PubMed

Related Articles Biomarkers in localized prostate cancer. Future Oncol. 2016 Jan 15; Authors: Ferro M, Buonerba C, Terracciano D, Lucarelli G, Cosimato V, Bottero D, Deliu VM, Ditonno P, Perdonà S, Autorino R, Coman I, Placido S, Lorenzo GD, Cobelli O Abstract Biomarkers can improve prostate cancer diagnosis and treatment. Accuracy of prostate-specific antigen (PSA) for early diagnosis of prostate cancer is not satisfactory, as it is an organ- but not cancer-specific biomarker, and it can be improved by using models that incorporate PSA along with other test results, such as prostate cancer antigen 3, the molecular forms of PSA (proPSA, benign PSA and intact PSA), as well as kallikreins. Recent reports suggest that new tools may be provided by metabolomic studies as shown by preliminary data on sarcosine. Additional molecular biomarkers have been identified by the use of genomics, proteomics and metabolomics. We review the most relevant biomarkers for early diagnosis and management of localized prostate cancer. PMID: 26768791 [PubMed - as supplied by publisher]

Related Articles [Effect of Acanthopanax senticosus Polysaccharides on Cardiac Endogenous Metabolism in Rats Based on Metabolomics]. Zhong Yao Cai. 2015 May;38(5):1004-8 Authors: Lu F, Yang XD, Jing YE, Zhang N, Liu SM Abstract OBJECTIVE: Using metabolomics method to study the influence of Acanthopanax senticosus polysaccharides on cardiac endogenous metabolism in rats, in order to find potential biomarkers and analyze the metabolic pathways which can explore the pharmacological effects and mechanisms of action. METHODS: 20 SD rats were randomly divided into two groups, the blank and Acanthopanax senticosus polysaccharides treatment groups, which were treated with saline and Acanthopanax senticosus polysaccharide for 20 days. On the 21th day,heart tissue were collected and each sample extract was analyzed by UPLC-Q-TOF/MS. RESULTS: 20 potential biomarkers and 6 major metabolic pathways related to cardiovascular and cerebrovascular diseases were identified. CONCLUSION: Acanthopanax senticosus polysaccharides has a certain pharmacological effects on cardio-cerebro vascular diseases, cancer and other diseases. Its mechanism may be related to the metabolic process of amino acids, fatty acid and folate. PMID: 26767296 [PubMed - in process]

Related Articles Genomic and experimental evidence for multiple metabolic functions in the RidA/YjgF/YER057c/UK114 (Rid) protein family. BMC Genomics. 2015;16:382 Authors: Niehaus TD, Gerdes S, Hodge-Hanson K, Zhukov A, Cooper AJ, ElBadawi-Sidhu M, Fiehn O, Downs DM, Hanson AD Abstract BACKGROUND: It is now recognized that enzymatic or chemical side-reactions can convert normal metabolites to useless or toxic ones and that a suite of enzymes exists to mitigate such metabolite damage. Examples are the reactive imine/enamine intermediates produced by threonine dehydratase, which damage the pyridoxal 5'-phosphate cofactor of various enzymes causing inactivation. This damage is pre-empted by RidA proteins, which hydrolyze the imines before they do harm. RidA proteins belong to the YjgF/YER057c/UK114 family (here renamed the Rid family). Most other members of this diverse and ubiquitous family lack defined functions. RESULTS: Phylogenetic analysis divided the Rid family into a widely distributed, apparently archetypal RidA subfamily and seven other subfamilies (Rid1 to Rid7) that are largely confined to bacteria and often co-occur in the same organism with RidA and each other. The Rid1 to Rid3 subfamilies, but not the Rid4 to Rid7 subfamilies, have a conserved arginine residue that, in RidA proteins, is essential for imine-hydrolyzing activity. Analysis of the chromosomal context of bacterial RidA genes revealed clustering with genes for threonine dehydratase and other pyridoxal 5'-phosphate-dependent enzymes, which fits with the known RidA imine hydrolase activity. Clustering was also evident between Rid family genes and genes specifying FAD-dependent amine oxidases or enzymes of carbamoyl phosphate metabolism. Biochemical assays showed that Salmonella enterica RidA and Rid2, but not Rid7, can hydrolyze imines generated by amino acid oxidase. Genetic tests indicated that carbamoyl phosphate overproduction is toxic to S. enterica cells lacking RidA, and metabolomic profiling of Rid knockout strains showed ten-fold accumulation of the carbamoyl phosphate-related metabolite dihydroorotate. CONCLUSIONS: Like the archetypal RidA subfamily, the Rid2, and probably the Rid1 and Rid3 subfamilies, have imine-hydrolyzing activity and can pre-empt damage from imines formed by amine oxidases as well as by pyridoxal 5'-phosphate enzymes. The RidA subfamily has an additional damage pre-emption role in carbamoyl phosphate metabolism that has yet to be biochemically defined. Finally, the Rid4 to Rid7 subfamilies appear not to hydrolyze imines and thus remain mysterious. PMID: 25975565 [PubMed - indexed for MEDLINE]

