PubMed

Metabolomics for improving pregnancy outcomes in women undergoing assisted reproductive technologies. Cochrane Database Syst Rev. 2018 Mar 16;3:CD011872 Authors: Siristatidis CS, Sertedaki E, Vaidakis D, Varounis C, Trivella M Abstract BACKGROUND: In order to overcome the low effectiveness of assisted reproductive technologies (ART) and the high incidence of multiple births, metabolomics is proposed as a non-invasive method to assess oocyte quality, embryo viability, and endometrial receptivity, and facilitate a targeted subfertility treatment. OBJECTIVES: To evaluate the effectiveness and safety of metabolomic assessment of oocyte quality, embryo viability, and endometrial receptivity for improving live birth or ongoing pregnancy rates in women undergoing ART, compared to conventional methods of assessment. SEARCH METHODS: We searched the Cochrane Gynaecology and Fertility Group Trials Register, CENTRAL, MEDLINE, Embase, CINAHL and two trial registers (Feburary 2018). We also examined the reference lists of primary studies and review articles, citation lists of relevant publications, and abstracts of major scientific meetings. SELECTION CRITERIA: Randomised controlled trials (RCTs) on metabolomic assessment of oocyte quality, embryo viability, and endometrial receptivity in women undergoing ART. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently assessed trial eligibility and risk of bias, and extracted the data. The primary outcomes were rates of live birth or ongoing pregnancy (composite outcome) and miscarriage. Secondary outcomes were clinical pregnancy, multiple and ectopic pregnancy, cycle cancellation, and foetal abnormalities. We combined data to calculate odds ratios (ORs) for dichotomous data and 95% confidence intervals (CIs). Statistical heterogeneity was assessed using the I² statistic. We assessed the overall quality of the evidence for the main comparisons using GRADE methods. MAIN RESULTS: We included four trials with a total of 924 women, with a mean age of 33 years. All assessed the role of metabolomic investigation of embryo viability. We found no RCTs that addressed the metabolomic assessment of oocyte quality or endometrial receptivity.We found low-quality evidence of little or no difference between metabolomic and non-metabolomic assessment of embryos for rates of live birth or ongoing pregnancy (OR 1.02, 95% CI 0.77 to 1.35, I² = 0%; four RCTs; N = 924), live birth alone (OR 0.99, 95% CI 0.69 to 1.44, I² = 0%; three RCTs; N = 597), or miscarriage (OR 1.18, 95% CI 0.77 to 1.82; I² = 0%; three RCTs; N = 869). A sensitivity analysis excluding studies at high risk of bias did not change the interpretation of the results for live birth or ongoing pregnancy (OR 0.90, 95% CI 0.66 to 1.25, I² = 0%; two RCTs; N = 744). Our findings suggested that if the rate of live birth or ongoing pregnancy was 36% in the non-metabolomic group, it would be between 32% and 45% with the use of metabolomics.We found low-quality evidence of little or no difference between groups in rates of clinical pregnancy (OR 1.11, 95% CI 0.85 to 1.45; I²= 44%; four trials; N = 924) or multiple pregnancy (OR 1.50, 95% CI 0.70 to 3.19; I² = 0%; two RCTs, N = 180). Rates of cycle cancellation were higher in the metabolomics group (OR 1.78, 95% CI 1.18 to 2.69; I² = 51%; two RCTs; N = 744, low quality evidence). There was very low-quality evidence of little or no difference between groups in rates of ectopic pregnancy rates (OR 3.00, 95% CI 0.12 to 74.07; one RCT; N = 417), and foetal abnormality (no events; one RCT; N = 125). Data were lacking on other adverse effects. A sensitivity analysis excluding studies at high risk of bias did not change the interpretation of the results for clinical pregnancy (OR 1.03, 95% CI 0.76 to 1.38; I² = 40%; two RCTs; N = 744).The overall quality of the evidence ranged from very low to low. Limitations included serious risk of bias (associated with poor reporting of methods, attrition bias, selective reporting, and other biases), imprecision, and inconsistency across trials. AUTHORS' CONCLUSIONS: According to current trials in women undergoing ART, there is no evidence to show that metabolomic assessment of embryos before implantation has any meaningful effect on rates of live birth, ongoing pregnancy, miscarriage, multiple pregnancy, ectopic pregnancy or foetal abnormalities. The existing evidence varied from very low to low-quality. Data on other adverse events were sparse, so we could not reach conclusions on these. At the moment, there is no evidence to support or refute the use of this technique for subfertile women undergoing ART. Robust evidence is needed from further RCTs, which study the effects on live birth and miscarriage rates for the metabolomic assessment of embryo viability. Well designed and executed trials are also needed to study the effects on oocyte quality and endometrial receptivity, since none are currently available. PMID: 29547689 [PubMed - as supplied by publisher]

