PubMed

Serum Biomarker Identification by Mass Spectrometry in Acute Aortic Dissection. Cell Physiol Biochem. 2017 Dec 12;44(6):2147-2157 Authors: Ren Y, Tang Q, Liu W, Tang Y, Zhu R, Li B Abstract BACKGROUND/AIMS: Aortic dissection (AD) is also known as intramural hematoma. This study aimed to screen peripheral blood biomarkers of small molecule metabolites for AD using high-performance liquid chromatography-mass spectrometry (HPLC-MS). METHODS: Sera from 25 healthy subjects, 25 patients with well-established AD, and 25 patients with well-established hypertension were investigated by HPLC-MS to detect metabolites, screen differentially expressed metabolites, and analyze metabolic pathways. RESULTS: Twenty-six and four metabolites were significantly up- and down-regulated in the hypertensive patients compared with the healthy subjects; 165 metabolites were significantly up-regulated and 109 significantly down-regulated in the AD patients compared with the hypertensive patients. Of these metabolites, 35 were up-regulated and 105 down-regulated only in AD patients. The metabolites that were differentially expressed in AD are mainly involved in tryptophan, histidine, glycerophospholipid, ether lipid, and choline metabolic pathways. As AD alters the peripheral blood metabolome, analysis of peripheral blood metabolites can be used in auxiliary diagnosis of AD. CONCLUSION: Eight metabolites are potential biomarkers for AD, 3 of which were differentially expressed and can be used for auxiliary diagnosis of AD and evaluation of treatment effectiveness. PMID: 29241182 [PubMed - as supplied by publisher]

Integrating transcriptomics and metabolomics to characterize the regulation of EPA biosynthesis in response to cold stress in seaweed Bangia fuscopurpurea. PLoS One. 2017;12(12):e0186986 Authors: Cao M, Wang D, Mao Y, Kong F, Bi G, Xing Q, Weng Z Abstract Bangia fuscopurpurea is a traditional mariculture crop having high nutritional value, eicosapntemacnioc acid (EPA) production, and protein content. As an intertidal species, it can tolerate drastic changes in abiotic factors such as temperature, hydration, and light radiation; however, genomic information on the evolutionary aspect and mechanism of EPA enrichment in B. fuscopurpurea and the role of EPA in cold tolerance in this species remain elusive. We conducted transcriptome profile analysis in B. fuscopurpurea to investigate the biological functions of genes associated with resistance to various environment factors. We identified 41,935 unigenes that were assembled and applied to public databases to define their functional annotation (NR, GO, KEGG, KOG, and SwissProt). We further identified genes that encoded key enzymes in EPA biosynthesis; five paralogous genes encoding delta5 desaturase were detected in B. fuscopurpurea. Fatty acid profiling and gene expression analysis of B. fuscopurpurea grown under cold stress were simultaneously performed. The EPA content was increased by 29.8% in the samples grown at 4°C, while the total amount of fatty acids remained unchanged. Moreover, all the EPA biosynthesis-related desaturase and elongase genes were upregulated under cold stress. Thus, we hypothesized that diverse EPA biosynthesis pathways and significant increase in gene copy numbers of fatty acid desaturases, together with the concomitant elevation in the transcriptional level of genes associated with fatty acid metabolism, lead to EPA accumulation and subsequently affect membrane fluidity, contributing to cold stress resistance in B. fuscopurpurea. Our findings not only provide a fundamental genetic background for further research in B. fuscopurpurea, but also have important implications for screening and genetic engineering of algae and plants for EPA production. PMID: 29240755 [PubMed - in process]