Related Articles Discovery of substrate cycles in large scale metabolic networks using hierarchical modularity. BMC Syst Biol. 2015;9:5 Authors: Sridharan GV, Ullah E, Hassoun S, Lee K Abstract BACKGROUND: A substrate cycle is a set of metabolic reactions, arranged in a loop, which does not result in net consumption or production of the metabolites. The cycle operates by transforming a cofactor, e.g. oxidizing a reducing equivalent. Substrate cycles have been found experimentally in many parts of metabolism; however, their physiological roles remain unclear. As genome-scale metabolic models become increasingly available, there is now the opportunity to comprehensively catalogue substrate cycles, and gain additional insight into this potentially important motif of metabolic networks. RESULTS: We present a method to identify substrate cycles in the context of metabolic modules, which facilitates functional analysis. This method utilizes elementary flux mode (EFM) analysis to find potential substrate cycles in the form of cyclical EFMs, and combines this analysis with network partition based on retroactive (cyclical) interactions between reactions. In addition to providing functional context, partitioning the network into modules allowed exhaustive EFM calculations on smaller, tractable subnetworks that are enriched in metabolic cycles. Applied to a large-scale model of human liver metabolism (HepatoNet1), our method found not only well-known substrate cycles involving ATP hydrolysis, but also potentially novel substrate cycles involving the transformation of other cofactors. A key characteristic of the substrate cycles identified in this study is that the lengths are relatively short (2-13 reactions), comparable to many experimentally observed substrate cycles. CONCLUSIONS: EFM computation for large scale networks remains computationally intractable for exhaustive substrate cycle enumeration. Our algorithm utilizes a 'divide and conquer' strategy where EFM analysis is performed on systematically identified network modules that are designed to be enriched in cyclical interactions. We find that several substrate cycles uncovered using our approach are not identified when the network is partitioned in a more generic manner based solely on connectivity rather than cycles, demonstrating the value of targeting motif searches to sub-networks replete with a topological feature that resembles the desired motif itself. PMID: 25884368 [PubMed - indexed for MEDLINE]

Related Articles Metabolic Profiling of Geobacter sulfurreducens during Industrial Bioprocess Scale-Up. Appl Environ Microbiol. 2015 May 15;81(10):3288-98 Authors: Muhamadali H, Xu Y, Ellis DI, Allwood JW, Rattray NJ, Correa E, Alrabiah H, Lloyd JR, Goodacre R Abstract During the industrial scale-up of bioprocesses it is important to establish that the biological system has not changed significantly when moving from small laboratory-scale shake flasks or culturing bottles to an industrially relevant production level. Therefore, during upscaling of biomass production for a range of metal transformations, including the production of biogenic magnetite nanoparticles by Geobacter sulfurreducens, from 100-ml bench-scale to 5-liter fermentors, we applied Fourier transform infrared (FTIR) spectroscopy as a metabolic fingerprinting approach followed by the analysis of bacterial cell extracts by gas chromatography-mass spectrometry (GC-MS) for metabolic profiling. FTIR results clearly differentiated between the phenotypic changes associated with different growth phases as well as the two culturing conditions. Furthermore, the clustering patterns displayed by multivariate analysis were in agreement with the turbidimetric measurements, which displayed an extended lag phase for cells grown in a 5-liter bioreactor (24 h) compared to those grown in 100-ml serum bottles (6 h). GC-MS analysis of the cell extracts demonstrated an overall accumulation of fumarate during the lag phase under both culturing conditions, coinciding with the detected concentrations of oxaloacetate, pyruvate, nicotinamide, and glycerol-3-phosphate being at their lowest levels compared to other growth phases. These metabolites were overlaid onto a metabolic network of G. sulfurreducens, and taking into account the levels of these metabolites throughout the fermentation process, the limited availability of oxaloacetate and nicotinamide would seem to be the main metabolic bottleneck resulting from this scale-up process. Additional metabolite-feeding experiments were carried out to validate the above hypothesis. Nicotinamide supplementation (1 mM) did not display any significant effects on the lag phase of G. sulfurreducens cells grown in the 100-ml serum bottles. However, it significantly improved the growth behavior of cells grown in the 5-liter bioreactor by reducing the lag phase from 24 h to 6 h, while providing higher yield than in the 100-ml serum bottles. PMID: 25746987 [PubMed - indexed for MEDLINE]