Metabolomics Identifies Distinctive Metabolite Signatures for Measures of Glucose Homeostasis: The Insulin Resistance Atherosclerosis Family Study (IRAS-FS). J Clin Endocrinol Metab. 2018 Mar 13;: Authors: Palmer ND, Okut H, Hsu FC, Ng MCY, Ida Chen YD, Goodarzi MO, Taylor KD, Norris JM, Lorenzo C, Rotter JI, Bergman RN, Langefeld CD, Wagenknecht LE, Bowden DW Abstract Context: Metabolomics provides a biochemical fingerprint which, when coupled with clinical phenotypes, can provide insight into physiological processes and disease. Objective: Survey metabolites associated with dynamic and basal measures of glucose homeostasis. Design: Analysis of 733 serum metabolites from the Insulin Resistance Atherosclerosis Family Study. Setting: Community-based. Participants: 1111 Mexican Americans. Main Outcome: Dynamic measures were obtained from the intravenous glucose tolerance test (FSIGT) and included insulin sensitivity (SI) and acute insulin response (AIRg). Basal measures included homeostatic model assessment of insulin resistance (HOMAIR) and beta-cell function (HOMAB). Results: SI was associated with 99 metabolites (P<6.82x10-5) explaining 28% of the variance (R2adj) beyond 28% by BMI. Beyond branched chain amino acids (BCAA; P=1.85x10-18-1.70x10-05, R2adj=8.1%) and phospholipids (P=3.51x10-17-3.00x10-05, R2adj=14%), novel signatures of long chain fatty acids (LCFAs; P=4.49x10-23-4.14x10-07, R2adj=11%) were observed. Conditional analysis suggested BCAA and LCFA signatures were independent. LCFAs were not associated with HOMAIR (P>0.024). AIRg was associated six metabolites; glucose had the strongest association (P=5.68x10-16). HOMAB had significant signatures from the urea cycle (P=9.64x10-14-7.27x10-06, R2adj=11%). Novel associations of poly unsaturated fatty acids (PUFA; P=2.58x10-13-6.70x10-05, R2adj=10%) and LCFA (P=9.06x10-15-3.93x10-07, R2adj=10%) were observed with glucose effectiveness (SG). Assessment of the hyperbolic relationship between insulin sensitivity and secretion through the disposition index (DI) revealed a distinctive signature of PUFA (P=1.55x10-12-5.81x10-06; R2adj=3.8%) beyond that of its component measures. Conclusions: Metabolomics reveals distinct signatures which differentiate dynamic and basal measures of glucose homeostasis and further identifies new metabolite classes associated with dynamic measures providing expanded insight into the metabolic basis of insulin resistance. . PMID: 29546329 [PubMed - as supplied by publisher]

Comprehensive Metabolic Profiling Reveals a Lipid-rich Fingerprint of Free Thyroxine Far Beyond Classical Parameters. J Clin Endocrinol Metab. 2018 Mar 12;: Authors: Lange T, Budde K, Homuth G, Kastenmüller G, Artati A, Krumsiek J, Völzke H, Adamski J, Petersmann A, Völker U, Nauck M, Friedrich N, Pietzner M Abstract Objective: Thyroid hormones are ubiqiutiously involved in human metabolism. However, the precise molecular patterns associated with alterations in thyroid hormones levels remain to be explored in detail. A number of recent studies took great advantage of metabolomics profiling to outline metabolic actions of thyroid hormones in humans. Methods: Among 952 participants of the Study of Health in Pomerania data on serum free thyroxine (FT4) and thyrotropin (TSH) as well as comprehensive (non-)targeted metabolomics data of plasma and urine samples were available. Linear regression analyses were performed to assess the association between FT4 or TSH and metabolite levels. Results and Conclusion: After accounting for major confounders 106 out of 613 plasma metabolites were significantly associated with FT4. Associations in urine were minor (12 out of 587). The majority of the plasma metabolites consisted of lipid species and subsequent analysis of highly resolved lipoprotein subclasses measured by 1H-NMR spectroscopy revealed a consistent decrease in varoius of these species (e.g. phospholipids) and large LDL- as well as small HDL-particles. The latter was unique to men. Several polyunsaturated and saturated fatty acids displayed an association with FT4 in women only. A random forest-based variable selection approach using phenotypic characteristics revealed higher alcohol intake in men and an adverse thyroid state as well as the menopause in women as putative mediating factors. In general, our observations confirmed the lipolytic and lipogenic effect of thyroid hormones even in the physiological range and revealed different phenotypic characteristics, e.g. lifestyle differences, as possible confounders for sex-specific findings. PMID: 29546278 [PubMed - as supplied by publisher]