Metabolic Profile of Ex Vivo Lung Perfusate Yields Biomarkers for Lung Transplant Outcomes. Ann Surg. 2018 Jan;267(1):196-197 Authors: Hsin MK, Zamel R, Cypel M, Wishart D, Han B, Keshavjee S, Liu M Abstract OBJECTIVE: To identify potential biomarkers during ex vivo lung perfusion (EVLP) using metabolomics approach. SUMMARY BACKGROUND DATA: EVLP increases the number of usable donor lungs for lung transplantation (LTx) by physiologic assessment of explanted marginal lungs. The underlying paradigm of EVLP is the normothermic perfusion of cadaveric lungs previously flushed and stored in hypothermic preservation fluid, which allows the resumption of active cellular metabolism and respiratory function. Metabolomics of EVLP perfusate may identify metabolic profiles of donor lungs associated with early LTx outcomes. METHODS: EVLP perfusate taken at 1and 4 hperfusion were collected from 50 clinical EVLP cases, and submitted to untargeted metabolic profiling with mass spectrometry. The findings were correlated with early LTx outcomes. RESULTS: Following EVLP, 7 cases were declined for LTx. In the remaining transplanted cases, 9 cases developed primary graft dysfunction (PGD) 3. For the metabolic profile at EVLP-1h, a logistic regression model based on palmitoyl-sphingomyelin, 5-aminovalerate, and decanoylcarnitine yielded a receiver operating characteristic (ROC) curve with an area under the curve (AUC) of 0.987 in differentiating PGD 3 from Non-PGD 3 outcomes. For the metabolic profile at EVLP-4h, a logistic regression model based on N2-methylguanosine, 5-aminovalerate, oleamide, and decanoylcarnitine yielded a ROC curve with AUC 0.985 in differentiating PGD 3 from non-PGD 3 outcomes. CONCLUSIONS: Metabolomics of EVLP perfusate revealed a small panel of metabolites highly correlated with early LTx outcomes, and may be potential biomarkers that can improve selection of marginal lungs on EVLP. Further validation studies are needed to confirm these findings. PMID: 29240608 [PubMed - in process]

Serum and plasma amino acids as markers of prediabetes, insulin resistance, and incident diabetes. Crit Rev Clin Lab Sci. 2017 Dec 14;:1-12 Authors: Gar C, Rottenkolber M, Prehn C, Adamski J, Seissler J, Lechner A Abstract Presently, routine screening misses many cases of prediabetes and early type 2 diabetes (T2D). Therefore, better biomarkers are needed for a simple and early detection of abnormalities of glucose metabolism and prediction of future T2D. Possible candidates for this include plasma or serum amino acids because glucose and amino acid metabolism are closely connected. This review presents the available evidence of this connectivity and discusses its clinical implications. First, we examine the underlying physiological, pre-analytical, and analytical issues. Then, we summarize results of human studies that evaluate amino acid levels as markers for insulin resistance, prediabetes, and future incident T2D. Finally, we illustrate the interconnection of amino acid levels and metabolic syndrome with our own data from a deeply phenotyped human cohort. We also discuss how amino acids may contribute to the pathophysiology of T2D. We conclude that elevated branched-chain amino acids and reduced glycine are currently the most robust and consistent amino acid markers for prediabetes, insulin resistance, and future T2D. Yet, we are cautious regarding the clinical potential even of these parameters because their discriminatory power is insufficient and their levels depend not only on glycemia, but also on other components of the metabolic syndrome. The identification of more precise intermediates of amino acid metabolism or combinations with other biomarkers will, therefore, be necessary to obtain in order to develop laboratory tests that can improve T2D screening. PMID: 29239245 [PubMed - as supplied by publisher]