Related Articles Lipid mediators of inflammation as novel plasma biomarkers to identify patients with bacteremia. J Infect. 2015 May;70(5):433-44 Authors: To KK, Lee KC, Wong SS, Lo KC, Lui YM, Jahan AS, Wu AL, Ke YH, Law CY, Sze KH, Lau SK, Woo PC, Lam CW, Yuen KY Abstract OBJECTIVES: Rapid diagnostic tests for bacteremia are important for early treatment to improve clinical outcome. We sought to identify plasma biomarkers that can identify patients with bacteremia using an untargeted global metabolomic analysis. METHODS: Plasma metabolomic profiles were analyzed for 145 adult patients with (cases) and without (controls) bacteremia using ultra-high-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UHPLC-Q-TOF-MS). All metabolites were compared between cases and controls using a 2-tier filtering approach, and each metabolite underwent receiver operating characteristic (ROC) curve analysis. Individual metabolites that distinguish between cases and controls were characterized. Subgroup analysis was performed to identify metabolites with prognostic significance. RESULTS: After 2-tier filtering, 128 molecular features were identified to be potential biomarkers that could distinguish cases from controls. Five metabolites had an area under the ROC curve (AUC) of >0.8 in ROC curve analysis, including a sphingolipid, an acylcarnitine, a fatty acid ester, and 2 glycerophosphocholines. These metabolites could distinguish cases from controls in the unsupervised hierarchical clustering analysis. Subgroup analysis of bacteremic patients showed that the level of trans-2,3,4-trimethoxycinnamate was lower in fatal than non-fatal cases. CONCLUSIONS: Plasma lipid mediators of inflammation can distinguish bacteremia cases from non-bacteremia controls. These biomarkers may be used as targets for rapid test in clinical practice. PMID: 25727996 [PubMed - indexed for MEDLINE]

Quantitative target analysis and kinetic profiling of acyl-CoAs reveal the rate-limiting step in cyanobacterial 1-butanol production. Metabolomics. 2016;12:26 Authors: Noguchi S, Putri SP, Lan EI, Laviña WA, Dempo Y, Bamba T, Liao JC, Fukusaki E Abstract Cyanobacterial 1-butanol production is an important model system for direct conversion of CO2 to fuels and chemicals. Metabolically-engineered cyanobacteria introduced with a heterologous Coenzyme A (CoA)-dependent pathway modified from Clostridium species can convert atmospheric CO2 into 1-butanol. Efforts to optimize the 1-butanol pathway in Synechococcus elongatus PCC 7942 have focused on the improvement of the CoA-dependent pathway thus, probing the in vivo metabolic state of the CoA-dependent pathway is essential for identifying its limiting steps. In this study, we performed quantitative target analysis and kinetic profiling of acyl-CoAs in the CoA-dependent pathway by reversed phase ion-pair liquid chromatography-triple quadrupole mass spectrometry. Using (13)C-labelled cyanobacterial cell extract as internal standard, measurement of the intracellular concentration of acyl-CoAs revealed that the reductive reaction of butanoyl-CoA to butanal is a possible rate-limiting step. In addition, improvement of the butanoyl-CoA to butanal reaction resulted in an increased rate of acetyl-CoA synthesis by possibly compensating for the limitation of free CoA species. We inferred that the efficient recycling of free CoA played a key role in enhancing the conversion of pyruvate to acetyl-CoA. PMID: 26766939 [PubMed - as supplied by publisher]