Metabolic profiles of triple-negative and luminal A breast cancer subtypes in African-American identify key metabolic differences. Oncotarget. 2018 Feb 20;9(14):11677-11690 Authors: Tayyari F, Gowda GAN, Olopade OF, Berg R, Yang HH, Lee MP, Ngwa WF, Mittal SK, Raftery D, Mohammed SI Abstract Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC. PMID: 29545929 [PubMed]

Comprehensive subcellular topologies of polypeptides in Streptomyces. Microb Cell Fact. 2018 Mar 15;17(1):43 Authors: Tsolis KC, Tsare EP, Orfanoudaki G, Busche T, Kanaki K, Ramakrishnan R, Rousseau F, Schymkowitz J, Rückert C, Kalinowski J, Anné J, Karamanou S, Klapa MI, Economou A Abstract BACKGROUND: Members of the genus Streptomyces are Gram-positive bacteria that are used as important cell factories to produce secondary metabolites and secrete heterologous proteins. They possess some of the largest bacterial genomes and thus proteomes. Understanding their complex proteomes and metabolic regulation will improve any genetic engineering approach. RESULTS: Here, we performed a comprehensive annotation of the subcellular localization of the proteome of Streptomyces lividans TK24 and developed the Subcellular Topology of Polypeptides in Streptomyces database (SToPSdb) to make this information widely accessible. We first introduced a uniform, improved nomenclature that re-annotated the names of ~ 4000 proteins based on functional and structural information. Then protein localization was assigned de novo using prediction tools and edited by manual curation for 7494 proteins, including information for 183 proteins that resulted from a recent genome re-annotation and are not available in current databases. The S. lividans proteome was also linked with those of other model bacterial strains including Streptomyces coelicolor A3(2) and Escherichia coli K-12, based on protein homology, and can be accessed through an open web interface. Finally, experimental data derived from proteomics experiments have been incorporated and provide validation for protein existence or topology for 579 proteins. Proteomics also reveals proteins released from vesicles that bleb off the membrane. All export systems known in S. lividans are also presented and exported proteins assigned export routes, where known. CONCLUSIONS: SToPSdb provides an updated and comprehensive protein localization annotation resource for S. lividans and other streptomycetes. It forms the basis for future linking to databases containing experimental data of proteomics, genomics and metabolomics studies for this organism. PMID: 29544487 [PubMed - in process]

Related Articles Automatic untargeted metabolic profiling analysis coupled with Chemometrics for improving metabolite identification quality to enhance geographical origin discrimination capability. J Chromatogr A. 2018 Mar 16;1541:12-20 Authors: Han L, Zhang YM, Song JJ, Fan MJ, Yu YJ, Liu PP, Zheng QX, Chen QS, Bai CC, Sun T, She YB Abstract Untargeted metabolic profiling analysis is employed to screen metabolites for specific purposes, such as geographical origin discrimination. However, the data analysis remains a challenging task. In this work, a new automatic untargeted metabolic profiling analysis coupled with a chemometric strategy was developed to improve the metabolite identification results and to enhance the geographical origin discrimination capability. Automatic untargeted metabolic profiling analysis with chemometrics (AuMPAC) was used to screen the total ion chromatographic (TIC) peaks that showed significant differences among the various geographical regions. Then, a chemometric peak resolution strategy is employed for the screened TIC peaks. The retrieved components were further analyzed using ANOVA, and those that showed significant differences were used to build a geographical origin discrimination model by using two-way encoding partial least squares. To demonstrate its performance, a geographical origin discrimination of flaxseed samples from six geographical regions in China was conducted, and 18 TIC peaks were screened. A total of 19 significant different metabolites were obtained after the peak resolution. The accuracy of the geographical origin discrimination was up to 98%. A comparison of the AuMPAC, AMDIS, and XCMS indicated that AuMPACobtained the best geographical origin discrimination results. In conclusion, AuMPAC provided another method for data analysis. PMID: 29448994 [PubMed - indexed for MEDLINE]