Best-matched internal standard normalization in liquid chromatography-mass spectrometry metabolomics applied to environmental samples. Anal Chem. 2017 Dec 14;: Authors: Boysen AK, Heal KR, Carlson LT, Ingalls AE Abstract The goal of metabolomics is to measure the entire range of small organic molecules in biological samples. In liquid chromatography-mass spectrometry-based metabolomics, formidable analytical challenges remain in removing the non-biological factors that affect chromatographic peak areas. These factors include sample matrix-induced ion suppression, chromatographic quality, and analytical drift. The combination of these factors is referred to as obscuring variation. Some metabolomics samples can exhibit intense obscuring variation due to matrix-induced ion suppression, rendering large amounts of data unreliable and difficult to interpret. Existing normalization techniques have limited applicability to these sample types. Here we present a data normalization method to minimize the effects of obscuring variation. We normalize peak areas using a batch-specific normalization process, which matches measured metabolites with isotope-labeled internal standards that behave similarly during the analysis. This method, called best-matched internal standard (B-MIS) normalization, can be applied to targeted or untargeted metabolomics datasets and yields relative concentrations. We evaluate and demonstrate the utility of B-MIS normalization using marine environmental samples and laboratory grown cultures of phytoplankton. In untargeted analyses, B-MIS normalization allowed for inclusion of mass features in downstream analyses that would have been considered unreliable without normalization due to obscuring variation. B-MIS normalization for targeted or untargeted metabolomics is freely available at https://github.com/IngallsLabUW/B-MIS-normalization. PMID: 29239170 [PubMed - as supplied by publisher]

Related Articles Translational systems pharmacology studies in pregnant women. CPT Pharmacometrics Syst Pharmacol. 2017 Dec 14;: Authors: Quinney SK, Gullapelli R, Haas DM Abstract Pregnancy involves rapid physiological adaptation and complex interplay between mother and fetus. New analytic technologies provide large amounts of genomic, proteomic, and metabolomics data. The integration of these data through bioinformatics, statistical, and systems pharmacology techniques can improve our understanding of the mechanisms of normal maternal physiologic changes and fetal development. New insights into the mechanisms of pregnancy-related disorders, such as preterm birth (PTB), may lead to the development of new therapeutic interventions and novel biomarkers. PMID: 29239132 [PubMed - as supplied by publisher]

Related Articles 13C-assisted metabolic flux analysis to investigate heterotrophic and mixotrophic metabolism in Cupriavidus necator H16. Metabolomics. 2018;14(1):9 Authors: Alagesan S, Minton NP, Malys N Abstract Introduction: Cupriavidus necator H16 is a gram-negative bacterium, capable of lithoautotrophic growth by utilizing hydrogen as an energy source and fixing carbon dioxide (CO2) through Calvin-Benson-Bassham (CBB) cycle. The potential to utilize synthesis gas (Syngas) and the prospects of rerouting carbon from polyhydroxybutyrate synthesis to value-added compounds makes C. necator an excellent chassis for industrial application. Objectives: In the context of lack of sufficient quantitative information of the metabolic pathways and to advance in rational metabolic engineering for optimized product synthesis in C. necator H16, we carried out a metabolic flux analysis based on steady-state 13C-labelling. Methods: In this study, steady-state carbon labelling experiments, using either d-[1-13C]fructose or [1,2-13C]glycerol, were undertaken to investigate the carbon flux through the central carbon metabolism in C. necator H16 under heterotrophic and mixotrophic growth conditions, respectively. Results: We found that the CBB cycle is active even under heterotrophic condition, and growth is indeed mixotrophic. While Entner-Doudoroff (ED) pathway is shown to be the major route for sugar degradation, tricarboxylic acid (TCA) cycle is highly active in mixotrophic condition. Enhanced flux is observed in reductive pentose phosphate pathway (redPPP) under the mixotrophic condition to supplement the precursor requirement for CBB cycle. The flux distribution was compared to the mRNA abundance of genes encoding enzymes involved in key enzymatic reactions of the central carbon metabolism. Conclusion: This study leads the way to establishing 13C-based quantitative fluxomics for rational pathway engineering in C. necator H16. PMID: 29238275 [PubMed]