Chemical Assignment of Structural Isomers of Sulfur-Containing Metabolites in Garlic by Liquid Chromatography-Fourier Transform Ion Cyclotron Resonance-Mass Spectrometry. J Nutr. 2016 Jan 13; Authors: Nakabayashi R, Sawada Y, Aoyagi M, Yamada Y, Hirai MY, Sakurai T, Kamoi T, Rowan DD, Saito K Abstract BACKGROUND: The chemical assignment of metabolites is crucial to understanding the relation between food composition and biological activity. OBJECTIVE: This study was designed to detect and chemically assign sulfur-containing metabolites by using LC-Fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) in Allium plants. METHODS: Ultrahigh resolution (>250,000 full width at half-maximum) and mass accuracy (<1 mDa) by FTICR-MS allowed us to distinguish ions containing sulfur isotopes ((32)S and (34)S). RESULTS: Putative 69 S-containing monoisotopic ions (S-ions) were extracted from the metabolome data of onion (Allium cepa), green onion (Allium fistulosum), and garlic (Allium sativum) on the basis of theoretical mass differences between (32)S-ions and their (34)S-substituted counterparts and on the natural abundance of (34)S. Eight S-ions were chemically assigned by using the reference data according to the guidelines of the Metabolomics Standards Initiative. Three ions detected in garlic were assigned as derived from the isomers γ-glutamyl-S-1-propenylcysteine and γ-glutamyl-S-2-propenylcysteine and as S-2-propenylmercaptoglutathione on the basis of differences in key product ions identified in reference tandem MS spectra. CONCLUSION: The ability to discriminate between such geometric isomers will be extremely useful for the chemical assignment of unknown metabolites in MS-based metabolomics. PMID: 26764333 [PubMed - as supplied by publisher]

Rapid comparison of metabolites in humans and rats of different sexes using untargeted UPLC-TOFMS and an in-house software platform. Eur J Mass Spectrom (Chichester, Eng). 2015;21(6):801-21 Authors: Liang Q, Xu W, Hong Q, Xiao C, Yang L, Ma Z, Wang Y, Tan H, Tang X, Gao Y Abstract Metabolite differences between sexes have rarely been observed in a global manner, but it has recently been made possible by the advancement in metabolomics techniques. In this study, untargeted ultraperformance liquid chromatography coupled to time-of-flight mass spectrometry and an in-house software platform were used for a rapid comparison of sex differences in urinary metabolites in humans and in urinary and serum metabolites in Sprague Dawley (SD) rats. In addition, the species differences of urinary metabolites between humans and SD rats were also observed. Principle component analysis showed that all the observed metabolite sex differences were more distinct in SD rats than in humans, indicating that the sex differences of human urinary metabolites is small compared with that of SD rats. In SD rats, the observed metabolite sex differences were more distinct in urine than in serum, indicating the importance of urine analysis for metabolomics studies. The species differences in the urinary metabolites of humans and SD rats were much more distinct than any of the observed sex differences. Many sex- and species-related markers were discovered and putatively identified. In both humans and SD rats, steroid metabolites appeared to constitute a major sex difference in urinary metabolites. This provides new proof of the special importance of steroid metabolites in sex differences from an untargeted metabolomics investigation, which is rare for sex differences. Contrary patterns involving adrenocortical activity appeared to exist between rodents and humans, which agrees with previous reports. In the serum metabolites of SD rats, sex differences in ascorbic acid or its isomer and pantothenic acid or its isomer, but not in steroid metabolites, were prominent. Human-specific α-N- phenylacetyl-l-glutamine and androsterone glucuronide were among the putative identities of the markers discriminating humans and SD rats. This study demonstrated the feasibility of an in-house software platform and provides metabolite-related information on sex and species differences. PMID: 26764310 [PubMed - in process]