Related Articles CLUH couples mitochondrial distribution to the energetic and metabolic status. J Cell Sci. 2017 Jun 01;130(11):1940-1951 Authors: Wakim J, Goudenege D, Perrot R, Gueguen N, Desquiret-Dumas V, Chao de la Barca JM, Dalla Rosa I, Manero F, Le Mao M, Chupin S, Chevrollier A, Procaccio V, Bonneau D, Logan DC, Reynier P, Lenaers G, Khiati S Abstract Mitochondrial dynamics and distribution are critical for supplying ATP in response to energy demand. CLUH is a protein involved in mitochondrial distribution whose dysfunction leads to mitochondrial clustering, the metabolic consequences of which remain unknown. To gain insight into the role of CLUH on mitochondrial energy production and cellular metabolism, we have generated CLUH-knockout cells using CRISPR/Cas9. Mitochondrial clustering was associated with a smaller cell size and with decreased abundance of respiratory complexes, resulting in oxidative phosphorylation (OXPHOS) defects. This energetic impairment was found to be due to the alteration of mitochondrial translation and to a metabolic shift towards glucose dependency. Metabolomic profiling by mass spectroscopy revealed an increase in the concentration of some amino acids, indicating a dysfunctional Krebs cycle, and increased palmitoylcarnitine concentration, indicating an alteration of fatty acid oxidation, and a dramatic decrease in the concentrations of phosphatidylcholine and sphingomyeline, consistent with the decreased cell size. Taken together, our study establishes a clear function for CLUH in coupling mitochondrial distribution to the control of cell energetic and metabolic status. PMID: 28424233 [PubMed - indexed for MEDLINE]

Rif1 phosphorylation site analysis in telomere length regulation and the response to damaged telomeres. DNA Repair (Amst). 2018 Mar 07;65:26-33 Authors: Wang J, Zhang H, Al Shibar M, Willard B, Ray A, Runge KW Abstract Telomeres, the ends of eukaryotic chromosomes, consist of repetitive DNA sequences and their bound proteins that protect the end from the DNA damage response. Short telomeres with fewer repeats are preferentially elongated by telomerase. Tel1, the yeast homolog of human ATM kinase, is preferentially recruited to short telomeres and Tel1 kinase activity is required for telomere elongation. Rif1, a telomere-binding protein, negatively regulates telomere length by forming a complex with two other telomere binding proteins, Rap1 and Rif2, to block telomerase recruitment. Rif1 has 14 SQ/TQ consensus phosphorylation sites for ATM kinases, including 6 in a SQ/TQ Cluster Domain (SCD) similar to other DNA damage response proteins. These 14 sites were analyzed as N-terminal, SCD and C-terminal domains. Mutating some sites to non-phosphorylatable residues increased telomere length in cells lacking Tel1 while a different set of phosphomimetic mutants increased telomere length in cells lacking Rif2, suggesting that Rif1 phosphorylation has both positive and negative effects on length regulation. While these mutations did not alter the sensitivity to DNA damaging agents, inducing telomere-specific damage by growing cells lacking YKU70 at high temperature revealed a role for the SCD. Mass spectrometry of Rif1 from wild type cells or those induced for telomere-specific DNA damage revealed increased phosphorylation in cells with telomere damage at an ATM consensus site in the SCD, S1351, and non-ATM sites S181 and S1637. A phosphomimetic rif1-S1351E mutation caused an increase in telomere length at synthetic telomeres but not natural telomeres. These results indicate that the Rif1 SCD can modulate Rif1 function. As all Rif1 orthologs have one or more SCD domains, these results for yeast Rif1 have implications for the regulation of Rif1 function in humans and other organisms. PMID: 29544213 [PubMed - as supplied by publisher]

Metabolomic association between venous thromboembolism in critically ill trauma patients and kynurenine pathway of tryptophan metabolism. Thromb Res. 2018 Mar 08;165:6-13 Authors: Voils SA, Shahin MH, Garrett TJ, Frye RF Abstract OBJECTIVE: Incidence of venous thromboembolism (VTE) in critically ill patients remains unacceptably high despite widespread use of thromboprophylaxis. A systems biology approach may be useful in understanding disease pathology and predicting response to treatment. Metabolite profile under specific environmental conditions provides the closest link to phenotype, but the relationship between metabolomics and risk of VTE in critically ill patients is unknown. In this study, metabolomics signatures are compared in patients with and without VTE. DESIGN: Multicenter case-control study using prospectively collected data from the Inflammation and Host Response to Injury program, with pathway and in silico gene expression analyses. SETTING: Eight level 1 US trauma centers. PATIENTS: Critically ill adults with blunt trauma who developed VTE within the first 28 days of hospitalization compared to patients without VTE (N-VTE). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients included in the study (n = 20 VTE, n = 20 N-VTE) were mean age of 34 years, injury severity score of 35, and VTE diagnosed a median of 10.5 days after admission. Global metabolomics revealed two kynurenine metabolites, N-formylkynurenine (AUC = 0.77; 95% CI: 0.59-0.89) and 5-hydroxy-N-formylkynurenine (AUC = 0.80; 95% CI:0.63-0.90) significantly discriminated VTE and N-VTE; ratio between N-formylkynurenine/5-hydroxy-N-formylkynurenine improved predictive power (AUC = 0.87; 95% CI: 0.74-0.95). In the pathway analysis, tryptophan was the only significant metabolic pathway including N-formylkynurenine and 5-hydroxy-N-formylkynurenine (p < 0.001), and 8 proteins directly or indirectly interacted with these metabolites in the interaction network analysis. Of the 8 genes tested in the in silico gene expression analyses, KYNU (p < 0.001), CCBL1 (p < 0.001), and CCBL2 (p = 0.001) were significantly different between VTE and N-VTE, controlling for age and sex. CONCLUSIONS: Two novel kynurenine metabolites in the tryptophan pathway associated with hospital-acquired VTE, and 3 candidate genes were identified via pathway and interaction network analyses. Future studies are warranted to validate these findings in diverse populations using a multi-omics approach. PMID: 29544199 [PubMed - as supplied by publisher]

Prediction of platinum-based chemotherapy efficacy in lung cancer based on LC-MS metabolomics approach. J Pharm Biomed Anal. 2018 Feb 23;154:95-101 Authors: Peng F, Liu Y, He C, Kong Y, Ouyang Q, Xie X, Liu T, Liu Z, Peng J Abstract Lung cancer is the common cause of cancer-related death worldwide. Platinum-based chemotherapy is the cornerstone of treatment for lung cancer. Platinum sensitivity is a major possibility for effective cancer treatment. In this study, several potential biomarkers were identified for evaluating and predicting the response to platinum-based chemotherapy. LC-MS-based metabolomics was performed on plasma samples from 43 lung cancer patients with different chemotherapy efficacy. By combing multivariate statistical analysis, pathway analysis with correlation analysis, 8 potential biomarkers were significantly associated with platinum chemotherapy response. Moreover, a prediction model with these biomarkers involved in citric acid cycle, glutamate metabolism and amino acid metabolism, showed 100% sensitivity and 100% specificity for predicting chemotherapy response in a validation set. Interestingly, 2-hydroxyglutaric acid (2-HG) as an oncometabolite accumulated in lung cancer was remarkably elevated in the partial response (PR) patients. Collectively, our findings implicated that metabolomics can serve as a potential tool to select lung cancer patients that are more likely to benefit from the platinum-based treatment. PMID: 29544107 [PubMed - as supplied by publisher]

CRH/CRHR1 mediates prenatal synthetic glucocorticoid programming of depression-like behavior across 2 generations. FASEB J. 2018 Mar 15;:fj201700948RR Authors: Xu YJ, Sheng H, Wu TW, Bao QY, Zheng Y, Zhang YM, Gong YX, Lu JQ, You ZD, Xia Y, Ni X Abstract Pregnant women at risk of preterm labor usually receive synthetic glucocorticoids (sGCs) to promote fetal lung development. Emerging evidence indicates that antenatal sGC increases the risk of affective disorders in offspring. Data from animal studies show that such disorders can be transmitted to the second generation. However, the molecular mechanisms underlying the intergenerational effects of prenatal sGC remain largely unknown. Here we show that prenatal dexamethasone (Dex) administration in late pregnancy induced depression-like behavior in first-generation (F1) offspring, which could be transmitted to second-generation (F2) offspring with maternal dependence. Moreover, corticotropin-releasing hormone (CRH) and CRH receptor type 1 (CRHR1) expression in the hippocampus was increased in F1 Dex offspring and F2 offspring from F1 Dex female rats. Administration of a CRHR1 antagonist to newborn F1 Dex offspring alleviated depression-like behavior in these rats at adult. Furthermore, we demonstrated that increased CRHR1 expression in F1 and F2 offspring was associated with hypomethylation of CpG islands in Crhr1 promoter. Our results revealed that prenatal sGC exposure could program Crh and Crhr1 gene expression in hippocampus across 2 generations, thereby leading to depression-like behavior. Our study indicates that prenatal sGC can cause epigenetic instability, which increases the risk of disease development in the offspring's later life.-Xu, Y.-J., Sheng, H., Wu, T.-W., Bao, Q.-Y., Zheng, Y., Zhang, Y.-M., Gong, Y.-X., Lu, J.-Q., You, Z.-D., Xia, Y., Ni, X. CRH/CRHR1 mediates prenatal synthetic glucocorticoid programming of depression-like behavior across 2 generations. PMID: 29543532 [PubMed - as supplied by publisher]

1H NMR metabolic profiling of gastric cancer patients with lymph node metastasis. Metabolomics. 2018;14(4):47 Authors: Zhang H, Cui L, Liu W, Wang Z, Ye Y, Li X, Wang H Abstract Introduction: Gastric cancer (GC) is a malignant tumor worldwide. As primary pathway for metastasis, the lymphatic system is an important prognostic factor for GC patients. Although the metabolic changes of gastric cancer have been investigated in extensive studies, little effort focused on the metabolic profiling of lymph node metastasis (LNM)-positive or negative GC patients. Objectives: We performed 1H NMR spectrum of GC tissue samples with and without LNM to identify novel potential metabolic biomarkers in the process of LNM of GC. Methods: 1H NMR-based untargeted metabolomics approach combined with multivariate statistical analyses were used to study the metabolic profiling of tissue samples from LNM-positive GC patients (n = 40), LNM-negative GC patients (n = 40) and normal controls (n = 40). Results: There was a clear separation between GC patients and normal controls, and 33 differential metabolites were identified in the study. Moreover, GC patients were also well-classified according to LNM-positive or negative. Totally eight distinguishing metabolites were selected in the metabolic profiling of GC patients with LNM-positive or negative, suggesting the metabolic dysfunction in the process of LNM. According to further validation and analysis, especially BCAAs metabolism (leucine, isoleucine, valine), GSH and betaine may be as potential factors of diagnose and prognosis of GC patients with or without LNM. Conclusion: To our knowledge, this is the first metabolomics study focusing on LNM of GC. The identified distinguishing metabolites showed a promising application on clinical diagnose and therapy prediction, and understanding the mechanism underlying the carcinogenesis, invasion and metastasis of GC. PMID: 29541009 [PubMed]

Alpha-oxoglutarate inhibits the proliferation of immortalized normal bladder epithelial cells via an epigenetic switch involving ARID1A. Sci Rep. 2018 Mar 14;8(1):4505 Authors: Shahid M, Gull N, Yeon A, Cho E, Bae J, Yoon HS, You S, Yoon H, Kim M, Berman BP, Kim J Abstract Interstitial cystitis (IC) is a chronic urinary tract disease that is characterized by unpleasant sensations, such as persistent pelvic pain, in the absence of infection or other identifiable causes. We previously performed comprehensive metabolomics profiling of urine samples from IC patients using nuclear magnetic resonance and gas-chromatography/mass spectrometry and found that urinary α-oxoglutarate (α-OG), was significantly elevated. α-OG, a tricarboxylic acid (TCA) cycle intermediate, reportedly functions to suppress the proliferation of immortalized normal human bladder epithelial cells. Here, we identified AT-rich interactive domain 1 A (ARID1A), a key chromatin remodeler, as being hypomethylated and upregulated by α-OG treatment. This was done through EPIC DNA methylation profiling and subsequent biochemical approaches, including quantitative RT-PCR and western blot analyses. Furthermore, we found that α-OG almost completely suppresses ten-eleven translocation (TET) activity, but does not affect DNA methyltransferase (DNMT) activity. Altogether, our studies reveal the potential role of α-OG in epigenetic remodeling through its effects on ARID1A and TET expression in the bladder. This may provide a new possible therapeutic strategy in treating IC. PMID: 29540744 [PubMed - in process]

Metabolomics reveals critical adrenergic regulatory checkpoints in glycolysis and pentose-phosphate pathways in embryonic heart. J Biol Chem. 2018 Mar 14;: Authors: Peoples JNR, Maxmillian T, Le Q, Nadtochiy SM, Brookes PS, Porter GA, Davidson VL, Ebert SN Abstract Cardiac energy demands during early embryonic periods are sufficiently met through glycolysis, but as development proceeds, oxidative phosphorylation in mitochondria becomes increasingly vital. Adrenergic hormones are known to stimulate metabolism in adult mammals and are essential for embryonic development, but relatively little is known about their effects on metabolism in the embryonic heart.  Here, we show that embryos lacking adrenergic stimulation have approximately 10-fold less cardiac ATP compared to littermate controls. Despite this deficit in steady-state ATP, neither the rates of ATP formation or degradation were affected in adrenergic-deficient hearts, suggesting that ATP synthesis and hydrolysis mechanisms were fully operational.  We thus hypothesized that adrenergic hormones stimulate metabolism of glucose to provide chemical substrates for oxidation in mitochondria. To test this hypothesis, we employed a metabolomics-based approach using liquid chromatography/mass spectrometry (LC/MS). Our results showed glucose-1-phosphate and glucose-6-phosphate concentrations were not significantly altered, but several downstream metabolites in both glycolytic and pentose-phosphate pathways were significantly lower compared to controls.  Further, we identified glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and glucose-6-phosphate dehydrogenase (G-6-PDH) as key enzymes in those respective metabolic pathways whose activity was significantly (p < 0.05) and substantially (80% and 40%, respectively) lower in adrenergic-deficient hearts.  Addition of pyruvate and to a lesser extent, ribose, led to significant recovery of steady-state ATP concentrations. These results demonstrate that without adrenergic stimulation, glucose metabolism in the embryonic heart is severely impaired in multiple pathways, ultimately leading to insufficient metabolic substrate availability for successful transition to aerobic respiration needed for survival. PMID: 29540484 [PubMed - as supplied by publisher]

Related Articles Cellular and Subcellular Level Localization of Maize Lipids and Metabolites Using High-Spatial Resolution MALDI Mass Spectrometry Imaging. Methods Mol Biol. 2018;1676:217-231 Authors: Dueñas ME, Feenstra AD, Korte AR, Hinners P, Lee YJ Abstract Recent technological advances have pushed the achievable spatial resolution for mass spectrometry imaging (MSI) to cellular and subcellular levels. Direct visualization of maize tissues by this tool has provided key insights into the localization of metabolites and lipids. This chapter outlines methodology for sample preparation, data acquisition, and data analysis of maize tissue sections using high-spatial resolution matrix-assisted laser desorption ionization (MALDI)-MSI, as well as the incorporation of a multi-resolution optical system, which allows for simple inter-conversion between different resolution setups (5, 10, and 50 μm imaging). PMID: 28986913 [PubMed - indexed for MEDLINE]

Related Articles Coupled brain and urine spectroscopy - in vivo metabolomic characterization of HMG-CoA lyase deficiency in 5 patients. Mol Genet Metab. 2017 Jun;121(2):111-118 Authors: Roland D, Jissendi-Tchofo P, Briand G, Vamecq J, Fontaine M, Ultré V, Acquaviva-Bourdain C, Mention K, Dobbelaere D Abstract BACKGROUND: 3-Hydroxy-3-Methylglutaryl-Coenzyme A (HMG-CoA) lyase deficiency is a rare inborn error of leucine metabolism and ketogenesis. Despite recurrent hypoglycemia and metabolic decompensations, most patients have a good clinical and neurological outcome contrasting with abnormal brain magnetic resonance imaging (MRI) signals and consistent abnormal brain proton magnetic resonance spectroscopy (1H-MRS) metabolite peaks. Identifying these metabolites could provide surrogate markers of the disease and improve understanding of MRI-clinical discrepancy and follow-up of affected patients. METHODS: Urine samples, brain MRI and 1H-MRS in 5 patients with HMG-CoA lyase deficiency (4 boys and 1 girl aged from 25days to 10years) were, for each patient, obtained on the same day. Brain and urine spectroscopy were performed at the same pH by studying urine at pH 7.4. Due to pH-induced modifications in chemical shifts and because reference 1H NMR spectra are obtained at pH 2.5, spectroscopy of normal urine added with the suspected metabolite was further performed at this pH to validate the correct identification of compounds. RESULTS: Mild to extended abnormal white matter MRI signals were observed in all cases. Brain spectroscopy abnormal peaks at 0.8-1.1ppm, 1.2-1.4ppm and 2.4ppm were also detected by urine spectroscopy at pH 7.4. Taking into account pH-induced changes in chemical shifts, brain abnormal peaks in patients were formally identified to be those of 3-hydroxyisovaleric, 3-methylglutaconic, 3-methylglutaric and 3-hydroxy-3-methylglutaric acids. CONCLUSION: 3-Methylglutaric, 3-hydroxyisovaleric and 3-hydroxy-3-methylglutaric acids identified on urine 1H-NMR spectra of 5 patients with HMG-CoA lyase deficiency are responsible for the cerebral spectroscopy signature seen in these patients, validating their local involvement in brain and putative contribution to brain neuropathology. PMID: 28396157 [PubMed - indexed for MEDLINE]

Diet, Genetics, and the Gut Microbiome Drive Dynamic Changes in Plasma Metabolites. Cell Rep. 2018 Mar 13;22(11):3072-3086 Authors: Fujisaka S, Avila-Pacheco J, Soto M, Kostic A, Dreyfuss JM, Pan H, Ussar S, Altindis E, Li N, Bry L, Clish CB, Kahn CR Abstract Diet, genetics, and the gut microbiome are determinants of metabolic status, in part through production of metabolites by the gut microbiota. To understand the mechanisms linking these factors, we performed LC-MS-based metabolomic analysis of cecal contents and plasma from C57BL/6J, 129S1/SvImJ, and 129S6/SvEvTac mice on chow or a high-fat diet (HFD) and HFD-treated with vancomycin or metronidazole. Prediction of the functional metagenome of gut bacteria by PICRUSt analysis of 16S sequences revealed dramatic differences in microbial metabolism. Cecal and plasma metabolites showed multifold differences reflecting the combined and integrated effects of diet, antibiotics, host background, and the gut microbiome. Eighteen plasma metabolites correlated positively or negatively with host insulin resistance across strains and diets. Over 1,000 still-unidentified metabolite peaks were also highly regulated by diet, antibiotics, and genetic background. Thus, diet, host genetics, and the gut microbiota interact to create distinct responses in plasma metabolites, which can contribute to regulation of metabolism and insulin resistance. PMID: 29539432 [PubMed - in process]

Metabolomic profiling of macrophages determines the discrete metabolomic signature and metabolomic interactome triggered by polarising immune stimuli. PLoS One. 2018;13(3):e0194126 Authors: Rattigan KM, Pountain AW, Regnault C, Achcar F, Vincent IM, Goodyear CS, Barrett MP Abstract Priming and activating immune stimuli have profound effects on macrophages, however, studies generally evaluate stimuli in isolation rather than in combination. In this study we have investigated the effects of pro-inflammatory and anti-inflammatory stimuli either alone or in combination on macrophage metabolism. These stimuli include host factors such as IFNγ and ovalbumin-immunoglobulin immune complexes, or pathogen factors such as LPS. Untargeted LC-MS based metabolomics provided an in-depth profile of the macrophage metabolome, and revealed specific changes in metabolite abundance upon either individual stimuli or combined stimuli. Here, by factoring in an interaction term in the linear model, we define the metabolome interactome. This approach allowed us to determine whether stimuli interact in a synergistic or antagonistic manner. In conclusion this study demonstrates a robust approach to interrogate immune-metabolism, especially systems that model host-pathogen interactions. PMID: 29538444 [PubMed - in process]

Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration. Methods Mol Biol. 2018;1754:265-292 Authors: Cheng J, Lan W, Zheng G, Gao X Abstract Metabolomics aims to quantitatively measure small-molecule metabolites in biological samples, such as bodily fluids (e.g., urine, blood, and saliva), tissues, and breathe exhalation, which reflects metabolic responses of a living system to pathophysiological stimuli or genetic modification. In the past decade, metabolomics has made notable progresses in providing useful systematic insights into the underlying mechanisms and offering potential biomarkers of many diseases. Metabolomics is a complementary manner of genomics and transcriptomics, and bridges the gap between genotype and phenotype, which reflects the functional output of a biological system interplaying with environmental factors. Recently, the technology of metabolomics study has been developed quickly. This review will discuss the whole pipeline of metabolomics study, including experimental design, sample collection and preparation, sample detection and data analysis, as well as mechanism interpretation, which can help understand metabolic effects and metabolite function for living organism in system level. PMID: 29536449 [PubMed - in process]

Promises and pitfalls of untargeted metabolomics. J Inherit Metab Dis. 2018 Mar 13;: Authors: Gertsman I, Barshop BA Abstract Metabolomics is one of the newer omics fields, and has enabled researchers to complement genomic and protein level analysis of disease with both semi-quantitative and quantitative metabolite levels, which are the chemical mediators that constitute a given phenotype. Over more than a decade, methodologies have advanced for both targeted (quantification of specific analytes) as well as untargeted metabolomics (biomarker discovery and global metabolite profiling). Untargeted metabolomics is especially useful when there is no a priori metabolic hypothesis. Liquid chromatography coupled to mass spectrometry (LC-MS) has been the preferred choice for untargeted metabolomics, given the versatility in metabolite coverage and sensitivity of these instruments. Resolving and profiling many hundreds to thousands of metabolites with varying chemical properties in a biological sample presents unique challenges, or pitfalls. In this review, we address the various obstacles and corrective measures available in four major aspects associated with an untargeted metabolomics experiment: (1) experimental design, (2) pre-analytical (sample collection and preparation), (3) analytical (chromatography and detection), and (4) post-analytical (data processing). PMID: 29536203 [PubMed - as supplied by publisher]