Related Articles Metabolic Profiling of Adiponectin Levels in Adults: Mendelian Randomization Analysis. Circ Cardiovasc Genet. 2017 Dec;10(6): Authors: Borges MC, Barros AJD, Ferreira DLS, Casas JP, Horta BL, Kivimaki M, Kumari M, Menon U, Gaunt TR, Ben-Shlomo Y, Freitas DF, Oliveira IO, Gentry-Maharaj A, Fourkala E, Lawlor DA, Hingorani AD Abstract BACKGROUND: Adiponectin, a circulating adipocyte-derived protein, has insulin-sensitizing, anti-inflammatory, antiatherogenic, and cardiomyocyte-protective properties in animal models. However, the systemic effects of adiponectin in humans are unknown. Our aims were to define the metabolic profile associated with higher blood adiponectin concentration and investigate whether variation in adiponectin concentration affects the systemic metabolic profile. METHODS AND RESULTS: We applied multivariable regression in ≤5909 adults and Mendelian randomization (using cis-acting genetic variants in the vicinity of the adiponectin gene as instrumental variables) for analyzing the causal effect of adiponectin in the metabolic profile of ≤37 545 adults. Participants were largely European from 6 longitudinal studies and 1 genome-wide association consortium. In the multivariable regression analyses, higher circulating adiponectin was associated with higher high-density lipoprotein lipids and lower very-low-density lipoprotein lipids, glucose levels, branched-chain amino acids, and inflammatory markers. However, these findings were not supported by Mendelian randomization analyses for most metabolites. Findings were consistent between sexes and after excluding high-risk groups (defined by age and occurrence of previous cardiovascular event) and 1 study with admixed population. CONCLUSIONS: Our findings indicate that blood adiponectin concentration is more likely to be an epiphenomenon in the context of metabolic disease than a key determinant. PMID: 29237687 [PubMed - in process]

Related Articles Statin Effects on Metabolic Profiles: Data From the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial). Circ Cardiovasc Genet. 2017 Dec;10(6): Authors: Kofink D, Eppinga RN, van Gilst WH, Bakker SJL, Dullaart RPF, van der Harst P, Asselbergs FW Abstract BACKGROUND: Statins lower cholesterol by inhibiting HMG-CoA reductase, the rate-limiting enzyme of the metabolic pathway that produces cholesterol and other isoprenoids. Little is known about their effects on metabolite and lipoprotein subclass profiles. We, therefore, investigated the molecular changes associated with pravastatin treatment compared with placebo administration using a nuclear magnetic resonance-based metabolomics platform. METHODS AND RESULTS: We performed metabolic profiling of 231 lipoprotein and metabolite measures in the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial) study, a placebo-controlled randomized clinical trial designed to test the effects of pravastatin (40 mg once daily) on cardiovascular risk. Metabolic profiles were assessed at baseline and after 3 months of treatment. Pravastatin lowered low-density lipoprotein cholesterol (change in SD units [95% confidence interval]: -1.01 [-1.14, -0.88]), remnant cholesterol (change in SD units [95% confidence interval]: -1.03 [-1.17, -0.89]), and apolipoprotein B (change in SD units [95% confidence interval]: -0.98 [-1.11, -0.86]) with similar effect magnitudes. In addition, pravastatin globally lowered levels of lipoprotein subclasses, with the exception of high-density lipoprotein subclasses, which displayed a more heterogeneous response pattern. The lipid-lowering effect of pravastatin was accompanied by selective changes in lipid composition, particularly in the cholesterol content of very-low-density lipoproteinparticles. In addition, pravastatin reduced levels of several fatty acids but had limited effects on fatty acid ratios. CONCLUSIONS: These randomized clinical trial data demonstrate the widespread effects of pravastatin treatment on lipoprotein subclass profiles and fatty acids. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT03073018. PMID: 29237679 [PubMed - in process]