Variable selection for binary classification using error rate p-values applied to metabolomics data. BMC Bioinformatics. 2016;17(1):33 Authors: van Reenen M, Reinecke CJ, Westerhuis JA, Venter JH Abstract BACKGROUND: Metabolomics datasets are often high-dimensional though only a limited number of variables are expected to be informative given a specific research question. The important task of selecting informative variables can therefore become complex. In this paper we look at discriminating between two groups. Two tasks need to be performed: (i) finding variables which differ between the two groups; and (ii) determining how the selected variables can be used to classify new subjects. We introduce an approach using minimum classification error rates as test statistics to find discriminatory and therefore informative variables. The thresholds resulting in the minimum error rates can be used to classify new subjects. This approach transforms error rates into p-values and is referred to as ERp. RESULTS: We show that non-parametric hypothesis testing, based on minimum classification error rates as test statistics, can find statistically significantly shifted variables. The discriminatory ability of variables becomes more apparent when error rates are evaluated based on their corresponding p-values, as relatively high error rates can still be statistically significant. ERp can handle unequal and small group sizes, as well as account for the cost of misclassification. ERp retains (if known) or reveals (if unknown) the shift direction, aiding in biological interpretation. The threshold resulting in the minimum error rate can immediately be used to classify new subjects. We use NMR generated metabolomics data to illustrate how ERp is able to discriminate subjects diagnosed with Mycobacterium tuberculosis infected meningitis from a control group. The list of discriminatory variables produced by ERp contains all biologically relevant variables with appropriate shift directions discussed in the original paper from which this data is taken. CONCLUSIONS: ERp performs variable selection and classification, is non-parametric and aids biological interpretation while handling unequal group sizes and misclassification costs. All this is achieved by a single approach which is easy to perform and interpret. ERp has the potential to address many other characteristics of metabolomics data. Future research aims to extend ERp to account for a large proportion of observations below the detection limit, as well as expand on interactions between variables. PMID: 26763892 [PubMed - in process]

Potential of monitoring isotopologues by quantitative gas chromatography with time-of-flight mass spectrometry for metabolomic assay. J Sep Sci. 2016 Jan 13; Authors: Wang Y, Hu H, Su Y, Zhang F, Guo Y Abstract Because of the extreme complexity of metabolomic samples, the effectiveness of quantitative gas chromatography with time-of-flight mass spectrometry depends substantially on the expanding of the linear dynamic range. Facing the existent of numerous saturated detector signals, a data processing method based on monitoring isotopologues has been developed. The monoisotopic ion kept the high mass spectrometry sensitivity and the less abundant isotopologue ions extended the linear dynamic range. The alternative method was proved to extend the linear dynamic range to five orders of magnitude successfully and overcome the quantitative problems induced by the ion detector saturation. Finally, to validate the applicability, the method was applied to a metabolomic assay of Alzheimer's disease. Comparing with the traditional monoisotopic method, the use of monitoring isotopologues helped to discover additional eight metabolites with significant difference and conducted a more reliable principal component analysis as well. The results demonstrated that monitoring isotopologues in quantitative gas chromatography with time-of-flight mass spectrometry could improve the authenticity of metabolomic analysis. This article is protected by copyright. All rights reserved. PMID: 26763370 [PubMed - as supplied by publisher]

Sample normalization methods in quantitative metabolomics. J Chromatogr A. 2015 Dec 10; Authors: Wu Y, Li L Abstract To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts. PMID: 26763302 [PubMed - as supplied by publisher]

Related Articles Comprehensive Metabolomic, Lipidomic and Microscopic Profiling of Yarrowia lipolytica during Lipid Accumulation Identifies Targets for Increased Lipogenesis. PLoS One. 2015;10(4):e0123188 Authors: Pomraning KR, Wei S, Karagiosis SA, Kim YM, Dohnalkova AC, Arey BW, Bredeweg EL, Orr G, Metz TO, Baker SE Abstract Yarrowia lipolytica is an oleaginous ascomycete yeast that accumulates large amounts of lipids and has potential as a biofuel producing organism. Despite a growing scientific literature focused on lipid production by Y. lipolytica, there remain significant knowledge gaps regarding the key biological processes involved. We applied a combination of metabolomic and lipidomic profiling approaches as well as microscopic techniques to identify and characterize the key pathways involved in de novo lipid accumulation from glucose in batch cultured, wild-type Y. lipolytica. We found that lipids accumulated rapidly and peaked at 48 hours during the five day experiment, concurrent with a shift in amino acid metabolism. We also report that exhaustion of extracellular sugars coincided with thickening of the cell wall, suggesting that genes involved in cell wall biogenesis may be a useful target for improving the efficiency of lipid producing yeast strains. PMID: 25905710 [PubMed - indexed for MEDLINE]

Related Articles Metabolic profiling analysis of berberine, palmatine, jatrorrhizine, coptisine and epiberberine in zebrafish by ultra-high performance liquid chromatography coupled with LTQ Orbitrap mass spectrometer. Xenobiotica. 2015 Apr;45(4):302-11 Authors: Li Y, Wang H, Si N, Ren W, Han L, Xin S, Zuo R, Wei X, Yang J, Zhao H, Bian B Abstract 1. Zebrafish has been used in metabolic study of drugs as a powerful tool in recent years. In this study, we make a feasible metabolism investigation of five protoberberine alkaloids (PBAs) applied in zebrafish model for the first time, including berberine (BBR), palmatine (PAL), jatrorrhizine (JAT), coptisine (COP) and epiberberine (EBBR). 2. After exposure for 24 hours, 19 metabolites were identified by LTQ Orbitrap mass spectrometer, including 9 phase I metabolites and 10 phase II metabolites. Demethylation, hydroxylation, sulfation and glucuronidation were the major metabolic transformation of PBAs in zebrafish, which were similar to mammals. Compared with reported literatures, BBR and JAT showed high consistency between human and zebrafish in metabolic pathways. 3. To our knowledge, this is the first time to study in vivo metabolism of COP, which provides useful information to other researchers. 4. This study indicated that zebrafish model is feasible and reasonable to predict the metabolism of PBAs. It showed great potential for developing a novel and rapid method for predicting the metabolism of trace compounds of botanical drugs, with the advantages of lower cost, higher performance and easier set up. PMID: 25369727 [PubMed - indexed for MEDLINE]

Annexin A1 sustains tumor metabolism and cellular proliferation upon stable loss of HIF1A. Oncotarget. 2015 Dec 29; Authors: Rohwer N, Bindel F, Grimm C, Lin SJ, Wappler J, Klinger B, Blüthgen N, Du Bois I, Schmeck B, Lehrach H, de Graauw M, Goncalves E, Saez-Rodriguez J, Tan P, Grabsch HI, Prigione A, Kempa S, Cramer T Abstract Despite the approval of numerous molecular targeted drugs, long-term antiproliferative efficacy is rarely achieved and therapy resistance remains a central obstacle of cancer care. Combined inhibition of multiple cancer-driving pathways promises to improve antiproliferative efficacy. HIF-1 is a driver of gastric cancer and considered to be an attractive target for therapy. We noted that gastric cancer cells are able to functionally compensate the stable loss of HIF-1α. Via transcriptomics we identified a group of upregulated genes in HIF-1α-deficient cells and hypothesized that these genes confer survival upon HIF-1α loss. Strikingly, simultaneous knock-down of HIF-1α and Annexin A1 (ANXA1), one of the identified genes, resulted in complete cessation of proliferation. Using stable isotope-resolved metabolomics, oxidative and reductive glutamine metabolism was found to be significantly impaired in HIF-1α/ANXA1-deficient cells, potentially explaining the proliferation defect. In summary, we present a conceptually novel application of stable gene inactivation enabling in-depth deconstruction of resistance mechanisms. In theory, this experimental approach is applicable to any cancer-driving gene or pathway and promises to identify various new targets for combination therapies. PMID: 26760764 [PubMed - as supplied by publisher]

The choice of amniotic fluid in metabolomics for the monitoring of fetus health. Expert Rev Mol Diagn. 2016 Jan 13; Authors: Palmas F, Fattuoni C, Noto A, Barberini L, Dessì A, Fanos V Abstract Amniotic fluid (AF) is a biological fluid in which metabolite transport is regulated by the placenta, the permeable skin, fetal lung egress and gastric fluid. During pregnancy, the composition of AF changes from similar to the interstitial fluid of the mother, to a more complex system, influenced by the fetus's urine. Since AF reflects the mother's and the fetus's health status at the same time, it may be an important diagnostic tool for a wider spectrum of clinical conditions. Indeed, the metabolic characterization of AF in relation to pathological occurrences may lead to the discovery of new biomarkers for a better clinical practice. For this reason, metabolomics may be the most suitable strategy for this task. In this review, research works on metabolomic AF analysis are discussed according to the morbidity of interest, being preterm birth/labor, gestational age and diabetes and fetal malformations, along with a number of other important studies. PMID: 26760526 [PubMed - as supplied by publisher]

LC-MS based metabolomics discovers purine endogenous associations with low dose salbutamol in urine collected for anti-doping tests. Anal Chem. 2016 Jan 13; Authors: Wang Y, Caldwell RT, Cowan DA, Legido-Quigley C Abstract Current anti-doping analytical methods are tailored mainly to the targeting of known drugs and endogenous molecules. This causes difficulties in rapidly reacting to emerging threats such as designer drugs, biological therapeutic agents and technologies. Biomarkers are considered as a promising approach for the fight against these threats to sport. The main purpose of this study was to find surrogate biomarkers induced by the intake of small amounts of the model compound salbutamol and explore a sensitive approach to help screen for possible drug misuse. Urine samples (91) from athletes with detectable salbutamol (30) and negative samples (61) were analyzed using a UHPLC-MS. A third group (30) was created by spiking salbutamol into negative samples to eliminate confounding effects. Data were then analysed in XCMS to extract metabolic features. Orthogonal Partial Least Squares - Discriminant Analysis was performed to select features correlated with detectable salbutamol (pcorr >0.5) and ROC analysis was performed to measure the predictive potential of the markers. Univariate analysis including Mann-Whitney U test and Spearman's correlation was conducted on selected markers. A total of 7,000 metabolic features were parsed, one feature identified as hypoxanthine increased with salbutamol (p <0.001). The ROC curve of hypoxanthine returned an AUC of 0.79 (p <0.001). Correlation with salbutamol (r=0.415, p <0.01, Spearman's correlation) showed hypoxanthine and purine metabolism have association to salbutamol administration. This surrogate discovery approach needs further PK studies but in the meantime can be used as an intelligence-based complementary approach for targeting of athletes to be further tested. PMID: 26760048 [PubMed - as supplied by publisher]

Related Articles CD47 Receptor Globally Regulates Metabolic Pathways That Control Resistance to Ionizing Radiation. J Biol Chem. 2015 Oct 9;290(41):24858-74 Authors: Miller TW, Soto-Pantoja DR, Schwartz AL, Sipes JM, DeGraff WG, Ridnour LA, Wink DA, Roberts DD Abstract Modulating tissue responses to stress is an important therapeutic objective. Oxidative and genotoxic stresses caused by ionizing radiation are detrimental to healthy tissues but beneficial for treatment of cancer. CD47 is a signaling receptor for thrombospondin-1 and an attractive therapeutic target because blocking CD47 signaling protects normal tissues while sensitizing tumors to ionizing radiation. Here we utilized a metabolomic approach to define molecular mechanisms underlying this radioprotective activity. CD47-deficient cells and cd47-null mice exhibited global advantages in preserving metabolite levels after irradiation. Metabolic pathways required for controlling oxidative stress and mediating DNA repair were enhanced. Some cellular energetics pathways differed basally in CD47-deficient cells, and the global declines in the glycolytic and tricarboxylic acid cycle metabolites characteristic of normal cell and tissue responses to irradiation were prevented in the absence of CD47. Thus, CD47 mediates signaling from the extracellular matrix that coordinately regulates basal metabolism and cytoprotective responses to radiation injury. PMID: 26311851 [PubMed - indexed for MEDLINE]

Related Articles Application of GC/MS-based metabonomic profiling in studying the therapeutic effects of Huangbai-Zhimu herb-pair (HZ) extract on streptozotocin-induced type 2 diabetes in mice. J Chromatogr B Analyt Technol Biomed Life Sci. 2015 Aug 1;997:96-104 Authors: Song L, Liu H, Wang Y, Wang Y, Liu J, Zhou Z, Chu H, Zhuang P, Zhang Y Abstract A protocol for metabolic profiling of mice urine was developed based on gas chromatograph-mass spectrometer (GC-MS) to explore metabolic state directly. The intra-day, inter-day, repeatability, and stability RSD for most endogenous compounds were less than 3%. Type 2 diabetic mellitus (T2DM) mice model was induced by high calorie diet combined with streptozocin. Urine from the control, T2DM and Huangbai-Zhimu herb-pair (HZ) treatment mice were enrolled in the subsequent study to show the usefulness of the method. OPLS-DA scores plots demonstrate that the cluster of T2DM mice is separated from that of control mice, while HZ-T2DM mice are located close to control mice, indicating that metabolic profiles of these HZ-T2DM mice are placed toward those of control group. The results illustrate that HZ treatment could lower the level of d-glucose, hexadecanoic acid, octadecanoic acid, propanoic acid, 3-hydroxybutyric acid, and 2,3-dihydroxybutanoic acid in urine of DM mice, meanwhile the results show that HZ treatment could ameliorate T2DM symptoms by intervening the fatty acid metabolism, starch and sucrose metabolism, and glyoxylate and dicarboxylate metabolism. This preliminary application indicated that the method is suitable and reliable for urine metabolic profiling. This study might explain the metabolic effects of T2DM and the mechanisms of action of HZ against T2DM. PMID: 26094210 [PubMed - indexed for MEDLINE]

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