acid cycle (TCA) activity. The majority of energy utilization patterns in MCF-7 cells were more similar to MDA-MB-468 cells, while the patterns for BT474 cells were more similar to MDA-MB-231 cells. Compared to the Luminal A cell lines, TNBC cell lines consumed more glutamine and less glucose. BT474 and MDA-MB-468 cells produced high amounts of 13C-glycine from media [U-13C]-glucose which was integrated into glutathione, indicating de novo synthesis. Conclusions. Stable isotopic resolved metabolomics using 13C substrates provided mechanistic information about energy utilization that was difficult to interpret using 1H data alone. Overall, cell lines that have different hormone receptor status have different energy utilization requirements, even if they are classified by the same clinical BCa subtype; and these differences offer clues about optimizing treatment strategies.

BackgroundMetabolomics is a promising method to investigate physiological effects of chemical exposures during pregnancy, with the potential to clarify toxicological mechanisms, suggest sensitive endpoints, and identify novel biomarkers of exposures.ObjectiveInvestigate the influence of chemical exposures on the maternal plasma metabolome during pregnancy.MethodsData were obtained from participants (n = 177) in the New Hampshire Birth Cohort Study, a prospective pregnancy cohort. Chemical exposures were assessed via silicone wristbands worn for one week at ~13 gestational weeks. Metabolomic features were assessed in plasma samples obtained at ~24–28 gestational weeks via the Biocrates AbsoluteIDQ® p180 kit and nuclear magnetic resonance (NMR) spectroscopy. Associations between chemical exposures and plasma metabolomics were investigated using multivariate modeling.ResultsChemical exposures predicted 11 (of 226) and 23 (of 125) metabolomic features in Biocrates and NMR, respectively. The joint chemical exposures did not significantly predict pathway enrichment, though some individual chemicals were associated with certain amino acids and related metabolic pathways. For example, N,N-diethyl-m-toluamide was associated with the amino acids glycine, L-glutamic acid, L-asparagine, and L-aspartic acid and enrichment of the ammonia recycling pathway.SignificanceThis study contributes evidence to the potential effects of chemical exposures during pregnancy upon the endogenous maternal plasma metabolome.

Alterations in hemodialysis patients’ serum trace metals have been documented. Early studies addressing associations levels of serum trace metals with erythropoietic responses and/or hematocrit generated mixed results. These studies were conducted prior to current approaches for erythropoiesis stimulating agent (ESA) drug dosing guidelines or without consideration of inflammation markers (e.g. hepcidin) important for regulation of iron availability. This study sought to determine if the serum trace metal concentrations of incident or chronic hemodialysis patients associated with the observed ESA response variability and with consideration to ESA dose response, hepcidin, and high sensitivity C-reactive protein levels. Inductively-coupled plasma-mass spectrometry was used to measure 14 serum trace metals in 29 incident and 79 prevalent dialysis patients recruited prospectively. We compared these data to three measures of ESA dose response, sex, and dialysis incidence versus dialysis prevalence. Hemoglobin was negatively associated with ESA dose and cadmium while positively associated with antimony, arsenic and lead. ESA dose was negatively associated with achieved hemoglobin and vanadium while positively associated with arsenic. ESA response was positively associated with arsenic. Vanadium, nickel, cadmium, and tin were increased in prevalent patients. Manganese was increased in incident patients. Vanadium, nickel, and arsenic increased with time on dialysis while manganese decreased. Changes in vanadium and manganese were largest and appeared to have some effect on anemia. Incident and prevalent patients’ chromium and antimony levels exceeded established accepted upper limits of normal.

Heterotrimeric G proteins were originally discovered through efforts to understand the effects of hormones, such as glucagon and epinephrine, on glucose metabolism. On the other hand, many cellular metabolites, including glucose, serve as ligands for G protein-coupled receptors. Here we investigate the consequences of glucose-mediated receptor signaling, and in particular the role of a G[alpha] subunit Gpa2 and a non-canonical G[beta] subunit, known as Asc1 in yeast and RACK1 in animals. Asc1/RACK1 is of particular interest because it has multiple, seemingly unrelated, functions in the cell. The existence of such \"moonlighting\" operations has complicated the determination of phenotype from genotype. Through a comparative analysis of individual gene deletion mutants, and by integrating transcriptomics and metabolomics measurements, we have determined the relative contributions of the G[alpha] and G[beta] protein subunits to glucose-initiated processes in yeast. We determined that Gpa2 is primarily involved in regulating carbohydrate metabolism while Asc1 is primarily involved in amino acid metabolism. Both proteins are involved in regulating purine metabolism. Of the two subunits, Gpa2 regulates a greater number of gene transcripts and was particularly important in determining the amplitude of response to glucose addition. We conclude that the two G protein subunits regulate distinct but complementary processes downstream of the glucose-sensing receptor, as well as processes that lead ultimately to changes in cell growth and metabolism.