Related Articles Integrated metabolomics and proteomics analysis of hippocampus in a rat model of depression. Neuroscience. 2017 Dec 10;: Authors: Zhang Y, Yuan S, Pu J, Yang L, Zhou X, Liu L, Jiang X, Zhang H, Teng T, Tian L, Xie P Abstract Major depressive disorder (MDD) is a prevalent and serious mental disorder with high rates of suicide and disability. However, the underlying pathogenesis of MDD is complicated and remains largely unclear. An integrated analysis of multiple types of omics data may improve comprehensive understanding of the entire molecular mechanism of MDD. In this study, we applied an integrated analysis of gas chromatography/mass spectrometry (GC-MS)-based metabolomics and isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics to investigate changes in the hippocampus in the chronic unpredictable mild stress (CUMS) rat model of depression. Only the stress-susceptible rats in the CUMS group were selected for profiling against controls. Differential analysis identified 30 metabolites and 170 proteins between the two groups. The integrated analyses revealed four major changes in the hippocampus of CUMS rats: (1) impairment in amino acid metabolism and protein synthesis/degradation; (2) dysregulation of glutamate and glycine metabolism and their transport/catabolism related proteins; (3) disturbances in fatty acid and glycerophospholipid metabolism accompanied by alterations in the corresponding metabolic enzymes; (4) abnormal expression of synapse-associated proteins. These results provide further important insights into the pathophysiology of depression and may help identify potential targets for antidepressant drugs. PMID: 29237567 [PubMed - as supplied by publisher]

Assessing Public Metabolomics Metadata, Towards Improving Quality. J Integr Bioinform. 2017 Dec 13;14(4): Authors: Ferreira JD, Inácio B, Salek RM, Couto FM Abstract Public resources need to be appropriately annotated with metadata in order to make them discoverable, reproducible and traceable, further enabling them to be interoperable or integrated with other datasets. While data-sharing policies exist to promote the annotation process by data owners, these guidelines are still largely ignored. In this manuscript, we analyse automatic measures of metadata quality, and suggest their application as a mean to encourage data owners to increase the metadata quality of their resources and submissions, thereby contributing to higher quality data, improved data sharing, and the overall accountability of scientific publications. We analyse these metadata quality measures in the context of a real-world repository of metabolomics data (i.e. MetaboLights), including a manual validation of the measures, and an analysis of their evolution over time. Our findings suggest that the proposed measures can be used to mimic a manual assessment of metadata quality. PMID: 29236679 [PubMed - in process]

Increased levels of circulating fatty acids are associated with protective effects against future cardiovascular events in non-diabetics. J Proteome Res. 2017 Dec 13;: Authors: Kamleh MA, McLeod O, Checa A, Baldassarre D, Veglia F, Gertow K, Humphries SE, Rauramaa R, deFaire U, Smit AJ, Giral P, Kurl S, Mannarino E, Tremoli E, Silveira A, Orvik J, Hamsten A, Wheelock CE Abstract Cardiovascular disease (CVD) is a major cause of morbidity and mortality worldwide, particularly in individuals with diabetes. The current study objective was to determine the circulating metabolite profiles associated with the risk of future cardiovascular events, with emphasis on diabetes status. Non-targeted metabolomics analysis was performed by LC-HRMS in combination with targeted quantification of eicosanoids and endocannabinoids. Plasma from 375 individuals from the IMPROVE pan-European cohort were included in a case-control study design. Following data processing, the three metabolite datasets were concatenated to produce a single dataset of 267 identified metabolites. Factor analysis identified six factors that described 26.6% of the variability in the given set of predictors. An association with cardiovascular events was only observed for one factor following adjustment (p=0.026). From this factor, we identified a free fatty acid signature (n=10 lipids, including saturated, monounsaturated, and polyunsaturated fatty acids) that was associated with lower risk of future cardiovascular events in non-diabetics only (OR=0.65, 0.27-0.80 95% CI, p=0.030), whereas no association was observed among diabetic individuals. These observations support the hypothesis that increased levels of circulating omega-6 and omega-3 fatty acids are associated with protective effects against future cardiovascular events. However, these effects were only observed in the non-diabetic population, further highlighting the need for patient stratification in clinical investigations. PMID: 29235871 [PubMed - as supplied by publisher]

A metabolomic signature of endometrial cancer. J Proteome Res. 2017 Dec 13;: Authors: Troisi J, Sarno L, Landolfi A, Scala G, Martinelli P, Venturella R, Di Cello A, Zullo F, Guida M Abstract Endometrial cancer (EC) is the most common cancer of the female reproductive tract in developed Countries. At the moment, no effective screening system is available. Here, we evaluate the diagnostic performance of a serum metabolomic signature. Two enrollments were carried out: one constituted of 168 subjects: 88 with EC and 80 healthy women, was used for building the classification models. The second (used to establish the performance of the classification algorithm) was constituted of 120 subjects: 30 with EC, 30 with ovarian cancer, 10 with benign endometrial disease and 50 healthy controls. Two ensemble models were built, one with all EC vs. controls (Model I) and one in which EC patients were aggregated according to their histotype (Model II). Serum metabolomic analysis was conducted via gas chromatography-mass spectrometry, while classification was done by an ensemble learning machine. Accuracy ranged from 62% to 99% for the Model I and from 67% to 100% for the Model II. Ensemble model showed an accuracy of 100% both for Model I and II. The most important metabolites in class separation were: lactic acid, progesterone, homocysteine, 3-hydroxybutyrate, linoleic acid, stearic acid, myristic acid, threonine, and valine. The serum metabolomics signature of endometrial cancer patients is peculiar because it differs from that of healthy controls and from that of benign endometrial disease and from other gynecological cancers (such as ovarian cancer). PMID: 29235868 [PubMed - as supplied by publisher]

Related Articles Post genomics era for orchid research. Bot Stud. 2017 Dec 12;58(1):61 Authors: Tsai WC, Dievart A, Hsu CC, Hsiao YY, Chiou SY, Huang H, Chen HH Abstract Among 300,000 species in angiosperms, Orchidaceae containing 30,000 species is one of the largest families. Almost every habitats on earth have orchid plants successfully colonized, and it indicates that orchids are among the plants with significant ecological and evolutionary importance. So far, four orchid genomes have been sequenced, including Phalaenopsis equestris, Dendrobium catenatum, Dendrobium officinale, and Apostaceae shengen. Here, we review the current progress and the direction of orchid research in the post genomics era. These include the orchid genome evolution, genome mapping (genome-wide association analysis, genetic map, physical map), comparative genomics (especially receptor-like kinase and terpene synthase), secondary metabolomics, and genome editing. PMID: 29234904 [PubMed]

Related Articles 1H-NMR Based Serum Metabolomics Study to Investigate Hepatoprotective Effect of Qin-Jiao on Carbon Tetrachloride-Induced Acute Hepatotoxicity in Rats. Evid Based Complement Alternat Med. 2017;2017:6091589 Authors: Li Z, Li Y, Lu L, Yang Z, Xue W, Tian X, Zhang X Abstract Gentiana macrophylla Radix, commonly known as Qin-Jiao (QJ), was recorded alone to treat jaundice in Compendium of Materia Medica and has been frequently prescribed for treatment of liver disease in China. However, the underlying mechanism remains unknown. In the present work, QJ of 1,2 g/kg or silybin of 40 mg/kg (positive control) was orally given to rats for 7 days to verify the protective effect on acute liver damage induced by tetrachloride (CCl4). Together with serum biochemistry and histopathological examination, 1H-NMR based metabolomics work was carried out to investigate the efficacy. It turned out that QJ of 2 g/kg exerted comparable protective effect with positive control and partially recovered disturbed metabolism by CCl4. Multivariate analysis was conducted and metabolites altered significantly among groups were assigned and discussed, including betaine, glucose, lactate, creatine, and LDL/VLDL. Metabolic regulations involved in QJ or silybin treatment were as follows: tricarboxylic acid (TCA) cycle, synthesis of LDL/VLDL, and gluconeogenesis were enhanced, while betaine metabolism, glycolysis, creatine metabolism, synthesis of ketone bodies, amino acids metabolism, and β-oxidation of fatty acids were suppressed. For the first time hepatoprotective effect of QJ on acute liver damage was revealed by 1H-NMR based metabolomics, prompting understanding of the underlying mechanism. PMID: 29234415 [PubMed]

Related Articles Antihyperglycemic, Antidiabetic, and Antioxidant Effects of Garcinia pedunculata in Rats. Evid Based Complement Alternat Med. 2017;2017:2979760 Authors: Ali MY, Paul S, Tanvir EM, Hossen MS, Rumpa NN, Saha M, Bhoumik NC, Aminul Islam M, Hossain MS, Alam N, Gan SH, Khalil MI Abstract The antihyperglycemic, antidiabetic, and antioxidant potentials of the methanolic extract of Garcinia pedunculata (GP) fruit in rats were investigated. The acute antihyperglycemic effect of different doses of GP was studied in normal male Wistar rats. Diabetes was induced by streptozotocin (STZ) injection in another cohort of male Wistar rats and they showed significantly higher blood glucose and glycated hemoglobin (HbA1c) levels, altered lipid profiles, and lower insulin levels compared to nondiabetic control animals. There were increased lipid peroxidation and reduced levels of cellular antioxidant enzymes in different tissues of diabetic rats. However, oral administration of GP extracts, especially the highest dose (1000 mg/kg), significantly ameliorated hyperglycemia (42%); elevated insulin levels (165%); decreased HbA1c (29.4%); restored lipid levels (reduction in TG by 25%, TC by 15%, and LDL-C by 75% and increase in HDL-C by 4%), liver and renal function markers, and lipid peroxidation (reduction by 52% in the liver, 39% in the kidney, 44% in the heart, and 46% in the pancreas); and stimulated tissue antioxidant enzymes to near normalcy. Overall, the findings suggest that GP fruit is effective against hyperglycemia and could be used in the treatment of diabetes and its complications and other oxidative stress-mediated pathological conditions. PMID: 29234381 [PubMed]

Related Articles From Discovery to Translation: Characterization of C-Mannosyltryptophan and Pseudouridine as Markers of Kidney Function. Sci Rep. 2017 Dec 12;7(1):17400 Authors: Sekula P, Dettmer K, Vogl FC, Gronwald W, Ellmann L, Mohney RP, Eckardt KU, Suhre K, Kastenmüller G, Oefner PJ, Köttgen A Abstract Using a non-targeted metabolomics platform, we recently identified C-mannosyltryptophan and pseudouridine as non-traditional kidney function markers. The aims of this study were to obtain absolute concentrations of both metabolites in blood and urine from individuals with and without CKD to provide reference ranges and to assess their fractional excretions (FE), and to assess the agreement with their non-targeted counterparts. In individuals without/with CKD, mean plasma and urine concentrations for C-mannosyltryptophan were 0.26/0.72 µmol/L and 3.39/4.30 µmol/mmol creatinine, respectively. The respective concentrations for pseudouridine were 2.89/5.67 µmol/L and 39.7/33.9 µmol/mmol creatinine. Median (25th, 75th percentiles) FEs were 70.8% (65.6%, 77.8%) for C-mannosyltryptophan and 76.0% (68.6%, 82.4%) for pseudouridine, indicating partial net reabsorption. Association analyses validated reported associations between single metabolites and eGFR. Targeted measurements of both metabolites agreed well with the non-targeted measurements, especially in urine. Agreement for composite nephrological measures FE and urinary metabolite-to-creatinine ratio was lower, but could be improved by replacing non-targeted creatinine measurements with a standard clinical creatinine test. In summary, targeted quantification and additional characterization in relevant populations are necessary steps in the translation of non-traditional biomarkers in nephrology from non-targeted discovery to clinical application. PMID: 29234020 [PubMed - in process]

Related Articles N- and O-glycosylation analysis of human C1-inhibitor reveals extensive mucin-type O-glycosylation. Mol Cell Proteomics. 2017 Dec 12;: Authors: Stavenhagen K, Kayili HM, Holst S, Koeleman C, Engel R, Wouters D, Zeerleder S, Salih B, Wuhrer M Abstract Human C1-inhibitor (C1-Inh) is a serine protease inhibitor and the major regulator of the contact activation pathway as well as the classical and lectin complement pathways. It is known to be a highly glycosylated plasma glycoprotein. However, both the structural features and biological role of C1-Inh glycosylation are largely unknown. Here, we performed for the first time an in-depth site-specific N- and O-glycosylation analysis of C1-Inh combining various mass spectrometric approaches, including C18-porous graphitized carbon (PGC)-LC-ESI-QTOF-MS/MS applying stepping-energy collision-induced dissociation (CID) and electron-transfer dissociation (ETD). Various proteases were applied, partly in combination with PNGase F and exoglycosidase treatment, in order to analyze the (glyco)peptides. The analysis revealed an extensively O-glycosylated N-terminal region. Five novel and five known O-glycosylation sites were identified, carrying mainly core1-type O-glycans. In addition, we detected a heavily O-glycosylated portion spanning from Thr82-Ser121 with up to 16 O-glycans attached. Likewise, all known six N-glycosylation sites were covered and confirmed by this site-specific glycosylation analysis. The glycoforms were in accordance with results on released N-glycans by MALDI-TOF/TOF-MS/MS. The comprehensive characterization of C1-Inh glycosylation described in this study will form the basis for further functional studies on the role of these glycan modifications. PMID: 29233911 [PubMed - as supplied by publisher]

Related Articles Metabolomics analysis of alloxan-induced diabetes in mice using UPLC-Q-TOF-MS after Crassostrea gigas polysaccharide treatment. Int J Biol Macromol. 2017 Dec 09;: Authors: Zhao G, Hou X, Li X, Qu M, Tong C, Li W Abstract Diabetes has become a global and serious health issues which causes a variety of complications. This study aims to explore the hypoglycemic effect of Crassostrea gigas polysaccharide (CGPS) and the dynamic changes in the the endogenous small molecule metabolites of urine from normal group, model group and CGPS high dose group by metabolomic approach (UPLC-Q-TOF-MS). In our study, the CGPS treatment could reduce the fasting blood glucose levels and recover the triglycerides (TG), total cholesterol (TC) and glycosylated serum protein (GSP) levels in serum of diabetic mice. Urine samples in normal group, model group and CGPS high dose group were dispersed in the PLS-DA score plots. Nineteen metabolites in urine such as L-carnitine, hippuric acid, pantothenate and ornithine were selected as potential therapeutic biomarkers and related metabolic pathways of CGPS for treating diabetes. They were mainly involved in amino acid metabolism, carbohydrate metabolism and purine metabolism. These data suggested that CGPS has antidiabetic activity and urine metabolites provided new understanding of CGPS for treating diabetes and its complications. PMID: 29233709 [PubMed - as supplied by publisher]

Related Articles HPLC-Based Metabolomic Analysis of Normal and Inflamed Gut. Methods Mol Biol. 2016;1422:63-75 Authors: Kao DJ, Lanis JM, Alexeev E, Kominsky DJ Abstract The idiopathic inflammatory bowel diseases, which include Crohn's disease and ulcerative colitis, are multifactorial chronic conditions that result in numerous perturbations of metabolism in the gastrointestinal mucosa. Thus, methodologies for the qualitative and quantitative analysis of small molecule metabolites in mucosal tissues are important for further elucidation of mechanisms driving inflammation and the metabolic consequences of inflammation. High-performance liquid chromatography (HPLC) is a ubiquitous analytical technique that can be adapted for both targeted and non-targeted metabolomic analysis. Here, protocols for reversed-phase (RP) HPLC-based methods using two different detection modalities are presented. Ultraviolet detection is used for the analysis of adenine nucleotide metabolites, whereas electrochemical detection is used for the analysis of multiple amino acid metabolites. These methodologies provide platforms for further characterization of the metabolic changes that occur during gastrointestinal inflammation. PMID: 27246023 [PubMed - indexed for MEDLINE]