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Sample records for metabolomics analysis reveals

  1. Capillary electrophoresis - Mass spectrometry metabolomics analysis revealed enrichment of hypotaurine in rat glioma tissues.

    Gao, Peng; Ji, Min; Fang, Xueyan; Liu, Yingyang; Yu, Zhigang; Cao, Yunfeng; Sun, Aijun; Zhao, Liang; Zhang, Yong

    2017-11-15

    Glioma is one of the most lethal brain malignancies with unknown etiologies. Many metabolomics analysis aiming at diverse kinds of samples had been performed. Due to the varied adopted analytical platforms, the reported disease-related metabolites were not consistent across different studies. Comparable metabolomics results are more likely to be acquired by analyzing the same sample types with identical analytical platform. For tumor researches, tissue samples metabolomics analysis own the unique advantage that it can gain more direct insight into disease-specific pathological molecules. In this light, a previous reported capillary electrophoresis - mass spectrometry human tissues metabolomics analysis method was employed to profile the metabolome of rat C6 cell implantation gliomas and the corresponding precancerous tissues. It was found that 9 metabolites increased in the glioma tissues. Of them, hypotaurine was the only metabolite that enriched in the malignant tissues as what had been reported in the relevant human tissues metabolomics analysis. Furthermore, hypotaurine was also proved to inhibit α-ketoglutarate-dependent dioxygenases (2-KDDs) through immunocytochemistry staining and in vitro enzymatic activity assays by using C6 cell cultures. This study reinforced the previous conclusion that hypotaurine acted as a competitive inhibitor of 2-KDDs and proved the value of metabolomics in oncology studies. Copyright © 2017. Published by Elsevier Inc.

  2. Metabolomics analysis reveals the metabolic and functional roles of flavonoids in light-sensitive tea leaves.

    Zhang, Qunfeng; Liu, Meiya; Ruan, Jianyun

    2017-03-20

    As the predominant secondary metabolic pathway in tea plants, flavonoid biosynthesis increases with increasing temperature and illumination. However, the concentration of most flavonoids decreases greatly in light-sensitive tea leaves when they are exposed to light, which further improves tea quality. To reveal the metabolism and potential functions of flavonoids in tea leaves, a natural light-sensitive tea mutant (Huangjinya) cultivated under different light conditions was subjected to metabolomics analysis. The results showed that chlorotic tea leaves accumulated large amounts of flavonoids with ortho-dihydroxylated B-rings (e.g., catechin gallate, quercetin and its glycosides etc.), whereas total flavonoids (e.g., myricetrin glycoside, epigallocatechin gallate etc.) were considerably reduced, suggesting that the flavonoid components generated from different metabolic branches played different roles in tea leaves. Furthermore, the intracellular localization of flavonoids and the expression pattern of genes involved in secondary metabolic pathways indicate a potential photoprotective function of dihydroxylated flavonoids in light-sensitive tea leaves. Our results suggest that reactive oxygen species (ROS) scavenging and the antioxidation effects of flavonoids help chlorotic tea plants survive under high light stress, providing new evidence to clarify the functional roles of flavonoids, which accumulate to high levels in tea plants. Moreover, flavonoids with ortho-dihydroxylated B-rings played a greater role in photo-protection to improve the acclimatization of tea plants.

  3. Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.

    Georgii, Elisabeth; Jin, Ming; Zhao, Jin; Kanawati, Basem; Schmitt-Kopplin, Philippe; Albert, Andreas; Winkler, J Barbro; Schäffner, Anton R

    2017-07-10

    Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response. In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways. Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome

  4. Comparative proteomic and metabolomic analysis reveal the antiosteoporotic molecular mechanism of icariin from Epimedium brevicornu maxim.

    Xue, Liming; Jiang, Yiping; Han, Ting; Zhang, Naidan; Qin, Luping; Xin, Hailiang; Zhang, Qiaoyan

    2016-11-04

    Icariin, a principal flavonoid glycoside of Epimedium brevicornu Maxim, has been widely proved to possess antiosteoporotic activity with promoting bone formation and decreasing bone resorption. However, the involving mechanisms remain unclear. To clear a global insight of signal pathways involved in anti-osteoporotic mechanism of icariin at proteins and metabolites level by integrating the proteomics and NMR metabonomics, in a systems biology approach. Mice were divided into sham, OVX model and icariin-treated OVX group, after 90 days treatment, difference gel electrophoresis combined with MALDI-TOF/TOF proteomics analysis on bone femur and serum metabolomics were carried out for monitor intracellular processes and elucidate anti-osteoporotic mechanism of icariin. Osteoblast and osteoclast were applied to evaluate the potential signal pathways. Twenty three proteins in bone femur, and 8 metabolites in serum, were significantly altered and identified, involving in bone remodeling, energy metabolism, cytoskeleton, lipid metabolism, MAPK signaling, Ca 2+ signaling et, al. Furthermore, animal experiment show icariin could enhance the BMD and BMC, decrease CTX-I level in ovariectomized mice. The mitochondrial membrane potential and the intracellular ATP levels were increased significantly, and the cytoskeleton were improved in icariin-treatment osteoblast and osteoclast. Icariin also increased mRNA expression of Runx2 and osterix of OB, decreased CTR and CAII mRNA expression and protein expression of P38 and JNK. However, icariin did not reveal any inhibition of the collagenolytic activity of cathepsin K, mRNA expression of MMP-9 and protein expression of ERK in osteoclast. we consider icariin as multi-targeting compounds for treating with osteoporosis, involve initiating osteoblastogenesis, inhibiting adipogenesis, and preventing osteoclast differentiation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  5. Metabolomics

    Kamstrup-Nielsen, Maja Hermann

    Metabolomics is the analysis of the whole metabolome and the focus in metabolomics studies is to measure as many metabolites as possible. The use of chemometrics in metabolomics studies is widespread, but there is a clear lack of validation in the developed models. The focus in this thesis has been...... how to properly handle complex metabolomics data, in order to achieve reliable and valid multivariate models. This has been illustrated by three case studies with examples of forecasting breast cancer and early detection of colorectal cancer based on data from nuclear magnetic resonance (NMR...... is a presentation of a core consistency diagnostic aiding in determining the number of components in a PARAFAC2 model. It is of great importance to validate especially PLS-DA models and if not done properly, the developed models might reveal spurious groupings. Furthermore, data from metabolomics studies contain...

  6. A synbiotic improves the immunity of white shrimp, Litopenaeus vannamei: Metabolomic analysis reveal compelling evidence.

    Huynh, Truong-Giang; Cheng, Ann-Chang; Chi, Chia-Chun; Chiu, Kuo-Hsun; Liu, Chun-Hung

    2018-05-18

    In this study, we examined the synergistic effects of a diet-administered synbiotic comprising galactooligosaccharide (GOS) and the probiotic Lactobacillus plantarum 7-40 on immune responses, immune-related gene expressions, and disease resistance to Vibrio alginolyticus in white shrimp Litopenaeus vannamei. To unravel the regulatory role of the synbiotic in activating the immune system of shrimp, 1 H nuclear magnetic resonance (NMR)-based metabolomic analysis were used to investigate hepatopancreas metabolites, then significantly altered metabolites were confirmed in both the hepatopancreas and plasma by reverse-phase high-performance liquid chromatography (RP-HPLC) and spectrophotometric analysis. Shrimp were fed four experimental diets for 60 days, including a basal diet with no GOS or probiotic (control), 0.4% GOS (PRE), probiotic (PRO), and 0.4% GOS in combination with the probiotic (SYN). Results showed that the SYN diet significantly increased survival of L. vannamei 24 h after a V. alginolyticus injection. Immune parameters such as phenoloxidase activity, respiratory bursts, phagocytic activity and gene expressions, including prophenoloxidase I, serine proteinase, and peroxinectin, of shrimp fed the SYN diet significantly increased, compared to the other treatments and control. In addition, results from the 1 H NMR analysis revealed that 22 hepatopancreas metabolites were matched and identified between the SYN and control groups, among which three metabolites, i.e., inosine monophosphate (IMP), valine, and betaine, significantly increased in the SYN group. Confirmation using RP-HPLC and spectrophotometric methods showed that IMP presented high amounts in the hepatopancreas, but not in the plasma of shrimp; in contrast, valine and betaine metabolites were in high concentrations in both the hepatopancreas and plasma. Our results suggested that GOS and the probiotic had a synergistic effect on enhancing immunity and disease resistance of L. vannamei against

  7. Metabolomics Analysis Reveals Specific Novel Tetrapeptide and Potential Anti-Inflammatory Metabolites in Pathogenic Aspergillus species.

    Lee, Kim-Chung; Tam, Emily W T; Lo, Ka-Ching; Tsang, Alan K L; Lau, Candy C Y; To, Kelvin K W; Chan, Jasper F W; Lam, Ching-Wan; Yuen, Kwok-Yung; Lau, Susanna K P; Woo, Patrick C Y

    2015-06-17

    Infections related to Aspergillus species have emerged to become an important focus in infectious diseases, as a result of the increasing use of immunosuppressive agents and high fatality associated with invasive aspergillosis. However, laboratory diagnosis of Aspergillus infections remains difficult. In this study, by comparing the metabolomic profiles of the culture supernatants of 30 strains of six pathogenic Aspergillus species (A. fumigatus, A. flavus, A. niger, A. terreus, A. nomius and A. tamarii) and 31 strains of 10 non-Aspergillus fungi, eight compounds present in all strains of the six Aspergillus species but not in any strain of the non-Aspergillus fungi were observed. One of the eight compounds, Leu-Glu-Leu-Glu, is a novel tetrapeptide and represents the first linear tetrapeptide observed in Aspergillus species, which we propose to be named aspergitide. Two other closely related Aspergillus-specific compounds, hydroxy-(sulfooxy)benzoic acid and (sulfooxy)benzoic acid, may possess anti-inflammatory properties, as 2-(sulfooxy)benzoic acid possesses a structure similar to those of aspirin [2-(acetoxy)benzoic acid] and salicylic acid (2-hydroxybenzoic acid). Further studies to examine the potentials of these Aspergillus-specific compounds for laboratory diagnosis of aspergillosis are warranted and further experiments will reveal whether Leu-Glu-Leu-Glu, hydroxy-(sulfooxy)benzoic acid and (sulfooxy)benzoic acid are virulent factors of the pathogenic Aspergillus species.

  8. Combined Analysis of the Fruit Metabolome and Transcriptome Reveals Candidate Genes Involved in Flavonoid Biosynthesis in Actinidia arguta.

    Li, Yukuo; Fang, Jinbao; Qi, Xiujuan; Lin, Miaomiao; Zhong, Yunpeng; Sun, Leiming; Cui, Wen

    2018-05-15

    To assess the interrelation between the change of metabolites and the change of fruit color, we performed a combined metabolome and transcriptome analysis of the flesh in two different Actinidia arguta cultivars: "HB" ("Hongbaoshixing") and "YF" ("Yongfengyihao") at two different fruit developmental stages: 70d (days after full bloom) and 100d (days after full bloom). Metabolite and transcript profiling was obtained by ultra-performance liquid chromatography quadrupole time-of-flight tandem mass spectrometer and high-throughput RNA sequencing, respectively. The identification and quantification results of metabolites showed that a total of 28,837 metabolites had been obtained, of which 13,715 were annotated. In comparison of HB100 vs. HB70, 41 metabolites were identified as being flavonoids, 7 of which, with significant difference, were identified as bracteatin, luteolin, dihydromyricetin, cyanidin, pelargonidin, delphinidin and (-)-epigallocatechin. Association analysis between metabolome and transcriptome revealed that there were two metabolic pathways presenting significant differences during fruit development, one of which was flavonoid biosynthesis, in which 14 structural genes were selected to conduct expression analysis, as well as 5 transcription factor genes obtained by transcriptome analysis. RT-qPCR results and cluster analysis revealed that AaF3H , AaLDOX , AaUFGT , AaMYB , AabHLH , and AaHB2 showed the best possibility of being candidate genes. A regulatory network of flavonoid biosynthesis was established to illustrate differentially expressed candidate genes involved in accumulation of metabolites with significant differences, inducing red coloring during fruit development. Such a regulatory network linking genes and flavonoids revealed a system involved in the pigmentation of all-red-fleshed and all-green-fleshed A. arguta , suggesting this conjunct analysis approach is not only useful in understanding the relationship between genotype and phenotype

  9. Large-scale Metabolomic Analysis Reveals Potential Biomarkers for Early Stage Coronary Atherosclerosis.

    Gao, Xueqin; Ke, Chaofu; Liu, Haixia; Liu, Wei; Li, Kang; Yu, Bo; Sun, Meng

    2017-09-18

    Coronary atherosclerosis (CAS) is the pathogenesis of coronary heart disease, which is a prevalent and chronic life-threatening disease. Initially, this disease is not always detected until a patient presents with seriously vascular occlusion. Therefore, new biomarkers for appropriate and timely diagnosis of early CAS is needed for screening to initiate therapy on time. In this study, we used an untargeted metabolomics approach to identify potential biomarkers that could enable highly sensitive and specific CAS detection. Score plots from partial least-squares discriminant analysis clearly separated early-stage CAS patients from controls. Meanwhile, the levels of 24 metabolites increased greatly and those of 18 metabolites decreased markedly in early CAS patients compared with the controls, which suggested significant metabolic dysfunction in phospholipid, sphingolipid, and fatty acid metabolism in the patients. Furthermore, binary logistic regression showed that nine metabolites could be used as a combinatorial biomarker to distinguish early-stage CAS patients from controls. The panel of nine metabolites was then tested with an independent cohort of samples, which also yielded satisfactory diagnostic accuracy (AUC = 0.890). In conclusion, our findings provide insight into the pathological mechanism of early-stage CAS and also supply a combinatorial biomarker to aid clinical diagnosis of early-stage CAS.

  10. Canonical correlation analysis of multiple sensory directed metabolomics data blocks reveals corresponding parts between data blocks.

    Doeswijk, T. G.; Hageman, J.A.; Westerhuis, J.A.; Tikunov, Y.; Bovy, A.; van Eeuwijk, F.A.

    2011-01-01

    Multiple analytical platforms are frequently used in metabolomics studies. The resulting multiple data blocks contain, in general, similar parts of information which can be disclosed by chemometric methods. The metabolites of interest, however, are usually just a minor part of the complete data

  11. Functional metabolomics reveals novel active products in the DHA metabolome

    Masakazu eShinohara

    2012-04-01

    Full Text Available Endogenous mechanisms for successful resolution of an acute inflammatory response and the local return to homeostasis are of interest because excessive inflammation underlies many human diseases. In this review, we provide an update and overview of functional metabolomics that identified a new bioactive metabolome of docosahexaenoic acid (DHA. Systematic studies revealed that DHA was converted to DHEA-derived novel bioactive products as well as aspirin-triggered (AT forms of protectins. The new oxygenated DHEA derived products blocked PMN chemotaxis, reduced P-selectin expression and platelet-leukocyte adhesion, and showed organ protection in ischemia/reperfusion injury. These products activated cannabinoid receptor (CB2 receptor and not CB1 receptors. The AT-PD1 reduced neutrophil (PMN recruitment in murine peritonitis. With human cells, AT-PD1 decreased transendothelial PMN migration as well as enhanced efferocytosis of apoptotic human PMN by macrophages. The recent findings reviewed here indicate that DHEA oxidative metabolism and aspirin-triggered conversion of DHA produce potent novel molecules with anti-inflammatory and organ-protective properties, opening the DHA metabolome functional roles.

  12. Comparative metabolome analysis of wheat embryo and endosperm reveals the dynamic changes of metabolites during seed germination.

    Han, Caixia; Zhen, Shoumin; Zhu, Gengrui; Bian, Yanwei; Yan, Yueming

    2017-06-01

    In this study, we performed the first comparative metabolomic analysis of the wheat embryo and endosperm during seed germination using GC-MS/MS. In total, 82 metabolites were identified in the embryo and endosperm. Principal component analysis (PCA), metabolite-metabolite correlation and hierarchical cluster analysis (HCA) revealed distinct dynamic changes in metabolites between the embryo and endosperm during seed germination. Generally, the metabolite changes in the embryo were much greater than those in the endosperm, suggesting that the embryo is more active than the endosperm during seed germination. Most amino acids were upregulated in both embryo and endosperm, while polysaccharides and organic acids associated with sugars were mainly downregulated in the embryo. Most of the sugars showed an upregulated trend in the endosperm, but significant changes in lipids occurred only in the embryo. Our results suggest that the embryo mobilises mainly protein and lipid metabolism, while the endosperm mobilises storage starch and minor protein metabolism during seed germination. The primary energy was generated mainly in the embryo by glycolysis during seed imbibition. The embryo containing most of the genetic information showed increased nucleotides during seed germination process, indicating more active transcription and translation metabolisms. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

  13. Metabolome analysis reveals the effect of carbon catabolite control on the poly(γ-glutamic acid) biosynthesis of Bacillus licheniformis ATCC 9945.

    Mitsunaga, Hitoshi; Meissner, Lena; Palmen, Thomas; Bamba, Takeshi; Büchs, Jochen; Fukusaki, Eiichiro

    2016-04-01

    Poly(γ-glutamic acid) (PGA) is a polymer composed of L- and/or D-glutamic acids that is produced by Bacillus sp. Because the polymer has various features as water soluble, edible, non-toxic and so on, it has attracted attention as a candidate for many applications such as foods, cosmetics and so on. However, although it is well known that the intracellular metabolism of Bacillus sp. is mainly regulated by catabolite control, the effect of the catabolite control on the PGA producing Bacillus sp. is largely unknown. This study is the first report of metabolome analysis on the PGA producing Bacillus sp. that reveals the effect of carbon catabolite control on the metabolism of PGA producing Bacillus licheniformis ATCC 9945. Results showed that the cells cultivated in glycerol-containing medium showed higher PGA production than the cells in glucose-containing medium. Furthermore, metabolome analysis revealed that the activators of CcpA and CodY, global regulatory proteins of the intracellular metabolism, accumulated in the cells cultivated in glycerol-containing and glucose-containing medium, respectively, with CodY apparently inhibiting PGA production. Moreover, the cells seemed to produce glutamate from citrate and ammonium using glutamine synthetase/glutamate synthase. Pulsed addition of di-ammonium hydrogen citrate, as suggested by the metabolome result, was able to achieve the highest value so far for PGA production in B. licheniformis. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  14. Transcriptome and metabolome analysis of Ferula gummosa Boiss. to reveal major biosynthetic pathways of galbanum compounds.

    Sobhani Najafabadi, Ahmad; Naghavi, Mohammad Reza; Farahmand, Hamid; Abbasi, Alireza

    2017-11-01

    Ferula gummosa Boiss. is an industrial and pharmaceutical plant that has been highly recognized for its valuable oleo-gum-resin, namely galbanum. Despite the fabulous value of galbanum, very little information on the genetic and biochemical mechanisms of its production existed. In the present study, the oleo-gum-resin and four organs (root, flower, stem, and leaf) of F. gummosa were assessed in terms of metabolic compositions and the expression of genes involved in their biosynthetic pathways. Results showed that the most accumulation of resin and essential oils were occurred in the roots (13.99 mg/g) and flowers (6.01 mg/g), respectively. While the most dominant compound of the resin was β-amyrin from triterpenes, the most abundant compounds of the essential oils were α-pinene and β-pinene from monoterpenes and α-eudesmol and germacrene-D from sesquiterpenes. Transcriptome analysis was performed by RNA sequencing (RNA-seq) for the plant roots and flowers. Differential gene expression analysis showed that 1172 unigenes were differential between two organs that 934 (79.6%) of them were up-regulated in the flowers and 238 (20.4%) unigenes were up-regulated in the roots (FDR ≤0.001). The most important up-regulated unigenes in the roots were involved in the biosynthesis of the major components of galbanum, including myrcene, germacrene-D, α-terpineol, and β-amyrin. The results obtained by RNA-Seq were confirmed by qPCR. These analyses showed that different organs of F. gummosa are involved in the production of oleo-gum-resin, but the roots are more active than other organs in terms of the biosynthesis of triterpenes and some mono- and sesquiterpenes. This study provides rich molecular and biochemical resources for further studies on molecular genetics and functional genomics of oleo-gum-resin production in F. gummosa.

  15. Comparative proteomic and metabolomic analysis of Streptomyces tsukubaensis reveals the metabolic mechanism of FK506 overproduction by feeding soybean oil.

    Wang, Jun; Liu, Huanhuan; Huang, Di; Jin, Lina; Wang, Cheng; Wen, Jianping

    2017-03-01

    FK506 (tacrolimus) is a 23-membered polyketide macrolide that possesses powerful immunosuppressant activity. In this study, feeding soybean oil into the fermentation culture of Streptomyces tsukubaensis improved FK506 production by 88.8%. To decipher the overproduction mechanism, comparative proteomic and metabolomic analysis was carried out. A total of 72 protein spots with differential expression in the two-dimensional gel electrophoresis (2-DE) were identified by matrix-assisted laser desorption/ionization time-of-flight/time-of-flight mass spectrometry (MALDI-TOF/TOF-MS), and 66 intracellular metabolites were measured by gas chromatography-mass spectrometer (GC-MS). The analysis of proteome and metabolome indicated that feeding soybean oil as a supplementary carbon source could not only strengthen the FK506 precursor metabolism and energy metabolism but also tune the pathways related to transcriptional regulation, translation, and stress response, suggesting a better intracellular metabolic environment for the synthesis of FK506. Based on these analyses, 20 key metabolites and precursors of FK506 were supplemented into the soybean oil medium. Among them, lysine, citric acid, shikimic acid, and malonic acid performed excellently for promoting the FK506 production and biomass. Especially, the addition of malonic acid achieved the highest FK506 production, which was 1.56-fold of that in soybean oil medium and 3.05-fold of that in initial medium. This report represented the first comprehensive study on the comparative proteomics and metabolomics applied in S. tsukubaensis, and it would be a rational guidance to further strengthen the FK506 production.

  16. Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: Investigation of nicotinic acid receptor agonists

    Zgoda-Pols, Joanna R.; Chowdhury, Swapan; Wirth, Mark; Milburn, Michael V.; Alexander, Danny C.; Alton, Kevin B.

    2011-01-01

    An investigative renal toxicity study using metabolomics was conducted with a potent nicotinic acid receptor (NAR) agonist, SCH 900424. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) techniques were used to identify small molecule biomarkers of acute kidney injury (AKI) that could aid in a better mechanistic understanding of SCH 900424-induced AKI in mice. The metabolomics study revealed 3-indoxyl sulfate (3IS) as a more sensitive marker of SCH 900424-induced renal toxicity than creatinine or urea. An LC-MS assay for quantitative determination of 3IS in mouse matrices was also developed. Following treatment with SCH 900424, 3IS levels were markedly increased in murine plasma and brain, thereby potentially contributing to renal- and central nervous system (CNS)-related rapid onset of toxicities. Furthermore, significant decrease in urinary excretion of 3IS in those animals due to compromised renal function may be associated with the elevation of 3IS in plasma and brain. These data suggest that 3IS has a potential to be a marker of renal and CNS toxicities during chemically-induced AKI in mice. In addition, based on the metabolomic analysis other statistically significant plasma markers including p-cresol-sulfate and tryptophan catabolites (kynurenate, kynurenine, 3-indole-lactate) might be of toxicological importance but have not been studied in detail. This comprehensive approach that includes untargeted metabolomic and targeted bioanalytical sample analyses could be used to investigate toxicity of other compounds that pose preclinical or clinical development challenges in a pharmaceutical discovery and development. - Research highlights: → Nicotinic acid receptor agonist, SCH 900424, caused acute kidney injury in mice. → MS-based metabolomics was conducted to identify potential small molecule markers of renal toxicity. → 3-indoxyl-sulfate was found to be as a more sensitive marker of renal toxicity than

  17. Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

    Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

    2018-01-01

    Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

  18. Combined Metabolomic Analysis of Plasma and Urine Reveals AHBA, Tryptophan and Serotonin Metabolism as Potential Risk Factors in Gestational Diabetes Mellitus (GDM

    Miriam Leitner

    2017-12-01

    Full Text Available Gestational diabetes mellitus during pregnancy has severe implications for the health of the mother and the fetus. Therefore, early prediction and an understanding of the physiology are an important part of prenatal care. Metabolite profiling is a long established method for the analysis and prediction of metabolic diseases. Here, we applied untargeted and targeted metabolomic protocols to analyze plasma and urine samples of pregnant women with and without GDM. Univariate and multivariate statistical analyses of metabolomic profiles revealed markers such as 2-hydroxybutanoic acid (AHBA, 3-hydroxybutanoic acid (BHBA, amino acids valine and alanine, the glucose-alanine-cycle, but also plant-derived compounds like sitosterin as different between control and GDM patients. PLS-DA and VIP analysis revealed tryptophan as a strong variable separating control and GDM. As tryptophan is biotransformed to serotonin we hypothesized whether serotonin metabolism might also be altered in GDM. To test this hypothesis we applied a method for the analysis of serotonin, metabolic intermediates and dopamine in urine by stable isotope dilution direct infusion electrospray ionization mass spectrometry (SID-MS. Indeed, serotonin and related metabolites differ significantly between control and GDM patients confirming the involvement of serotonin metabolism in GDM. Clustered correlation coefficient visualization of metabolite correlation networks revealed the different metabolic signatures between control and GDM patients. Eventually, the combination of selected blood plasma and urine sample metabolites improved the AUC prediction accuracy to 0.99. The detected GDM candidate biomarkers and the related systemic metabolic signatures are discussed in their pathophysiological context. Further studies with larger cohorts are necessary to underpin these observations.

  19. Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

    Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

    2016-06-01

    Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

  20. Metabolome analysis of Drosophila melanogaster during embryogenesis.

    An, Phan Nguyen Thuy; Yamaguchi, Masamitsu; Bamba, Takeshi; Fukusaki, Eiichiro

    2014-01-01

    The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos' metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo.

  1. Functional Analysis of Metabolomics Data.

    Chagoyen, Mónica; López-Ibáñez, Javier; Pazos, Florencio

    2016-01-01

    Metabolomics aims at characterizing the repertory of small chemical compounds in a biological sample. As it becomes more massive and larger sets of compounds are detected, a functional analysis is required to convert these raw lists of compounds into biological knowledge. The most common way of performing such analysis is "annotation enrichment analysis," also used in transcriptomics and proteomics. This approach extracts the annotations overrepresented in the set of chemical compounds arisen in a given experiment. Here, we describe the protocols for performing such analysis as well as for visualizing a set of compounds in different representations of the metabolic networks, in both cases using free accessible web tools.

  2. Fish mucus metabolome reveals fish life-history traits

    Reverter, M.; Sasal, P.; Banaigs, B.; Lecchini, D.; Lecellier, G.; Tapissier-Bontemps, N.

    2017-06-01

    Fish mucus has important biological and ecological roles such as defense against fish pathogens and chemical mediation among several species. A non-targeted liquid chromatography-mass spectrometry metabolomic approach was developed to study gill mucus of eight butterflyfish species in Moorea (French Polynesia), and the influence of several fish traits (geographic site and reef habitat, species taxonomy, phylogeny, diet and parasitism levels) on the metabolic variability was investigated. A biphasic extraction yielding two fractions (polar and apolar) was used. Fish diet (obligate corallivorous, facultative corallivorous or omnivorous) arose as the main driver of the metabolic differences in the gill mucus in both fractions, accounting for 23% of the observed metabolic variability in the apolar fraction and 13% in the polar fraction. A partial least squares discriminant analysis allowed us to identify the metabolites (variable important in projection, VIP) driving the differences between fish with different diets (obligate corallivores, facultative corallivores and omnivorous). Using accurate mass data and fragmentation data, we identified some of these VIP as glycerophosphocholines, ceramides and fatty acids. Level of monogenean gill parasites was the second most important factor shaping the gill mucus metabolome, and it explained 10% of the metabolic variability in the polar fraction and 5% in the apolar fraction. A multiple regression tree revealed that the metabolic variability due to parasitism in the polar fraction was mainly due to differences between non-parasitized and parasitized fish. Phylogeny and butterflyfish species were factors contributing significantly to the metabolic variability of the apolar fraction (10 and 3%, respectively) but had a less pronounced effect in the polar fraction. Finally, geographic site and reef habitat of butterflyfish species did not influence the gill mucus metabolome of butterflyfishes.

  3. The next wave in metabolome analysis

    Nielsen, Jens; Oliver, S.

    2005-01-01

    The metabolome of a cell represents the amplification and integration of signals from other functional genomic levels, such as the transcriptome and the proteome. Although this makes metabolomics a useful tool for the high-throughput analysis of phenotypes, the lack of a direct connection...... to the genome makes it difficult to interpret metabolomic data. Nevertheless, functional genomics has produced examples of the use of metabolomics to elucidate the phenotypes of otherwise silent mutations. Despite several successes, we believe that future metabolomic studies must focus on the accurate...... measurement of the concentrations of unambiguously identified metabolites. The research community must develop databases of metabolite concentrations in cells that are grown in several well-defined conditions if metabolomic data are to be integrated meaningfully with data from the other levels of functional...

  4. Combined Metabolomic Analysis of Plasma and Urine Reveals AHBA, Tryptophan and Serotonin Metabolism as Potential Risk Factors in Gestational Diabetes Mellitus (GDM)

    Leitner, Miriam; Fragner, Lena; Danner, Sarah; Holeschofsky, Nastassja; Leitner, Karoline; Tischler, Sonja; Doerfler, Hannes; Bachmann, Gert; Sun, Xiaoliang; Jaeger, Walter; Kautzky-Willer, Alexandra; Weckwerth, Wolfram

    2017-01-01

    Gestational diabetes mellitus during pregnancy has severe implications for the health of the mother and the fetus. Therefore, early prediction and an understanding of the physiology are an important part of prenatal care. Metabolite profiling is a long established method for the analysis and prediction of metabolic diseases. Here, we applied untargeted and targeted metabolomic protocols to analyze plasma and urine samples of pregnant women with and without GDM. Univariate and multivariate sta...

  5. Probabilistic Principal Component Analysis for Metabolomic Data.

    Nyamundanda, Gift

    2010-11-23

    Abstract Background Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique for analyzing metabolomic data. However, PCA is limited by the fact that it is not based on a statistical model. Results Here, probabilistic principal component analysis (PPCA) which addresses some of the limitations of PCA, is reviewed and extended. A novel extension of PPCA, called probabilistic principal component and covariates analysis (PPCCA), is introduced which provides a flexible approach to jointly model metabolomic data and additional covariate information. The use of a mixture of PPCA models for discovering the number of inherent groups in metabolomic data is demonstrated. The jackknife technique is employed to construct confidence intervals for estimated model parameters throughout. The optimal number of principal components is determined through the use of the Bayesian Information Criterion model selection tool, which is modified to address the high dimensionality of the data. Conclusions The methods presented are illustrated through an application to metabolomic data sets. Jointly modeling metabolomic data and covariates was successfully achieved and has the potential to provide deeper insight to the underlying data structure. Examination of confidence intervals for the model parameters, such as loadings, allows for principled and clear interpretation of the underlying data structure. A software package called MetabolAnalyze, freely available through the R statistical software, has been developed to facilitate implementation of the presented methods in the metabolomics field.

  6. Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

    Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

    2016-08-01

    Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

  7. Analysis of metabolomics data from twin families

    Draisma, Hermanus Henricus Maria

    2011-01-01

    Metabolomics is the comprehensive analysis of small molecules involved in metabolism, on the basis of samples that have been obtained from organisms in a given physiological state. Data obtained from measurements of trait levels in twin families can be used to elucidate the importance of genetic and

  8. Metabolomics reveals variation and correlation among different tissues of olive (Olea europaea L.

    Rao Guodong

    2017-09-01

    Full Text Available Metabolites in olives are associated with nutritional value and physiological properties. However, comprehensive information regarding the olive metabolome is limited. In this study, we identified 226 metabolites from three different tissues of olive using a non-targeted metabolomic profiling approach, of which 76 named metabolites were confirmed. Further statistical analysis revealed that these 76 metabolites covered different types of primary metabolism and some of the secondary metabolism pathways. One-way analysis of variance (ANOVA statistical assay was performed to calculate the variations within the detected metabolites, and levels of 65 metabolites were differentially expressed in different samples. Hierarchical cluster analysis (HCA dendrograms showed variations among different tissues that were similar to the metabolite profiles observed in new leaves and fruit. Additionally, 5776 metabolite-metabolite correlations were detected by a Pearson correlation coefficient approach. Screening of the calculated correlations revealed 3136, 3025, and 5184 were determined to metabolites and had significant correlations in three different combinations, respectively. This work provides the first comprehensive metabolomic of olive, which will provide new insights into understanding the olive metabolism, and potentially help advance studies in olive metabolic engineering.

  9. Quantitative Metabolomics and Instationary 13C-Metabolic Flux Analysis Reveals Impact of Recombinant Protein Production on Trehalose and Energy Metabolism in Pichia pastoris

    Joel Jordà

    2014-05-01

    Full Text Available Pichia pastoris has been recognized as an effective host for recombinant protein production. In this work, we combine metabolomics and instationary 13C metabolic flux analysis (INST 13C-MFA using GC-MS and LC-MS/MS to evaluate the potential impact of the production of a Rhizopus oryzae lipase (Rol on P. pastoris central carbon metabolism. Higher oxygen uptake and CO2 production rates and slightly reduced biomass yield suggest an increased energy demand for the producing strain. This observation is further confirmed by 13C-based metabolic flux analysis. In particular, the flux through the methanol oxidation pathway and the TCA cycle was increased in the Rol-producing strain compared to the reference strain. Next to changes in the flux distribution, significant variations in intracellular metabolite concentrations were observed. Most notably, the pools of trehalose, which is related to cellular stress response, and xylose, which is linked to methanol assimilation, were significantly increased in the recombinant strain.

  10. Metabolomic analysis reveals key metabolites related to the rapid adaptation of Saccharomyce cerevisiae to multiple inhibitors of furfural, acetic acid, and phenol.

    Wang, Xin; Li, Bing-Zhi; Ding, Ming-Zhu; Zhang, Wei-Wen; Yuan, Ying-Jin

    2013-03-01

    During hydrolysis of lignocellulosic biomass, a broad range of inhibitors are generated, which interfere with yeast growth and bioethanol production. In order to improve the strain tolerance to multiple inhibitors--acetic acid, furfural, and phenol (three representative lignocellulose-derived inhibitors) and uncover the underlying tolerant mechanism, an adaptation experiment was performed in which the industrial Saccharomyces cerevisiae was cultivated repeatedly in a medium containing multiple inhibitors. The adaptation occurred quickly, accompanied with distinct increase in growth rate, glucose utilization rate, furfural metabolism rate, and ethanol yield, only after the first transfer. A similar rapid adaptation was also observed for the lab strains of BY4742 and BY4743. The metabolomic analysis was employed to investigate the responses of the industrial S. cereviaise to three inhibitors during the adaptation. The results showed that higher levels of 2-furoic acid, 2, 3-butanediol, intermediates in glycolytic pathway, and amino acids derived from glycolysis, were discovered in the adapted strains, suggesting that enhanced metabolic activity in these pathways may relate to resistance against inhibitors. Additionally, through single-gene knockouts, several genes related to alanine metabolism, GABA shunt, and glycerol metabolism were verified to be crucial for the resistance to multiple inhibitors. This study provides new insights into the tolerance mechanism against multiple inhibitors, and guides for the improvement of tolerant ethanologenic yeast strains for lignocellulose-bioethanol fermentation.

  11. Combination of Metabolomic and Proteomic Analysis Revealed Different Features among Lactobacillus delbrueckii Subspecies bulgaricus and lactis Strains While In Vivo Testing in the Model Organism Caenorhabditis elegans Highlighted Probiotic Properties

    Elena Zanni

    2017-06-01

    Full Text Available Lactobacillus delbrueckii represents a technologically relevant member of lactic acid bacteria, since the two subspecies bulgaricus and lactis are widely associated with fermented dairy products. In the present work, we report the characterization of two commercial strains belonging to L. delbrueckii subspecies bulgaricus, lactis and a novel strain previously isolated from a traditional fermented fresh cheese. A phenomic approach was performed by combining metabolomic and proteomic analysis of the three strains, which were subsequently supplemented as food source to the model organism Caenorhabditis elegans, with the final aim to evaluate their possible probiotic effects. Restriction analysis of 16S ribosomal DNA revealed that the novel foodborne strain belonged to L. delbrueckii subspecies lactis. Proteomic and metabolomic approaches showed differences in folate, aminoacid and sugar metabolic pathways among the three strains. Moreover, evaluation of C. elegans lifespan, larval development, brood size, and bacterial colonization capacity demonstrated that L. delbrueckii subsp. bulgaricus diet exerted beneficial effects on nematodes. On the other hand, both L. delbrueckii subsp. lactis strains affected lifespan and larval development. We have characterized three strains belonging to L. delbrueckii subspecies bulgaricus and lactis highlighting their divergent origin. In particular, the two closely related isolates L. delbrueckii subspecies lactis display different galactose metabolic capabilities. Moreover, the L. delbrueckii subspecies bulgaricus strain demonstrated potential probiotic features. Combination of omic platforms coupled with in vivo screening in the simple model organism C. elegans is a powerful tool to characterize industrially relevant bacterial isolates.

  12. Combination of Metabolomic and Proteomic Analysis Revealed Different Features among Lactobacillus delbrueckii Subspecies bulgaricus and lactis Strains While In Vivo Testing in the Model Organism Caenorhabditis elegans Highlighted Probiotic Properties.

    Zanni, Elena; Schifano, Emily; Motta, Sara; Sciubba, Fabio; Palleschi, Claudio; Mauri, Pierluigi; Perozzi, Giuditta; Uccelletti, Daniela; Devirgiliis, Chiara; Miccheli, Alfredo

    2017-01-01

    Lactobacillus delbrueckii represents a technologically relevant member of lactic acid bacteria, since the two subspecies bulgaricus and lactis are widely associated with fermented dairy products. In the present work, we report the characterization of two commercial strains belonging to L. delbrueckii subspecies bulgaricus , lactis and a novel strain previously isolated from a traditional fermented fresh cheese. A phenomic approach was performed by combining metabolomic and proteomic analysis of the three strains, which were subsequently supplemented as food source to the model organism Caenorhabditis elegans , with the final aim to evaluate their possible probiotic effects. Restriction analysis of 16S ribosomal DNA revealed that the novel foodborne strain belonged to L. delbrueckii subspecies lactis . Proteomic and metabolomic approaches showed differences in folate, aminoacid and sugar metabolic pathways among the three strains. Moreover, evaluation of C. elegans lifespan, larval development, brood size, and bacterial colonization capacity demonstrated that L. delbrueckii subsp. bulgaricus diet exerted beneficial effects on nematodes. On the other hand, both L. delbrueckii subsp. lactis strains affected lifespan and larval development. We have characterized three strains belonging to L. delbrueckii subspecies bulgaricus and lactis highlighting their divergent origin. In particular, the two closely related isolates L. delbrueckii subspecies lactis display different galactose metabolic capabilities. Moreover, the L. delbrueckii subspecies bulgaricus strain demonstrated potential probiotic features. Combination of omic platforms coupled with in vivo screening in the simple model organism C. elegans is a powerful tool to characterize industrially relevant bacterial isolates.

  13. Metabolomics reveals distinct neurochemical profiles associated with stress resilience

    Brooke N. Dulka

    2017-12-01

    Full Text Available Acute social defeat represents a naturalistic form of conditioned fear and is an excellent model in which to investigate the biological basis of stress resilience. While there is growing interest in identifying biomarkers of stress resilience, until recently, it has not been feasible to associate levels of large numbers of neurochemicals and metabolites to stress-related phenotypes. The objective of the present study was to use an untargeted metabolomics approach to identify known and unknown neurochemicals in select brain regions that distinguish susceptible and resistant individuals in two rodent models of acute social defeat. In the first experiment, male mice were first phenotyped as resistant or susceptible. Then, mice were subjected to acute social defeat, and tissues were immediately collected from the ventromedial prefrontal cortex (vmPFC, basolateral/central amygdala (BLA/CeA, nucleus accumbens (NAc, and dorsal hippocampus (dHPC. Ultra-high performance liquid chromatography coupled with high resolution mass spectrometry (UPLC-HRMS was used for the detection of water-soluble neurochemicals. In the second experiment, male Syrian hamsters were paired in daily agonistic encounters for 2 weeks, during which they formed stable dominant-subordinate relationships. Then, 24 h after the last dominance encounter, animals were exposed to acute social defeat stress. Immediately after social defeat, tissue was collected from the vmPFC, BLA/CeA, NAc, and dHPC for analysis using UPLC-HRMS. Although no single biomarker characterized stress-related phenotypes in both species, commonalities were found. For instance, in both model systems, animals resistant to social defeat stress also show increased concentration of molecules to protect against oxidative stress in the NAc and vmPFC. Additionally, in both mice and hamsters, unidentified spectral features were preliminarily annotated as potential targets for future experiments. Overall, these findings

  14. Metabolomic Analysis in Brain Research: Opportunities & Challenges

    Catherine G Vasilopoulou

    2016-05-01

    Full Text Available Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s. Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results.

  15. Deconstructing the pig sex metabolome: Targeted metabolomics in heavy pigs revealed sexual dimorphisms in plasma biomarkers and metabolic pathways.

    Bovo, S; Mazzoni, G; Calò, D G; Galimberti, G; Fanelli, F; Mezzullo, M; Schiavo, G; Scotti, E; Manisi, A; Samoré, A B; Bertolini, F; Trevisi, P; Bosi, P; Dall'Olio, S; Pagotto, U; Fontanesi, L

    2015-12-01

    Metabolomics has opened new possibilities to investigate metabolic differences among animals. In this study, we applied a targeted metabolomic approach to deconstruct the pig sex metabolome as defined by castrated males and entire gilts. Plasma from 545 performance-tested Italian Large White pigs (172 castrated males and 373 females) sampled at about 160 kg live weight were analyzed for 186 metabolites using the Biocrates AbsoluteIDQ p180 Kit. After filtering, 132 metabolites (20 AA, 11 biogenic amines, 1 hexose, 13 acylcarnitines, 11 sphingomyelins, 67 phosphatidylcholines, and 9 lysophosphatidylcholines) were retained for further analyses. The multivariate approach of the sparse partial least squares discriminant analysis was applied, together with a specifically designed statistical pipeline, that included a permutation test and a 10 cross-fold validation procedure that produced stability and effect size statistics for each metabolite. Using this approach, we identified 85 biomarkers (with metabolites from all analyzed chemical families) that contributed to the differences between the 2 groups of pigs ( metabolic shift in castrated males toward energy storage and lipid production. Similar general patterns were observed for most sphingomyelins, phosphatidylcholines, and lysophosphatidylcholines. Metabolomic pathway analysis and pathway enrichment identified several differences between the 2 sexes. This metabolomic overview opened new clues on the biochemical mechanisms underlying sexual dimorphism that, on one hand, might explain differences in terms of economic traits between castrated male pigs and entire gilts and, on the other hand, could strengthen the pig as a model to define metabolic mechanisms related to fat deposition.

  16. Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

    Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

    2018-04-01

    Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

  17. Metabolomic Analyses of Leishmania Reveal Multiple Species Differences and Large Differences in Amino Acid Metabolism.

    Gareth D Westrop

    Full Text Available Comparative genomic analyses of Leishmania species have revealed relatively minor heterogeneity amongst recognised housekeeping genes and yet the species cause distinct infections and pathogenesis in their mammalian hosts. To gain greater information on the biochemical variation between species, and insights into possible metabolic mechanisms underpinning visceral and cutaneous leishmaniasis, we have undertaken in this study a comparative analysis of the metabolomes of promastigotes of L. donovani, L. major and L. mexicana. The analysis revealed 64 metabolites with confirmed identity differing 3-fold or more between the cell extracts of species, with 161 putatively identified metabolites differing similarly. Analysis of the media from cultures revealed an at least 3-fold difference in use or excretion of 43 metabolites of confirmed identity and 87 putatively identified metabolites that differed to a similar extent. Strikingly large differences were detected in their extent of amino acid use and metabolism, especially for tryptophan, aspartate, arginine and proline. Major pathways of tryptophan and arginine catabolism were shown to be to indole-3-lactate and arginic acid, respectively, which were excreted. The data presented provide clear evidence on the value of global metabolomic analyses in detecting species-specific metabolic features, thus application of this technology should be a major contributor to gaining greater understanding of how pathogens are adapted to infecting their hosts.

  18. Metabolome analysis for discovering biomarkers of gastroenterological cancer.

    Suzuki, Makoto; Nishiumi, Shin; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-09-01

    Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

  19. Serum metabolomics analysis of patients with chikungunya and dengue mono/co-infections reveals distinct metabolite signatures in the three disease conditions

    Shrinet, Jatin; Shastri, Jayanthi S.; Gaind, Rajni; Bhavesh, Neel Sarovar; Sunil, Sujatha

    2016-11-01

    Chikungunya and dengue are arboviral infections with overlapping clinical symptoms. A subset of chikungunya infection occurs also as co-infections with dengue, resulting in complications during diagnosis and patient management. The present study was undertaken to identify the global metabolome of patient sera infected with chikungunya as mono infections and with dengue as co-infections. Using nuclear magnetic resonance (NMR) spectroscopy, the metabolome of sera of three disease conditions, namely, chikungunya and dengue as mono-infections and when co-infected were ascertained and compared with healthy individuals. Further, the cohorts were analyzed on the basis of age, onset of fever and joint involvement. Here we show that many metabolites in the serum are significantly differentially regulated during chikungunya mono-infection as well as during chikungunya co-infection with dengue. We observed that glycine, serine, threonine, galactose and pyrimidine metabolisms are the most perturbed pathways in both mono and co-infection conditions. The affected pathways in our study correlate well with the clinical manifestation like fever, inflammation, energy deprivation and joint pain during the infections. These results may serve as a starting point for validations and identification of distinct biomolecules that could be exploited as biomarker candidates thereby helping in better patient management.

  20. Metabolomics reveals metabolic alterations by intrauterine growth restriction in the fetal rabbit brain.

    Erwin van Vliet

    Full Text Available Intrauterine Growth Restriction (IUGR due to placental insufficiency occurs in 5-10% of pregnancies and is a major risk factor for abnormal neurodevelopment. The perinatal diagnosis of IUGR related abnormal neurodevelopment represents a major challenge in fetal medicine. The development of clinical biomarkers is considered a promising approach, but requires the identification of biochemical/molecular alterations by IUGR in the fetal brain. This targeted metabolomics study in a rabbit IUGR model aimed to obtain mechanistic insight into the effects of IUGR on the fetal brain and identify metabolite candidates for biomarker development.At gestation day 25, IUGR was induced in two New Zealand rabbits by 40-50% uteroplacental vessel ligation in one horn and the contralateral horn was used as control. At day 30, fetuses were delivered by Cesarian section, weighed and brains collected for metabolomics analysis. Results showed that IUGR fetuses had a significantly lower birth and brain weight compared to controls. Metabolomics analysis using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS and database matching identified 78 metabolites. Comparison of metabolite intensities using a t-test demonstrated that 18 metabolites were significantly different between control and IUGR brain tissue, including neurotransmitters/peptides, amino acids, fatty acids, energy metabolism intermediates and oxidative stress metabolites. Principle component and hierarchical cluster analysis showed cluster formations that clearly separated control from IUGR brain tissue samples, revealing the potential to develop predictive biomarkers. Moreover birth weight and metabolite intensity correlations indicated that the extent of alterations was dependent on the severity of IUGR.IUGR leads to metabolic alterations in the fetal rabbit brain, involving neuronal viability, energy metabolism, amino acid levels, fatty acid profiles and oxidative stress

  1. Cartilaginous Metabolomic Study Reveals Potential Mechanisms of Osteophyte Formation in Osteoarthritis.

    Xu, Zhongwei; Chen, Tingmei; Luo, Jiao; Ding, Shijia; Gao, Sichuan; Zhang, Jian

    2017-04-07

    Osteophyte is one of the inevitable consequences of progressive osteoarthritis with the main characteristics of cartilage degeneration and endochondral ossification. The pathogenesis of osteophyte formation is not fully understood to date. In this work, metabolomic approaches were employed to explore potential mechanisms of osteophyte formation by detecting metabolic variations between extracts of osteophyte cartilage tissues (n = 32) and uninvolved control cartilage tissues (n = 34), based on the platform of ultraperformance liquid chromatography tandem quadrupole time-of-flight mass spectrometry, as well as the use of multivariate statistic analysis and univariate statistic analysis. The osteophyte group was significantly separated from the control group by the orthogonal partial least-squares discriminant analysis models, indicating that metabolic state of osteophyte cartilage had been changed. In total, 28 metabolic variations further validated by mass spectrum (MS) match, tandom mass spectrum (MS/MS) match, and standards match mainly included amino acids, sulfonic acids, glycerophospholipids, and fatty acyls. These metabolites were related to some specific physiological or pathological processes (collagen dissolution, boundary layers destroyed, self-restoration triggered, etc.) which might be associated with the procedure of osteophyte formation. Pathway analysis showed phenylalanine metabolism (PI = 0.168, p = 0.004) was highly correlative to this degenerative process. Our findings provided a direction for targeted metabolomic study and an insight into further reveal the molecular mechanisms of ostophyte formation.

  2. NMR-based metabolomics reveals urinary metabolome modifications in female Sprague-Dawley rats by cranberry procyanidins.

    Liu, Haiyan; Tayyari, Fariba; Edison, Arthur S; Su, Zhihua; Gu, Liwei

    2016-08-01

    A (1)H NMR global metabolomics approach was used to investigate the urinary metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) or partially purified apple procyanidins (PPAP). After collecting 24-h baseline urine, 24 female Sprague-Dawley rats were randomly separated into two groups and gavaged with PPCP or PPAP twice using a dose of 250 mg extracts per kilogram body weight. The 24-h urine samples were collected after the gavage. Urine samples were analyzed using (1)H NMR. Multivariate analyses showed that the urinary metabolome in rats was modified after administering PPCP or PPAP compared to baseline urine metabolic profiles. 2D (1)H-(13)C HSQC NMR was conducted to assist identification of discriminant metabolites. An increase of hippurate, lactate and succinate and a decrease of citrate and α-ketoglutarate were observed in rat urine after administering PPCP. Urinary levels of d-glucose, d-maltose, 3-(3'-hydroxyphenyl)-3-hydroxypropanoic acid, p-hydroxyphenylacetic acid, formate and phenol increased but citrate, α-ketoglutarate and creatinine decreased in rats after administering PPAP. Furthermore, the NMR analysis showed that the metabolome in the urine of rats administered with PPCP differed from those gavaged with PPAP. Compared to PPAP, PPCP caused an increase of urinary excretion of hippurate but a decrease of 3-(3'-hydroxyphenyl)-3-hydroxypropanoic acid, p-hydroxyphenylacetic acid and phenol. These metabolome changes caused by cranberry procyanidins may help to explain its reported health benefits and identify biomarkers of cranberry procyanidin intake. Copyright © 2016 Elsevier Inc. All rights reserved.

  3. Informatics for Metabolomics.

    Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

    2016-01-01

    Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

  4. Dynamic Metabolomics Reveals that Insulin Primes the Adipocyte for Glucose Metabolism

    James R. Krycer

    2017-12-01

    Full Text Available Insulin triggers an extensive signaling cascade to coordinate adipocyte glucose metabolism. It is considered that the major role of insulin is to provide anabolic substrates by activating GLUT4-dependent glucose uptake. However, insulin stimulates phosphorylation of many metabolic proteins. To examine the implications of this on glucose metabolism, we performed dynamic tracer metabolomics in cultured adipocytes treated with insulin. Temporal analysis of metabolite concentrations and tracer labeling revealed rapid and distinct changes in glucose metabolism, favoring specific glycolytic branch points and pyruvate anaplerosis. Integrating dynamic metabolomics and phosphoproteomics data revealed that insulin-dependent phosphorylation of anabolic enzymes occurred prior to substrate accumulation. Indeed, glycogen synthesis was activated independently of glucose supply. We refer to this phenomenon as metabolic priming, whereby insulin signaling creates a demand-driven system to “pull” glucose into specific anabolic pathways. This complements the supply-driven regulation of anabolism by substrate accumulation and highlights an additional role for insulin action in adipocyte glucose metabolism.

  5. Metabolomics reveals the heterogeneous secretome of two entomopathogenic fungi to ex vivo cultured insect tissues.

    Charissa de Bekker

    Full Text Available Fungal entomopathogens rely on cellular heterogeneity during the different stages of insect host infection. Their pathogenicity is exhibited through the secretion of secondary metabolites, which implies that the infection life history of this group of environmentally important fungi can be revealed using metabolomics. Here metabolomic analysis in combination with ex vivo insect tissue culturing shows that two generalist isolates of the genus Metarhizium and Beauveria, commonly used as biological pesticides, employ significantly different arrays of secondary metabolites during infectious and saprophytic growth. It also reveals that both fungi exhibit tissue specific strategies by a distinguishable metabolite secretion on the insect tissues tested in this study. In addition to showing the important heterogeneous nature of these two entomopathogens, this study also resulted in the discovery of several novel destruxins and beauverolides that have not been described before, most likely because previous surveys did not use insect tissues as a culturing system. While Beauveria secreted these cyclic depsipeptides when encountering live insect tissues, Metarhizium employed them primarily on dead tissue. This implies that, while these fungi employ comparable strategies when it comes to entomopathogenesis, there are most certainly significant differences at the molecular level that deserve to be studied.

  6. Environmental metabolomics: a SWOT analysis (strengths, weaknesses, opportunities, and threats).

    Miller, Marion G

    2007-02-01

    Metabolomic approaches have the potential to make an exceptional contribution to understanding how chemicals and other environmental stressors can affect both human and environmental health. However, the application of metabolomics to environmental exposures, although getting underway, has not yet been extensively explored. This review will use a SWOT analysis model to discuss some of the strengths, weaknesses, opportunities, and threats that are apparent to an investigator venturing into this relatively new field. SWOT has been used extensively in business settings to uncover new outlooks and identify problems that would impede progress. The field of environmental metabolomics provides great opportunities for discovery, and this is recognized by a high level of interest in potential applications. However, understanding the biological consequence of environmental exposures can be confounded by inter- and intra-individual differences. Metabolomic profiles can yield a plethora of data, the interpretation of which is complex and still being evaluated and researched. The development of the field will depend on the availability of technologies for data handling and that permit ready access metabolomic databases. Understanding the relevance of metabolomic endpoints to organism health vs adaptation vs variation is an important step in understanding what constitutes a substantive environmental threat. Metabolomic applications in reproductive research are discussed. Overall, the development of a comprehensive mechanistic-based interpretation of metabolomic changes offers the possibility of providing information that will significantly contribute to the protection of human health and the environment.

  7. Revealing metabolomic variations in Cortex Moutan from different root parts using HPLC-MS method.

    Xiao, Chaoni; Wu, Man; Chen, Yongyong; Zhang, Yajun; Zhao, Xinfeng; Zheng, Xiaohui

    2015-01-01

    The distribution of metabolites in the different root parts of Cortex Moutan (the root bark of Paeonia suffruticosa Andrews) is not well understood, therefore, scientific evidence is not available for quality assessment of Cortex Moutan. To reveal metabolomic variations in Cortex Moutan in order to gain deeper insights to enable quality control. Metabolomic variations in the different root parts of Cortex Moutan were characterised using high-performance liquid chromatography combined with mass spectrometry (HPLC-MS) and multivariate data analysis. The discriminating metabolites in different root parts were evaluated by the one-way analysis of variance and a fold change parameter. The metabolite profiles of Cortex Moutan were largely dominated by five primary and 41 secondary metabolites . Higher levels of malic acid, gallic acid and mudanoside-B were mainly observed in the second lateral roots, whereas dihydroxyacetophenone, benzoyloxypaeoniflorin, suffruticoside-A, kaempferol dihexoside, mudanpioside E and mudanpioside J accumulated in the first lateral and axial roots. The highest contents of paeonol, galloyloxypaeoniflorin and procyanidin B were detected in the axial roots. Accordingly, metabolite compositions of Cortex Moutan were found to vary among different root parts. The axial roots have higher quality than the lateral roots in Cortex Moutan due to the accumulation of bioactive secondary metabolites associated with plant physiology. These findings provided important scientific evidence for grading Cortex Moutan on the general market. Copyright © 2014 John Wiley & Sons, Ltd.

  8. Targeted metabolomics analysis reveals the association between maternal folic acid supplementation and fatty acids and amino acids profiles in rat pups.

    Liu, Zhipeng; Liu, Rui; Chou, Jing; Yu, Jiaying; Liu, Xiaowei; Sun, Changhao; Li, Ying; Liu, Liyan

    2018-07-15

    Maternal diet during pregnancy can influence offspring's health by affecting development and metabolism. This study aimed to analyze the influence of maternal folic acid (FA) supplementation on the metabolism of rat pups using targeted metabolomics. Twenty female rats were randomly assigned to a FA supplementation (FAS group, n = 10) or control group (n = 10), which were fed AIN93G diet with 2 or 10 mg/kg FA, respectively. We then measured amino acids and their derivatives, biogenic amines, and fatty acids in the female rats and their pups by ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC/MS-MS) and gas chromatography-mass spectrometry (GC/MS-MS). In maternal rats, the significant changes of three metabolites (proline, γ-aminobutyric acid and esterified octadecatetraenoic acid, P acids (leucine, isoleucine, serine, proline) were obtained in FAS pups. Furthermore, there were the decreased esterified fatty acids (arachidonic acid, eicosapentaenoic acid, and docosatetraenoic acid) and free fatty acids (oleic acid, linoleic acid, γ-linolenic acid, octadecatetraenoic acid, arachidonic acid, eicosapentaenoic acid and selacholeic acid) in FAS pups. Metabolic changes in the FAS pups were characterized by changes in fatty acids and amino acids. These results suggested that FA supplementation during pregnancy influenced amino acids and fatty acids metabolism in rat pups. This study provides new insights into the regulation of amino acids and fatty acids metabolism during early life. Copyright © 2018 Elsevier B.V. All rights reserved.

  9. Targeted metabolomic analysis reveals the association between the postprandial change in palmitic acid, branched-chain amino acids and insulin resistance in young obese subjects.

    Liu, Liyan; Feng, Rennan; Guo, Fuchuan; Li, Ying; Jiao, Jundong; Sun, Changhao

    2015-04-01

    Obesity is the result of a positive energy balance and often leads to difficulties in maintaining normal postprandial metabolism. The changes in postprandial metabolites after an oral glucose tolerance test (OGTT) in young obese Chinese men are unclear. In this work, the aim is to investigate the complex metabolic alterations in obesity provoked by an OGTT using targeted metabolomics. We used gas chromatography-mass spectrometry and ultra high performance liquid chromatography-triple quadrupole mass spectrometry to analyze serum fatty acids, amino acids and biogenic amines profiles from 15 control and 15 obese subjects at 0, 30, 60, 90 and 120 min during an OGTT. Metabolite profiles from 30 obese subjects as independent samples were detected in order to validate the change of metabolites. There were the decreased levels of fatty acid, amino acids and biogenic amines after OGTT in obesity. At 120 min, percent change of 20 metabolites in obesity has statistical significance when comparing with the controls. The obese parameters was positively associated with changes in arginine and histidine (Pchange in palmitic acid (PA), branched-chain amino acids (BCAAs) and phenylalanine between 1 and 120 min were positively associated with fasting insulin and HOMA-IR (all Presistance in obesity. Our findings offer new insights in the complex physiological regulation of the metabolism during an OGTT in obesity. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  10. Seed metabolomic study reveals significant metabolite variations and correlations among different soybean cultivars.

    Lin, Hong; Rao, Jun; Shi, Jianxin; Hu, Chaoyang; Cheng, Fang; Wilson, Zoe A; Zhang, Dabing; Quan, Sheng

    2014-09-01

    Soybean [Glycine max (L.) Merr.] is one of the world's major crops, and soybean seeds are a rich and important resource for proteins and oils. While "omics" studies, such as genomics, transcriptomics, and proteomics, have been widely applied in soybean molecular research, fewer metabolomic studies have been conducted for large-scale detection of low molecular weight metabolites, especially in soybean seeds. In this study, we investigated the seed metabolomes of 29 common soybean cultivars through combined gas chromatography-mass spectrometry and ultra-performance liquid chromatography-tandem mass spectrometry. One hundred sixty-nine named metabolites were identified and subsequently used to construct a metabolic network of mature soybean seed. Among the 169 detected metabolites, 104 were found to be significantly variable in their levels across tested cultivars. Metabolite markers that could be used to distinguish genetically related soybean cultivars were also identified, and metabolite-metabolite correlation analysis revealed some significant associations within the same or among different metabolite groups. Findings from this work may potentially provide the basis for further studies on both soybean seed metabolism and metabolic engineering to improve soybean seed quality and yield. © 2014 Institute of Botany, Chinese Academy of Sciences.

  11. Seed metabolomic study reveals significant metabolite variations and correlations among different soybean cultivars

    Hong Lin; Jun Rao; Jianxin Shi; Chaoyang Hu; Fang Cheng; Zoe AWilson; Dabing Zhang; Sheng Quan

    2014-01-01

    Soybean [Glycine max (L.) Merr.] is one of the world’s major crops, and soybean seeds are a rich and important resource for proteins and oils. While “omics”studies, such as genomics, transcriptomics, and proteomics, have been widely applied in soybean molecular research, fewer metabolomic studies have been conducted for large-scale detection of low molecular weight metabolites, especial y in soybean seeds. In this study, we investigated the seed metabolomes of 29 common soybean cultivars through combined gas chromatography-mass spectrometry and ultra-performance liquid chromatography-tandem mass spectrometry. One hundred sixty-nine named metabolites were identified and subsequently used to construct a metabolic network of mature soybean seed. Among the 169 detected metabolites, 104 were found to be significantly variable in their levels across tested cultivars. Metabolite markers that could be used to distinguish genetical y related soybean cultivars were also identified, and metabolite-metabolite correlation analysis revealed some significant associations within the same or among different metabolite groups. Findings from this work may potentially provide the basis for further studies on both soybean seed metabolism and metabolic engineering to improve soybean seed quality and yield.

  12. Serum and urine metabolomics study reveals a distinct diagnostic model for cancer cachexia

    Yang, Quan‐Jun; Zhao, Jiang‐Rong; Hao, Juan; Li, Bin; Huo, Yan; Han, Yong‐Long; Wan, Li‐Li; Li, Jie; Huang, Jinlu; Lu, Jin

    2017-01-01

    Abstract Background Cachexia is a multifactorial metabolic syndrome with high morbidity and mortality in patients with advanced cancer. The diagnosis of cancer cachexia depends on objective measures of clinical symptoms and a history of weight loss, which lag behind disease progression and have limited utility for the early diagnosis of cancer cachexia. In this study, we performed a nuclear magnetic resonance‐based metabolomics analysis to reveal the metabolic profile of cancer cachexia and establish a diagnostic model. Methods Eighty‐four cancer cachexia patients, 33 pre‐cachectic patients, 105 weight‐stable cancer patients, and 74 healthy controls were included in the training and validation sets. Comparative analysis was used to elucidate the distinct metabolites of cancer cachexia, while metabolic pathway analysis was employed to elucidate reprogramming pathways. Random forest, logistic regression, and receiver operating characteristic analyses were used to select and validate the biomarker metabolites and establish a diagnostic model. Results Forty‐six cancer cachexia patients, 22 pre‐cachectic patients, 68 weight‐stable cancer patients, and 48 healthy controls were included in the training set, and 38 cancer cachexia patients, 11 pre‐cachectic patients, 37 weight‐stable cancer patients, and 26 healthy controls were included in the validation set. All four groups were age‐matched and sex‐matched in the training set. Metabolomics analysis showed a clear separation of the four groups. Overall, 45 metabolites and 18 metabolic pathways were associated with cancer cachexia. Using random forest analysis, 15 of these metabolites were identified as highly discriminating between disease states. Logistic regression and receiver operating characteristic analyses were used to create a distinct diagnostic model with an area under the curve of 0.991 based on three metabolites. The diagnostic equation was Logit(P) = −400.53 – 481.88

  13. Metagenomic and metabolomic analysis of the toxic effects of trichloroacetamide-induced gut microbiome and urine metabolome perturbations in mice.

    Zhang, Yan; Zhao, Fuzheng; Deng, Yongfeng; Zhao, Yanping; Ren, Hongqiang

    2015-04-03

    Disinfection byproducts (DBPs) in drinking water have been linked to various diseases, including colon, colorectal, rectal, and bladder cancer. Trichloroacetamide (TCAcAm) is an emerging nitrogenous DBP, and our previous study found that TCAcAm could induce some changes associated with host-gut microbiota co-metabolism. In this study, we used an integrated approach combining metagenomics, based on high-throughput sequencing, and metabolomics, based on nuclear magnetic resonance (NMR), to evaluate the toxic effects of TCAcAm exposure on the gut microbiome and urine metabolome. High-throughput sequencing revealed that the gut microbiome's composition and function were significantly altered after TCAcAm exposure for 90 days in Mus musculus mice. In addition, metabolomic analysis showed that a number of gut microbiota-related metabolites were dramatically perturbed in the urine of the mice. These results may provide novel insight into evaluating the health risk of environmental pollutants as well as revealing the potential mechanism of TCAcAm's toxic effects.

  14. SECIMTools: a suite of metabolomics data analysis tools.

    Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

    2018-04-20

    Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

  15. Proteome-metabolome profiling of ovarian cancer ascites reveals novel components involved in intercellular communication.

    Shender, Victoria O; Pavlyukov, Marat S; Ziganshin, Rustam H; Arapidi, Georgij P; Kovalchuk, Sergey I; Anikanov, Nikolay A; Altukhov, Ilya A; Alexeev, Dmitry G; Butenko, Ivan O; Shavarda, Alexey L; Khomyakova, Elena B; Evtushenko, Evgeniy; Ashrafyan, Lev A; Antonova, Irina B; Kuznetcov, Igor N; Gorbachev, Alexey Yu; Shakhparonov, Mikhail I; Govorun, Vadim M

    2014-12-01

    Ovarian cancer ascites is a native medium for cancer cells that allows investigation of their secretome in a natural environment. This medium is of interest as a promising source of potential biomarkers, and also as a medium for cell-cell communication. The aim of this study was to elucidate specific features of the malignant ascites metabolome and proteome. In order to omit components of the systemic response to ascites formation, we compared malignant ascites with cirrhosis ascites. Metabolome analysis revealed 41 components that differed significantly between malignant and cirrhosis ascites. Most of the identified cancer-specific metabolites are known to be important signaling molecules. Proteomic analysis identified 2096 and 1855 proteins in the ovarian cancer and cirrhosis ascites, respectively; 424 proteins were specific for the malignant ascites. Functional analysis of the proteome demonstrated that the major differences between cirrhosis and malignant ascites were observed for the cluster of spliceosomal proteins. Additionally, we demonstrate that several splicing RNAs were exclusively detected in malignant ascites, where they probably existed within protein complexes. This result was confirmed in vitro using an ovarian cancer cell line. Identification of spliceosomal proteins and RNAs in an extracellular medium is of particular interest; the finding suggests that they might play a role in the communication between cancer cells. In addition, malignant ascites contains a high number of exosomes that are known to play an important role in signal transduction. Thus our study reveals the specific features of malignant ascites that are associated with its function as a medium of intercellular communication. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  16. Plasma metabolomics reveal the correlation of metabolic pathways and Prakritis of humans

    Amey Shirolkar

    2018-04-01

    Full Text Available Background: Ayurveda, an ancient Indian medicinal system, has categorized human body constitutions in three broad constitutional types (prakritis i.e. Vata, Pitta and Kapha. Objectives: Analysis of plasma metabolites and related pathways to classify Prakriti specific dominant marker metabolites and metabolic pathways. Materials and methods: 38 healthy male individuals were assessed for dominant Prakritis and their fasting blood samples were collected. The processed plasma samples were subjected to rapid resolution liquid chromatography–electrospray ionization–quadrupole time of flight mass spectrometry (RRLC–ESI–QTOFMS. Mass profiles were aligned and subjected to multivariate analysis. Results: Partial least square discriminant analysis (PLS-DA model showed 97.87% recognition capability. List of PLS-DA metabolites was subjected to permutative Benjamini–Hochberg false discovery rate (FDR correction and final list of 76 metabolites with p  2.0 was identified. Pathway analysis using metascape and JEPETTO plugins in Cytoscape revealed that steroidal hormone biosynthesis, amino acid, and arachidonic acid metabolism are major pathways varying with different constitution. Biological Go processes analysis showed that aromatic amino acids, sphingolipids, and pyrimidine nucleotides metabolic processes were dominant in kapha type of body constitution. Fat soluble vitamins, cellular amino acid, and androgen biosynthesis process along with branched chain amino acid and glycerolipid catabolic processes were dominant in pitta type individuals. Vata Prakriti was found to have dominant catecholamine, arachidonic acid and hydrogen peroxide metabolomics processes. Conclusion: The neurotransmission and oxidative stress in vata, BCAA catabolic, androgen, xenobiotics metabolic processes in pitta, and aromatic amino acids, sphingolipid, and pyrimidine metabolic process in kapha Prakriti were the dominant marker pathways. Keywords: Ayurveda, Prakriti, Human

  17. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools.

    Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K Sreekumaran; Sumner, Susan; Subramaniam, Shankar

    2016-01-04

    The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Integration of metabolome data with metabolic networks reveals reporter reactions

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

  19. Metabolomics of dates (Phoenix dactylifera) reveals a highly dynamic ripening process accounting for major variation in fruit composition.

    Diboun, Ilhame; Mathew, Sweety; Al-Rayyashi, Maryam; Elrayess, Mohamed; Torres, Maria; Halama, Anna; Méret, Michaël; Mohney, Robert P; Karoly, Edward D; Malek, Joel; Suhre, Karsten

    2015-12-16

    Dates are tropical fruits with appreciable nutritional value. Previous attempts at global metabolic characterization of the date metabolome were constrained by small sample size and limited geographical sampling. In this study, two independent large cohorts of mature dates exhibiting substantial diversity in origin, varieties and fruit processing conditions were measured by metabolomics techniques in order to identify major determinants of the fruit metabolome. Multivariate analysis revealed a first principal component (PC1) significantly associated with the dates' countries of production. The availability of a smaller dataset featuring immature dates from different development stages served to build a model of the ripening process in dates, which helped reveal a strong ripening signature in PC1. Analysis revealed enrichment in the dry type of dates amongst fruits with early ripening profiles at one end of PC1 as oppose to an overrepresentation of the soft type of dates with late ripening profiles at the other end of PC1. Dry dates are typical to the North African region whilst soft dates are more popular in the Gulf region, which partly explains the observed association between PC1 and geography. Analysis of the loading values, expressing metabolite correlation levels with PC1, revealed enrichment patterns of a comprehensive range of metabolite classes along PC1. Three distinct metabolic phases corresponding to known stages of date ripening were observed: An early phase enriched in regulatory hormones, amines and polyamines, energy production, tannins, sucrose and anti-oxidant activity, a second phase with on-going phenylpropanoid secondary metabolism, gene expression and phospholipid metabolism and a late phase with marked sugar dehydration activity and degradation reactions leading to increased volatile synthesis. These data indicate the importance of date ripening as a main driver of variation in the date metabolome responsible for their diverse nutritional and

  20. Untargeted Metabolomics Reveals Predominant Alterations in Lipid Metabolism Following Light Exposure in Broccoli Sprouts

    Mariateresa Maldini

    2015-06-01

    Full Text Available The consumption of vegetables belonging to the family Brassicaceae (e.g., broccoli and cauliflower is linked to a reduced incidence of cancer and cardiovascular diseases. The molecular composition of such plants is strongly affected by growing conditions. Here we developed an unbiased metabolomics approach to investigate the effect of light and dark exposure on the metabolome of broccoli sprouts and we applied such an approach to provide a bird’s-eye view of the overall metabolic response after light exposure. Broccoli seeds were germinated and grown hydroponically for five days in total darkness or with a light/dark photoperiod (16 h light/8 h dark cycle. We used an ultra-performance liquid-chromatography system coupled to an ion-mobility, time-of-flight mass spectrometer to profile the large array of metabolites present in the sprouts. Differences at the metabolite level between groups were analyzed using multivariate statistical analyses, including principal component analysis and correlation analysis. Altered metabolites were identified by searching publicly available and in-house databases. Metabolite pathway analyses were used to support the identification of subtle but significant changes among groups of related metabolites that may have gone unnoticed with conventional approaches. Besides the chlorophyll pathway, light exposure activated the biosynthesis and metabolism of sterol lipids, prenol lipids, and polyunsaturated lipids, which are essential for the photosynthetic machinery. Our results also revealed that light exposure increased the levels of polyketides, including flavonoids, and oxylipins, which play essential roles in the plant’s developmental processes and defense mechanism against herbivores. This study highlights the significant contribution of light exposure to the ultimate metabolic phenotype, which might affect the cellular physiology and nutritional value of broccoli sprouts. Furthermore, this study highlights the

  1. Metabolomics Reveals Cryptic Interactive Effects of Species Interactions and Environmental Stress on Nitrogen and Sulfur Metabolism in Seagrass

    Hasler-Sheetal, Harald; Castorani, Max C. N.; Glud, Ronnie N.

    2016-01-01

    Eutrophication of estuaries and coastal seas is accelerating, increasing light stress on subtidal marine plants and changing their interactions with other species. To date, we have limited understanding of how such variations in environmental and biological stress modify the impact of interactions...... among foundational species and eventually affect ecosystem health. Here, we used metabolomics to assess the impact of light reductions on interactions between the seagrass Zostera marina, an important habitat-forming marine plant, and the abundant and commercially important blue mussel Mytilus edulis....... Plant performance varied with light availability but was unaffected by the presence of mussels. Metabolomic analysis, on the other hand, revealed an interaction between light availability and presence of M. edulis on seagrass metabolism. Under high light, mussels stimulated seagrass nitrogen and energy...

  2. Chicken hepatic response to chronic heat stress using integrated transcriptome and metabolome analysis.

    Sara F Jastrebski

    Full Text Available The liver plays a central role in metabolism and is important in maintaining homeostasis throughout the body. This study integrated transcriptomic and metabolomic data to understand how the liver responds under chronic heat stress. Chickens from a rapidly growing broiler line were heat stressed for 8 hours per day for one week and liver samples were collected at 28 days post hatch. Transcriptome analysis reveals changes in genes responsible for cell cycle regulation, DNA replication, and DNA repair along with immune function. Integrating the metabolome and transcriptome data highlighted multiple pathways affected by heat stress including glucose, amino acid, and lipid metabolism along with glutathione production and beta-oxidation.

  3. "Gear mechanism" of bariatric interventions revealed by untargeted metabolomics.

    Samczuk, Paulina; Luba, Magdalena; Godzien, Joanna; Mastrangelo, Annalaura; Hady, Hady Razak; Dadan, Jacek; Barbas, Coral; Gorska, Maria; Kretowski, Adam; Ciborowski, Michal

    2018-03-20

    Mechanisms responsible for metabolic gains after bariatric surgery are not entirely clear. The purpose of this study was evaluation of metabolic changes after laparoscopic Roux-en-Y gastric bypass or laparoscopic sleeve gastrectomy in semi-annual follow up. The study participants were selected from obese patients with T2DM who underwent one of the mentioned bariatric procedures. Serum metabolic fingerprinting by use of liquid and gas chromatography with mass spectrometry detection was performed on samples obtained from studied patients before, one, and six months post-surgery. Performed analyses resulted in 49 significant and identified metabolites. Comparison of the two described procedures has allowed to detect metabolites linked with numerous pathways, processes and diseases. Based on the metabolites detected and pathways affected, we propose a "gear mechanism" showing molecular changes evoked by both bariatric procedures. Critical evaluation of clinical data and obtained metabolomics results enables us to conclude that both procedures are very similar in terms of general clinical outcome, but they strongly differ from each other in molecular mechanisms leading to the final effect. For the first time general metabolic effect of bariatric procedures is described. New hypotheses concerning molecular mechanisms induced by bariatric surgeries and new gut microbiota modulations are presented. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Metabolomics Approach Reveals Integrated Metabolic Network Associated with Serotonin Deficiency

    Weng, Rui; Shen, Sensen; Tian, Yonglu; Burton, Casey; Xu, Xinyuan; Liu, Yi; Chang, Cuilan; Bai, Yu; Liu, Huwei

    2015-07-01

    Serotonin is an important neurotransmitter that broadly participates in various biological processes. While serotonin deficiency has been associated with multiple pathological conditions such as depression, schizophrenia, Alzheimer’s disease and Parkinson’s disease, the serotonin-dependent mechanisms remain poorly understood. This study therefore aimed to identify novel biomarkers and metabolic pathways perturbed by serotonin deficiency using metabolomics approach in order to gain new metabolic insights into the serotonin deficiency-related molecular mechanisms. Serotonin deficiency was achieved through pharmacological inhibition of tryptophan hydroxylase (Tph) using p-chlorophenylalanine (pCPA) or genetic knockout of the neuronal specific Tph2 isoform. This dual approach improved specificity for the serotonin deficiency-associated biomarkers while minimizing nonspecific effects of pCPA treatment or Tph2 knockout (Tph2-/-). Non-targeted metabolic profiling and a targeted pCPA dose-response study identified 21 biomarkers in the pCPA-treated mice while 17 metabolites in the Tph2-/- mice were found to be significantly altered compared with the control mice. These newly identified biomarkers were associated with amino acid, energy, purine, lipid and gut microflora metabolisms. Oxidative stress was also found to be significantly increased in the serotonin deficient mice. These new biomarkers and the overall metabolic pathways may provide new understanding for the serotonin deficiency-associated mechanisms under multiple pathological states.

  5. Integrated Metabolomics and Morphogenesis Reveal Volatile Signaling of the Nematode-Trapping Fungus Arthrobotrys oligospora.

    Wang, Bai-Le; Chen, Yong-Hong; He, Jia-Ning; Xue, Hua-Xi; Yan, Ni; Zeng, Zhi-Jun; Bennett, Joan W; Zhang, Ke-Qin; Niu, Xue-Mei

    2018-05-01

    The adjustment of metabolic patterns is fundamental to fungal biology and plays vital roles in adaptation to diverse ecological challenges. Nematode-trapping fungi can switch their lifestyle from saprophytic to pathogenic by developing specific trapping devices induced by nematodes to infect their prey as a response to nutrient depletion in nature. However, the chemical identity of the specific fungal metabolites used during the switch remains poorly understood. We hypothesized that these important signal molecules might be volatile in nature. Gas chromatography-mass spectrometry was used to carry out comparative analysis of fungal metabolomics during the saprophytic and pathogenic lifestyles of the model species Arthrobotrys oligospora Two media commonly used in research on this species, cornmeal agar (CMA) and potato dextrose agar (PDA), were chosen for use in this study. The fungus produced a small group of volatile furanone and pyrone metabolites that were associated with the switch from the saprophytic to the pathogenic stage. A. oligospora fungi grown on CMA tended to produce more traps and employ attractive furanones to improve the utilization of traps, while fungi grown on PDA developed fewer traps and used nematode-toxic furanone metabolites to compensate for insufficient traps. Another volatile pyrone metabolite, maltol, was identified as a morphological regulator for enhancing trap formation. Deletion of the gene AOL_s00079g496 in A. oligospora led to increased amounts of the furanone attractant (2-fold) in mutants and enhanced the attractive activity (1.5-fold) of the fungus, while it resulted in decreased trap formation. This investigation provides new insights regarding the comprehensive tactics of fungal adaptation to environmental stress, integrating both morphological and metabolomic mechanisms. IMPORTANCE Nematode-trapping fungi are a unique group of soil-living fungi that can switch from the saprophytic to the pathogenic lifestyle once they come

  6. GC-MS Metabolomic Analysis to Reveal the Metabolites and Biological Pathways Involved in the Developmental Stages and Tissue Response of Panax ginseng

    Jia Liu

    2017-03-01

    Full Text Available Ginsenosides, the major compounds present in ginseng, are known to have numerous physiological and pharmacological effects. The physiological processes, enzymes and genes involved in ginsenoside synthesis in P. ginseng have been well characterized. However, relatively little information is known about the dynamic metabolic changes that occur during ginsenoside accumulation in ginseng. To explore this topic, we isolated metabolites from different tissues at different growth stages, and identified and characterized them by using gas chromatography coupled with mass spectrometry (GC-MS. The results showed that a total of 30, 16, 20, 36 and 31 metabolites were identified and involved in different developmental stages in leaf, stem, petiole, lateral root and main root, respectively. To investigate the contribution of tissue to the biosynthesis of ginsenosides, we examined the metabolic changes of leaf, stem, petiole, lateral root and main root during five development stages: 1-, 2-, 3-, 4- and 5-years. The score plots of partial least squares-discriminate analysis (PLS-DA showed clear discrimination between growth stages and tissue samples. Kyoto Encyclopedia of Genes and Genomes (KEGG pathway analysis in the same tissue at different growth stages indicated profound biochemical changes in several pathways, including carbohydrate metabolism and pentose phosphate metabolism, in addition, the tissues displayed significant variations in amino acid metabolism, sugar metabolism and energy metabolism. These results should facilitate further dissection of the metabolic flux regulation of ginsenoside accumulation in different developmental stages or different tissues of ginseng.

  7. The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets

    Carroll Adam J

    2010-07-01

    Full Text Available Abstract Background Standardization of analytical approaches and reporting methods via community-wide collaboration can work synergistically with web-tool development to result in rapid community-driven expansion of online data repositories suitable for data mining and meta-analysis. In metabolomics, the inter-laboratory reproducibility of gas-chromatography/mass-spectrometry (GC/MS makes it an obvious target for such development. While a number of web-tools offer access to datasets and/or tools for raw data processing and statistical analysis, none of these systems are currently set up to act as a public repository by easily accepting, processing and presenting publicly submitted GC/MS metabolomics datasets for public re-analysis. Description Here, we present MetabolomeExpress, a new File Transfer Protocol (FTP server and web-tool for the online storage, processing, visualisation and statistical re-analysis of publicly submitted GC/MS metabolomics datasets. Users may search a quality-controlled database of metabolite response statistics from publicly submitted datasets by a number of parameters (eg. metabolite, species, organ/biofluid etc.. Users may also perform meta-analysis comparisons of multiple independent experiments or re-analyse public primary datasets via user-friendly tools for t-test, principal components analysis, hierarchical cluster analysis and correlation analysis. They may interact with chromatograms, mass spectra and peak detection results via an integrated raw data viewer. Researchers who register for a free account may upload (via FTP their own data to the server for online processing via a novel raw data processing pipeline. Conclusions MetabolomeExpress https://www.metabolome-express.org provides a new opportunity for the general metabolomics community to transparently present online the raw and processed GC/MS data underlying their metabolomics publications. Transparent sharing of these data will allow researchers to

  8. Exploring the analysis of structured metabolomics data

    Verouden, M.P.H.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2009-01-01

    In metabolomics research a large number of metabolites are measured that reflect the cellular state under the experimental conditions studied. In many occasions the experiments are performed according to an experimental design to make sure that sufficient variation is induced in the metabolite

  9. Untargeted metabolomics reveals specific withanolides and fatty acyl glycoside as tentative metabolites to differentiate organic and conventional Physalis peruviana fruits.

    Llano, Sandra M; Muñoz-Jiménez, Ana M; Jiménez-Cartagena, Claudio; Londoño-Londoño, Julián; Medina, Sonia

    2018-04-01

    The agronomic production systems may affect the levels of food metabolites. Metabolomics approaches have been applied as useful tool for the characterization of fruit metabolome. In this study, metabolomics techniques were used to assess the differences in phytochemical composition between goldenberry samples produced by organic and conventional systems. To verify that the organic samples were free of pesticides, individual pesticides were analyzed. Principal component analysis showed a clear separation of goldenberry samples from two different farming systems. Via targeted metabolomics assays, whereby carotenoids and ascorbic acid were analyzed, not statistical differences between both crops were found. Conversely, untargeted metabolomics allowed us to identify two withanolides and one fatty acyl glycoside as tentative metabolites to differentiate goldenberry fruits, recording organic fruits higher amounts of these compounds than conventional samples. Hence, untargeted metabolomics technology could be suitable to research differences on phytochemicals under different agricultural management practices and to authenticate organic products. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

    Susanna K. P. Lau

    2016-02-01

    Full Text Available To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6, lysophosphatidylethanolamine (LysoPE (n = 3, sphingomyelins (SM (n = 2 and phosphatidylcholine (PC (n = 1, with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0 possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%, and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%. Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0 representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.

  11. Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis.

    Lau, Susanna K P; Lee, Kim-Chung; Lo, George C S; Ding, Vanessa S Y; Chow, Wang-Ngai; Ke, Tony Y H; Curreem, Shirly O T; To, Kelvin K W; Ho, Deborah T Y; Sridhar, Siddharth; Wong, Sally C Y; Chan, Jasper F W; Hung, Ivan F N; Sze, Kong-Hung; Lam, Ching-Wan; Yuen, Kwok-Yung; Woo, Patrick C Y

    2016-02-27

    To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.

  12. Metabolomic analysis of three Mollicute species.

    Anna A Vanyushkina

    Full Text Available We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer.

  13. Comparative Circadian Metabolomics Reveal Differential Effects of Nutritional Challenge in the Serum and Liver.

    Abbondante, Serena; Eckel-Mahan, Kristin L; Ceglia, Nicholas J; Baldi, Pierre; Sassone-Corsi, Paolo

    2016-02-05

    Diagnosis and therapeutic interventions in pathological conditions rely upon clinical monitoring of key metabolites in the serum. Recent studies show that a wide range of metabolic pathways are controlled by circadian rhythms whose oscillation is affected by nutritional challenges, underscoring the importance of assessing a temporal window for clinical testing and thereby questioning the accuracy of the reading of critical pathological markers in circulation. We have been interested in studying the communication between peripheral tissues under metabolic homeostasis perturbation. Here we present a comparative circadian metabolomic analysis on serum and liver in mice under high fat diet. Our data reveal that the nutritional challenge induces a loss of serum metabolite rhythmicity compared with liver, indicating a circadian misalignment between the tissues analyzed. Importantly, our results show that the levels of serum metabolites do not reflect the circadian liver metabolic signature or the effect of nutritional challenge. This notion reveals the possibility that misleading reads of metabolites in circulation may result in misdiagnosis and improper treatments. Our findings also demonstrate a tissue-specific and time-dependent disruption of metabolic homeostasis in response to altered nutrition. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

  14. Talaromyces marneffei Genomic, Transcriptomic, Proteomic and Metabolomic Studies Reveal Mechanisms for Environmental Adaptations and Virulence

    Susanna K. P. Lau

    2017-06-01

    Full Text Available Talaromyces marneffei is a thermally dimorphic fungus causing systemic infections in patients positive for HIV or other immunocompromised statuses. Analysis of its ~28.9 Mb draft genome and additional transcriptomic, proteomic and metabolomic studies revealed mechanisms for environmental adaptations and virulence. Meiotic genes and genes for pheromone receptors, enzymes which process pheromones, and proteins involved in pheromone response pathway are present, indicating its possibility as a heterothallic fungus. Among the 14 Mp1p homologs, only Mp1p is a virulence factor binding a variety of host proteins, fatty acids and lipids. There are 23 polyketide synthase genes, one for melanin and two for mitorubrinic acid/mitorubrinol biosynthesis, which are virulence factors. Another polyketide synthase is for biogenesis of the diffusible red pigment, which consists of amino acid conjugates of monascorubin and rubropunctatin. Novel microRNA-like RNAs (milRNAs and processing proteins are present. The dicer protein, dcl-2, is required for biogenesis of two milRNAs, PM-milR-M1 and PM-milR-M2, which are more highly expressed in hyphal cells. Comparative transcriptomics showed that tandem repeat-containing genes were overexpressed in yeast phase, generating protein polymorphism among cells, evading host’s immunity. Comparative proteomics between yeast and hyphal cells revealed that glyceraldehyde-3-phosphate dehydrogenase, up-regulated in hyphal cells, is an adhesion factor for conidial attachment.

  15. The metabolomic signature of Leber's hereditary optic neuropathy reveals endoplasmic reticulum stress.

    Chao de la Barca, Juan Manuel; Simard, Gilles; Amati-Bonneau, Patrizia; Safiedeen, Zainab; Prunier-Mirebeau, Delphine; Chupin, Stéphanie; Gadras, Cédric; Tessier, Lydie; Gueguen, Naïg; Chevrollier, Arnaud; Desquiret-Dumas, Valérie; Ferré, Marc; Bris, Céline; Kouassi Nzoughet, Judith; Bocca, Cinzia; Leruez, Stéphanie; Verny, Christophe; Miléa, Dan; Bonneau, Dominique; Lenaers, Guy; Martinez, M Carmen; Procaccio, Vincent; Reynier, Pascal

    2016-11-01

    Leber's hereditary optic neuropathy (MIM#535000), the commonest mitochondrial DNA-related disease, is caused by mutations affecting mitochondrial complex I. The clinical expression of the disorder, usually occurring in young adults, is typically characterized by subacute, usually sequential, bilateral visual loss, resulting from the degeneration of retinal ganglion cells. As the precise action of mitochondrial DNA mutations on the overall cell metabolism in Leber's hereditary optic neuropathy is unknown, we investigated the metabolomic profile of the disease. High performance liquid chromatography coupled with tandem mass spectrometry was used to quantify 188 metabolites in fibroblasts from 16 patients with Leber's hereditary optic neuropathy and eight healthy control subjects. Latent variable-based statistical methods were used to identify discriminating metabolites. One hundred and twenty-four of the metabolites were considered to be accurately quantified. A supervised orthogonal partial least squares discriminant analysis model separating patients with Leber's hereditary optic neuropathy from control subjects showed good predictive capability (Q 2cumulated = 0.57). Thirty-eight metabolites appeared to be the most significant variables, defining a Leber's hereditary optic neuropathy metabolic signature that revealed decreased concentrations of all proteinogenic amino acids, spermidine, putrescine, isovaleryl-carnitine, propionyl-carnitine and five sphingomyelin species, together with increased concentrations of 10 phosphatidylcholine species. This signature was not reproduced by the inhibition of complex I with rotenone or piericidin A in control fibroblasts. The importance of sphingomyelins and phosphatidylcholines in the Leber's hereditary optic neuropathy signature, together with the decreased amino acid pool, suggested an involvement of the endoplasmic reticulum. This was confirmed by the significantly increased phosphorylation of PERK and eIF2α, as well as

  16. Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

    Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J.

    2016-01-01

    Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: "1H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of "1H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by changes in the

  17. Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

    Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J., E-mail: myrna.simpson@utoronto.ca

    2016-01-15

    Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: {sup 1}H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of {sup 1}H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by

  18. Metabolomics Reveals that Momordica charantia Attenuates Metabolic Changes in Experimental Obesity.

    Gong, Zhi-Gang; Zhang, Jianbing; Xu, Yong-Jiang

    2017-02-01

    Momordica charantia L., also known as bitter melon, has been shown to ameliorate obesity and insulin resistance. However, metabolic changes regulated by M. charantia in obesity are not clearly understood. In this study, serums obtained from obese and M. charantia-treated mice were analyzed by using gas and liquid chromatography-mass spectrometry, and multivariate statistical analysis was performed by Orthogonal partial least squares discriminant analysis. The results from this study indicated that body weight fat and insulin levels of obese mice are dramatically suppressed by 8 weeks of dietary supplementation of M. charantia. Metabolomic data revealed that overproductions of energy and nutrient metabolism in obese mice were restored by M. charantia treatment. The antiinflammatory and inhibition of insulin resistance effect of M. charantia in obesity was illustrated with the restoration of free fatty acids and eicosanoids. The findings achieved in this study further strengthen the therapeutic value of using M. charantia to treat obesity. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  19. A Metabolome-Wide Study of Dry Eye Disease Reveals Serum Androgens as Biomarkers.

    Vehof, Jelle; Hysi, Pirro G; Hammond, Christopher J

    2017-04-01

    To test the association between serum metabolites and dry eye disease (DED) using a hypothesis-free metabolomics approach. Cross-sectional association study. A total of 2819 subjects from the population-representative TwinsUK cohort in the United Kingdom, with a mean age of 57 years (range, 17-82 years). We tested associations between 222 known serum metabolites and DED. All subjects underwent nontargeted metabolomic analysis of plasma samples using gas and liquid chromatography in combination with mass spectrometry (Metabolon Inc., Durham, NC). Dry eye disease was defined from the validated Short Questionnaire for Dry Eye Syndrome (SQDES) as a previous diagnosis of DED by a clinician or "often" or "constant" symptoms of dryness and irritation. Analyses were performed with linear mixed effect models that included age, BMI, and sex as covariates, corrected for multiple testing. Primary outcome was DED as defined by the SQDES, and secondary outcomes were symptom score of DED and a clinical diagnosis of DED. Prevalence of DED as defined by the SQDES was 15.5% (n = 436). A strong and metabolome-wide significant association with DED was found with decreased levels of the metabolites androsterone sulfate (P = 0.00030) and epiandrosterone sulfate (P = 0.00036). Three other metabolites involved in androgen metabolism, 4-androsten-3beta,17beta-diol disulfate 1 and 2, and dehydroepiandrosterone sulfate, were the next most strongly associated of the 222 metabolites, but did not reach metabolome-wide significance. Dryness and irritation symptoms, as opposed to a clinical diagnosis, were particularly strongly associated with decreased androgen steroid metabolites, with all reaching metabolome-wide significance (androsterone sulfate, P = 0.000000029; epiandrosterone sulfate, P = 0.0000040; 4-androsten-3beta,17beta-diol disulfate 1, P = 0.000016; 4-androsten-3beta,17beta-diol disulfate 2, P = 0.000064; and dehydroepiandrosterone sulfate, P = 0.00011). Of these 5

  20. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

  1. MetaFIND: A feature analysis tool for metabolomics data

    Cunningham Pádraig

    2008-11-01

    Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

  2. Metabolomics reveals metabolic biomarkers of Crohn's disease

    Jansson, J.K.; Willing, B.; Lucio, M.; Fekete, A.; Dicksved, J.; Halfvarson, J.; Tysk, C.; Schmitt-Kopplin, P.

    2009-06-01

    The causes and etiology of Crohn's disease (CD) are currently unknown although both host genetics and environmental factors play a role. Here we used non-targeted metabolic profiling to determine the contribution of metabolites produced by the gut microbiota towards disease status of the host. Ion Cyclotron Resonance Fourier Transform Mass Spectrometry (ICR-FT/MS) was used to discern the masses of thousands of metabolites in fecal samples collected from 17 identical twin pairs, including healthy individuals and those with CD. Pathways with differentiating metabolites included those involved in the metabolism and or synthesis of amino acids, fatty acids, bile acids and arachidonic acid. Several metabolites were positively or negatively correlated to the disease phenotype and to specific microbes previously characterized in the same samples. Our data reveal novel differentiating metabolites for CD that may provide diagnostic biomarkers and/or monitoring tools as well as insight into potential targets for disease therapy and prevention.

  3. Unbiased plasma metabolomics reveal the correlation of metabolic pathways and Prakritis of humans.

    Shirolkar, Amey; Chakraborty, Sutapa; Mandal, Tusharkanti; Dabur, Rajesh

    2017-11-25

    Ayurveda, an ancient Indian medicinal system, has categorized human body constitutions in three broad constitutional types (prakritis) i.e. Vata, Pitta and Kapha. Analysis of plasma metabolites and related pathways to classify Prakriti specific dominant marker metabolites and metabolic pathways. 38 healthy male individuals were assessed for dominant Prakritis and their fasting blood samples were collected. The processed plasma samples were subjected to rapid resolution liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (RRLC-ESI-QTOFMS). Mass profiles were aligned and subjected to multivariate analysis. Partial least square discriminant analysis (PLS-DA) model showed 97.87% recognition capability. List of PLS-DA metabolites was subjected to permutative Benjamini-Hochberg false discovery rate (FDR) correction and final list of 76 metabolites with p  2.0 was identified. Pathway analysis using metascape and JEPETTO plugins in Cytoscape revealed that steroidal hormone biosynthesis, amino acid, and arachidonic acid metabolism are major pathways varying with different constitution. Biological Go processes analysis showed that aromatic amino acids, sphingolipids, and pyrimidine nucleotides metabolic processes were dominant in kapha type of body constitution. Fat soluble vitamins, cellular amino acid, and androgen biosynthesis process along with branched chain amino acid and glycerolipid catabolic processes were dominant in pitta type individuals. Vata Prakriti was found to have dominant catecholamine, arachidonic acid and hydrogen peroxide metabolomics processes. The neurotransmission and oxidative stress in vata, BCAA catabolic, androgen, xenobiotics metabolic processes in pitta, and aromatic amino acids, sphingolipid, and pyrimidine metabolic process in kaphaPrakriti were the dominant marker pathways. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights

  4. Metabolomic Profiling of the Malaria Box Reveals Antimalarial Target Pathways

    Allman, Erik L.; Painter, Heather J.; Samra, Jasmeet; Carrasquilla, Manuela

    2016-01-01

    The threat of widespread drug resistance to frontline antimalarials has renewed the urgency for identifying inexpensive chemotherapeutic compounds that are effective against Plasmodium falciparum, the parasite species responsible for the greatest number of malaria-related deaths worldwide. To aid in the fight against malaria, a recent extensive screening campaign has generated thousands of lead compounds with low micromolar activity against blood stage parasites. A subset of these leads has been compiled by the Medicines for Malaria Venture (MMV) into a collection of structurally diverse compounds known as the MMV Malaria Box. Currently, little is known regarding the activity of these Malaria Box compounds on parasite metabolism during intraerythrocytic development, and a majority of the targets for these drugs have yet to be defined. Here we interrogated the in vitro metabolic effects of 189 drugs (including 169 of the drug-like compounds from the Malaria Box) using ultra-high-performance liquid chromatography–mass spectrometry (UHPLC-MS). The resulting metabolic fingerprints provide information on the parasite biochemical pathways affected by pharmacologic intervention and offer a critical blueprint for selecting and advancing lead compounds as next-generation antimalarial drugs. Our results reveal several major classes of metabolic disruption, which allow us to predict the mode of action (MoA) for many of the Malaria Box compounds. We anticipate that future combination therapies will be greatly informed by these results, allowing for the selection of appropriate drug combinations that simultaneously target multiple metabolic pathways, with the aim of eliminating malaria and forestalling the expansion of drug-resistant parasites in the field. PMID:27572391

  5. Metabolomics reveals the metabolic shifts following an intervention with rye bread in postmenopausal women- a randomized control trial

    Moazzami Ali A

    2012-10-01

    Full Text Available Abstract Background Epidemiological studies have consistently shown that whole grain (WG cereals can protect against the development of chronic diseases, but the underlying mechanism is not fully understood. Among WG products, WG rye is considered even more potent because of its unique discrepancy in postprandial insulin and glucose responses known as the rye factor. In this study, an NMR-based metabolomics approach was applied to study the metabolic effects of WG rye as a tool to determine the beneficial effects of WG rye on human health. Methods Thirty-three postmenopausal Finnish women with elevated serum total cholesterol (5.0-8.5 mmol/L and BMI of 20–33 kg/m2 consumed a minimum of 20% of their daily energy intake as high fiber WG rye bread (RB or refined wheat bread (WB in a randomized, controlled, crossover design with two 8-wk intervention periods separated by an 8-wk washout period. At the end of each intervention period, fasting serum was collected for NMR-based metabolomics and the analysis of cholesterol fractions. Multilevel partial least squares discriminant analysis was used for paired comparisons of multivariate data. Results The metabolomics analysis of serum showed lower leucine and isoleucine and higher betaine and N,N-dimethylglycine levels after RB than WB intake. To further investigate the metabolic effects of RB, the serum cholesterol fractions were measured. Total- and LDL-cholesterol levels were higher after RB intake than after WB (p Conclusions This study revealed favorable shifts in branched amino acid and single carbon metabolism and an unfavorable shift in serum cholesterol levels after RB intake in postmenopausal women, which should be considered for evaluating health beneficial effects of rye products.

  6. Neurochemical Metabolomics Reveals Disruption to Sphingolipid Metabolism Following Chronic Haloperidol Administration.

    McClay, Joseph L; Vunck, Sarah A; Batman, Angela M; Crowley, James J; Vann, Robert E; Beardsley, Patrick M; van den Oord, Edwin J

    2015-09-01

    Haloperidol is an effective antipsychotic drug for treatment of schizophrenia, but prolonged use can lead to debilitating side effects. To better understand the effects of long-term administration, we measured global metabolic changes in mouse brain following 3 mg/kg/day haloperidol for 28 days. These conditions lead to movement-related side effects in mice akin to those observed in patients after prolonged use. Brain tissue was collected following microwave tissue fixation to arrest metabolism and extracted metabolites were assessed using both liquid and gas chromatography mass spectrometry (MS). Over 300 unique compounds were identified across MS platforms. Haloperidol was found to be present in all test samples and not in controls, indicating experimental validity. Twenty-one compounds differed significantly between test and control groups at the p < 0.05 level. Top compounds were robust to analytical method, also being identified via partial least squares discriminant analysis. Four compounds (sphinganine, N-acetylornithine, leucine and adenosine diphosphate) survived correction for multiple testing in a non-parametric analysis using false discovery rate threshold < 0.1. Pathway analysis of nominally significant compounds (p < 0.05) revealed significant findings for sphingolipid metabolism (p = 0.015) and protein biosynthesis (p = 0.024). Altered sphingolipid metabolism is suggestive of disruptions to myelin. This interpretation is supported by our observation of elevated N-acetyl-aspartyl-glutamate in the haloperidol-treated mice (p = 0.004), a marker previously associated with demyelination. This study further demonstrates the utility of murine neurochemical metabolomics as a method to advance understanding of CNS drug effects.

  7. Metabolome analysis - mass spectrometry and microbial primary metabolites

    Højer-Pedersen, Jesper Juul

    2008-01-01

    , and therefore sample preparation is critical for metabolome analysis. The three major steps in sample preparation for metabolite analysis are sampling, extraction and concentration. These three steps were evaluated for the yeast Saccharomyces cerevisiae with primary focus on analysis of a large number...... of metabolites by one method. The results highlighted that there were discrepancies between different methods. To increase the throughput of cultivation, S. cerevisiae was grown in microtitier plates (MTPs), and the growth was found to be comparable with cultivations in shake flasks. The carbon source was either...... a theoretical metabolome. This showed that in combination with the specificity of MS up to 84% of the metabolites can be identified in a high-accuracy ESI-spectrum. A total of 66 metabolites were systematically analyzed by positive and negative ESI-MS/MS with the aim of initiating a spectral library for ESI...

  8. Metabolomic profiling reveals mitochondrial-derived lipid biomarkers that drive obesity-associated inflammation.

    Brante P Sampey

    Full Text Available Obesity has reached epidemic proportions worldwide. Several animal models of obesity exist, but studies are lacking that compare traditional lard-based high fat diets (HFD to "Cafeteria diets" (CAF consisting of nutrient poor human junk food. Our previous work demonstrated the rapid and severe obesogenic and inflammatory consequences of CAF compared to HFD including rapid weight gain, markers of Metabolic Syndrome, multi-tissue lipid accumulation, and dramatic inflammation. To identify potential mediators of CAF-induced obesity and Metabolic Syndrome, we used metabolomic analysis to profile serum, muscle, and white adipose from rats fed CAF, HFD, or standard control diets. Principle component analysis identified elevations in clusters of fatty acids and acylcarnitines. These increases in metabolites were associated with systemic mitochondrial dysfunction that paralleled weight gain, physiologic measures of Metabolic Syndrome, and tissue inflammation in CAF-fed rats. Spearman pairwise correlations between metabolites, physiologic, and histologic findings revealed strong correlations between elevated markers of inflammation in CAF-fed animals, measured as crown like structures in adipose, and specifically the pro-inflammatory saturated fatty acids and oxidation intermediates laurate and lauroyl carnitine. Treatment of bone marrow-derived macrophages with lauroyl carnitine polarized macrophages towards the M1 pro-inflammatory phenotype through downregulation of AMPK and secretion of pro-inflammatory cytokines. Results presented herein demonstrate that compared to a traditional HFD model, the CAF diet provides a robust model for diet-induced human obesity, which models Metabolic Syndrome-related mitochondrial dysfunction in serum, muscle, and adipose, along with pro-inflammatory metabolite alterations. These data also suggest that modifying the availability or metabolism of saturated fatty acids may limit the inflammation associated with obesity

  9. Computational Approaches for Integrative Analysis of the Metabolome and Microbiome

    Jasmine Chong

    2017-11-01

    Full Text Available The study of the microbiome, the totality of all microbes inhabiting the host or an environmental niche, has experienced exponential growth over the past few years. The microbiome contributes functional genes and metabolites, and is an important factor for maintaining health. In this context, metabolomics is increasingly applied to complement sequencing-based approaches (marker genes or shotgun metagenomics to enable resolution of microbiome-conferred functionalities associated with health. However, analyzing the resulting multi-omics data remains a significant challenge in current microbiome studies. In this review, we provide an overview of different computational approaches that have been used in recent years for integrative analysis of metabolome and microbiome data, ranging from statistical correlation analysis to metabolic network-based modeling approaches. Throughout the process, we strive to present a unified conceptual framework for multi-omics integration and interpretation, as well as point out potential future directions.

  10. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    Hajduk, Joanna; Klupczynska, Agnieszka; Dereziński, Paweł; Matysiak, Jan; Kokot, Piotr; Nowak, Dorota; Gajęcka, Marzena; Nowak-Markwitz, Ewa; Kokot, Zenon

    2015-01-01

    The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid ...

  11. A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

    Joanna Hajduk

    2015-12-01

    Full Text Available The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18 and a matched control group (n = 13. The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44% and specificity (84.62%, as well as the total group membership classification value (90.32% calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases.

  12. Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

    Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

    2015-02-01

    Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides

  13. Metaproteomics and metabolomics analyses of chronically petroleum-polluted sites reveal the importance of general anaerobic processes uncoupled with degradation.

    Bargiela, Rafael; Herbst, Florian-Alexander; Martínez-Martínez, Mónica; Seifert, Jana; Rojo, David; Cappello, Simone; Genovese, María; Crisafi, Francesca; Denaro, Renata; Chernikova, Tatyana N; Barbas, Coral; von Bergen, Martin; Yakimov, Michail M; Ferrer, Manuel; Golyshin, Peter N

    2015-10-01

    Crude oil is one of the most important natural assets for humankind, yet it is a major environmental pollutant, notably in marine environments. One of the largest crude oil polluted areas in the word is the semi-enclosed Mediterranean Sea, in which the metabolic potential of indigenous microbial populations towards the large-scale chronic pollution is yet to be defined, particularly in anaerobic and micro-aerophilic sites. Here, we provide an insight into the microbial metabolism in sediments from three chronically polluted marine sites along the coastline of Italy: the Priolo oil terminal/refinery site (near Siracuse, Sicily), harbour of Messina (Sicily) and shipwreck of MT Haven (near Genoa). Using shotgun metaproteomics and community metabolomics approaches, the presence of 651 microbial proteins and 4776 metabolite mass features have been detected in these three environments, revealing a high metabolic heterogeneity between the investigated sites. The proteomes displayed the prevalence of anaerobic metabolisms that were not directly related with petroleum biodegradation, indicating that in the absence of oxygen, biodegradation is significantly suppressed. This suppression was also suggested by examining the metabolome patterns. The proteome analysis further highlighted the metabolic coupling between methylotrophs and sulphate reducers in oxygen-depleted petroleum-polluted sediments. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Metaproteomics and metabolomics analyses of chronically petroleum‐polluted sites reveal the importance of general anaerobic processes uncoupled with degradation

    Bargiela, Rafael; Herbst, Florian‐Alexander; Martínez‐Martínez, Mónica; Seifert, Jana; Rojo, David; Cappello, Simone; Genovese, María; Crisafi, Francesca; Denaro, Renata; Chernikova, Tatyana N.; Barbas, Coral; von Bergen, Martin; Yakimov, Michail M.; Golyshin, Peter N.

    2015-01-01

    Crude oil is one of the most important natural assets for humankind, yet it is a major environmental pollutant, notably in marine environments. One of the largest crude oil polluted areas in the word is the semi‐enclosed Mediterranean Sea, in which the metabolic potential of indigenous microbial populations towards the large‐scale chronic pollution is yet to be defined, particularly in anaerobic and micro‐aerophilic sites. Here, we provide an insight into the microbial metabolism in sediments from three chronically polluted marine sites along the coastline of Italy: the Priolo oil terminal/refinery site (near Siracuse, Sicily), harbour of Messina (Sicily) and shipwreck of MT Haven (near Genoa). Using shotgun metaproteomics and community metabolomics approaches, the presence of 651 microbial proteins and 4776 metabolite mass features have been detected in these three environments, revealing a high metabolic heterogeneity between the investigated sites. The proteomes displayed the prevalence of anaerobic metabolisms that were not directly related with petroleum biodegradation, indicating that in the absence of oxygen, biodegradation is significantly suppressed. This suppression was also suggested by examining the metabolome patterns. The proteome analysis further highlighted the metabolic coupling between methylotrophs and sulphate reducers in oxygen‐depleted petroleum‐polluted sediments. PMID:26201687

  15. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

    Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2014-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544

  16. Retinal metabolic events in preconditioning light stress as revealed by wide-spectrum targeted metabolomics.

    de la Barca, Juan Manuel Chao; Huang, Nuan-Ting; Jiao, Haihan; Tessier, Lydie; Gadras, Cédric; Simard, Gilles; Natoli, Riccardo; Tcherkez, Guillaume; Reynier, Pascal; Valter, Krisztina

    2017-01-01

    Light is the primary stimulus for vision, but may also cause damage to the retina. Pre-exposing the retina to sub-lethal amount of light (or preconditioning) improves chances for retinal cells to survive acute damaging light stress. This study aims at exploring the changes in retinal metabolome after mild light stress and identifying mechanisms that may be involved in preconditioning. Retinas from 12 rats exposed to mild light stress (1000 lux × for 12 h) and 12 controls were collected one and seven days after light stress (LS). One retina was used for targeted metabolomics analysis using the Biocrates p180 kit while the fellow retina was used for histological and immunohistochemistry analysis. Immunohistochemistry confirmed that in this experiment, a mild LS with retinal immune response and minimal photoreceptor loss occurred. Compared to controls, LS induced an increased concentration in phosphatidylcholines. The concentration in some amino acids and biogenic amines, particularly those related to the nitric oxide pathway (like asymmetric dimethylarginine (ADMA), arginine and citrulline) also increased 1 day after LS. 7 days after LS, the concentration in two sphingomyelins and phenylethylamine was found to be higher. We further found that in controls, retina metabolome was different between males and females: male retinas had an increased concentration in tyrosine, acetyl-ornithine, phosphatidylcholines and (acyl)-carnitines. Besides retinal sexual metabolic dimorphism, this study shows that preconditioning is mostly associated with re-organisation of lipid metabolism and changes in amino acid composition, likely reflecting the involvement of arginine-dependent NO signalling.

  17. Non-Targeted Metabolomics Analysis of Golden Retriever Muscular Dystrophy-Affected Muscles Reveals Alterations in Arginine and Proline Metabolism, and Elevations in Glutamic and Oleic Acid In Vivo

    Abdullah, Muhammad; Kornegay, Joe N.; Honcoop, Aubree; Parry, Traci L.; Balog-Alvarez, Cynthia J.; Muehlbauer, Michael J.; Newgard, Christopher B.; Patterson, Cam

    2017-01-01

    Background: Like Duchenne muscular dystrophy (DMD), the Golden Retriever Muscular Dystrophy (GRMD) dog model of DMD is characterized by muscle necrosis, progressive paralysis, and pseudohypertrophy in specific skeletal muscles. This severe GRMD phenotype includes moderate atrophy of the biceps femoris (BF) as compared to unaffected normal dogs, while the long digital extensor (LDE), which functions to flex the tibiotarsal joint and serves as a digital extensor, undergoes the most pronounced atrophy. A recent microarray analysis of GRMD identified alterations in genes associated with lipid metabolism and energy production. Methods: We, therefore, undertook a non-targeted metabolomics analysis of the milder/earlier stage disease GRMD BF muscle versus the more severe/chronic LDE using GC-MS to identify underlying metabolic defects specific for affected GRMD skeletal muscle. Results: Untargeted metabolomics analysis of moderately-affected GRMD muscle (BF) identified eight significantly altered metabolites, including significantly decreased stearamide (0.23-fold of controls, p = 2.89 × 10−3), carnosine (0.40-fold of controls, p = 1.88 × 10−2), fumaric acid (0.40-fold of controls, p = 7.40 × 10−4), lactamide (0.33-fold of controls, p = 4.84 × 10−2), myoinositol-2-phosphate (0.45-fold of controls, p = 3.66 × 10−2), and significantly increased oleic acid (1.77-fold of controls, p = 9.27 × 10−2), glutamic acid (2.48-fold of controls, p = 2.63 × 10−2), and proline (1.73-fold of controls, p = 3.01 × 10−2). Pathway enrichment analysis identified significant enrichment for arginine/proline metabolism (p = 5.88 × 10−4, FDR 4.7 × 10−2), where alterations in L-glutamic acid, proline, and carnosine were found. Additionally, multiple Krebs cycle intermediates were significantly decreased (e.g., malic acid, fumaric acid, citric/isocitric acid, and succinic acid), suggesting that altered energy metabolism may be underlying the observed GRMD BF muscle

  18. Phenotypic diversity of diploid and haploid Emiliania huxleyi cells and of cells in different growth phases revealed by comparative metabolomics.

    Mausz, Michaela A; Pohnert, Georg

    2015-01-01

    In phytoplankton a high species diversity of microalgae co-exists at a given time. But diversity is not only reflected by the species composition. Within these species different life phases as well as different metabolic states can cause additional diversity. One important example is the coccolithophore Emiliania huxleyi. Diploid cells play an important role in marine ecosystems since they can form massively abundant algal blooms but in addition the less abundant haploid life phase of E. huxleyi occurs in lower quantities. Both life phases may fulfill different functions in the plankton. We hypothesize that in addition to the functional diversity caused by this life phase transition the growth stage of cells can also influence the metabolic composition and thus the ecological impact of E. huxleyi. Here we introduce a metabolomic survey in dependence of life phases as well as different growth phases to reveal such changes. The comparative metabolomic approach is based on the extraction of intracellular metabolites from intact microalgae, derivatization and analysis by gas chromatography coupled to mass spectrometry (GC-MS). Automated data processing and statistical analysis using canonical analysis of principal coordinates (CAP) revealed unique metabolic profiles for each life phase. Concerning the correlations of metabolites to growth phases, complex patterns were observed. As for example the saccharide mannitol showed its highest concentration in the exponential phase, whereas fatty acids were correlated to stationary and sterols to declining phase. These results are indicative for specific ecological roles of these stages of E. huxleyi and are discussed in the context of previous physiological and ecological studies. Copyright © 2014 Elsevier GmbH. All rights reserved.

  19. Diagnosis of adenylosuccinate lyase deficiency by metabolomic profiling in plasma reveals a phenotypic spectrum

    Taraka R. Donti

    2016-09-01

    Full Text Available Adenylosuccinate lyase (ADSL deficiency is a rare autosomal recessive neurometabolic disorder that presents with a broad-spectrum of neurological and physiological symptoms. The ADSL gene produces an enzyme with binary molecular roles in de novo purine synthesis and purine nucleotide recycling. The biochemical phenotype of ADSL deficiency, accumulation of SAICAr and succinyladenosine (S-Ado in biofluids of affected individuals, serves as the traditional target for diagnosis with targeted quantitative urine purine analysis employed as the predominate method of detection. In this study, we report the diagnosis of ADSL deficiency using an alternative method, untargeted metabolomic profiling, an analytical scheme capable of generating semi-quantitative z-score values for over 1000 unique compounds in a single analysis of a specimen. Using this method to analyze plasma, we diagnosed ADSL deficiency in four patients and confirmed these findings with targeted quantitative biochemical analysis and molecular genetic testing. ADSL deficiency is part of a large a group of neurometabolic disorders, with a wide range of severity and sharing a broad differential diagnosis. This phenotypic similarity among these many inborn errors of metabolism (IEMs has classically stood as a hurdle in their initial diagnosis and subsequent treatment. The findings presented here demonstrate the clinical utility of metabolomic profiling in the diagnosis of ADSL deficiency and highlights the potential of this technology in the diagnostic evaluation of individuals with neurologic phenotypes.

  20. Metabolomic profiling reveals deep chemical divergence between two morphotypes of the zoanthid Parazoanthus axinellae

    Cachet, Nadja; Genta-Jouve, Grégory; Ivanisevic, Julijana; Chevaldonné, Pierre; Sinniger, Frédéric; Culioli, Gérald; Pérez, Thierry; Thomas, Olivier P.

    2015-01-01

    Metabolomics has recently proven its usefulness as complementary tool to traditional morphological and genetic analyses for the classification of marine invertebrates. Among the metabolite-rich cnidarian order Zoantharia, Parazoanthus is a polyphyletic genus whose systematics and phylogeny remain controversial. Within this genus, one of the most studied species, Parazoanthus axinellae is prominent in rocky shallow waters of the Mediterranean Sea and the NE Atlantic Ocean. Although different morphotypes can easily be distinguished, only one species is recognized to date. Here, a metabolomic profiling approach has been used to assess the chemical diversity of two main Mediterranean morphotypes, the “slender” and “stocky” forms of P. axinellae. Targeted profiling of their major secondary metabolites revealed a significant chemical divergence between the morphotypes. While zoanthoxanthin alkaloids and ecdysteroids are abundant in both morphs, the “slender” morphotype is characterized by the presence of additional and bioactive 3,5-disubstituted hydantoin derivatives named parazoanthines. The absence of these specific compounds in the “stocky” morphotype was confirmed by spatial and temporal monitoring over an annual cycle. Moreover, specimens of the “slender” morphotype are also the only ones found as epibionts of several sponge species, particularly Cymbaxinella damicornis thus suggesting a putative ecological link. PMID:25655432

  1. Untargeted GC-MS Metabolomics Reveals Changes in the Metabolite Dynamics of Industrial Scale Batch Fermentations of Streptoccoccus thermophilus Broth

    Khakimov, Bekzod; Christiansen, Lene D.; Heins, Anna-Lena

    2017-01-01

    An industrial scale biomass production using batch or fed-batch fermentations usually optimized by selection of bacterial strains, tuning fermentation media, feeding strategy, and temperature. However, in-depth investigation of the biomass metabolome during the production may reveal new knowledge...... shows that in-depth metabolic analysis of fermentation broth provides a new tool for advanced optimization of high-volume-low-cost biomass production by lowering the cost, increase the yield, and augment the product quality....... for better optimization. In this study, for the first time, the authors investigated seven fermentation batches performed on five Streptoccoccus thermophilus strains during the biomass production at Chr. Hansen (Denmark) in a real life large scale fermentation process. The study is designed to investigate...

  2. Global metabolomics reveals potential urinary biomarkers of esophageal squamous cell carcinoma for diagnosis and staging

    Xu, Jing; Chen, Yanhua; Zhang, Ruiping; He, Jiuming; Song, Yongmei; Wang, Jingbo; Wang, Huiqing; Wang, Luhua; Zhan, Qimin; Abliz, Zeper

    2016-10-01

    We performed a metabolomics study using liquid chromatography-mass spectrometry (LC-MS) combined with multivariate data analysis (MVDA) to discriminate global urine profiles in urine samples from esophageal squamous cell carcinoma (ESCC) patients and healthy controls (NC). Our work evaluated the feasibility of employing urine metabolomics for the diagnosis and staging of ESCC. The satisfactory classification between the healthy controls and ESCC patients was obtained using the MVDA model, and obvious classification of early-stage and advanced-stage patients was also observed. The results suggest that the combination of LC-MS analysis and MVDA may have potential applications for ESCC diagnosis and staging. We then conducted LC-MS/MS experiments to identify the potential biomarkers with large contributions to the discrimination. A total of 83 potential diagnostic biomarkers for ESCC were screened out, and 19 potential biomarkers were identified; the variations between the differences in staging using these potential biomarkers were further analyzed. These biomarkers may not be unique to ESCCs, but instead result from any malignant disease. To further elucidate the pathophysiology of ESCC, we studied related metabolic pathways and found that ESCC is associated with perturbations of fatty acid β-oxidation and the metabolism of amino acids, purines, and pyrimidines.

  3. Metabolomic analysis in severe childhood pneumonia in the Gambia, West Africa: findings from a pilot study.

    Evagelia C Laiakis

    Full Text Available BACKGROUND: Pneumonia remains the leading cause of death in young children globally and improved diagnostics are needed to better identify cases and reduce case fatality. Metabolomics, a rapidly evolving field aimed at characterizing metabolites in biofluids, has the potential to improve diagnostics in a range of diseases. The objective of this pilot study is to apply metabolomic analysis to childhood pneumonia to explore its potential to improve pneumonia diagnosis in a high-burden setting. METHODOLOGY/PRINCIPAL FINDINGS: Eleven children with World Health Organization (WHO-defined severe pneumonia of non-homogeneous aetiology were selected in The Gambia, West Africa, along with community controls. Metabolomic analysis of matched plasma and urine samples was undertaken using Ultra Performance Liquid Chromatography (UPLC coupled to Time-of-Flight Mass Spectrometry (TOFMS. Biomarker extraction was done using SIMCA-P+ and Random Forests (RF. 'Unsupervised' (blinded data were analyzed by Principal Component Analysis (PCA, while 'supervised' (unblinded analysis was by Partial Least Squares-Discriminant Analysis (PLS-DA and Orthogonal Projection to Latent Structures (OPLS. Potential markers were extracted from S-plots constructed following analysis with OPLS, and markers were chosen based on their contribution to the variation and correlation within the data set. The dataset was additionally analyzed with the machine-learning algorithm RF in order to address issues of model overfitting and markers were selected based on their variable importance ranking. Unsupervised PCA analysis revealed good separation of pneumonia and control groups, with even clearer separation of the groups with PLS-DA and OPLS analysis. Statistically significant differences (p<0.05 between groups were seen with the following metabolites: uric acid, hypoxanthine and glutamic acid were higher in plasma from cases, while L-tryptophan and adenosine-5'-diphosphate (ADP were lower

  4. Introducing Undergraduate Students to Metabolomics Using a NMR-Based Analysis of Coffee Beans

    Sandusky, Peter Olaf

    2017-01-01

    Metabolomics applies multivariate statistical analysis to sets of high-resolution spectra taken over a population of biologically derived samples. The objective is to distinguish subpopulations within the overall sample population, and possibly also to identify biomarkers. While metabolomics has become part of the standard analytical toolbox in…

  5. Serum metabolomics reveals betaine and phosphatidylcholine as potential biomarkers for the toxic responses of processed Aconitum carmichaelii Debx.

    Tan, Yong; Ko, Joshua; Liu, Xinru; Lu, Cheng; Li, Jian; Xiao, Cheng; Li, Li; Niu, Xuyan; Jiang, Miao; He, Xiaojuan; Zhao, Hongyan; Zhang, Zhongxiao; Bian, Zhaoxiang; Yang, Zhijun; Zhang, Ge; Zhang, Weidong; Lu, Aiping

    2014-07-29

    We recently reported that processed Aconitum carmichaelii Debx (Bai-Fu-Pian in Chinese, BFP) elicits differential toxic responses in rats under various health conditions. The present study aimed to determine the graded toxicity of BFP so as to derive a safe therapeutic rationale in clinical practice. Sensitive and reliable biomarkers of toxicity were also identified, with the corresponding metabolic pathways being unveiled. Thirty male Sprague-Dawley rats were divided into five groups (n = 6) and received oral administration of BFP extract (0.32, 0.64, 1.28 or 2.56 g kg(-1) per day) or an equal volume of drinking water (control) for 15 days. The metabolomic profiles of rat serum were analyzed by liquid chromatography quadruple time-of-flight mass spectrometry (LC-Q-TOF-MS). Linear regression analysis and Ingenuity Pathway Analysis (IPA) were used to elucidate the differentiated altered metabolites and associated network relationships. Results from biochemical and histopathological examinations revealed that BFP could induce prominent toxicity in the heart, liver and kidneys at a dose of 2.56 g kg(-1) per day. Betaine up-regulation and phosphatidylcholine down-regulation were detected in the serum samples of drug-treated groups in a dose-dependent manner. In summary, betaine and phosphatidylcholine could be regarded as sensitive biomarkers for the toxic responses of BFP. Perturbations of RhoA signaling, choline metabolism and free radical scavenging were found to be partly responsible for the toxic effects of the herbal drug. Based on the metabolomics findings, we could establish a safe therapeutic range in the clinical use of BFP, with promising predictions of possible drug toxicity.

  6. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    Yufeng Jane Tseng

    2013-05-01

    Full Text Available Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  7. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    Tsai, I-Lin [Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan (China); The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan (China); Kuo, Tien-Chueh [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Room 410 BL Building, No. 1, Roosevelt Road, Sec. 4, Taipei 106, Taiwan (China); Ho, Tsung-Jung [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China); Harn, Yeu-Chern [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Graduate Institute of Networking and Multimedia, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China); Wang, San-Yuan [The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China); Fu, Wen-Mei [Department of Pharmacology, National Taiwan University, 11 F No. 1 Sec. 1, Ren-ai Rd., Taipei 10051, Taiwan (China); Kuo, Ching-Hua, E-mail: kuoch@ntu.edu.tw [Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan (China); The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan (China); Tseng, Yufeng Jane, E-mail: kuoch@ntu.edu.tw [Department of Pharmacy, National Taiwan University, No. 1, Jen-Ai Road, Section 1 Taipei 10051, Taiwan (China); The Metabolomics Group, National Taiwan University, Taipei 106, Taiwan (China); Center for Genomic Medicine, National Taiwan University, Taipei 10051, Taiwan (China); Graduate Institute of Biomedical Electronic and Bioinformatics, National Taiwan University, Room 410 BL Building, No. 1, Roosevelt Road, Sec. 4, Taipei 106, Taiwan (China); Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan (China)

    2013-05-03

    Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis.

  8. Metabolomic Dynamic Analysis of Hypoxia in MDA-MB-231 and the Comparison with Inferred Metabolites from Transcriptomics Data

    Tsai, I-Lin; Kuo, Tien-Chueh; Ho, Tsung-Jung; Harn, Yeu-Chern; Wang, San-Yuan; Fu, Wen-Mei; Kuo, Ching-Hua; Tseng, Yufeng Jane

    2013-01-01

    Hypoxia affects the tumor microenvironment and is considered important to metastasis progression and therapy resistance. Thus far, the majority of global analyses of tumor hypoxia responses have been limited to just a single omics level. Combining multiple omics data can broaden our understanding of tumor hypoxia. Here, we investigate the temporal change of the metabolite composition with gene expression data from literature to provide a more comprehensive insight into the system level in response to hypoxia. Nuclear magnetic resonance spectroscopy was used to perform metabolomic profiling on the MDA-MB-231 breast cancer cell line under hypoxic conditions. Multivariate statistical analysis revealed that the metabolic difference between hypoxia and normoxia was similar over 24 h, but became distinct over 48 h. Time dependent microarray data from the same cell line in the literature displayed different gene expressions under hypoxic and normoxic conditions mostly at 12 h or earlier. The direct metabolomic profiles show a large overlap with theoretical metabolic profiles deduced from previous transcriptomic studies. Consistent pathways are glycolysis/gluconeogenesis, pyruvate, purine and arginine and proline metabolism. Ten metabolic pathways revealed by metabolomics were not covered by the downstream of the known transcriptomic profiles, suggesting new metabolic phenotypes. These results confirm previous transcriptomics understanding and expand the knowledge from existing models on correlation and co-regulation between transcriptomic and metabolomics profiles, which demonstrates the power of integrated omics analysis

  9. Integrative analysis of metabolomics and transcriptomics data

    Brink-Jensen, Kasper; Bak, Søren; Jørgensen, Kirsten

    2013-01-01

    ) measurements from the same samples, to identify genes controlling the production of metabolites. Due to the high dimensionality of both LC-MS and DNA microarray data, dimension reduction and variable selection are key elements of the analysis. Our proposed approach starts by identifying the basis functions......The abundance of high-dimensional measurements in the form of gene expression and mass spectroscopy calls for models to elucidate the underlying biological system. For widely studied organisms like yeast, it is possible to incorporate prior knowledge from a variety of databases, an approach used...... ("building blocks") that constitute the output from a mass spectrometry experiment. Subsequently, the weights of these basis functions are related to the observations from the corresponding gene expression data in order to identify which genes are associated with specific patterns seen in the metabolite data...

  10. Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

    Mónica Escandón

    2018-04-01

    Full Text Available The integrative omics approach is crucial to identify the molecular mechanisms underlying high-temperature response in non-model species. Based on future scenarios of heat increase, Pinus radiata plants were exposed to a temperature of 40°C for a period of 5 days, including recovered plants (30 days after last exposure to 40°C in the analysis. The analysis of the metabolome using complementary mass spectrometry techniques (GC-MS and LC-Orbitrap-MS allowed the reliable quantification of 2,287 metabolites. The analysis of identified metabolites and highlighter metabolic pathways across heat time exposure reveal the dynamism of the metabolome in relation to high-temperature response in P. radiata, identifying the existence of a turning point (on day 3 at which P. radiata plants changed from an initial stress response program (shorter-term response to an acclimation one (longer-term response. Furthermore, the integration of metabolome and physiological measurements, which cover from the photosynthetic state to hormonal profile, suggests a complex metabolic pathway interaction network related to heat-stress response. Cytokinins (CKs, fatty acid metabolism and flavonoid and terpenoid biosynthesis were revealed as the most important pathways involved in heat-stress response in P. radiata, with zeatin riboside (ZR and isopentenyl adenosine (iPA as the key hormones coordinating these multiple and complex interactions. On the other hand, the integrative approach allowed elucidation of crucial metabolic mechanisms involved in heat response in P. radiata, as well as the identification of thermotolerance metabolic biomarkers (L-phenylalanine, hexadecanoic acid, and dihydromyricetin, crucial metabolites which can reschedule the metabolic strategy to adapt to high temperature.

  11. Metabolomic profiling reveals a role for CPT1c in neuronal oxidative metabolism.

    Lee, Jieun; Wolfgang, Michael J

    2012-10-25

    Carnitine Palmitoyltransferase-1c (CPT1c) is a neuron specific homologue of the carnitine acyltransferase family of enzymes. CPT1 isoenzymes transfer long chain acyl groups to carnitine. This constitutes a rate setting step for mitochondrial fatty acid beta-oxidation by facilitating the initial step in acyl transfer to the mitochondrial matrix. In general, neurons do not heavily utilize fatty acids for bioenergetic needs and definitive enzymatic activity has been unable to be demonstrated for CPT1c. Although there are studies suggesting an enzymatic role of CPT1c, its role in neurochemistry remains elusive. In order to better understand how CPT1c functions in neural metabolism, we performed unbiased metabolomic profiling on wild-type (WT) and CPT1c knockout (KO) mouse brains. Consistent with the notion that CPT1c is not involved in fatty acid beta-oxidation, there were no changes in metabolites associated with fatty acid oxidation. Endocannabinoids were suppressed in the CPT1c KO, which may explain the suppression of food intake seen in CPT1c KO mice. Although products of beta-oxidation were unchanged, small changes in carnitine and carnitine metabolites were observed. Finally, we observed changes in redox homeostasis including a greater than 2-fold increase in oxidized glutathione. This indicates that CPT1c may play a role in neural oxidative metabolism. Steady-state metabolomic analysis of CPT1c WT and KO mouse brains identified a small number of metabolites that differed between CPT1c WT and KO mice. The subtle changes in a broad range of metabolites in vivo indicate that CPT1c does not play a significant or required role in fatty acid oxidation; however, it could play an alternative role in neuronal oxidative metabolism.

  12. Metabolomic profiling reveals a role for CPT1c in neuronal oxidative metabolism

    Lee Jieun

    2012-10-01

    Full Text Available Abstract Background Carnitine Palmitoyltransferase-1c (CPT1c is a neuron specific homologue of the carnitine acyltransferase family of enzymes. CPT1 isoenzymes transfer long chain acyl groups to carnitine. This constitutes a rate setting step for mitochondrial fatty acid beta-oxidation by facilitating the initial step in acyl transfer to the mitochondrial matrix. In general, neurons do not heavily utilize fatty acids for bioenergetic needs and definitive enzymatic activity has been unable to be demonstrated for CPT1c. Although there are studies suggesting an enzymatic role of CPT1c, its role in neurochemistry remains elusive. Results In order to better understand how CPT1c functions in neural metabolism, we performed unbiased metabolomic profiling on wild-type (WT and CPT1c knockout (KO mouse brains. Consistent with the notion that CPT1c is not involved in fatty acid beta-oxidation, there were no changes in metabolites associated with fatty acid oxidation. Endocannabinoids were suppressed in the CPT1c KO, which may explain the suppression of food intake seen in CPT1c KO mice. Although products of beta-oxidation were unchanged, small changes in carnitine and carnitine metabolites were observed. Finally, we observed changes in redox homeostasis including a greater than 2-fold increase in oxidized glutathione. This indicates that CPT1c may play a role in neural oxidative metabolism. Conclusions Steady-state metabolomic analysis of CPT1c WT and KO mouse brains identified a small number of metabolites that differed between CPT1c WT and KO mice. The subtle changes in a broad range of metabolites in vivo indicate that CPT1c does not play a significant or required role in fatty acid oxidation; however, it could play an alternative role in neuronal oxidative metabolism.

  13. Cerebrospinal fluid metabolomics reveals altered waste clearance and accelerated aging in HIV patients with neurocognitive impairment

    Cassol, Edana; Misra, Vikas; Dutta, Anupriya; Morgello, Susan; Gabuzda, Dana

    2014-01-01

    Objective(s): HIV-associated neurocognitive disorders (HAND) remain prevalent in HIV-infected patients on antiretroviral therapy (ART), but the underlying mechanisms are unclear. Some features of HAND resemble those of age-associated cognitive decline in the absence of HIV, suggesting that overlapping mechanisms may contribute to neurocognitive impairment. Design: Cross-sectional analysis of cerebrospinal fluid (CSF) from 100 individuals (46 HIV-positive patients and 54 HIV-negative controls). Methods: Untargeted CSF metabolite profiling was performed using liquid/gas chromatography followed by mass spectrometry. Cytokine profiling was performed by Bioplex. Bioinformatic analyses were performed in Metaboanalyst and R. Results: Alterations in the CSF metabolome of HIV patients on ART mapped to pathways associated with neurotransmitter production, mitochondrial function, oxidative stress, and metabolic waste. Many CSF metabolites altered in HIV overlapped with those altered with advanced age in HIV-negative controls, suggesting a pattern indicative of accelerated aging. Machine learning models identified neurotransmitters (glutamate, N-acetylaspartate), markers of glial activation (myo-inositol), and ketone bodies (beta-hydroxybutyric acid, 1,2-propanediol) as top-ranked classifiers of HAND. These CSF metabolites correlated with worse neurocognitive test scores, plasma inflammatory biomarkers [interferon (IFN)-α, IFN-γ, interleukin (IL)-8, IL-1β, IL-6, IL-2Ra], and intrathecal IFN responses (IFN-γ and kynurenine : tryptophan ratio), suggesting inter-relationships between systemic and intrathecal inflammation and metabolic alterations in CSF. Conclusions: Alterations in the CSF metabolome of HIV patients on ART suggest that persistent inflammation, glial responses, glutamate neurotoxicity, and altered brain waste disposal systems contribute to mechanisms involved in HAND that may be augmented with aging. PMID:24752083

  14. Independent component analysis in non-hypothesis driven metabolomics

    Li, Xiang; Hansen, Jakob; Zhao, Xinjie

    2012-01-01

    In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori...... information on the investigated process and moreover can separate statistically independent source signals with non-Gaussian distribution, we aimed to elucidate the analytical power of ICA for the metabolic pattern analysis and the identification of key metabolites in this exercise study. A novel approach...... based on descriptive statistics was established to optimize ICA model. In the GC-TOF MS data set the number of principal components after whitening and the number of independent components of ICA were optimized and systematically selected by descriptive statistics. The elucidated dominating independent...

  15. Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI)

    Amberg, Alexander; Barrett, Dave; Beale, Michael H.; Beger, Richard; Daykin, Clare A.; Fan, Teresa W.-M.; Fiehn, Oliver; Goodacre, Royston; Griffin, Julian L.; Hankemeier, Thomas; Hardy, Nigel; Harnly, James; Higashi, Richard; Kopka, Joachim; Lane, Andrew N.; Lindon, John C.; Marriott, Philip; Nicholls, Andrew W.; Reily, Michael D.; Thaden, John J.; Viant, Mark R.

    2013-01-01

    There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum. PMID:24039616

  16. Metabolic regulation of trisporic acid on Blakeslea trispora revealed by a GC-MS-based metabolomic approach.

    Jie Sun

    Full Text Available The zygomycete Blakeslea trispora is used commercially as natural source of â-carotene. Trisporic acid (TA is secreted from the mycelium of B. trispora during mating between heterothallic strains and is considered as a mediator of the regulation of mating processes and an enhancer of carotene biosynthesis. Gas chromatography-mass spectrometry and multivariate analysis were employed to investigate TA-associated intracellular biochemical changes in B. trispora. By principal component analysis, the differential metabolites discriminating the control groups from the TA-treated groups were found, which were also confirmed by the subsequent hierarchical cluster analysis. The results indicate that TA is a global regulator and its main effects at the metabolic level are reflected on the content changes in several fatty acids, carbohydrates, and amino acids. The carbon metabolism and fatty acids synthesis are sensitive to TA addition. Glycerol, glutamine, and ã-aminobutyrate might play important roles in the regulation of TA. Complemented by two-dimensional electrophoresis, the results indicate that the actions of TA at the metabolic level involve multiple metabolic processes, such as glycolysis and the bypass of the classical tricarboxylic acid cycle. These results reveal that the metabolomics strategy is a powerful tool to gain insight into the mechanism of a microorganism's cellular response to signal inducers at the metabolic level.

  17. Genetic transformation of rare Verbascum eriophorum Godr. plants and metabolic alterations revealed by NMR-based metabolomics.

    Marchev, Andrey; Yordanova, Zhenya; Alipieva, Kalina; Zahmanov, Georgi; Rusinova-Videva, Snezhana; Kapchina-Toteva, Veneta; Simova, Svetlana; Popova, Milena; Georgiev, Milen I

    2016-09-01

    To develop a protocol to transform Verbascum eriophorum and to study the metabolic differences between mother plants and hairy root culture by applying NMR and processing the datasets with chemometric tools. Verbascum eriophorum is a rare species with restricted distribution, which is poorly studied. Agrobacterium rhizogenes-mediated genetic transformation of V. eriophorum and hairy root culture induction are reported for the first time. To determine metabolic alterations, V. eriophorum mother plants and relevant hairy root culture were subjected to comprehensive metabolomic analyses, using NMR (1D and 2D). Metabolomics data, processed using chemometric tools (and principal component analysis in particular) allowed exploration of V. eriophorum metabolome and have enabled identification of verbascoside (by means of 2D-TOCSY NMR) as the most abundant compound in hairy root culture. Metabolomics data contribute to the elucidation of metabolic alterations after T-DNA transfer to the host V. eriophorum genome and the development of hairy root culture for sustainable bioproduction of high value verbascoside.

  18. Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data

    Kevin Schwahn

    2017-12-01

    Full Text Available Recent advances in metabolomics technologies have resulted in high-quality (time-resolved metabolic profiles with an increasing coverage of metabolic pathways. These data profiles represent read-outs from often non-linear dynamics of metabolic networks. Yet, metabolic profiles have largely been explored with regression-based approaches that only capture linear relationships, rendering it difficult to determine the extent to which the data reflect the underlying reaction rates and their couplings. Here we propose an approach termed Stoichiometric Correlation Analysis (SCA based on correlation between positive linear combinations of log-transformed metabolic profiles. The log-transformation is due to the evidence that metabolic networks can be modeled by mass action law and kinetics derived from it. Unlike the existing approaches which establish a relation between pairs of metabolites, SCA facilitates the discovery of higher-order dependence between more than two metabolites. By using a paradigmatic model of the tricarboxylic acid cycle we show that the higher-order dependence reflects the coupling of concentration of reactant complexes, capturing the subtle difference between the employed enzyme kinetics. Using time-resolved metabolic profiles from Arabidopsis thaliana and Escherichia coli, we show that SCA can be used to quantify the difference in coupling of reactant complexes, and hence, reaction rates, underlying the stringent response in these model organisms. By using SCA with data from natural variation of wild and domesticated wheat and tomato accession, we demonstrate that the domestication is accompanied by loss of such couplings, in these species. Therefore, application of SCA to metabolomics data from natural variation in wild and domesticated populations provides a mechanistic way to understanding domestication and its relation to metabolic networks.

  19. Mass Spectrometry-Based Quantitative Metabolomics Revealed a Distinct Lipid Profile in Breast Cancer Patients

    Yun Yen

    2013-04-01

    Full Text Available Breast cancer accounts for the largest number of newly diagnosed cases in female cancer patients. Although mammography is a powerful screening tool, about 20% of breast cancer cases cannot be detected by this method. New diagnostic biomarkers for breast cancer are necessary. Here, we used a mass spectrometry-based quantitative metabolomics method to analyze plasma samples from 55 breast cancer patients and 25 healthy controls. A number of 30 patients and 20 age-matched healthy controls were used as a training dataset to establish a diagnostic model and to identify potential biomarkers. The remaining samples were used as a validation dataset to evaluate the predictive accuracy for the established model. Distinct separation was obtained from an orthogonal partial least squares-discriminant analysis (OPLS-DA model with good prediction accuracy. Based on this analysis, 39 differentiating metabolites were identified, including significantly lower levels of lysophosphatidylcholines and higher levels of sphingomyelins in the plasma samples obtained from breast cancer patients compared with healthy controls. Using logical regression, a diagnostic equation based on three metabolites (lysoPC a C16:0, PC ae C42:5 and PC aa C34:2 successfully differentiated breast cancer patients from healthy controls, with a sensitivity of 98.1% and a specificity of 96.0%.

  20. NMR-based metabolomics applications

    Iaccarino, Nunzia

    Metabolomics is the scientific discipline that identifies and quantifies endogenous and exogenous metabolites in different biological samples. Metabolites are crucial components of a biological system and they are highly informative about its functional state, due to their closeness to the organism...... focused on the analysis of various samples covering a wide range of fields, namely, food and nutraceutical sciences, cell metabolomics and medicine using a metabolomics approach. Indeed, the first part of the thesis describes two exploratory studies performed on Algerian extra virgin olive oil and apple...... juice from ancient Danish apple cultivars. Both studies revealed variety-related peculiarities that would have been difficult to detect by means of traditional analysis. The second part of the project includes four metabolomics studies performed on samples of biological origin. In particular, the first...

  1. Statistical methods for the analysis of high-throughput metabolomics data

    Fabian J. Theis

    2013-01-01

    Full Text Available Metabolomics is a relatively new high-throughput technology that aims at measuring all endogenous metabolites within a biological sample in an unbiased fashion. The resulting metabolic profiles may be regarded as functional signatures of the physiological state, and have been shown to comprise effects of genetic regulation as well as environmental factors. This potential to connect genotypic to phenotypic information promises new insights and biomarkers for different research fields, including biomedical and pharmaceutical research. In the statistical analysis of metabolomics data, many techniques from other omics fields can be reused. However recently, a number of tools specific for metabolomics data have been developed as well. The focus of this mini review will be on recent advancements in the analysis of metabolomics data especially by utilizing Gaussian graphical models and independent component analysis.

  2. Software and Database Usage on Metabolomic Studies: Using XCMS on LC-MS Data Analysis

    Mustafa Celebier

    2014-04-01

    Full Text Available Metabolome is the complete set of small-molecule metabolites to be found in a cell or a single organism. Metabolomics is the scientific study to determine and identify the chemicals in metabolome with advanced analytical techniques. Nowadays, the elucidation of the molecular mechanism of any disease with genome analysis and proteome analysis is not sufficient. Instead of these, a holistic assessment including metabolomic studies provides rational and accurate results. Metabolite levels in an organism are associated with the cellular functions. Thus, determination of the metabolite amounts identifies the phenotype of a cell or tissue related with the genetic and some other variations. Even though, the analysis of metabolites for medical diagnosis and therapy have been performed for a long time, the studies to improve the analysis methods for metabolite profiling are recently increased. The application of metabolomics includes the identification of biomarkers, enzyme-substract interactions, drug-activity studies, metabolic pathway analysis and some other studies related with the system biology. The preprocessing and computing of the data obtained from LC-MS, GC-MS, CE-MS and NMR for metabolite profiling are helpful for preventing from time consuming manual data analysis processes and possible random errors on profiling period. In addition, such preprocesses allow us to identify low amount of metabolites which are not possible to be analyzed by manual processing. Therefore, the usage of software and databases for this purpose could not be ignored. In this study, it is briefly presented the software and database used on metabolomics and it is evaluated the capability of these software on metabolite profiling. Particularly, the performance of one of the most popular software called XCMS on the evaluation of LC-MS results for metabolomics was overviewed. In the near future, metabolomics with software and database support is estimated to be a routine

  3. Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics.

    Wilmes, Anja; Bielow, Chris; Ranninger, Christina; Bellwon, Patricia; Aschauer, Lydia; Limonciel, Alice; Chassaigne, Hubert; Kristl, Theresa; Aiche, Stephan; Huber, Christian G; Guillou, Claude; Hewitt, Philipp; Leonard, Martin O; Dekant, Wolfgang; Bois, Frederic; Jennings, Paul

    2015-12-25

    Cisplatin is one of the most widely used chemotherapeutic agents for the treatment of solid tumours. The major dose-limiting factor is nephrotoxicity, in particular in the proximal tubule. Here, we use an integrated omics approach, including transcriptomics, proteomics and metabolomics coupled to biokinetics to identify cell stress response pathways induced by cisplatin. The human renal proximal tubular cell line RPTEC/TERT1 was treated with sub-cytotoxic concentrations of cisplatin (0.5 and 2 μM) in a daily repeat dose treating regime for up to 14 days. Biokinetic analysis showed that cisplatin was taken up from the basolateral compartment, transported to the apical compartment, and accumulated in cells over time. This is in line with basolateral uptake of cisplatin via organic cation transporter 2 and bioactivation via gamma-glutamyl transpeptidase located on the apical side of proximal tubular cells. Cisplatin affected several pathways including, p53 signalling, Nrf2 mediated oxidative stress response, mitochondrial processes, mTOR and AMPK signalling. In addition, we identified novel pathways changed by cisplatin, including eIF2 signalling, actin nucleation via the ARP/WASP complex and regulation of cell polarization. In conclusion, using an integrated omic approach together with biokinetics we have identified both novel and established mechanisms of cisplatin toxicity. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Metabolomics reveals metabolic changes in male reproductive cells exposed to thirdhand smoke

    Xu, Bo; Chen, Minjian; Yao, Mengmeng; Ji, Xiaoli; Mao, Zhilei; Tang, Wei; Qiao, Shanlei; Schick, Suzaynn F.; Mao, Jian-Hua; Hang, Bo; Xia, Yankai

    2015-10-01

    Thirdhand smoke (THS) is a new term for the toxins in cigarette smoke that linger in the environment long after the cigarettes are extinguished. The effects of THS exposure on male reproduction have not yet been studied. In this study, metabolic changes in male germ cell lines (GC-2 and TM-4) were analyzed after THS treatment for 24 h. THS-loaded chromatography paper samples were generated in a laboratory chamber system and extracted in DMEM. At a paper: DMEM ratio of 50 μg/ml, cell viability in both cell lines was normal, as measured by the MTT assay and markers of cytotoxicity, cell cycle, apoptosis and ROS production were normal as measured by quantitative immunofluorescence. Metabolomic analysis was performed on methanol extracts of GC-2 and TM-4 cells. Glutathione metabolism in GC-2 cells, and nucleic acid and ammonia metabolism in TM-4 cells, was changed significantly by THS treatment. RT-PCR analyses of mRNA for enzyme genes Gss and Ggt in GC-2 cells, and TK, SMS and Glna in TM-4 cells reinforced these findings, showing changes in the levels of enzymes involved in the relevant pathways. In conclusion, exposure to THS at very low concentrations caused distinct metabolic changes in two different types of male reproductive cell lines.

  5. Metabarcoding and metabolome analyses of copepod grazing reveal feeding preference and linkage to metabolite classes in dynamic microbial plankton communities.

    Ray, Jessica L; Althammer, Julia; Skaar, Katrine S; Simonelli, Paolo; Larsen, Aud; Stoecker, Diane; Sazhin, Andrey; Ijaz, Umer Z; Quince, Christopher; Nejstgaard, Jens C; Frischer, Marc; Pohnert, Georg; Troedsson, Christofer

    2016-11-01

    In order to characterize copepod feeding in relation to microbial plankton community dynamics, we combined metabarcoding and metabolome analyses during a 22-day seawater mesocosm experiment. Nutrient amendment of mesocosms promoted the development of haptophyte (Phaeocystis pouchetii)- and diatom (Skeletonema marinoi)-dominated plankton communities in mesocosms, in which Calanus sp. copepods were incubated for 24 h in flow-through chambers to allow access to prey particles (<500 μm). Copepods and mesocosm water sampled six times spanning the experiment were analysed using metabarcoding, while intracellular metabolite profiles of mesocosm plankton communities were generated for all experimental days. Taxon-specific metabarcoding ratios (ratio of consumed prey to available prey in the surrounding seawater) revealed diverse and dynamic copepod feeding selection, with positive selection on large diatoms, heterotrophic nanoflagellates and fungi, while smaller phytoplankton, including P. pouchetii, were passively consumed or even negatively selected according to our indicator. Our analysis of the relationship between Calanus grazing ratios and intracellular metabolite profiles indicates the importance of carbohydrates and lipids in plankton succession and copepod-prey interactions. This molecular characterization of Calanus sp. grazing therefore provides new evidence for selective feeding in mixed plankton assemblages and corroborates previous findings that copepod grazing may be coupled to the developmental and metabolic stage of the entire prey community rather than to individual prey abundances. © 2016 John Wiley & Sons Ltd.

  6. Fusarium oxysporum mediates systems metabolic reprogramming of chickpea roots as revealed by a combination of proteomics and metabolomics.

    Kumar, Yashwant; Zhang, Limin; Panigrahi, Priyabrata; Dholakia, Bhushan B; Dewangan, Veena; Chavan, Sachin G; Kunjir, Shrikant M; Wu, Xiangyu; Li, Ning; Rajmohanan, Pattuparambil R; Kadoo, Narendra Y; Giri, Ashok P; Tang, Huiru; Gupta, Vidya S

    2016-07-01

    Molecular changes elicited by plants in response to fungal attack and how this affects plant-pathogen interaction, including susceptibility or resistance, remain elusive. We studied the dynamics in root metabolism during compatible and incompatible interactions between chickpea and Fusarium oxysporum f. sp. ciceri (Foc), using quantitative label-free proteomics and NMR-based metabolomics. Results demonstrated differential expression of proteins and metabolites upon Foc inoculations in the resistant plants compared with the susceptible ones. Additionally, expression analysis of candidate genes supported the proteomic and metabolic variations in the chickpea roots upon Foc inoculation. In particular, we found that the resistant plants revealed significant increase in the carbon and nitrogen metabolism; generation of reactive oxygen species (ROS), lignification and phytoalexins. The levels of some of the pathogenesis-related proteins were significantly higher upon Foc inoculation in the resistant plant. Interestingly, results also exhibited the crucial role of altered Yang cycle, which contributed in different methylation reactions and unfolded protein response in the chickpea roots against Foc. Overall, the observed modulations in the metabolic flux as outcome of several orchestrated molecular events are determinant of plant's role in chickpea-Foc interactions. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  7. Metabolomic analysis using porcine skin: a pilot study of analytical techniques

    Wu, Julie; Fiehn, Oliver; Armstrong, April W

    2014-01-01

    Background: Metabolic byproducts serve as indicators of the chemical processes and can provide valuable information on pathogenesis by measuring the amplified output. Standardized techniques for metabolome extraction of skin samples serve as a critical foundation to this field but have not been developed. Objectives: We sought to determine the optimal cell lysage techniques for skin sample preparation and to compare GC-TOF-MS and UHPLC-QTOF-MS for metabolomic analysis. ...

  8. Metabolomics of pulmonary exacerbations reveals the personalized nature of cystic fibrosis disease

    Robert A. Quinn

    2016-08-01

    Full Text Available Background. Cystic fibrosis (CF is a genetic disease that results in chronic infections of the lungs. CF patients experience intermittent pulmonary exacerbations (CFPE that are associated with poor clinical outcomes. CFPE involves an increase in disease symptoms requiring more aggressive therapy. Methods. Longitudinal sputum samples were collected from 11 patients (n = 44 samples to assess the effect of exacerbations on the sputum metabolome using liquid chromatography-tandem mass spectrometry (LC-MS/MS. The data was analyzed with MS/MS molecular networking and multivariate statistics. Results. The individual patient source had a larger influence on the metabolome of sputum than the clinical state (exacerbation, treatment, post-treatment, or stable. Of the 4,369 metabolites detected, 12% were unique to CFPE samples; however, the only known metabolites significantly elevated at exacerbation across the dataset were platelet activating factor (PAF and a related monacylglycerophosphocholine lipid. Due to the personalized nature of the sputum metabolome, a single patient was followed for 4.2 years (capturing four separate exacerbation events as a case study for the detection of personalized biomarkers with metabolomics. PAF and related lipids were significantly elevated during CFPEs of this patient and ceramide was elevated during CFPE treatment. Correlating the abundance of bacterial 16S rRNA gene amplicons to metabolomics data from the same samples during a CFPE demonstrated that antibiotics were positively correlated to Stenotrophomonas and Pseudomonas, while ceramides and other lipids were correlated with Streptococcus, Rothia, and anaerobes. Conclusions. This study identified PAF and other inflammatory lipids as potential biomarkers of CFPE, but overall, the metabolome of CF sputum was patient specific, supporting a personalized approach to molecular detection of CFPE onset.

  9. Variable selection in the explorative analysis of several data blocks in metabolomics

    Karaman, İbrahim; Nørskov, Natalja; Yde, Christian Clement

    highly correlated data sets in one integrated approach. Due to the high number of variables in data sets from metabolomics (both raw data and after peak picking) the selection of important variables in an explorative analysis is difficult, especially when different data sets of metabolomics data need...... to be related. Tools for the handling of mental overflow minimising false discovery rates both by using statistical and biological validation in an integrative approach are needed. In this paper different strategies for variable selection were considered with respect to false discovery and the possibility...... for biological validation. The data set used in this study is metabolomics data from an animal intervention study. The aim of the metabolomics study was to investigate the metabolic profile in pigs fed various cereal fractions with special attention to the metabolism of lignans using NMR and LC-MS based...

  10. Dendrobium huoshanense polysaccharide prevents ethanol-induced liver injury in mice by metabolomic analysis.

    Wang, Xiao-Yu; Luo, Jian-Ping; Chen, Rui; Zha, Xue-Qiang; Pan, Li-Hua

    2015-01-01

    The prevalence of alcohol consumption has increased in modern dietary life and alcoholic liver injury can follow. Dendrobium huoshanense polysaccharide (DHP) is a homogeneous polysaccharide isolated from Dendrobium huoshanense, which possesses hepatoprotection function. In this study, we investigated the metabolic profiles of serum and liver tissues extracts from control, ethanol-treated and DHP\\ethanol-treated mice using a UHPLC/LTQ Orbitrap XL MS-based metabolomics approach. Our results indicated that DHP alleviated early steatosis and inflammation in liver histology and the metabolomic analysis of serum and hepatic tissue revealed that first, ethanol treatment mainly altered phosphatidylcholines (PCs) including PC (13:0) and phosphocholine, arachidonic acid metabolites including 20-ethyl PGF2α and amino acids including L-Proline; Second, DHP supplementation ameliorated the altered metabolic levels particularly involved in phosphocholine and L-Proline. These data suggested that DHP might restore the perturbed metabolism pathways by ethanol exposure to prevent the progression of alcoholic liver injury. Copyright © 2015 Elsevier B.V. All rights reserved.

  11. Global metabolomic profiling reveals an association of metal fume exposure and plasma unsaturated fatty acids.

    Yongyue Wei

    Full Text Available Welding-associated air pollutants negatively affect the health of exposed workers; however, their molecular mechanisms in causing disease remain largely unclear. Few studies have systematically investigated the systemic toxic effects of welding fumes on humans.To explore the effects of welding fumes on the plasma metabolome, and to identify biomarkers for risk assessment of welding fume exposure.The two-stage, self-controlled exploratory study included 11 boilermakers from a 2011 discovery panel and 8 boilermakers from a 2012 validation panel. Plasma samples were collected pre- and post-welding fume exposure and analyzed by chromatography/mass spectrometry.Eicosapentaenoic or docosapentaenoic acid metabolic changes post-welding were significantly associated with particulate (PM2.5 exposure (p<0.05. The combined analysis by linear mixed-effects model showed that exposure was associated with a statistically significant decline in metabolite change of eicosapentaenoic acid [β(95% CI = -0.013(-0.022 ≈ -0.004; p = 0.005], docosapentaenoic acid n3 [β(95% CI = -0.010(-0.018 ≈ -0.002; p = 0.017], and docosapentaenoic acid n6 [β(95% CI = -0.007(-0.013 ≈ -0.001; p = 0.021]. Pathway analysis identified an association of the unsaturated fatty acid pathway with exposure (p Study-2011 = 0.025; p Study-2012 = 0.021; p Combined = 0.009. The functional network built by these fatty acids and their interactive genes contained significant enrichment of genes associated with various diseases, including neoplasms, cardiovascular diseases, and lipid metabolism disorders.High-dose exposure of metal welding fumes decreases unsaturated fatty acids with an exposure-response relationship. This alteration in fatty acids is a potential biological mediator and biomarker for exposure-related health disorders.

  12. Metabolomics approach reveals metabolic disorders and potential biomarkers associated with the developmental toxicity of tetrabromobisphenol A and tetrachlorobisphenol A

    Ye, Guozhu; Chen, Yajie; Wang, Hong-Ou; Ye, Ting; Lin, Yi; Huang, Qiansheng; Chi, Yulang; Dong, Sijun

    2016-10-01

    Tetrabromobisphenol A and tetrachlorobisphenol A are halogenated bisphenol A (H-BPA), and has raised concerns about their adverse effects on the development of fetuses and infants, however, the molecular mechanisms are unclear, and related metabolomics studies are limited. Accordingly, a metabolomics study based on gas chromatography-mass spectrometry was employed to elucidate the molecular developmental toxicology of H-BPA using the marine medaka (Oryzias melastigmas) embryo model. Here, we revealed decreased synthesis of nucleosides, amino acids and lipids, and disruptions in the TCA (tricarboxylic acid) cycle, glycolysis and lipid metabolism, thus inhibiting the developmental processes of embryos exposed to H-BPA. Unexpectedly, we observed enhanced neural activity accompanied by lactate accumulation and accelerated heart rates due to an increase in dopamine pathway and a decrease in inhibitory neurotransmitters following H-BPA exposure. Notably, disorders of the neural system, and disruptions in glycolysis, the TCA cycle, nucleoside metabolism, lipid metabolism, glutamate and aspartate metabolism induced by H-BPA exposure were heritable. Furthermore, lactate and dopa were identified as potential biomarkers of the developmental toxicity of H-BPA and related genetic effects. This study has demonstrated that the metabolomics approach is a useful tool for obtaining comprehensive and novel insights into the molecular developmental toxicity of environmental pollutants.

  13. The Lipopolysaccharide-Induced Metabolome Signature in Arabidopsis thaliana Reveals Dynamic Reprogramming of Phytoalexin and Phytoanticipin Pathways

    Finnegan, Tarryn; Steenkamp, Paul A.; Piater, Lizelle A.

    2016-01-01

    Lipopolysaccharides (LPSs), as MAMP molecules, trigger the activation of signal transduction pathways involved in defence. Currently, plant metabolomics is providing new dimensions into understanding the intracellular adaptive responses to external stimuli. The effect of LPS on the metabolomes of Arabidopsis thaliana cells and leaf tissue was investigated over a 24 h period. Cellular metabolites and those secreted into the medium were extracted with methanol and liquid chromatography coupled to mass spectrometry was used for quantitative and qualitative analyses. Multivariate statistical data analyses were used to extract interpretable information from the generated multidimensional LC-MS data. The results show that LPS perception triggered differential changes in the metabolomes of cells and leaves, leading to variation in the biosynthesis of specialised secondary metabolites. Time-dependent changes in metabolite profiles were observed and biomarkers associated with the LPS-induced response were tentatively identified. These include the phytohormones salicylic acid and jasmonic acid, and also the associated methyl esters and sugar conjugates. The induced defensive state resulted in increases in indole—and other glucosinolates, indole derivatives, camalexin as well as cinnamic acid derivatives and other phenylpropanoids. These annotated metabolites indicate dynamic reprogramming of metabolic pathways that are functionally related towards creating an enhanced defensive capacity. The results reveal new insights into the mode of action of LPS as an activator of plant innate immunity, broadens knowledge about the defence metabolite pathways involved in Arabidopsis responses to LPS, and identifies specialised metabolites of functional importance that can be employed to enhance immunity against pathogen infection. PMID:27656890

  14. A Metabolome-Wide Study of Dry Eye Disease Reveals Serum Androgens as Biomarkers

    Vehof, Jelle; Hysi, Pirro G.; Hammond, Christopher J.

    Purpose: To test the association between serum metabolites and dry eye disease (DED) using a hypothesisfree metabolomics approach. Design: Cross-sectional association study. Participants: A total of 2819 subjects from the population-representative TwinsUK cohort in the United Kingdom, with a mean

  15. Mechanism of cisplatin proximal tubule toxicity revealed by integrating transcriptomics, proteomics, metabolomics and biokinetics

    Wilmes, Anja; Bielow, Chris; Ranninger, Christina; Bellwon, Patricia; Aschauer, Lydia; Limonciel, Alice; Chassaigne, Hubert; Kristl, Theresa; Aiche, Stephan; Huber, Christian G; Guillou, Claude; Hewitt, Philipp; Leonard, Martin O; Dekant, Wolfgang; Bois, Frederic Y; Jennings, Paul

    2015-01-01

    Cisplatin is one of the most widely used chemotherapeutic agents for the treatment of solid tumours. The major dose-limiting factor is nephrotoxicity, in particular in the proximal tubule. Here, we use an integrated omics approach, including transcriptomics, proteomics and metabolomics coupled to

  16. Metabolomic assessment reveals a stimulatory effect of calcium treatment on glucosinolates contents in broccoli microgreen

    Preharvest calcium application has been shown to increase broccoli microgreen yield and extend shelf life. Here we investigated the effect of calcium application on its metabolome using ultra high-performance liquid chromatography (UHPLC) tandem with mass spectrometry (HRMS). The data collected were...

  17. CE-MS-based metabolomics reveals the metabolic profile of maitake mushroom (Grifola frondosa) strains with different cultivation characteristics.

    Sato, Mayumi; Miyagi, Atsuko; Yoneyama, Shozo; Gisusi, Seiki; Tokuji, Yoshihiko; Kawai-Yamada, Maki

    2017-12-01

    Maitake mushroom (Grifola frondosa [Dicks.] Gray) is generally cultured using the sawdust of broadleaf trees. The maitake strain Gf433 has high production efficiency, with high-quality of fruiting bodies even when 30% of the birch sawdust on the basal substrate is replaced with conifer sawdust. We performed metabolome analysis to investigate the effect of different cultivation components on the metabolism of Gf433 and Mori52 by performing CE-MS on their fruiting bodies in different cultivation conditions to quantify the levels of amino acids, organic acids, and phosphorylated organic acids. We found that amino acid and organic acid content in Gf433 were not affected by the kind of sawdust. However, Gf433 contained more organic acids and less amino acids than Mori52, and Gf433 also contained more chitin compared with Mori52. We believe that these differences in the metabolome contents of the two strains are related to the high production efficiency of Gf433.

  18. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    Xia, Jianguo; Wishart, David S

    2016-09-07

    MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

  19. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production

    Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

    2015-01-01

    Objective The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a ‘Westernised’ lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Design and results Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Conclusions Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. PMID:25431456

  20. Comparative metabolomics in vegans and omnivores reveal constraints on diet-dependent gut microbiota metabolite production.

    Wu, Gary D; Compher, Charlene; Chen, Eric Z; Smith, Sarah A; Shah, Rachana D; Bittinger, Kyle; Chehoud, Christel; Albenberg, Lindsey G; Nessel, Lisa; Gilroy, Erin; Star, Julie; Weljie, Aalim M; Flint, Harry J; Metz, David C; Bennett, Michael J; Li, Hongzhe; Bushman, Frederic D; Lewis, James D

    2016-01-01

    The consumption of an agrarian diet is associated with a reduced risk for many diseases associated with a 'Westernised' lifestyle. Studies suggest that diet affects the gut microbiota, which subsequently influences the metabolome, thereby connecting diet, microbiota and health. However, the degree to which diet influences the composition of the gut microbiota is controversial. Murine models and studies comparing the gut microbiota in humans residing in agrarian versus Western societies suggest that the influence is large. To separate global environmental influences from dietary influences, we characterised the gut microbiota and the host metabolome of individuals consuming an agrarian diet in Western society. Using 16S rRNA-tagged sequencing as well as plasma and urinary metabolomic platforms, we compared measures of dietary intake, gut microbiota composition and the plasma metabolome between healthy human vegans and omnivores, sampled in an urban USA environment. Plasma metabolome of vegans differed markedly from omnivores but the gut microbiota was surprisingly similar. Unlike prior studies of individuals living in agrarian societies, higher consumption of fermentable substrate in vegans was not associated with higher levels of faecal short chain fatty acids, a finding confirmed in a 10-day controlled feeding experiment. Similarly, the proportion of vegans capable of producing equol, a soy-based gut microbiota metabolite, was less than that was reported in Asian societies despite the high consumption of soy-based products. Evidently, residence in globally distinct societies helps determine the composition of the gut microbiota that, in turn, influences the production of diet-dependent gut microbial metabolites. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  1. Untargeted Metabolomic Analysis of Capsicum spp. by GC-MS.

    Aranha, Bianca Camargo; Hoffmann, Jessica Fernanda; Barbieri, Rosa Lia; Rombaldi, Cesar Valmor; Chaves, Fábio Clasen

    2017-09-01

    In order to conserve the biodiversity of Capsicum species and find genotypes with potential to be utilised commercially, Embrapa Clima Temperado maintains an active germplasm collection (AGC) that requires characterisation, enabling genotype selection and support for breeding programmes. The objective of this study was to characterise pepper accessions from the Embrapa Clima Temperado AGC and differentiate species based on their metabolic profile using an untargeted metabolomics approach. Cold (-20°C) methanol extraction residue of freeze-dried fruit samples was partitioned into water/methanol (A) and chloroform (B) fractions. The polar fraction (A) was derivatised and both fractions (A and B) were analysed by gas chromatography coupled to mass spectrometry (GC-MS). Data from each fraction was analysed using a multivariate principal component analysis (PCA) with XCMS software. Amino acids, sugars, organic acids, capsaicinoids, and hydrocarbons were identified. Outlying accessions including P116 (C. chinense), P46, and P76 (C. annuum) were observed in a PCA plot mainly due to their high sucrose and fructose contents. PCA also indicated a separation of P221 (C. annuum) and P200 (C. chinense), because of their high dihydrocapsaicin content. Although the metabolic profiling did not allow for grouping by species, it permitted the simultaneous identification and quantification of several compounds complementing and expanding the metabolic database of the studied Capsicum spp. in the AGC. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  2. Integration of metabolomic and transcriptomic networks in pregnant women reveals biological pathways and predictive signatures associated with preeclampsia.

    Kelly, Rachel S; Croteau-Chonka, Damien C; Dahlin, Amber; Mirzakhani, Hooman; Wu, Ann C; Wan, Emily S; McGeachie, Michael J; Qiu, Weiliang; Sordillo, Joanne E; Al-Garawi, Amal; Gray, Kathryn J; McElrath, Thomas F; Carey, Vincent J; Clish, Clary B; Litonjua, Augusto A; Weiss, Scott T; Lasky-Su, Jessica A

    2017-01-01

    Preeclampsia is a leading cause of maternal and fetal mortality worldwide, yet its exact pathogenesis remains elusive. This study, nested within the Vitamin D Antenatal Asthma Reduction Trial (VDAART), aimed to develop integrated omics models of preeclampsia that have utility in both prediction and in the elucidation of underlying biological mechanisms. Metabolomic profiling was performed on first trimester plasma samples of 47 pregnant women from VDAART who subsequently developed preeclampsia and 62 controls with healthy pregnancies, using liquid-chromatography tandem mass-spectrometry. Metabolomic profiles were generated based on logistic regression models and assessed using Received Operator Characteristic Curve analysis. These profiles were compared to profiles from generated using third trimester samples. The first trimester metabolite profile was then integrated with a pre-existing transcriptomic profile using network methods. In total, 72 (0.9%) metabolite features were associated (pIntegration with the transcriptomic signature refined these results suggesting a particular role for lipid imbalance, immune function and the circulatory system. These findings suggest it is possible to develop a predictive metabolomic profile of preeclampsia. This profile is characterized by changes in lipid and amino acid metabolism and dysregulation of immune response and can be refined through interaction with transcriptomic data. However validation in larger and more diverse populations is required.

  3. A Metabolomic Perspective on Coeliac Disease

    Calabrò, Antonio

    2014-01-01

    Metabolomics is an “omic” science that is now emerging with the purpose of elaborating a comprehensive analysis of the metabolome, which is the complete set of metabolites (i.e., small molecules intermediates) in an organism, tissue, cell, or biofluid. In the past decade, metabolomics has already proved to be useful for the characterization of several pathological conditions and offers promises as a clinical tool. A metabolomics investigation of coeliac disease (CD) revealed that a metabolic fingerprint for CD can be defined, which accounts for three different but complementary components: malabsorption, energy metabolism, and alterations in gut microflora and/or intestinal permeability. In this review, we will discuss the major advancements in metabolomics of CD, in particular with respect to the role of gut microbiome and energy metabolism. PMID:24665364

  4. Targeted metabolomics reveals reduced levels of polyunsaturated choline plasmalogens and a smaller dimethylarginine/arginine ratio in the follicular fluid of patients with a diminished ovarian reserve.

    de la Barca, J M Chao; Boueilh, T; Simard, G; Boucret, L; Ferré-L'Hotellier, V; Tessier, L; Gadras, C; Bouet, P E; Descamps, P; Procaccio, V; Reynier, P; May-Panloup, P

    2017-11-01

    Does the metabolomic profile of the follicular fluid (FF) of patients with a diminished ovarian reserve (DOR) differ from that of patients with a normal ovarian reserve (NOR)? The metabolomic signature of the FF reveals a significant decrease in polyunsaturated choline plasmalogens and methyl arginine transferase activity in DOR patients compared to NOR patients. The composition of the FF reflects the exchanges between the oocyte and its microenvironment during its acquisition of gametic competence. Studies of the FF have allowed identification of biomarkers and metabolic pathways involved in various pathologies affecting oocyte quality, but no large metabolomic analysis in the context of ovarian ageing and DOR has been undertaken so far. This was an observational study of the FF retrieved from 57 women undergoing in vitro fertilization at the University Hospital of Angers, France, from November 2015 to September 2016. The women were classified in two groups: one including 28 DOR patients, and the other including 29 NOR patients, serving as controls. Patients were enrolled in the morning of oocyte retrieval after ovarian stimulation. Once the oocytes were isolated for fertilization and culture, the FF was pooled and centrifuged for analysis. A targeted quantitative metabolomic analysis was performed using high-performance liquid chromatography coupled with tandem mass spectrometry, and the Biocrates Absolute IDQ p180 kit. The FF levels of 188 metabolites and several sums and ratios of metabolic significance were assessed by multivariate and univariate analyses. A total of 136 metabolites were accurately quantified and used for calculating 23 sums and ratios. Samples were randomly divided into training and validation sets. The training set, allowed the construction of multivariate statistical models with a projection-supervised method, i.e. orthogonal partial least squares discriminant analysis (OPLS-DA), applied to the full set of metabolites, or the penalized

  5. Metabolic versatility in Haemophilus influenzae: a metabolomic and genomic analysis

    Dk Seti Maimonah Pg eOthman

    2014-03-01

    Full Text Available Haemophilus influenzae is a host adapted human pathogen known to contribute to a variety of acute and chronic diseases of the upper and lower respiratory tract as well as the middle ear. At the sites of infection as well as during growth as a commensal the environmental conditions encountered by H. influenzae will vary significantly, especially in terms of oxygen availability, however, the mechanisms by which the bacteria can adapt their metabolism to cope with such changes have not been studied in detail. Using targeted metabolomics the spectrum of metabolites produced during growth of H. influenzae on glucose in RPMI-based medium was found to change from acetate as the main product during aerobic growth to formate as the major product during anaerobic growth. This is likely caused by a switch in the major pyruvate degrading route. Neither lactate nor succinate or fumarate were major products of H. influenzae growth under any condition studied Gene expression studies and enzyme activity data revealed that despite an identical genetic makeup and very similar metabolite production profiles, H. influenzae strain Rd appeared to favour glucose degradation via the PPP, while strain 2019, a clinical isolate, showed higher expression of enzymes involved in glycolysis. Components of the respiratory chain were most highly expressed during microaerophilic and anaerobic growth in both strains, but again clear differences existed in the expression of genes associated e.g. with NADH oxidation, nitrate and nitrite reduction in the two strains studied.Together our results indicate that H. influenzae uses a specialized type of metabolism that could be termed ‘respiration assisted fermentation’ where the respiratory chain likely serves to alleviate redox imbalances caused by incomplete glucose oxidation, and at the same time provides a means of converting a variety of compounds including nitrite and nitrate that arise as part of the host defence mechanisms.

  6. Effects of Perfluorooctanoic Acid on Metabolic Profiles in Brain and Liver of Mouse Revealed by a High-throughput Targeted Metabolomics Approach

    Yu, Nanyang; Wei, Si; Li, Meiying; Yang, Jingping; Li, Kan; Jin, Ling; Xie, Yuwei; Giesy, John P.; Zhang, Xiaowei; Yu, Hongxia

    2016-04-01

    Perfluorooctanoic acid (PFOA), a perfluoroalkyl acid, can result in hepatotoxicity and neurobehavioral effects in animals. The metabolome, which serves as a connection among transcriptome, proteome and toxic effects, provides pathway-based insights into effects of PFOA. Since understanding of changes in the metabolic profile during hepatotoxicity and neurotoxicity were still incomplete, a high-throughput targeted metabolomics approach (278 metabolites) was used to investigate effects of exposure to PFOA for 28 d on brain and liver of male Balb/c mice. Results of multivariate statistical analysis indicated that PFOA caused alterations in metabolic pathways in exposed individuals. Pathway analysis suggested that PFOA affected metabolism of amino acids, lipids, carbohydrates and energetics. Ten and 18 metabolites were identified as potential unique biomarkers of exposure to PFOA in brain and liver, respectively. In brain, PFOA affected concentrations of neurotransmitters, including serotonin, dopamine, norepinephrine, and glutamate in brain, which provides novel insights into mechanisms of PFOA-induced neurobehavioral effects. In liver, profiles of lipids revealed involvement of β-oxidation and biosynthesis of saturated and unsaturated fatty acids in PFOA-induced hepatotoxicity, while alterations in metabolism of arachidonic acid suggesting potential of PFOA to cause inflammation response in liver. These results provide insight into the mechanism and biomarkers for PFOA-induced effects.

  7. NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma

    Rocha, CM; Barros, AS; Goodfellow, BJ; Carreira, IM; Gomes, AA; Sousa, V; Bernardo, J; Carvalho, L; Gil, AM; Duarte, IF

    2015-01-01

    Lung tumour subtyping, particularly the distinction between adenocarcinoma (AdC) and squamous cell carcinoma (SqCC), is a critical diagnostic requirement. In this work, the metabolic signatures of lung carcinomas were investigated through (1)H NMR metabolomics, with a view to provide additional criteria for improved diagnosis and treatment planning. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (NMR) spectroscopy was used to analyse matched tumour and adjacent control tissue...

  8. A pilot study of the effect of human breast milk on urinary metabolome analysis in infants.

    Shoji, Hiromichi; Taka, Hikari; Kaga, Naoko; Ikeda, Naho; Kitamura, Tomohiro; Miura, Yoshiki; Shimizu, Toshiaki

    2017-08-28

    This study aimed to examine the nutritional effect of breast feeding on healthy term infants by using urinary metabolome analysis. Urine samples were collected from 19 and 14 infants at 1 and 6 months, respectively. Infants were separated into two groups: the breast-fed group receiving metabolome analysis was performed using capillary electrophoresis-time-of-flight mass spectrometry (CE-TOF/MS). A total of 29 metabolites were detected by CE-TOF/MS metabolome analysis in all samples. Urinary excretion of choline metabolites (choline base solution, N,N-dimethylglycine, sarcosine, and betaine) at 1 month were significantly (pmetabolome analysis by the CE-TOF/MS method is useful for assessing nutritional metabolism in infants.

  9. Metabolomic and proteomic analysis of D-lactate-producing Lactobacillus delbrueckii under various fermentation conditions.

    Liang, Shaoxiong; Gao, Dacheng; Liu, Huanhuan; Wang, Cheng; Wen, Jianping

    2018-05-28

    As an important feedstock monomer for the production of biodegradable stereo-complex poly-lactic acid polymer, D-lactate has attracted much attention. To improve D-lactate production by microorganisms such as Lactobacillus delbrueckii, various fermentation conditions were performed, such as the employment of anaerobic fermentation, the utilization of more suitable neutralizing agents, and exploitation of alternative nitrogen sources. The highest D-lactate titer could reach 133 g/L under the optimally combined fermentation condition, increased by 70.5% compared with the control. To decipher the potential mechanisms of D-lactate overproduction, the time-series response of intracellular metabolism to different fermentation conditions was investigated by GC-MS and LC-MS/MS-based metabolomic analysis. Then the metabolomic datasets were subjected to weighted correlation network analysis (WGCNA), and nine distinct metabolic modules and eight hub metabolites were identified to be specifically associated with D-lactate production. Moreover, a quantitative iTRAQ-LC-MS/MS proteomic approach was employed to further analyze the change of intracellular metabolism under the combined fermentation condition, identifying 97 up-regulated and 42 down-regulated proteins compared with the control. The in-depth analysis elucidated how the key factors exerted influence on D-lactate biosynthesis. The results revealed that glycolysis and pentose phosphate pathways, transport of glucose, amino acids and peptides, amino acid metabolism, peptide hydrolysis, synthesis of nucleotides and proteins, and cell division were all strengthened, while ATP consumption for exporting proton, cell damage, metabolic burden caused by stress response, and bypass of pyruvate were decreased under the combined condition. These might be the main reasons for significantly improved D-lactate production. These findings provide the first omics view of cell growth and D-lactate overproduction in L. delbrueckii, which

  10. MetabR: an R script for linear model analysis of quantitative metabolomic data

    Ernest Ben

    2012-10-01

    Full Text Available Abstract Background Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data. Findings Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program. Conclusions We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

  11. The Lipopolysaccharide-Induced Metabolome Signature in Arabidopsis thaliana Reveals Dynamic Reprogramming of Phytoalexin and Phytoanticipin Pathways.

    Tarryn Finnegan

    Full Text Available Lipopolysaccharides (LPSs, as MAMP molecules, trigger the activation of signal transduction pathways involved in defence. Currently, plant metabolomics is providing new dimensions into understanding the intracellular adaptive responses to external stimuli. The effect of LPS on the metabolomes of Arabidopsis thaliana cells and leaf tissue was investigated over a 24 h period. Cellular metabolites and those secreted into the medium were extracted with methanol and liquid chromatography coupled to mass spectrometry was used for quantitative and qualitative analyses. Multivariate statistical data analyses were used to extract interpretable information from the generated multidimensional LC-MS data. The results show that LPS perception triggered differential changes in the metabolomes of cells and leaves, leading to variation in the biosynthesis of specialised secondary metabolites. Time-dependent changes in metabolite profiles were observed and biomarkers associated with the LPS-induced response were tentatively identified. These include the phytohormones salicylic acid and jasmonic acid, and also the associated methyl esters and sugar conjugates. The induced defensive state resulted in increases in indole-and other glucosinolates, indole derivatives, camalexin as well as cinnamic acid derivatives and other phenylpropanoids. These annotated metabolites indicate dynamic reprogramming of metabolic pathways that are functionally related towards creating an enhanced defensive capacity. The results reveal new insights into the mode of action of LPS as an activator of plant innate immunity, broadens knowledge about the defence metabolite pathways involved in Arabidopsis responses to LPS, and identifies specialised metabolites of functional importance that can be employed to enhance immunity against pathogen infection.

  12. Comprehensive transcriptome analyses correlated with untargeted metabolome reveal differentially expressed pathways in response to cell wall alterations.

    Reem, Nathan T; Chen, Han-Yi; Hur, Manhoi; Zhao, Xuefeng; Wurtele, Eve Syrkin; Li, Xu; Li, Ling; Zabotina, Olga

    2018-03-01

    This research provides new insights into plant response to cell wall perturbations through correlation of transcriptome and metabolome datasets obtained from transgenic plants expressing cell wall-modifying enzymes. Plants respond to changes in their cell walls in order to protect themselves from pathogens and other stresses. Cell wall modifications in Arabidopsis thaliana have profound effects on gene expression and defense response, but the cell signaling mechanisms underlying these responses are not well understood. Three transgenic Arabidopsis lines, two with reduced cell wall acetylation (AnAXE and AnRAE) and one with reduced feruloylation (AnFAE), were used in this study to investigate the plant responses to cell wall modifications. RNA-Seq in combination with untargeted metabolome was employed to assess differential gene expression and metabolite abundance. RNA-Seq results were correlated with metabolite abundances to determine the pathways involved in response to cell wall modifications introduced in each line. The resulting pathway enrichments revealed the deacetylation events in AnAXE and AnRAE plants induced similar responses, notably, upregulation of aromatic amino acid biosynthesis and changes in regulation of primary metabolic pathways that supply substrates to specialized metabolism, particularly those related to defense responses. In contrast, genes and metabolites of lipid biosynthetic pathways and peroxidases involved in lignin polymerization were downregulated in AnFAE plants. These results elucidate how primary metabolism responds to extracellular stimuli. Combining the transcriptomics and metabolomics datasets increased the power of pathway prediction, and demonstrated the complexity of pathways involved in cell wall-mediated signaling.

  13. A functional genomics approach using metabolomics and in silico pathway analysis

    Förster, Jochen; Gombert, Andreas Karoly; Nielsen, Jens

    2002-01-01

    analysis techniques and changes in the genotype will in many cases lead to different metabolite profiles. Here, a theoretical framework that may be applied to identify the function of orphan genes is presented. The approach is based on a combination of metabolome analysis combined with in silico pathway...

  14. An R package for the integrated analysis of metabolomics and spectral data.

    Costa, Christopher; Maraschin, Marcelo; Rocha, Miguel

    2016-06-01

    Recently, there has been a growing interest in the field of metabolomics, materialized by a remarkable growth in experimental techniques, available data and related biological applications. Indeed, techniques as nuclear magnetic resonance, gas or liquid chromatography, mass spectrometry, infrared and UV-visible spectroscopies have provided extensive datasets that can help in tasks as biological and biomedical discovery, biotechnology and drug development. However, as it happens with other omics data, the analysis of metabolomics datasets provides multiple challenges, both in terms of methodologies and in the development of appropriate computational tools. Indeed, from the available software tools, none addresses the multiplicity of existing techniques and data analysis tasks. In this work, we make available a novel R package, named specmine, which provides a set of methods for metabolomics data analysis, including data loading in different formats, pre-processing, metabolite identification, univariate and multivariate data analysis, machine learning, and feature selection. Importantly, the implemented methods provide adequate support for the analysis of data from diverse experimental techniques, integrating a large set of functions from several R packages in a powerful, yet simple to use environment. The package, already available in CRAN, is accompanied by a web site where users can deposit datasets, scripts and analysis reports to be shared with the community, promoting the efficient sharing of metabolomics data analysis pipelines. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. Transcriptome and metabolome of synthetic Solanum autotetraploids reveal key genomic stress events following polyploidization.

    Fasano, Carlo; Diretto, Gianfranco; Aversano, Riccardo; D'Agostino, Nunzio; Di Matteo, Antonio; Frusciante, Luigi; Giuliano, Giovanni; Carputo, Domenico

    2016-06-01

    Polyploids are generally classified as autopolyploids, derived from a single species, and allopolyploids, arising from interspecific hybridization. The former represent ideal materials with which to study the consequences of genome doubling and ascertain whether there are molecular and functional rules operating following polyploidization events. To investigate whether the effects of autopolyploidization are common to different species, or if species-specific or stochastic events are prevalent, we performed a comprehensive transcriptomic and metabolomic characterization of diploids and autotetraploids of Solanum commersonii and Solanum bulbocastanum. Autopolyploidization remodelled the transcriptome and the metabolome of both species. In S. commersonii, differentially expressed genes (DEGs) were highly enriched in pericentromeric regions. Most changes were stochastic, suggesting a strong genotypic response. However, a set of robustly regulated transcripts and metabolites was also detected, including purine bases and nucleosides, which are likely to underlie a common response to polyploidization. We hypothesize that autopolyploidization results in nucleotide pool imbalance, which in turn triggers a genomic shock responsible for the stochastic events observed. The more extensive genomic stress and the higher number of stochastic events observed in S. commersonii with respect to S. bulbocastanum could be the result of the higher nucleoside depletion observed in this species. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

  16. Metabolomics for laboratory diagnostics.

    Bujak, Renata; Struck-Lewicka, Wiktoria; Markuszewski, Michał J; Kaliszan, Roman

    2015-09-10

    Metabolomics is an emerging approach in a systems biology field. Due to continuous development in advanced analytical techniques and in bioinformatics, metabolomics has been extensively applied as a novel, holistic diagnostic tool in clinical and biomedical studies. Metabolome's measurement, as a chemical reflection of a current phenotype of a particular biological system, is nowadays frequently implemented to understand pathophysiological processes involved in disease progression as well as to search for new diagnostic or prognostic biomarkers of various organism's disorders. In this review, we discussed the research strategies and analytical platforms commonly applied in the metabolomics studies. The applications of the metabolomics in laboratory diagnostics in the last 5 years were also reviewed according to the type of biological sample used in the metabolome's analysis. We also discussed some limitations and further improvements which should be considered taking in mind potential applications of metabolomic research and practice. Copyright © 2014 Elsevier B.V. All rights reserved.

  17. Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

    Kümmel, Anne; Panke, Sven; Heinemann, Matthias

    2006-01-01

    As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic

  18. Differential metabolome analysis of field-grown maize kernels in response to drought stress

    Drought stress constrains maize kernel development and can exacerbate aflatoxin contamination. In order to identify drought responsive metabolites and explore pathways involved in kernel responses, a metabolomics analysis was conducted on kernels from a drought tolerant line, Lo964, and a sensitive ...

  19. Comparative transcriptomic and metabolomic analysis of fenofibrate and fish oil treatments in mice

    Lu, Y.; Boekschoten, M.V.; Wopereis, S.; Muller, M.R.; Kersten, A.H.

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 wk

  20. Comparative transcriptomics and metabolomic analysis of fenofibrate and fish oil treatments in mice

    Lu Yingchang (Kevin), Y.; Boekschoten, Mark; Wopereis, Suzan; Muller, Michael; Kersten, Sander

    2011-01-01

    Elevated circulating triglycerides, which are considered a risk factor for cardiovascular disease, can be targeted by treatment with fenofibrate or fish oil. To gain insight into underlying mechanisms, we carried out a comparative transcriptomics and metabolomics analysis of the effect of 2 week

  1. Metabolomics reveals impaired maturation of HDL particles in adolescents with hyperinsulinaemic androgen excess.

    Samino, Sara; Vinaixa, Maria; Díaz, Marta; Beltran, Antoni; Rodríguez, Miguel A; Mallol, Roger; Heras, Mercedes; Cabre, Anna; Garcia, Lorena; Canela, Nuria; de Zegher, Francis; Correig, Xavier; Ibáñez, Lourdes; Yanes, Oscar

    2015-06-23

    Hyperinsulinaemic androgen excess (HIAE) in prepubertal and pubertal girls usually precedes a broader pathological phenotype in adulthood that is associated with anovulatory infertility, metabolic syndrome and type 2 diabetes. The metabolic derangements that determine these long-term health risks remain to be clarified. Here we use NMR and MS-based metabolomics to show that serum levels of methionine sulfoxide in HIAE girls are an indicator of the degree of oxidation of methionine-148 residue in apolipoprotein-A1. Oxidation of apo-A1 in methionine-148, in turn, leads to an impaired maturation of high-density lipoproteins (HDL) that is reflected in a decline of large HDL particles. Notably, such metabolic alterations occur in the absence of impaired glucose tolerance, hyperglycemia and hypertriglyceridemia, and were partially restored after 18 months of treatment with a low-dose combination of pioglitazone, metformin and flutamide.

  2. Metabolomic and Genome-wide Association Studies Reveal Potential Endogenous Biomarkers for OATP1B1.

    Yee, S W; Giacomini, M M; Hsueh, C-H; Weitz, D; Liang, X; Goswami, S; Kinchen, J M; Coelho, A; Zur, A A; Mertsch, K; Brian, W; Kroetz, D L; Giacomini, K M

    2016-11-01

    Transporter-mediated drug-drug interactions (DDIs) are a major cause of drug toxicities. Using published genome-wide association studies (GWAS) of the human metabolome, we identified 20 metabolites associated with genetic variants in organic anion transporter, OATP1B1 (P acids and fatty acid dicarboxylates were among the metabolites discovered using both GWAS and CSA administration. In vitro studies confirmed tetradecanedioate (TDA) and hexadecanedioate (HDA) were novel substrates of OATP1B1 as well as OAT1 and OAT3. This study highlights the use of multiple datasets for the discovery of endogenous metabolites that represent potential in vivo biomarkers for transporter-mediated DDIs. Future studies are needed to determine whether these metabolites can serve as qualified biomarkers for organic anion transporters. Quantitative relationships between metabolite levels and modulation of transporters should be established. © 2016 American Society for Clinical Pharmacology and Therapeutics.

  3. Analysis of metabolomic data: tools, current strategies and future challenges for omics data integration.

    Cambiaghi, Alice; Ferrario, Manuela; Masseroli, Marco

    2017-05-01

    Metabolomics is a rapidly growing field consisting of the analysis of a large number of metabolites at a system scale. The two major goals of metabolomics are the identification of the metabolites characterizing each organism state and the measurement of their dynamics under different situations (e.g. pathological conditions, environmental factors). Knowledge about metabolites is crucial for the understanding of most cellular phenomena, but this information alone is not sufficient to gain a comprehensive view of all the biological processes involved. Integrated approaches combining metabolomics with transcriptomics and proteomics are thus required to obtain much deeper insights than any of these techniques alone. Although this information is available, multilevel integration of different 'omics' data is still a challenge. The handling, processing, analysis and integration of these data require specialized mathematical, statistical and bioinformatics tools, and several technical problems hampering a rapid progress in the field exist. Here, we review four main tools for number of users or provided features (MetaCoreTM, MetaboAnalyst, InCroMAP and 3Omics) out of the several available for metabolomic data analysis and integration with other 'omics' data, highlighting their strong and weak aspects; a number of related issues affecting data analysis and integration are also identified and discussed. Overall, we provide an objective description of how some of the main currently available software packages work, which may help the experimental practitioner in the choice of a robust pipeline for metabolomic data analysis and integration. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  4. Mass spectrometry data of metabolomics analysis of Nepenthes pitchers

    Muhammad Aqil Fitri Rosli

    2017-10-01

    Full Text Available Hybridisation plays a significant role in the evolution and diversification of plants. Hybridisation among Nepenthes species is extensive, either naturally or man-made. To investigate the effects of hybridisation on the chemical compositions, we carried out metabolomics study on pitcher tissue of Nepenthes ampullaria, Nepenthes rafflesiana and their hybrid, Nepenthes × hookeriana. Pitcher samples were harvested and extracted in methanol:chloroform:water via sonication-assisted extraction before analysed using LC-TOF-MS. MS data were analysed using XCMS online version 2.2.5. This is the first MS data report towards the profiling, identification and comprehensive comparison of metabolites present in Nepenthes species.

  5. Targeted Metabolomics Reveals Early Dominant Optic Atrophy Signature in Optic Nerves of Opa1delTTAG/+ Mice.

    Chao de la Barca, Juan Manuel; Simard, Gilles; Sarzi, Emmanuelle; Chaumette, Tanguy; Rousseau, Guillaume; Chupin, Stéphanie; Gadras, Cédric; Tessier, Lydie; Ferré, Marc; Chevrollier, Arnaud; Desquiret-Dumas, Valérie; Gueguen, Naïg; Leruez, Stéphanie; Verny, Christophe; Miléa, Dan; Bonneau, Dominique; Amati-Bonneau, Patrizia; Procaccio, Vincent; Hamel, Christian; Lenaers, Guy; Reynier, Pascal; Prunier-Mirebeau, Delphine

    2017-02-01

    Dominant optic atrophy (MIM No. 165500) is a blinding condition related to mutations in OPA1, a gene encoding a large GTPase involved in mitochondrial inner membrane dynamics. Although several mouse models mimicking the disease have been developed, the pathophysiological mechanisms responsible for retinal ganglion cell degeneration remain poorly understood. Using a targeted metabolomic approach, we measured the concentrations of 188 metabolites in nine tissues, that is, brain, three types of skeletal muscle, heart, liver, retina, optic nerve, and plasma in symptomatic 11-month-old Opa1delTTAG/+ mice. Significant metabolic signatures were found only in the optic nerve and plasma of female mice. The optic nerve signature was characterized by altered concentrations of phospholipids, amino acids, acylcarnitines, and carnosine, whereas the plasma signature showed decreased concentrations of amino acids and sarcosine associated with increased concentrations of several phospholipids. In contrast, the investigation of 3-month-old presymptomatic Opa1delTTAG/+ mice showed no specific plasma signature but revealed a significant optic nerve signature in both sexes, although with a sex effect. The Opa1delTTAG/+ versus wild-type optic nerve signature was characterized by the decreased concentrations of 10 sphingomyelins and 10 lysophosphatidylcholines, suggestive of myelin sheath alteration, and by alteration in the concentrations of metabolites involved in neuroprotection, such as dimethylarginine, carnitine, spermine, spermidine, carnosine, and glutamate, suggesting a concomitant axonal metabolic dysfunction. Our comprehensive metabolomic investigations revealed in symptomatic as well as in presymptomatic Opa1delTTAG/+ mice, a specific sensitiveness of the optic nerve to Opa1 insufficiency, opening new routes for protective therapeutic strategies.

  6. Non-invasive metabolomic analysis using a commercial NIR instrument for embryo selection

    Ioannis A Sfontouris

    2013-01-01

    Full Text Available Context: Metabolomics was introduced in human in vitro fertilization (IVF for noninvasive identification of viable embryos with the highest developmental competence. Aims: To determine whether embryo selection using a commercial version of metabolomic analysis leads to increased implantation rates (IRs with fetal cardiac activity (FCA compared with morphology evaluation alone. Setting and Design: Randomized controlled trial from April to December 2010 at a private IVF unit. The study was terminated prematurely due to the market withdrawal of the instrument. Materials and Methods: IVF patients ≥18 and ≤43 years with ≥4 × 2PN were randomly allocated to metabolomic analysis combined with embryo morphology (ViaMetrics-E; metabolomics + morphology group or embryo morphology alone (morphology group. Cycles with frozen embryos, oocyte donations, or testicular biopsy were excluded. Statistical Analysis: Categorical and continuous data were analyzed for statistical significance using 2-tailed Fisher′s exact test and t-test, respectively. Statistical significance was accepted when P < 0.05. Results: A total of 125 patients were included in the study; 39 patients were allocated to metabolomics + morphology group and 86 patients to morphology group. Patients were stratified according to the day of embryo transfer (Days 2, 3, or 5. IRs with FCA were similar for Days 2 and 3 transfers in both groups. For Day 5 transfers, IRs with FCA were significantly higher in the metabolomics + morphology group (46.8% vs. 28.9%; P = 0.041; 95% confidence intervalp [CI]: 1.09-34.18. Pregnancy and live births rates were similar for Days 2, 3, and 5 in both groups. The study was terminated early following the voluntary market withdrawal of ViaMetrics-E in December 2010. Conclusions: Metabolomic analysis using the commercial near-infrared (NIR instrument does not appear to have a beneficial effect on pregnancy and live births, with improvement in IR with FCA for Day 5

  7. Metabolomic Analysis of Complex Chinese Remedies: Examples of Induced Nephrotoxicity in the Mouse from a Series of Remedies Containing Aristolochic Acid

    Dong-Ming Tsai

    2013-01-01

    Full Text Available Aristolochic acid nephropathy is caused by aristolochic acid (AA and AA-containing herbs. In traditional Chinese medicine, a principle called “Jun-Chen-Zou-Shi” may be utilized to construct a remedial herbal formula that attempts to mitigate the toxicity of the main ingredient. This study used Bu-Fei-A-Jiao-Tang (BFAJT to test if the compound remedy based on a principle of “Jun-Chen-Zou-Shi” can decrease the toxicity of AA-containing herbs. We compared the three toxicities of AA standard, Madouling (an Aristolochia herb, and a herbal formula BFAJT. AA standard was given for BALB/c mice at a dose of 5 mg/kg bw/day or 7.5 mg/kg bw/day for 10 days. Madouling and BFAJT were given at an equivalence of AA 0.5 mg/kg bw/day for 21 days. Nephrotoxicity was evaluated by metabolomics and histopathology. The urinary metabolomics profiles were characterized by 1H NMR spectroscopy. The spectral data was analyzed with partial least squares discriminant analysis, and the significant differential metabolites between groups were identified. The result showed different degrees of acute renal tubular injuries, and metabolomics analysis found that the kidney injuries were focused in proximal renal tubules. Both metabolomics and pathological studies revealed that AA standard, Madouling, and BFAJT were all nephrotoxicants. The compositions of the compound remedy did not diminish the nephrotoxicity caused by AA.

  8. Metabolomic Studies in Drosophila.

    Cox, James E; Thummel, Carl S; Tennessen, Jason M

    2017-07-01

    Metabolomic analysis provides a powerful new tool for studies of Drosophila physiology. This approach allows investigators to detect thousands of chemical compounds in a single sample, representing the combined contributions of gene expression, enzyme activity, and environmental context. Metabolomics has been used for a wide range of studies in Drosophila , often providing new insights into gene function and metabolic state that could not be obtained using any other approach. In this review, we survey the uses of metabolomic analysis since its entry into the field. We also cover the major methods used for metabolomic studies in Drosophila and highlight new directions for future research. Copyright © 2017 by the Genetics Society of America.

  9. Metabolomic and elemental analysis of camel and bovine urine by GC-MS and ICP-MS.

    Ahamad, Syed Rizwan; Alhaider, Abdul Qader; Raish, Mohammad; Shakeel, Faiyaz

    2017-01-01

    Recent studies from the author's laboratory indicated that camel urine possesses antiplatelet activity and anti-cancer activity which is not present in bovine urine. The objective of this study is to compare the volatile and elemental components of bovine and camel urine using GC-MS and ICP-MS analysis. We are interested to know the component that performs these biological activities. The freeze dried urine was dissolved in dichloromethane and then derivatization process followed by using BSTFA for GC-MS analysis. Thirty different compounds were analyzed by the derivatization process in full scan mode. For ICP-MS analysis twenty eight important elements were analyzed in both bovine and camel urine. The results of GC-MS and ICP-MS analysis showed marked difference in the urinary metabolites. GC-MS evaluation of camel urine finds a lot of products of metabolism like benzene propanoic acid derivatives, fatty acid derivatives, amino acid derivatives, sugars, prostaglandins and canavanine. Several research reports reveal the metabolomics studies on camel urine but none of them completely reported the pharmacology related metabolomics. The present data of GC-MS suggest and support the previous studies and activities related to camel urine.

  10. Exploratory Metabolomic Analyses Reveal Compounds Correlated with Lutein Concentration in Frontal Cortex, Hippocampus, and Occipital Cortex of Human Infant Brain.

    Jacqueline C Lieblein-Boff

    Full Text Available Lutein is a dietary carotenoid well known for its role as an antioxidant in the macula, and recent reports implicate a role for lutein in cognitive function. Lutein is the dominant carotenoid in both pediatric and geriatric brain tissue. In addition, cognitive function in older adults correlated with macular and postmortem brain lutein concentrations. Furthermore, lutein was found to preferentially accumulate in the infant brain in comparison to other carotenoids that are predominant in diet. While lutein is consistently related to cognitive function, the mechanisms by which lutein may influence cognition are not clear. In an effort to identify potential mechanisms through which lutein might influence neurodevelopment, an exploratory study relating metabolite signatures and lutein was completed. Post-mortem metabolomic analyses were performed on human infant brain tissues in three regions important for learning and memory: the frontal cortex, hippocampus, and occipital cortex. Metabolomic profiles were compared to lutein concentration, and correlations were identified and reported here. A total of 1276 correlations were carried out across all brain regions. Of 427 metabolites analyzed, 257 were metabolites of known identity. Unidentified metabolite correlations (510 were excluded. In addition, moderate correlations with xenobiotic relationships (2 or those driven by single outliers (3 were excluded from further study. Lutein concentrations correlated with lipid pathway metabolites, energy pathway metabolites, brain osmolytes, amino acid neurotransmitters, and the antioxidant homocarnosine. These correlations were often brain region-specific. Revealing relationships between lutein and metabolic pathways may help identify potential candidates on which to complete further analyses and may shed light on important roles of lutein in the human brain during development.

  11. Benznidazole biotransformation and multiple targets in Trypanosoma cruzi revealed by metabolomics.

    Andrea Trochine

    2014-05-01

    Full Text Available The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, involves administration of benznidazole (Bzn. Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active, although its mode of action is not fully understood. In the present work we used a non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols trypanothione, homotrypanothione and cysteine were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment. These metabolites included reduction products, fragments and covalent adducts of reduced Bzn linked to each of the major low molecular weight thiols: trypanothione, glutathione, γ-glutamylcysteine, glutathionylspermidine, cysteine and ovothiol A. Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI, were found within the parasites, but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.Our data is indicative of a major role of the thiol binding capacity of Bzn reduction products in the mechanism of Bzn toxicity against T. cruzi.

  12. Metabolomics reveals biotic and abiotic elicitor effects on the soft coral Sarcophyton ehrenbergi terpenoid content.

    Farag, Mohamed A; Al-Mahdy, Dalia A; Meyer, Achim; Westphal, Hildegard; Wessjohann, Ludger A

    2017-04-05

    The effects of six biotic and abiotic elicitors, i.e. MeJA (methyl jasmonate), SA (salicylic acid), ZnCl 2 , glutathione and β-glucan BG (fungal elicitor), and wounding, on the secondary metabolite accumulation in the soft coral Sarcophyton ehrenbergi were assessed. Upon elicitation, metabolites were extracted and analysed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Except for MeJA, no differences in photosynthetic efficiency were observed after treatments, suggesting the absence of a remarkable stress on primary production. Chemometric analyses of UPLC-MS data showed clear segregation of SA and ZnCl 2 elicited samples at 24 and 48 h post elicitation. Levels of acetylated diterpene and sterol viz., sarcophytonolide I and cholesteryl acetate, was increased in ZnCl 2 and SA groups, respectively, suggesting an activation of specific acetyl transferases. Post elicitation, sarcophytonolide I level increased 132 and 17-folds at 48 h in 0.1 mM SA and 1 mM ZnCl 2 groups, respectively. Interestingly, decrease in sarcophine, a major diterpene was observed only in response to ZnCl 2 , whereas no change was observed in sesquiterpene content following treatments. To the best of our knowledge, this study provides the first documentation for elicitation effects on a soft corals secondary metabolome and suggests that SA could be applied to increase diterpenoid levels in corals.

  13. Neurochemical metabolomics reveals disruption to sphingolipid metabolism following chronic haloperidol administration

    McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Crowley, James J.; Vann, Robert E.; Beardsley, Patrick M.; van den Oord, Edwin J.

    2015-01-01

    Haloperidol is an effective antipsychotic drug for treatment of schizophrenia, but prolonged use can lead to debilitating side effects. To better understand the effects of long-term administration, we measured global metabolic changes in mouse brain following 3 mg/kg/day haloperidol for 28 days. These conditions lead to movement-related side effects in mice akin to those observed in patients after prolonged use. Brain tissue was collected following microwave tissue fixation to arrest metabolism and extracted metabolites were assessed using both liquid and gas chromatography mass spectrometry (MS). Over 300 unique compounds were identified across MS platforms. Haloperidol was found to be present in all test samples and not in controls, indicating experimental validity. Twenty-one compounds differed significantly between test and control groups at the p haloperidol-treated mice (p = 0.004), a marker previously associated with demyelination. This study further demonstrates the utility of murine neurochemical metabolomics as a method to advance understanding of CNS drug effects. PMID:25850894

  14. Comparative metabolomics in primates reveals the effects of diet and gene regulatory variation on metabolic divergence.

    Blekhman, Ran; Perry, George H; Shahbaz, Sevini; Fiehn, Oliver; Clark, Andrew G; Gilad, Yoav

    2014-07-28

    Human diets differ from those of non-human primates. Among few obvious differences, humans consume more meat than most non-human primates and regularly cook their food. It is hypothesized that a dietary shift during human evolution has been accompanied by molecular adaptations in metabolic pathways. Consistent with this notion, comparative studies of gene expression levels in primates have found that the regulation of genes with metabolic functions tend to evolve rapidly in the human lineage. The metabolic consequences of these regulatory differences, however, remained unknown. To address this gap, we performed a comparative study using a combination of gene expression and metabolomic profiling in livers from humans, chimpanzees, and rhesus macaques. We show that dietary differences between species have a strong effect on metabolic concentrations. In addition, we found that differences in metabolic concentration across species are correlated with inter-species differences in the expression of the corresponding enzymes, which control the same metabolic reaction. We identified a number of metabolic compounds with lineage-specific profiles, including examples of human-species metabolic differences that may be directly related to dietary differences.

  15. Cell metabolomics reveals the neurotoxicity mechanism of cadmium in PC12 cells.

    Zong, Li; Xing, Junpeng; Liu, Shu; Liu, Zhiqiang; Song, Fengrui

    2018-01-01

    The heavy metals such as cadmium (Cd) can induce neurotoxicity. Extensive studies about the effects of Cd on human health have been reported, however, a systematic investigation on the molecular mechanisms of the effects of Cd on central nervous system is still needed. In this paper, the neuronal PC-12 cells were treated with a series of concentrations of CdCl 2 for 48h. Then the cytotoxicity was evaluated by MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide) assay. The IC 15 value (15% inhibiting concentration) was selected for further mechanism studies. After PC-12 cells incubated with CdCl 2 at a dose of IC 15 for 48h, the intracellular and extracellular metabolites were profiled using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS)-based cell metabolomics approach. As found, the effects of the heavy metal Cd produced on the PC-12 cell viability were dose-dependent. The metabolic changes were involved in the glycolysis and gluconeogenesis, biopterin metabolism, tryptophan metabolism, tyrosine metabolism, glycerophospholipid metabolism, and fatty acids beta-oxidation. These could cause the perturbation of cell membrane, redox balance, energy supply, cellular detoxification, further affecting the cellular proliferation and apoptosis and other cellular activities. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. Whole Blood Reveals More Metabolic Detail of the Human Metabolome than Serum as Measured by 1H-NMR Spectroscopy: Implications for Sepsis Metabolomics

    Stringer, Kathleen A.; Younger, John G.; McHugh, Cora; Yeomans, Larisa; Finkel, Michael A.; Puskarich, Michael A.; Jones, Alan E.; Trexel, Julie; Karnovsky, Alla

    2015-01-01

    Serum is a common sample of convenience for metabolomics studies. Its processing time can be lengthy and may result in the loss of metabolites including those of red blood cells (RBC). Unlike serum, whole blood (WB) is quickly processed, minimizing the influence of variable hemolysis while including RBC metabolites. To determine differences between serum and WB metabolomes, both sample types, collected from healthy volunteers, were assayed by 1H-NMR spectroscopy. A total of 34 and 50 aqueous metabolites were quantified from serum and WB, respectively. Free hemoglobin (Hgb) levels in serum were measured and the correlation between Hgb and metabolite concentrations was determined. All metabolites detected in serum were at higher concentrations in WB with the exception of acetoacetate and propylene glycol. The 18 unique metabolites of WB included adenosine, AMP, ADP and ATP, which are associated with RBC metabolism. The use of serum results in the underrepresentation of a number of metabolic pathways including branched chain amino acid degradation and glycolysis and gluconeogenesis. The range of free Hgb in serum was 0.03-0.01 g/dL and 8 metabolites were associated (p ≤ 0.05) with free Hgb. The range of free Hgb in serum samples from 18 sepsis patients was 0.02-0.46 g/dL. WB and serum have unique aqueous metabolite profiles but the use of serum may introduce potential pathway bias. Use of WB for metabolomics may be particularly important for studies in diseases like sepsis in which RBC metabolism is altered and mechanical and sepsis-induced hemolysis contributes to variance in the metabolome. PMID:26009817

  17. Proteomic and Metabolomic Analyses Reveal Contrasting Anti-Inflammatory Effects of an Extract of Mucor Racemosus Secondary Metabolites Compared to Dexamethasone.

    Meier, Samuel M; Muqaku, Besnik; Ullmann, Ronald; Bileck, Andrea; Kreutz, Dominique; Mader, Johanna C; Knasmüller, Siegfried; Gerner, Christopher

    2015-01-01

    Classical drug assays are often confined to single molecules and targeting single pathways. However, it is also desirable to investigate the effects of complex mixtures on complex systems such as living cells including the natural multitude of signalling pathways. Evidence based on herbal medicine has motivated us to investigate potential beneficial health effects of Mucor racemosus (M rac) extracts. Secondary metabolites of M rac were collected using a good-manufacturing process (GMP) approved production line and a validated manufacturing process, in order to obtain a stable product termed SyCircue (National Drug Code USA: 10424-102). Toxicological studies confirmed that this product does not contain mycotoxins and is non-genotoxic. Potential effects on inflammatory processes were investigated by treating stimulated cells with M rac extracts and the effects were compared to the standard anti-inflammatory drug dexamethasone on the levels of the proteome and metabolome. Using 2D-PAGE, slight anti-inflammatory effects were observed in primary white blood mononuclear cells, which were more pronounced in primary human umbilical vein endothelial cells (HUVECs). Proteome profiling based on nLC-MS/MS analysis of tryptic digests revealed inhibitory effects of M rac extracts on pro-inflammatory cytoplasmic mediators and secreted cytokines and chemokines in these endothelial cells. This finding was confirmed using targeted proteomics, here treatment of stimulated cells with M rac extracts down-regulated the secretion of IL-6, IL-8, CXCL5 and GROA significantly. Finally, the modulating effects of M rac on HUVECs were also confirmed on the level of the metabolome. Several metabolites displayed significant concentration changes upon treatment of inflammatory activated HUVECs with the M rac extract, including spermine and lysophosphatidylcholine acyl C18:0 and sphingomyelin C26:1, while the bulk of measured metabolites remained unaffected. Interestingly, the effects of M rac

  18. Transcriptional and metabolomic analysis of Ascophyllum nodosum mediated freezing tolerance in Arabidopsis thaliana

    Nair Prasanth

    2012-11-01

    Full Text Available Abstract Background We have previously shown that lipophilic components (LPC of the brown seaweed Ascophyllum nodosum (ANE improved freezing tolerance in Arabidopsis thaliana. However, the mechanism(s of this induced freezing stress tolerance is largely unknown. Here, we investigated LPC induced changes in the transcriptome and metabolome of A. thaliana undergoing freezing stress. Results Gene expression studies revealed that the accumulation of proline was mediated by an increase in the expression of the proline synthesis genes P5CS1 and P5CS2 and a marginal reduction in the expression of the proline dehydrogenase (ProDH gene. Moreover, LPC application significantly increased the concentration of total soluble sugars in the cytosol in response to freezing stress. Arabidopsis sfr4 mutant plants, defective in the accumulation of free sugars, treated with LPC, exhibited freezing sensitivity similar to that of untreated controls. The 1H NMR metabolite profile of LPC-treated Arabidopsis plants exposed to freezing stress revealed a spectrum dominated by chemical shifts (δ representing soluble sugars, sugar alcohols, organic acids and lipophilic components like fatty acids, as compared to control plants. Additionally, 2D NMR spectra suggested an increase in the degree of unsaturation of fatty acids in LPC treated plants under freezing stress. These results were supported by global transcriptome analysis. Transcriptome analysis revealed that LPC treatment altered the expression of 1113 genes (5% in comparison with untreated plants. A total of 463 genes (2% were up regulated while 650 genes (3% were down regulated. Conclusion Taken together, the results of the experiments presented in this paper provide evidence to support LPC mediated freezing tolerance enhancement through a combination of the priming of plants for the increased accumulation of osmoprotectants and alteration of cellular fatty acid composition.

  19. Metabolomic analysis applied to chemosystematics and evolution of megadiverse Brazilian Vernonieae (Asteraceae).

    Gallon, Marília Elias; Monge, Marcelo; Casoti, Rosana; Da Costa, Fernando Batista; Semir, João; Gobbo-Neto, Leonardo

    2018-06-01

    Vernonia sensu lato is the largest and most complex genus of the tribe Vernonieae (Asteraceae). The tribe is chemically characterized by the presence of sesquiterpene lactones and flavonoids. Over the years, several taxonomic classifications have been proposed for Vernonia s.l. and for the tribe; however, there has been no consensus among the researches. According to traditional classification, Vernonia s.l. comprises more than 1000 species divided into sections, subsections and series (sensu Bentham). In a more recent classification, these species have been segregated into other genera and some subtribes were proposed, while the genus Vernonia sensu stricto was restricted to 22 species distributed mainly in North America (sensu Robinson). In this study, species from the subtribes Vernoniinae, Lepidaploinae and Rolandrinae were analyzed by UHPLC-UV-HRMS followed by multivariate statistical analysis. Data mining was performed using unsupervised (HCA and PCA) and supervised methods (OPLS-DA). The HCA showed the segregation of the species into four main groups. Comparing the HCA with taxonomical classifications of Vernonieae, we observed that the groups of the dendogram, based on metabolic profiling, were in accordance with the generic classification proposed by Robinson and with previous phylogenetic studies. The species of the genera Stenocephalum, Stilpnopappus, Strophopappus and Rolandra (Group 1) were revealed to be more related to the species of the genus Vernonanthura (Group 2), while the genera Cyrtocymura, Chrysolaena and Echinocoryne (Group 3) were chemically more similar to the genera Lessingianthus and Lepidaploa (Group 4). These findings indicated that the subtribes Vernoniinae and Lepidaploinae are non-chemically homogeneous groups and highlighted the application of untargeted metabolomic tools for taxonomy and as indicators of species evolution. Discriminant compounds for the groups obtained by OPLS-DA were determined. Groups 1 and 2 were characterized

  20. Sample normalization methods in quantitative metabolomics.

    Wu, Yiman; Li, Liang

    2016-01-22

    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. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. A Guideline to Univariate Statistical Analysis for LC/MS-Based Untargeted Metabolomics-Derived Data

    Maria Vinaixa

    2012-10-01

    Full Text Available Several metabolomic software programs provide methods for peak picking, retention time alignment and quantification of metabolite features in LC/MS-based metabolomics. Statistical analysis, however, is needed in order to discover those features significantly altered between samples. By comparing the retention time and MS/MS data of a model compound to that from the altered feature of interest in the research sample, metabolites can be then unequivocally identified. This paper reports on a comprehensive overview of a workflow for statistical analysis to rank relevant metabolite features that will be selected for further MS/MS experiments. We focus on univariate data analysis applied in parallel on all detected features. Characteristics and challenges of this analysis are discussed and illustrated using four different real LC/MS untargeted metabolomic datasets. We demonstrate the influence of considering or violating mathematical assumptions on which univariate statistical test rely, using high-dimensional LC/MS datasets. Issues in data analysis such as determination of sample size, analytical variation, assumption of normality and homocedasticity, or correction for multiple testing are discussed and illustrated in the context of our four untargeted LC/MS working examples.

  2. Metabolomic and high-throughput sequencing analysis – modern approach for the assessment of biodeterioration of materials from historic buildings

    Beata eGutarowska

    2015-09-01

    Full Text Available Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II-Birkenau concentration and extermination camp in Oświęcim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM, metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and 9 fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of

  3. Metabolomic and high-throughput sequencing analysis-modern approach for the assessment of biodeterioration of materials from historic buildings.

    Gutarowska, Beata; Celikkol-Aydin, Sukriye; Bonifay, Vincent; Otlewska, Anna; Aydin, Egemen; Oldham, Athenia L; Brauer, Jonathan I; Duncan, Kathleen E; Adamiak, Justyna; Sunner, Jan A; Beech, Iwona B

    2015-01-01

    Preservation of cultural heritage is of paramount importance worldwide. Microbial colonization of construction materials, such as wood, brick, mortar, and stone in historic buildings can lead to severe deterioration. The aim of the present study was to give modern insight into the phylogenetic diversity and activated metabolic pathways of microbial communities colonized historic objects located in the former Auschwitz II-Birkenau concentration and extermination camp in Oświecim, Poland. For this purpose we combined molecular, microscopic and chemical methods. Selected specimens were examined using Field Emission Scanning Electron Microscopy (FESEM), metabolomic analysis and high-throughput Illumina sequencing. FESEM imaging revealed the presence of complex microbial communities comprising diatoms, fungi and bacteria, mainly cyanobacteria and actinobacteria, on sample surfaces. Microbial diversity of brick specimens appeared higher than that of the wood and was dominated by algae and cyanobacteria, while wood was mainly colonized by fungi. DNA sequences documented the presence of 15 bacterial phyla representing 99 genera including Halomonas, Halorhodospira, Salinisphaera, Salinibacterium, Rubrobacter, Streptomyces, Arthrobacter and nine fungal classes represented by 113 genera including Cladosporium, Acremonium, Alternaria, Engyodontium, Penicillium, Rhizopus, and Aureobasidium. Most of the identified sequences were characteristic of organisms implicated in deterioration of wood and brick. Metabolomic data indicated the activation of numerous metabolic pathways, including those regulating the production of primary and secondary metabolites, for example, metabolites associated with the production of antibiotics, organic acids and deterioration of organic compounds. The study demonstrated that a combination of electron microscopy imaging with metabolomic and genomic techniques allows to link the phylogenetic information and metabolic profiles of microbial communities

  4. Protein catabolism and high lipid metabolism associated with long-distance exercise are revealed by plasma NMR metabolomics in endurance horses.

    Laurence Le Moyec

    Full Text Available During long distance endurance races, horses undergo high physiological and metabolic stresses. The adaptation processes involve the modulation of the energetic pathways in order to meet the energy demand. The aims were to evaluate the effects of long endurance exercise on the plasma metabolomic profiles and to investigate the relationships with the individual horse performances. The metabolomic profiles of the horses were analyzed using the non-dedicated methodology, NMR spectroscopy and statistical multivariate analysis. The advantage of this method is to investigate several metabolomic pathways at the same time in a single sample. The plasmas were obtained before exercise (BE and post exercise (PE from 69 horses competing in three endurance races at national level (130-160 km. Biochemical assays were also performed on the samples taken at PE. The proton NMR spectra were compared using the supervised orthogonal projection on latent structure method according to several factors. Among these factors, the race location was not significant whereas the effect of the race exercise (sample BE vs PE of same horse was highly discriminating. This result was confirmed by the projection of unpaired samples (only BE or PE sample of different horses. The metabolomic profiles proved that protein, energetic and lipid metabolisms as well as glycoproteins content are highly affected by the long endurance exercise. The BE samples from finisher horses could be discriminated according to the racing speed based on their metabolomic lipid content. The PE samples could be discriminated according to the horse ranking position at the end of the race with lactate as unique correlated metabolite. As a conclusion, the metabolomic profiles of plasmas taken before and after the race provided a better understanding of the high energy demand and protein catabolism pathway that could expose the horses to metabolic disorders.

  5. Metabolomics Reveals Relationship between Plasma Inositols and Birth Weight: Possible Markers for Fetal Programming of Type 2 Diabetes

    Pia Marlene Nissen

    2011-01-01

    Full Text Available Epidemiological studies in man and with experimental animal models have shown that intrauterine growth restriction (IUGR resulting in low birth weight is associated with higher risk of programming welfare diseases in later life. In the pig, severe IUGR occurs naturally and contribute substantially to a large intralitter variation in birth weight and may therefore be a good model for man. In the present paper the natural form of IUGR in pigs was studied close to term by nuclear magnetic resonance (NMR-based metabolomics. The NMR-based investigations revealed different metabolic profiles of plasma samples from low-birth weight (LW and high-birth weight (HW piglets, respectively, and differences were assigned to levels of glucose and myo-inositol. Further studies by GC-MS revealed that LW piglets had a significant higher concentration of myoinositol and D-chiro-inositol in plasma compared to larger littermates. Myo-inositol and D-chiro-inositol have been coupled with glucose intolerance and insulin resistance in adults, and the present paper therefore suggests that IUGR is related to impaired glucose metabolism during fetal development, which may cause type 2 diabetes in adulthood.

  6. An integrated lipidomics and metabolomics reveal nephroprotective effect and biochemical mechanism of Rheum officinale in chronic renal failure

    Zhang, Zhi-Hao; Vaziri, Nosratola D.; Wei, Feng; Cheng, Xian-Long; Bai, Xu; Zhao, Ying-Yong

    2016-01-01

    Chronic renal failure (CRF) is a major public health problem worldwide. Earlier studies have revealed salutary effects of rhubarb extracts in CRF. In this study, we employed lipidomic and metabolomic approaches to identify the plasma biomarkers and to determine the effect of treatment with petroleum ether, ethyl acetate and n-butanol extracts of rhubarb in a rat model of CRF with adenine-induced chronic tubulointerstitial nephropathy. In addition, clinical biochemistry, histological evaluation and pro-fibrotic protein expression were analyzed. Significant changes were found between the CRF and control groups representing characteristic phenotypes of rats with CRF. Treatment with the three rhubarb extracts improved renal injury and dysfunction, either fully or partially reversed the plasma metabolites abnormalities and attenuated upregulation of pro-fibrotic proteins including TGF-β1, α-SMA, PAI-1, CTGF, FN and collagen-1. The nephroprotective effect of ethyl acetate extract was better than other extracts. The differential metabolites were closely associated with glycerophospholipid, fatty acid and amino acid metabolisms. The results revealed a strong link between renal tubulointerstitial fibrosis and glycerophospholipid metabolism and L-carnitine metabolism in the development of CRF. Amelioration of CRF with the three rhubarb extracts was associated with the delayed development and/or reversal the disorders in key metabolites associated with adenine-induced CRF. PMID:26903149

  7. Metabolomic analysis based on 1H-nuclear magnetic resonance spectroscopy metabolic profiles in tuberculous, malignant and transudative pleural effusion

    Wang, Cheng; Peng, Jingjin; Kuang, Yanling; Zhang, Jiaqiang; Dai, Luming

    2017-01-01

    Pleural effusion is a common clinical manifestation with various causes. Current diagnostic and therapeutic methods have exhibited numerous limitations. By involving the analysis of dynamic changes in low molecular weight catabolites, metabolomics has been widely applied in various types of disease and have provided platforms to distinguish many novel biomarkers. However, to the best of our knowledge, there are few studies regarding the metabolic profiling for pleural effusion. In the current study, 58 pleural effusion samples were collected, among which 20 were malignant pleural effusions, 20 were tuberculous pleural effusions and 18 were transudative pleural effusions. The small molecule metabolite spectrums were obtained by adopting 1H nuclear magnetic resonance technology, and pattern-recognition multi-variable statistical analysis was used to screen out different metabolites. One-way analysis of variance, and Student-Newman-Keuls and the Kruskal-Wallis test were adopted for statistical analysis. Over 400 metabolites were identified in the untargeted metabolomic analysis and 26 metabolites were identified as significantly different among tuberculous, malignant and transudative pleural effusions. These metabolites were predominantly involved in the metabolic pathways of amino acids metabolism, glycometabolism and lipid metabolism. Statistical analysis revealed that eight metabolites contributed to the distinction between the three groups: Tuberculous, malignant and transudative pleural effusion. In the current study, the feasibility of identifying small molecule biochemical profiles in different types of pleural effusion were investigated reveal novel biological insights into the underlying mechanisms. The results provide specific insights into the biology of tubercular, malignant and transudative pleural effusion and may offer novel strategies for the diagnosis and therapy of associated diseases, including tuberculosis, advanced lung cancer and congestive heart

  8. Metabolomic analysis using porcine skin: a pilot study of analytical techniques.

    Wu, Julie; Fiehn, Oliver; Armstrong, April W

    2014-06-15

    Metabolic byproducts serve as indicators of the chemical processes and can provide valuable information on pathogenesis by measuring the amplified output. Standardized techniques for metabolome extraction of skin samples serve as a critical foundation to this field but have not been developed. We sought to determine the optimal cell lysage techniques for skin sample preparation and to compare GC-TOF-MS and UHPLC-QTOF-MS for metabolomic analysis. Using porcine skin samples, we pulverized the skin via various combinations of mechanical techniques for cell lysage. After extraction, the samples were subjected to GC-TOF-MS and/or UHPLC-QTOF-MS. Signal intensities from GC-TOF-MS analysis showed that ultrasonication (2.7x107) was most effective for cell lysage when compared to mortar-and-pestle (2.6x107), ball mill followed by ultrasonication (1.6x107), mortar-and-pestle followed by ultrasonication (1.4x107), and homogenization (trial 1: 8.4x106; trial 2: 1.6x107). Due to the similar signal intensities, ultrasonication and mortar-and-pestle were applied to additional samples and subjected to GC-TOF-MS and UHPLC-QTOF-MS. Ultrasonication yielded greater signal intensities than mortar-and-pestle for 92% of detected metabolites following GC-TOF-MS and for 68% of detected metabolites following UHPLC-QTOF-MS. Overall, ultrasonication is the preferred method for efficient cell lysage of skin tissue for both metabolomic platforms. With standardized sample preparation, metabolomic analysis of skin can serve as a powerful tool in elucidating underlying biological processes in dermatological conditions.

  9. MassTRIX reloaded: combined analysis and visualization of transcriptome and metabolome data.

    Brigitte Wägele

    Full Text Available Systems Biology is a field in biological science that focuses on the combination of several or all "omics"-approaches in order to find out how genes, transcripts, proteins and metabolites act together in the network of life. Metabolomics as analog to genomics, transcriptomics and proteomics is more and more integrated into biological studies and often transcriptomic and metabolomic experiments are combined in one setup. At a first glance both data types seem to be completely different, but both produce information on biological entities, either transcripts or metabolites. Both types can be overlaid on metabolic pathways to obtain biological information on the studied system. For the joint analysis of both data types the MassTRIX webserver was updated. MassTRIX is freely available at www.masstrix.org.

  10. Metabolomics reveals metabolic targets and biphasic responses in breast cancer cells treated by curcumin alone and in association with docetaxel.

    Mathilde Bayet-Robert

    Full Text Available BACKGROUND: Curcumin (CUR has deserved extensive research due to its anti-inflammatory properties, of interest in human diseases including cancer. However, pleiotropic even paradoxical responses of tumor cells have been reported, and the mechanisms of action of CUR remain uncompletely elucidated. METHODOLOGY/PRINCIPAL FINDINGS: (1H-NMR spectroscopy-based metabolomics was applied to get novel insight into responses of MCF7 and MDA-MB-231 breast cancer cells to CUR alone, and MCF7 cells to CUR in cotreatment with docetaxel (DTX. In both cell types, a major target of CUR was glutathione metabolism. Total glutathione (GSx increased at low dose CUR (≤ 10 mg.l(-1-28 µM- (up to +121% in MCF7 cells, P<0.01, and +138% in MDA-MB-231 cells, P<0.01, but decreased at high dose (≥ 25 mg.l(-1 -70 µM- (-49%, in MCF7 cells, P<0.02, and -56% in MDA-MB-231 cells, P<0.025. At high dose, in both cell types, GSx-related metabolites decreased, including homocystein, creatine and taurine (-60 to -80%, all, P<0.05. Together with glutathione-S-transferase actvity, data established that GSx biosynthesis was upregulated at low dose, and GSx consumption activated at high dose. Another major target, in both cell types, was lipid metabolism involving, at high doses, accumulation of polyunsaturated and total free fatty acids (between ×4.5 and ×11, P<0.025, and decrease of glycerophospho-ethanolamine and -choline (about -60%, P<0.025. Multivariate statistical analyses showed a metabolic transition, even a biphasic behavior of some metabolites including GSx, between low and high doses. In addition, CUR at 10 mg.l(-1 in cotreatment with DTX induced modifications in glutathione metabolism, lipid metabolism, and glucose utilization. Some of these changes were biphasic depending on the duration of exposure to CUR. CONCLUSIONS/SIGNIFICANCE: Metabolomics reveals major metabolic targets of CUR in breast cancer cells, and biphasic responses that challenge the widely accepted

  11. Optimized Method for Untargeted Metabolomics Analysis of MDA-MB-231 Breast Cancer Cells

    Amanda L. Peterson

    2016-09-01

    Full Text Available Cancer cells often have dysregulated metabolism, which is largely characterized by the Warburg effect—an increase in glycolytic activity at the expense of oxidative phosphorylation—and increased glutamine utilization. Modern metabolomics tools offer an efficient means to investigate metabolism in cancer cells. Currently, a number of protocols have been described for harvesting adherent cells for metabolomics analysis, but the techniques vary greatly and they lack specificity to particular cancer cell lines with diverse metabolic and structural features. Here we present an optimized method for untargeted metabolomics characterization of MDA-MB-231 triple negative breast cancer cells, which are commonly used to study metastatic breast cancer. We found that an approach that extracted all metabolites in a single step within the culture dish optimally detected both polar and non-polar metabolite classes with higher relative abundance than methods that involved removal of cells from the dish. We show that this method is highly suited to diverse applications, including the characterization of central metabolic flux by stable isotope labelling and differential analysis of cells subjected to specific pharmacological interventions.

  12. In situ proteo-metabolomics reveals metabolite secretion by the acid mine drainage bio-indicator, Euglena mutabilis

    Halter, David; Goulhen-Chollet, Florence; Gallien, Sébastien; Casiot, Corinne; Hamelin, Jérôme; Gilard, Françoise; Heintz, Dimitri; Schaeffer, Christine; Carapito, Christine; Van Dorsselaer, Alain; Tcherkez, Guillaume; Arsène-Ploetze, Florence; Bertin, Philippe N

    2012-01-01

    Euglena mutabilis is a photosynthetic protist found in acidic aquatic environments such as peat bogs, volcanic lakes and acid mine drainages (AMDs). Through its photosynthetic metabolism, this protist is supposed to have an important role in primary production in such oligotrophic ecosystems. Nevertheless, the exact contribution of E. mutabilis in organic matter synthesis remains unclear and no evidence of metabolite secretion by this protist has been established so far. Here we combined in situ proteo-metabolomic approaches to determine the nature of the metabolites accumulated by this protist or potentially secreted into an AMD. Our results revealed that the secreted metabolites are represented by a large number of amino acids, polyamine compounds, urea and some sugars but no fatty acids, suggesting a selective organic matter contribution in this ecosystem. Such a production may have a crucial impact on the bacterial community present on the study site, as it has been suggested previously that prokaryotes transport and recycle in situ most of the metabolites secreted by E. mutabilis. Consequently, this protist may have an indirect but important role in AMD ecosystems but also in other ecological niches often described as nitrogen-limited. PMID:22237547

  13. Comparative Metabolomic Profiling Reveals That Dysregulated Glycolysis Stemming from Lack of Salvage NAD+ Biosynthesis Impairs Reproductive Development in Caenorhabditis elegans.

    Wang, Wenqing; McReynolds, Melanie R; Goncalves, Jimmy F; Shu, Muya; Dhondt, Ineke; Braeckman, Bart P; Lange, Stephanie E; Kho, Kelvin; Detwiler, Ariana C; Pacella, Marisa J; Hanna-Rose, Wendy

    2015-10-23

    Temporal developmental progression is highly coordinated in Caenorhabditis elegans. However, loss of nicotinamidase PNC-1 activity slows reproductive development, uncoupling it from its typical progression relative to the soma. Using LC/MS we demonstrate that pnc-1 mutants do not salvage the nicotinamide released by NAD(+) consumers to resynthesize NAD(+), resulting in a reduction in global NAD(+) bioavailability. We manipulate NAD(+) levels to demonstrate that a minor deficit in NAD(+) availability is incompatible with a normal pace of gonad development. The NAD(+) deficit compromises NAD(+) consumer activity, but we surprisingly found no functional link between consumer activity and reproductive development. As a result we turned to a comparative metabolomics approach to identify the cause of the developmental phenotype. We reveal widespread metabolic perturbations, and using complementary pharmacological and genetic approaches, we demonstrate that a glycolytic block accounts for the slow pace of reproductive development. Interestingly, mitochondria are protected from both the deficiency in NAD(+) biosynthesis and the effects of reduced glycolytic output. We suggest that compensatory metabolic processes that maintain mitochondrial activity in the absence of efficient glycolysis are incompatible with the requirements for reproductive development, which requires high levels of cell division. In addition to demonstrating metabolic requirements for reproductive development, this work also has implications for understanding the mechanisms behind therapeutic interventions that target NAD(+) salvage biosynthesis for the purposes of inhibiting tumor growth. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  14. Comparative Metabolomic Profiling Reveals That Dysregulated Glycolysis Stemming from Lack of Salvage NAD+ Biosynthesis Impairs Reproductive Development in Caenorhabditis elegans*

    Wang, Wenqing; McReynolds, Melanie R.; Goncalves, Jimmy F.; Shu, Muya; Dhondt, Ineke; Braeckman, Bart P.; Lange, Stephanie E.; Kho, Kelvin; Detwiler, Ariana C.; Pacella, Marisa J.; Hanna-Rose, Wendy

    2015-01-01

    Temporal developmental progression is highly coordinated in Caenorhabditis elegans. However, loss of nicotinamidase PNC-1 activity slows reproductive development, uncoupling it from its typical progression relative to the soma. Using LC/MS we demonstrate that pnc-1 mutants do not salvage the nicotinamide released by NAD+ consumers to resynthesize NAD+, resulting in a reduction in global NAD+ bioavailability. We manipulate NAD+ levels to demonstrate that a minor deficit in NAD+ availability is incompatible with a normal pace of gonad development. The NAD+ deficit compromises NAD+ consumer activity, but we surprisingly found no functional link between consumer activity and reproductive development. As a result we turned to a comparative metabolomics approach to identify the cause of the developmental phenotype. We reveal widespread metabolic perturbations, and using complementary pharmacological and genetic approaches, we demonstrate that a glycolytic block accounts for the slow pace of reproductive development. Interestingly, mitochondria are protected from both the deficiency in NAD+ biosynthesis and the effects of reduced glycolytic output. We suggest that compensatory metabolic processes that maintain mitochondrial activity in the absence of efficient glycolysis are incompatible with the requirements for reproductive development, which requires high levels of cell division. In addition to demonstrating metabolic requirements for reproductive development, this work also has implications for understanding the mechanisms behind therapeutic interventions that target NAD+ salvage biosynthesis for the purposes of inhibiting tumor growth. PMID:26350462

  15. Create, run, share, publish, and reference your LC-MS, FIA-MS, GC-MS, and NMR data analysis workflows with the Workflow4Metabolomics 3.0 Galaxy online infrastructure for metabolomics.

    Guitton, Yann; Tremblay-Franco, Marie; Le Corguillé, Gildas; Martin, Jean-François; Pétéra, Mélanie; Roger-Mele, Pierrick; Delabrière, Alexis; Goulitquer, Sophie; Monsoor, Misharl; Duperier, Christophe; Canlet, Cécile; Servien, Rémi; Tardivel, Patrick; Caron, Christophe; Giacomoni, Franck; Thévenot, Etienne A

    2017-12-01

    Metabolomics is a key approach in modern functional genomics and systems biology. Due to the complexity of metabolomics data, the variety of experimental designs, and the multiplicity of bioinformatics tools, providing experimenters with a simple and efficient resource to conduct comprehensive and rigorous analysis of their data is of utmost importance. In 2014, we launched the Workflow4Metabolomics (W4M; http://workflow4metabolomics.org) online infrastructure for metabolomics built on the Galaxy environment, which offers user-friendly features to build and run data analysis workflows including preprocessing, statistical analysis, and annotation steps. Here we present the new W4M 3.0 release, which contains twice as many tools as the first version, and provides two features which are, to our knowledge, unique among online resources. First, data from the four major metabolomics technologies (i.e., LC-MS, FIA-MS, GC-MS, and NMR) can be analyzed on a single platform. By using three studies in human physiology, alga evolution, and animal toxicology, we demonstrate how the 40 available tools can be easily combined to address biological issues. Second, the full analysis (including the workflow, the parameter values, the input data and output results) can be referenced with a permanent digital object identifier (DOI). Publication of data analyses is of major importance for robust and reproducible science. Furthermore, the publicly shared workflows are of high-value for e-learning and training. The Workflow4Metabolomics 3.0 e-infrastructure thus not only offers a unique online environment for analysis of data from the main metabolomics technologies, but it is also the first reference repository for metabolomics workflows. Copyright © 2017 Elsevier Ltd. All rights reserved.

  16. 1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil

    Myrna J. Simpson

    2013-08-01

    Full Text Available 1H NMR-based metabolomics was used to measure the response of Eisenia fetida earthworms after exposure to sub-lethal concentrations of perfluorooctane sulfonate (PFOS in soil. Earthworms were exposed to a range of PFOS concentrations (five, 10, 25, 50, 100 or 150 mg/kg for two, seven and fourteen days. Earthworm tissues were extracted and analyzed by 1H NMR. Multivariate statistical analysis of the metabolic response of E. fetida to PFOS exposure identified time-dependent responses that were comprised of two separate modes of action: a non-polar narcosis type mechanism after two days of exposure and increased fatty acid oxidation after seven and fourteen days of exposure. Univariate statistical analysis revealed that 2-hexyl-5-ethyl-3-furansulfonate (HEFS, betaine, leucine, arginine, glutamate, maltose and ATP are potential indicators of PFOS exposure, as the concentrations of these metabolites fluctuated significantly. Overall, NMR-based metabolomic analysis suggests elevated fatty acid oxidation, disruption in energy metabolism and biological membrane structure and a possible interruption of ATP synthesis. These conclusions obtained from analysis of the metabolic profile in response to sub-lethal PFOS exposure indicates that NMR-based metabolomics is an excellent discovery tool when the mode of action (MOA of contaminants is not clearly defined.

  17. Metabolomics analysis of metabolic effects of nicotinamide phosphoribosyltransferase (NAMPT inhibition on human cancer cells.

    Vladimir Tolstikov

    Full Text Available Nicotinamide phosphoribosyltransferase (NAMPT plays an important role in cellular bioenergetics. It is responsible for converting nicotinamide to nicotinamide adenine dinucleotide, an essential molecule in cellular metabolism. NAMPT has been extensively studied over the past decade due to its role as a key regulator of nicotinamide adenine dinucleotide-consuming enzymes. NAMPT is also known as a potential target for therapeutic intervention due to its involvement in disease. In the current study, we used a global mass spectrometry-based metabolomic approach to investigate the effects of FK866, a small molecule inhibitor of NAMPT currently in clinical trials, on metabolic perturbations in human cancer cells. We treated A2780 (ovarian cancer and HCT-116 (colorectal cancer cell lines with FK866 in the presence and absence of nicotinic acid. Significant changes were observed in the amino acids metabolism and the purine and pyrimidine metabolism. We also observed metabolic alterations in glycolysis, the citric acid cycle (TCA, and the pentose phosphate pathway. To expand the range of the detected polar metabolites and improve data confidence, we applied a global metabolomics profiling platform by using both non-targeted and targeted hydrophilic (HILIC-LC-MS and GC-MS analysis. We used Ingenuity Knowledge Base to facilitate the projection of metabolomics data onto metabolic pathways. Several metabolic pathways showed differential responses to FK866 based on several matches to the list of annotated metabolites. This study suggests that global metabolomics can be a useful tool in pharmacological studies of the mechanism of action of drugs at a cellular level.

  18. Integrated Analysis of the Transcriptome and Metabolome of Corynebacterium glutamicum during Penicillin-Induced Glutamic Acid Production.

    Hirasawa, Takashi; Saito, Masaki; Yoshikawa, Katsunori; Furusawa, Chikara; Shmizu, Hiroshi

    2018-05-01

    Corynebacterium glutamicum is known for its ability to produce glutamic acid and has been utilized for the fermentative production of various amino acids. Glutamic acid production in C. glutamicum is induced by penicillin. In this study, the transcriptome and metabolome of C. glutamicum is analyzed to understand the mechanism of penicillin-induced glutamic acid production. Transcriptomic analysis with DNA microarray revealed that expression of some glycolysis- and TCA cycle-related genes, which include those encoding the enzymes involved in conversion of glucose to 2-oxoglutaric acid, is upregulated after penicillin addition. Meanwhile, expression of some TCA cycle-related genes, encoding the enzymes for conversion of 2-oxoglutaric acid to oxaloacetic acid, and the anaplerotic reactions decreased. In addition, expression of NCgl1221 and odhI, encoding proteins involved in glutamic acid excretion and inhibition of the 2-oxoglutarate dehydrogenase, respectively, is upregulated. Functional category enrichment analysis of genes upregulated and downregulated after penicillin addition revealed that genes for signal transduction systems are enriched among upregulated genes, whereas those for energy production and carbohydrate and amino acid metabolisms are enriched among the downregulated genes. As for the metabolomic analysis using capillary electrophoresis time-of-flight mass spectrometry, the intracellular content of most metabolites of the glycolysis and the TCA cycle decreased dramatically after penicillin addition. Overall, these results indicate that the cellular metabolism and glutamic acid excretion are mainly optimized at the transcription level during penicillin-induced glutamic acid production by C. glutamicum. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Metabolomics reveals reduction of metabolic oxidation in women with polycystic ovary syndrome after pioglitazone-flutamide-metformin polytherapy.

    Maria Vinaixa

    Full Text Available Polycystic ovary syndrome (PCOS is a variable disorder characterized by a broad spectrum of anomalies, including hyperandrogenemia, insulin resistance, dyslipidemia, body adiposity, low-grade inflammation and increased cardiovascular disease risks. Recently, a new polytherapy consisting of low-dose flutamide, metformin and pioglitazone in combination with an estro-progestagen resulted in the regulation of endocrine clinical markers in young and non-obese PCOS women. However, the metabolic processes involved in this phenotypic amelioration remain unidentified. In this work, we used NMR and MS-based untargeted metabolomics to study serum samples of young non-obese PCOS women prior to and at the end of a 30 months polytherapy receiving low-dose flutamide, metformin and pioglitazone in combination with an estro-progestagen. Our results reveal that the treatment decreased the levels of oxidized LDL particles in serum, as well as downstream metabolic oxidation products of LDL particles such as 9- and 13-HODE, azelaic acid and glutaric acid. In contrast, the radiuses of small dense LDL and large HDL particles were substantially increased after the treatment. Clinical and endocrine-metabolic markers were also monitored, showing that the level of HDL cholesterol was increased after the treatment, whereas the level of androgens and the carotid intima-media thickness were reduced. Significantly, the abundance of azelaic acid and the carotid intima-media thickness resulted in a high degree of correlation. Altogether, our results reveal that this new polytherapy markedly reverts the oxidant status of untreated PCOS women, and potentially improves the pro-atherosclerosis condition in these patients.

  20. RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

    Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

    2018-02-22

    The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be

  1. Metabolomics and transcriptomics reveal the toxicity of difenoconazole to the early life stages of zebrafish (Danio rerio).

    Teng, Miaomiao; Zhu, Wentao; Wang, Dezhen; Qi, Suzhen; Wang, Yao; Yan, Jin; Dong, Kai; Zheng, Mingqi; Wang, Chengju

    2018-01-01

    Difenoconazole is widely used to inhibit the growth of fungi, but its residue in the water environment may threaten ecosystem and human health. Here, 1 H nuclear magnetic resonance (NMR) and LC-MS/MS based metabolomics and transcriptomics approaches were used to assess the response of zebrafish to difenoconazole exposure. Early life stages of zebrafish were exposed to difenoconazole at environmentally relevant concentrations for 168h. Their comparison with the control group suggested an adverse development and disturbance of steroid hormones and VTG. KEGG pathway analysis identified five biological processes on the basis of differentially expressed genes (DEGs), as well as altered metabolites and amino acids in zebrafish following difenoconazole exposure. These affected processes included energy metabolism, amino acids metabolism, lipid metabolism, nucleotide metabolism, and an immune-related pathway. Collectively, these results bring us closer to an incremental understanding of the toxic effects of difenoconazole on zebrafish in its early development, and lend support to the continued use of the early life stages of zebrafish as a classical model to evaluate underlying environmental risks of xenobiotics in aquatic organisms. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. CE-TOF MS-based metabolomic profiling revealed characteristic metabolic pathways in postmortem porcine fast and slow type muscles.

    Muroya, Susumu; Oe, Mika; Nakajima, Ikuyo; Ojima, Koichi; Chikuni, Koichi

    2014-12-01

    To determine key compounds and metabolic pathways associated with meat quality, we profiled metabolites in postmortem porcine longissimus lumborum (LL) and vastus intermedius (VI) muscles with different aging times by global metabolomics using capillary electrophoresis-time of flight mass spectrometry. Loading analyses of the principal component analysis showed that hydrophilic amino acids and β-alanine-related compounds contributed to the muscle type positively and negatively, respectively, whereas glycolytic and ATP degradation products contributed to aging time. At 168h postmortem, LL samples were characterized by abundance of combinations of amino acids, dipeptides, and glycolytic products, whereas the VI samples were characterized by abundance of both sulfur-containing compounds and amino acids. The AMP and inosine contents in the VI were approx. 10 times higher than those in the LL at 4h postmortem, suggesting different rates of inosine 5'-monophosphate (IMP) accumulation by adenylate kinase 7 and 5'-nucleotidase, and subsequent different production levels of IMP and hypoxanthine between these two porcine muscles. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. Metabolomics reveals the mechanisms for the cardiotoxicity of Pinelliae Rhizoma and the toxicity-reducing effect of processing

    Su, Tao; Tan, Yong; Tsui, Man-Shan; Yi, Hua; Fu, Xiu-Qiong; Li, Ting; Chan, Chi Leung; Guo, Hui; Li, Ya-Xi; Zhu, Pei-Li; Tse, Anfernee Kai Wing; Cao, Hui; Lu, Ai-Ping; Yu, Zhi-Ling

    2016-10-01

    Pinelliae Rhizoma (PR) is a commonly used Chinese medicinal herb, but it has been frequently reported about its toxicity. According to the traditional Chinese medicine theory, processing can reduce the toxicity of the herbs. Here, we aim to determine if processing reduces the toxicity of raw PR, and to explore the underlying mechanisms of raw PR-induced toxicities and the toxicity-reducing effect of processing. Biochemical and histopathological approaches were used to evaluate the toxicities of raw and processed PR. Rat serum metabolites were analyzed by LC-TOF-MS. Ingenuity pathway analysis of the metabolomics data highlighted the biological pathways and network functions involved in raw PR-induced toxicities and the toxicity-reducing effect of processing, which were verified by molecular approaches. Results showed that raw PR caused cardiotoxicity, and processing reduced the toxicity. Inhibition of mTOR signaling and activation of the TGF-β pathway contributed to raw PR-induced cardiotoxicity, and free radical scavenging might be responsible for the toxicity-reducing effect of processing. Our data shed new light on the mechanisms of raw PR-induced cardiotoxicity and the toxicity-reducing effect of processing. This study provides scientific justifications for the traditional processing theory of PR, and should help in optimizing the processing protocol and clinical combinational application of PR.

  4. Metabolomic profiling reveals distinct patterns of tricarboxylic acid disorders in blood stasis syndrome associated with coronary heart disease.

    Wang, Yong; Li, Chun; Chang, Hong; Lu, Ling-Hui; Qiu, Qi; Ouyang, Yu-Lin; Yu, Jun-da; Guo, Shu-Zhen; Han, Jing; Wang, Wei

    2016-08-01

    To investigate the underlying metabolomic profifiling of coronary heart disease (CHD) with blood stasis syndrome (BSS). CHD model was induced by a nameroid constrictor in Chinese miniature swine. Fifteen miniature swine were randomly divided into a model group (n=9) and a control group (n=6), respectively according to arandom number table. After 4 weeks, plasma hemorheology was detected by automatic hemorheological analyzer, indices including hematocrit, plasma viscosity, blood viscosity, rigidity index and erythrocyte sedimentation rate; cardiac function was assessed by echocardiograph to detect left ventricular end-systolic diameter (LVED), left ventricular end-diastolic diameter (LVEDd), ejection fraction (EF), fractional shortening (FS) and other indicators. Gas chromatography coupled with mass spectrometry (GC-MS) and bioinformatics were applied to analyze spectra of CHD plasma with BSS. The results of hemorheology analysis showed signifificant changes in viscosity, with low shear whole blood viscosity being lower and plasma viscosity higher in the model group compared with the control group. Moreover, whole blood reduction viscosity at high shear rate and whole blood reduction viscosity at low shear rate increased signifificantly (P patterns involved were associated with dysfunction of energy metabolism including glucose and lipid disorders, especially in glycolysis/gluconeogenesis, galactose metabolism and adenosine-triphosphate-binding cassette transporters. Glucose metabolism and lipid metabolism disorders were the major contributors to the syndrome classifification of CHD with BSS.

  5. MetaboLab - advanced NMR data processing and analysis for metabolomics

    Günther Ulrich L

    2011-09-01

    Full Text Available Abstract Background Despite wide-spread use of Nuclear Magnetic Resonance (NMR in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis. Results Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments. Conclusions The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.

  6. Toxicological effects of benzo(a)pyrene, DDT and their mixture on the green mussel Perna viridis revealed by proteomic and metabolomic approaches.

    Song, Qinqin; Chen, