PubMed

Related Articles Structural elucidation of novel biomarkers of known metabolic disorders based on multistage fragmentation mass spectra. J Inherit Metab Dis. 2017 Nov 14;: Authors: Václavík J, Coene KLM, Vrobel I, Najdekr L, Friedecký D, Karlíková R, Mádrová L, Petsalo A, Engelke UFH, van Wegberg A, Kluijtmans LAJ, Adam T, Wevers RA Abstract Specific diagnostic markers are the key to effective diagnosis and treatment of inborn errors of metabolism (IEM). Untargeted metabolomics allows for the identification of potential novel diagnostic biomarkers. Current separation techniques coupled to high-resolution mass spectrometry provide a powerful tool for structural elucidation of unknown compounds in complex biological matrices. This is a proof-of-concept study testing this methodology to determine the molecular structure of as yet uncharacterized m/z signals that were significantly increased in plasma samples from patients with phenylketonuria and 3-hydroxy-3-methylglutaryl-CoA lyase deficiency. A hybrid linear ion trap-orbitrap high resolution mass spectrometer, capable of multistage fragmentation, was used to acquire accurate masses and product ion spectra of the uncharacterized m/z signals. In order to determine the molecular structures, spectral databases were searched and fragmentation prediction software was used. This approach enabled structural elucidation of novel compounds potentially useful as biomarkers in diagnostics and follow-up of IEM patients. Two new conjugates, glutamyl-glutamyl-phenylalanine and phenylalanine-hexose, were identified in plasma of phenylketonuria patients. These novel markers showed high inter-patient variation and did not correlate to phenylalanine levels, illustrating their potential added value for follow-up. As novel biomarkers for 3-hydroxy-3-methylglutaryl-CoA lyase deficiency, three positional isomers of 3-methylglutaconyl carnitine could be detected in patient plasma. Our results highlight the applicability of current accurate mass multistage fragmentation techniques for structural elucidation of unknown metabolites in human biofluids, offering an unprecedented opportunity to gain further biochemical insights in known inborn errors of metabolism by enabling high confidence identification of novel biomarkers. PMID: 29139026 [PubMed - as supplied by publisher]

Related Articles [Metabolomics and Cancer]. Pathologe. 2017 Nov 14;: Authors: Schwab M, Fisel P, Schäffeler E PMID: 29138896 [PubMed - as supplied by publisher]

Related Articles Myokine mediated muscle-kidney crosstalk suppresses metabolic reprogramming and fibrosis in damaged kidneys. Nat Commun. 2017 Nov 14;8(1):1493 Authors: Peng H, Wang Q, Lou T, Qin J, Jung S, Shetty V, Li F, Wang Y, Feng XH, Mitch WE, Graham BH, Hu Z Abstract Kidney injury initiates metabolic reprogramming in tubule cells that contributes to the development of chronic kidney disease (CKD). Exercise has been associated with beneficial effects in patients with CKD. Here we show that the induction of a myokine, irisin, improves kidney energy metabolism and prevents kidney damage. In response to kidney injury, mice with muscle-specific PGC-1α overexpression (mPGC-1α) exhibit reduced kidney damage and fibrosis. Metabolomics analysis reveals increased ATP production and improved energy metabolism in injured kidneys from mPGC-1α mice. We identify irisin as a serum factor that mediates these metabolic effects during progressive kidney injury by inhibiting TGF-β type 1 receptor. Irisin depletion from serum blunts the induction of oxygen consumption rate observed in tubule cells treated with mPGC-1α serum. In mice, recombinant irisin administration attenuates kidney damage and fibrosis and improves kidney functions. We suggest that myokine-mediated muscle-kidney crosstalk can suppress metabolic reprograming and fibrogenesis during kidney disease. PMID: 29138395 [PubMed - in process]

Related Articles Combining traditional dietary assessment methods with novel metabolomics techniques: present efforts by the Food Biomarker Alliance. Proc Nutr Soc. 2017 Nov;76(4):619-627 Authors: Brouwer-Brolsma EM, Brennan L, Drevon CA, van Kranen H, Manach C, Dragsted LO, Roche HM, Andres-Lacueva C, Bakker SJL, Bouwman J, Capozzi F, De Saeger S, Gundersen TE, Kolehmainen M, Kulling SE, Landberg R, Linseisen J, Mattivi F, Mensink RP, Scaccini C, Skurk T, Tetens I, Vergeres G, Wishart DS, Scalbert A, Feskens EJM Abstract FFQ, food diaries and 24 h recall methods represent the most commonly used dietary assessment tools in human studies on nutrition and health, but food intake biomarkers are assumed to provide a more objective reflection of intake. Unfortunately, very few of these biomarkers are sufficiently validated. This review provides an overview of food intake biomarker research and highlights present research efforts of the Joint Programming Initiative 'A Healthy Diet for a Healthy Life' (JPI-HDHL) Food Biomarkers Alliance (FoodBAll). In order to identify novel food intake biomarkers, the focus is on new food metabolomics techniques that allow the quantification of up to thousands of metabolites simultaneously, which may be applied in intervention and observational studies. As biomarkers are often influenced by various other factors than the food under investigation, FoodBAll developed a food intake biomarker quality and validity score aiming to assist the systematic evaluation of novel biomarkers. Moreover, to evaluate the applicability of nutritional biomarkers, studies are presently also focusing on associations between food intake biomarkers and diet-related disease risk. In order to be successful in these metabolomics studies, knowledge about available electronic metabolomics resources is necessary and further developments of these resources are essential. Ultimately, present efforts in this research area aim to advance quality control of traditional dietary assessment methods, advance compliance evaluation in nutritional intervention studies, and increase the significance of observational studies by investigating associations between nutrition and health. PMID: 29137687 [PubMed - in process]

Related Articles Longitudinal serum metabolomics evaluation of trastuzumab and everolimus combination as pre-operative treatment for HER-2 positive breast cancer patients. Oncotarget. 2017 Oct 13;8(48):83570-83584 Authors: Jobard E, Trédan O, Bachelot T, Vigneron AM, Aït-Oukhatar CM, Arnedos M, Rios M, Bonneterre J, Diéras V, Jimenez M, Merlin JL, Campone M, Elena-Herrmann B Abstract The mammalian target of rapamycin complex 1 (mTORC1) is an attractive target for HER-2 positive breast cancer therapy because of its key role in protein translation regulation, cell growth and metabolism. We present here a metabolomic investigation exploring the impact of mTOR inhibition on serum metabolic profiles from patients with non-metastatic breast cancer overexpressing HER-2. Baseline, treatment-related and post-treatment serum samples were analyzed for 79 patients participating in the French clinical trial RADHER, in which randomized patients with HER-2 positive breast cancer received either trastuzumab alone (arm T) or a trastuzumab and everolimus combination (arm T+E). Longitudinal series of NMR serum metabolic profiles were exploited to investigate treatment effects on the patients metabolism over time, in both group. Trastuzumab and everolimus combination induces faster changes in patients metabolism than trastuzumab alone, visible after only one week of treatment as well as a residual effect detectable up to three weeks after ending the treatment. These metabolic fingerprints highlight the involvement of several metabolic pathways reflecting a systemic effect, particularly on the liver and visceral fat. Comparison of serum metabolic profiles between the two arms shows that everolimus, an mTORC1 inhibitor, is responsible for host metabolism modifications observed in arm T+E. In HER-2 positive breast cancer, our metabolomic approach confirms a fast and persistent host metabolism modification caused by mTOR inhibition. PMID: 29137365 [PubMed]

Related Articles Integration of metabolomics, transcriptomics, and microRNA expression profiling reveals a miR-143-HK2-glucose network underlying zinc-deficiency-associated esophageal neoplasia. Oncotarget. 2017 Oct 10;8(47):81910-81925 Authors: Fong LY, Jing R, Smalley KJ, Taccioli C, Fahrmann J, Barupal DK, Alder H, Farber JL, Fiehn O, Croce CM Abstract Esophageal squamous cell carcinoma (ESCC) in humans is a deadly disease associated with dietary zinc (Zn)-deficiency. In the rat esophagus, Zn-deficiency induces cell proliferation, alters mRNA and microRNA gene expression, and promotes ESCC. We investigated whether Zn-deficiency alters cell metabolism by evaluating metabolomic profiles of esophageal epithelia from Zn-deficient and replenished rats vs sufficient rats, using untargeted gas chromatography time-of-flight mass spectrometry (n = 8/group). The Zn-deficient proliferative esophagus exhibits a distinct metabolic profile with glucose down 153-fold and lactic acid up 1.7-fold (P < 0.0001), indicating aerobic glycolysis (the "Warburg effect"), a hallmark of cancer cells. Zn-replenishment rapidly increases glucose content, restores deregulated metabolites to control levels, and reverses the hyperplastic phenotype. Integration of metabolomics and our reported transcriptomic data for this tissue unveils a link between glucose down-regulation and overexpression of HK2, an enzyme that catalyzes the first step of glycolysis and is overexpressed in cancer cells. Searching our published microRNA profile, we find that the tumor-suppressor miR-143, a negative regulator of HK2, is down-regulated in Zn-deficient esophagus. Using in situ hybridization and immunohistochemical analysis, the inverse correlation between miR-143 down-regulation and HK2 overexpression is documented in hyperplastic Zn-deficient esophagus, archived ESCC-bearing Zn-deficient esophagus, and human ESCC tissues. Thus, to sustain uncontrolled cell proliferation, Zn-deficiency reprograms glucose metabolism by modulating expression of miR-143 and its target HK2. Our work provides new insight into critical roles of Zn in ESCC development and prevention. PMID: 29137232 [PubMed]

Related Articles Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics. Metabolites. 2017 Nov 13;7(4): Authors: Sridharan GV, Bruinsma B, Bale SS, Swaminathan A, Saeidi N, Yarmush ML, Uygun K Abstract Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses. PMID: 29137180 [PubMed]

Related Articles Metabolic Profile of the Cellulolytic Industrial Actinomycete Thermobifida fusca. Metabolites. 2017 Nov 11;7(4): Authors: Vanee N, Brooks JP, Fong SS Abstract Actinomycetes have a long history of being the source of numerous valuable natural products and medicinals. To expedite product discovery and optimization of biochemical production, high-throughput technologies can now be used to screen the library of compounds present (or produced) at a given time in an organism. This not only facilitates chemical product screening, but also provides a comprehensive methodology to the study cellular metabolic networks to inform cellular engineering. Here, we present some of the first metabolomic data of the industrial cellulolytic actinomycete Thermobifida fusca generated using LC-MS/MS. The underlying objective of conducting global metabolite profiling was to gain better insight on the innate capabilities of T. fusca, with a long-term goal of facilitating T. fusca-based bioprocesses. The T. fusca metabolome was characterized for growth on two cellulose-relevant carbon sources, cellobiose and Avicel. Furthermore, the comprehensive list of measured metabolites was computationally integrated into a metabolic model of T. fusca, to study metabolic shifts in the network flux associated with carbohydrate and amino acid metabolism. PMID: 29137138 [PubMed]

Related Articles Alteration in the liver metabolome of rats with metabolic syndrome after treatment with Hydroxytyrosol. A Mass Spectrometry And Nuclear Magnetic Resonance - based metabolomics study. Talanta. 2018 Feb 01;178:246-257 Authors: Dagla I, Benaki D, Baira E, Lemonakis N, Poudyal H, Brown L, Tsarbopoulos A, Skaltsounis AL, Mikros E, Gikas E Abstract Metabolic syndrome (MetS) represents a group of abnormalities that enhances the risk for cardiovascular disease, diabetes and stroke. The Mediterranean diet seems to be an important dietary pattern, which reduces the incidence of MetS. Hydroxytyrosol (HT) - a simple phenol found in olive oil - has received increased attention for its antioxidant activity. Recently, the European Foods Safety Authority (EFSA) claimed that dietary consumption of HT exhibits a protective role against cardiovascular disease. In this study, an experimental protocol has been setup, including isolated HT administration in a diet induced model of MetS in young Wistar rats, in order to find out whether HT has a protective effect against MetS. Rats were randomly divided into two groups nurtured by high-carbohydrate high-fat (H) (MetS inducing diet) and high-carbohydrate high-fat + HT (HHT). HT (20mg/kg/d oral gavage, water vehicle) was administered for 8 weeks on the basal diet. Previous pharmacological evaluation of HT showed that hepatic steatosis was reduced and the inflammatory cells into the liver were infiltrated. These indicate that HT shows bioactivity against metabolic syndrome. Therefore, the metabolomics evaluation of liver extracts would indicate the putative biochemical mechanisms of HT activity. Thus, the extracts of liver tissues were analyzed using Ultra Performance Liquid Chromatography - High Resolution Mass Spectrometry (UPLC-HRMS, Orbitrap Discovery) and Nuclear Magnetic Resonance (NMR) spectroscopy (Bruker Avance III 600MHz). Multivariate analysis was performed in order to gain insight on the metabolic effects of HT administration on the liver metabolome. Normalization employing multiple internal standards and Quality Control-based Robust LOESS (LOcally Estimated Scatterplot Smoothing) Signal Correction algorithm (QC-RLSC) was added in the processing pipeline to enhance the reliability of metabolomic analysis by reducing unwanted information. Experimentally, HHT rats were clearly distinguished from H in PLS-DA, showing differences in the liver metabolome between the groups and specific biomarkers were determined supporting the pharmacological findings. More specifically, HT has shown to be effective towards the mobilization of lipids as various lipid classes being differentially regulated between the H and HHT groups. Interestingly branched fatty acid esters of hydroxy oleic acids (OAHSA) lipids have been shown to be up regulated to the HHT group, denoting the alleviation of the MetS to the animals administered with HT. PMID: 29136819 [PubMed - in process]

[Metabolomics study of tris(2-chloroethyl) phosphate induced hepaotoxicity and nephrotoxicity in Sprague-Dawley rats]. Zhonghua Yu Fang Yi Xue Za Zhi. 2017 Nov 06;51(11):1041-1047 Authors: Yang WQ, Zhao F, Li L, Fang YJ Abstract Objective: To discuss the potential toxic target organ and the toxic effects and mechanisms of tris (2-chloroethyl) phosphate (TCEP) on SD rats. Methods: 40 female SD rats weaning from milk for 21 days, weighted (50±2.3)g were selected as subjects and marked by the weight. They were randomly divided into 4 groups, namely control group, 50 (L), 100 (M) and 250 (H) mg·kg(-1)·d(-1) dose of TCEP group. Each group has 10 rats, and administrated the corresponding dose of drug or vehicle by mouth, quaque die for 60 days. All rats were sacrificed after the last administration. The livers and kidneys were dyed by HE for pathological observation; and the blood samples were collected to analyze the biochemical index. H(1)-Nuclear Magnetic Resonance ((1)H-NMR)-based metabolomics methods coupling with histopathogy examination were used to investigate the toxic effects of TCEP. Results: Inflammatory cell infiltration and hepatic necrosis were observed in the liver of TCEP-treated rats. Inflammatory cells invaded and calcification/ossification foci were also found in renal of TCEP-treated rats and tumor hyperplasia were existed in renal tubule in H group. The level of HDL-C in the L, M and H group were separately (1.7±0.09) , (1.5±0.07) and (1.3±0.1) µmol/L, which were all significantly lower than that of control group ( (1.9±0.2) µmol/L) (P<0.05) . The activity of cholinesterase (CHE) in the L, M and H group were separately (918±14.8) , (828±28.6) and (674±36.5) U/L, which were all significantly lower than that of control group ((1056±28.8) µmol/L) (P<0.05). Moreover, The level of creatinine (CRE) in the L, M and H group were separately (29.8±4.6) , (28.9±5.3) and (25.8±6.2) µmol/L, which were all significantly lower than that of control group ((30.2±3.9) µmol/L) (P<0.05). In the H group, the enzyme activities of alanine aminotransferase (ALT), lactate dehydrogenase (LDH), creatine kinase (CK), alkaline phosphatase (ALP) and the contents of total bilirubin (TBIL), glucose (GLU) and uric acid (UA) were all significantly higher than the results in control group. The results of (1)H-NMR metabolomics showed that the contents of lactate, glycine, high-density lipoprotein, low-density lipoprotein and phosphatidylcholine in blood of rats would decrease by TCEP exposure, while N-acetylglycoprotein, acetate, alanine, glucose, lipids, lipoproteins and fatty acids would increase. Conclusion: TCEP caused disorders in endogenous energy metabolism, leading to the pathological changes of inflammatory cells infiltration and necrosis in liver and kidney, caused enzyme activity changes of ALT, ALP and the content changes of other liver and kidney injury-related markers. PMID: 29136753 [PubMed - in process]

Advancing the large-scale CCS database for metabolomics and lipidomics at the machine-learning era. Curr Opin Chem Biol. 2017 Nov 11;42:34-41 Authors: Zhou Z, Tu J, Zhu ZJ Abstract Metabolomics and lipidomics aim to comprehensively measure the dynamic changes of all metabolites and lipids that are present in biological systems. The use of ion mobility-mass spectrometry (IM-MS) for metabolomics and lipidomics has facilitated the separation and the identification of metabolites and lipids in complex biological samples. The collision cross-section (CCS) value derived from IM-MS is a valuable physiochemical property for the unambiguous identification of metabolites and lipids. However, CCS values obtained from experimental measurement and computational modeling are limited available, which significantly restricts the application of IM-MS. In this review, we will discuss the recently developed machine-learning based prediction approach, which could efficiently generate precise CCS databases in a large scale. We will also highlight the applications of CCS databases to support metabolomics and lipidomics. PMID: 29136580 [PubMed - as supplied by publisher]

Non-targeted metabolomics-guided sildenafil metabolism study in human liver microsomes. J Chromatogr B Analyt Technol Biomed Life Sci. 2017 Nov 07;1072:86-93 Authors: Kim JH, Jo JH, Seo KA, Hwang H, Lee HS, Lee S Abstract Metabolomics combined with high-resolution mass spectrometry (HR-MS) and multivariate data analysis has broad applications in the study of xenobiotic metabolism. Although information about xenobiotic metabolism is essential to understand toxic mechanisms, pharmacokinetic parameters and excretion pathways, it is limited to predict all generated metabolites in biological fluids. Here, we revisited sildenafil metabolism in human liver microsomes using a metabolomics approach to achieve a global picture of sildenafil phase 1 metabolism. Finally, 12 phase 1 metabolites were identified in human liver microsomes; M1-M5 were previously known metabolites. The chemical structures of the novel metabolites were elucidated by MS(2) fragmentation using an HR-MS system as follows: M6, reduced sildenafil; M7, N,N-deethylation and mono-oxidation; M8, demethanamine, N,N-deethylation and mono-hydroxylation; M9, demethanamine and N,N-deethylation; M10 and M11, mono-oxidation in the piperazine ring after N-demethylation; and M12, mono-oxidation. All metabolites, except M1, were formed by CYP3A4 and CYP3A5. In conclusion, we successfully updated the metabolic pathway of sildenafil in human liver, including 7 novel metabolites using metabolomics combined with HR-MS and multivariate data analysis. PMID: 29136555 [PubMed - as supplied by publisher]

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research. Nucleic Acids Res. 2017 Nov 10;: Authors: Slenter DN, Kutmon M, Hanspers K, Riutta A, Windsor J, Nunes N, Mélius J, Cirillo E, Coort SL, Digles D, Ehrhart F, Giesbertz P, Kalafati M, Martens M, Miller R, Nishida K, Rieswijk L, Waagmeester A, Eijssen LMT, Evelo CT, Pico AR, Willighagen EL Abstract WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. PMID: 29136241 [PubMed - as supplied by publisher]

The microbiome and HIV persistence: implications for viral remission and cure. Curr Opin HIV AIDS. 2017 Nov 10;: Authors: Koay WLA, Siems LV, Persaud D Abstract PURPOSE OF REVIEW: This article discusses the interaction between HIV infection, the gut microbiome, inflammation and immune activation, and HIV reservoirs, along with interventions to target the microbiome and their implications for HIV remission and cure. RECENT FINDINGS: Most studies show that HIV-infected adults have a gut microbiome associated with decreased bacterial richness and diversity, and associated systemic inflammation and immune activation. A unique set of individuals, elite controllers, who spontaneously control HIV replication, have a similar microbiome to HIV-uninfected individuals. Conversely, exposure to maternal HIV in infants was shown to alter the gut microbiome, even in infants who escaped perinatal infection. Emerging research highlights the importance of the metabolomics and metaproteomics of the gut microbiome, which may have relevance for HIV remission and cure. Together, these studies illustrate the complexity of the relationship between HIV infection, the gut microbiome, and its systemic effects. SUMMARY: Understanding the association of HIV with the microbiome, metabolome, and metaproteome may lead to novel therapies to decrease inflammation and immune activation, and impact HIV reservoir size and vaccine responses. Further research in this area is important to inform HIV remission and cure treatments. PMID: 29135490 [PubMed - as supplied by publisher]

Related Articles Proteomic and metabolomic characterization of streptozotocin-induced diabetic nephropathy in TIMP3-deficient mice. Acta Diabetol. 2017 Nov 13;: Authors: Rossi C, Marzano V, Consalvo A, Zucchelli M, Levi Mortera S, Casagrande V, Mavilio M, Sacchetta P, Federici M, Menghini R, Urbani A, Ciavardelli D Abstract AIMS: The tissue inhibitor of metalloproteinase TIMP3 is a stromal protein that restrains the activity of both protease and receptor in the extracellular matrix and has been found to be down-regulated in diabetic nephropathy (DN), the leading cause of end-stage renal disease in developed countries. METHODS: In order to gain deeper insights on the association of loss of TIMP3 and DN, we performed differential proteomic analysis of kidney and blood metabolic profiling of wild-type and Timp3-knockout mice before and after streptozotocin (STZ) treatment, widely used to induce insulin deficiency and hyperglycemia. RESULTS: Kidney proteomic data and blood metabolic profiles suggest significant alterations of peroxisomal and mitochondrial fatty acids β-oxidation in Timp3-knockout mice compared to wild-type mice under basal condition. These alterations were exacerbated in response to STZ treatment. CONCLUSIONS: Proteomic and metabolomic approaches showed that loss of TIMP3 alone or in combination with STZ treatment results in significant alterations of kidney lipid metabolism and peripheral acylcarnitine levels, supporting the idea that loss of TIMP3 may generate a phenotype more prone to DN. PMID: 29134286 [PubMed - as supplied by publisher]

Related Articles Metabolomics identifies metabolite biomarkers associated with acute rejection after heart transplantation in rats. Sci Rep. 2017 Nov 13;7(1):15422 Authors: Lin F, Ou Y, Huang CZ, Lin SZ, Ye YB Abstract The aim of this study was to identify metabolite biomarkers associated with acute rejection after heart transplantation in rats using a LC-MS-based metabolomics approach. A model of heterotopic cardiac xenotransplantation was established in rats, with Wistar rats as donors and SD rats as recipients. Blood and cardiac samples were collected from blank control rats (Group A), rats 5 (Group B) and 7 days (Group C) after heart transplantation, and pretreated rats 5 (Group D) and 7 days (Group E) post-transplantation for pathological and metabolomics analyses. We assessed International Society for Heart and Lung Transplantation (ISHLT) grades 0, 3B, 4, 1 and 1 rejection in groups A to E. There were 15 differential metabolites between groups A and B, 14 differential metabolites between groups A and C, and 10 differential metabolites between groups B and C. In addition, four common differential metabolites, including D-tagatose, choline, C16 sphinganine and D-glutamine, were identified between on days 5 and 7 post-transplantation. Our findings demonstrate that the panel of D-tagatose, choline, C16 sphinganine and D-glutamine exhibits a high sensitivity and specificity for the early diagnosis of acute rejection after heart transplantation, and LC-MS-based metabolomics approach has a potential value for screening post-transplantation biomarkers. PMID: 29133921 [PubMed - in process]

Related Articles Neuronal hyperactivity due to loss of inhibitory tone in APOE4 mice lacking Alzheimer's disease-like pathology. Nat Commun. 2017 Nov 13;8(1):1464 Authors: Nuriel T, Angulo SL, Khan U, Ashok A, Chen Q, Figueroa HY, Emrani S, Liu L, Herman M, Barrett G, Savage V, Buitrago L, Cepeda-Prado E, Fung C, Goldberg E, Gross SS, Hussaini SA, Moreno H, Small SA, Duff KE Abstract The ε4 allele of apolipoprotein E (APOE) is the dominant genetic risk factor for late-onset Alzheimer's disease (AD). However, the reason APOE4 is associated with increased AD risk remains a source of debate. Neuronal hyperactivity is an early phenotype in both AD mouse models and in human AD, which may play a direct role in the pathogenesis of the disease. Here, we have identified an APOE4-associated hyperactivity phenotype in the brains of aged APOE mice using four complimentary techniques-fMRI, in vitro electrophysiology, in vivo electrophysiology, and metabolomics-with the most prominent hyperactivity occurring in the entorhinal cortex. Further analysis revealed that this neuronal hyperactivity is driven by decreased background inhibition caused by reduced responsiveness of excitatory neurons to GABAergic inhibitory inputs. Given the observations of neuronal hyperactivity in prodromal AD, we propose that this APOE4-driven hyperactivity may be a causative factor driving increased risk of AD among APOE4 carriers. PMID: 29133888 [PubMed - in process]

Related Articles Effects of microgravity on osteoblast mitochondria: a proteomic and metabolomics profile. Sci Rep. 2017 Nov 13;7(1):15376 Authors: Michaletti A, Gioia M, Tarantino U, Zolla L Abstract The response of human primary osteoblasts exposed to simulated microgravity has been investigated and analysis of metabolomic and proteomic profiles demonstrated a prominent dysregulation of mitochondrion homeostasis. Gravitational unloading treatment induced a decrease in mitochondrial proteins, mainly affecting efficiency of the respiratory chain. Metabolomic analysis revealed that microgravity influenced several metabolic pathways; stimulating glycolysis and the pentose phosphate pathways, while the Krebs cycle was interrupted at succinate-fumarate transformation. Interestingly, proteomic analysis revealed that Complex II of the mitochondrial respiratory chain, which catalyses the biotransformation of this step, was under-represented by 50%. Accordingly, down-regulation of quinones 9 and 10 was measured. Complex III resulted in up-regulation by 60%, while Complex IV was down-regulated by 14%, accompanied by a reduction in proton transport synthesis of ATP. Finally, microgravity treatment induced an oxidative stress response, indicated by significant decreases in oxidised glutathione and antioxidant enzymes. Decrease in malate dehydrogenase induced a reverse in the malate-aspartate shuttle, contributing to dysregulation of ATP synthesis. Beta-oxidation of fatty acids was inhibited, promoting triglyceride production along with a reduction in the glycerol shuttle. Taken together, our findings suggest that microgravity may suppress bone cell functions, impairing mitochondrial energy potential and the energy state of the cell. PMID: 29133864 [PubMed - in process]

Related Articles Significance estimation for large scale metabolomics annotations by spectral matching. Nat Commun. 2017 Nov 14;8(1):1494 Authors: Scheubert K, Hufsky F, Petras D, Wang M, Nothias LF, Dührkop K, Bandeira N, Dorrestein PC, Böcker S Abstract The annotation of small molecules in untargeted mass spectrometry relies on the matching of fragment spectra to reference library spectra. While various spectrum-spectrum match scores exist, the field lacks statistical methods for estimating the false discovery rates (FDR) of these annotations. We present empirical Bayes and target-decoy based methods to estimate the false discovery rate (FDR) for 70 public metabolomics data sets. We show that the spectral matching settings need to be adjusted for each project. By adjusting the scoring parameters and thresholds, the number of annotations rose, on average, by +139% (ranging from -92 up to +5705%) when compared with a default parameter set available at GNPS. The FDR estimation methods presented will enable a user to assess the scoring criteria for large scale analysis of mass spectrometry based metabolomics data that has been essential in the advancement of proteomics, transcriptomics, and genomics science. PMID: 29133785 [PubMed - in process]

Related Articles Bridging the Global Digital Health Divide for Cardiovascular Disease. Circ Cardiovasc Qual Outcomes. 2017 Nov;10(11): Authors: Banerjee A PMID: 29133470 [PubMed - in process]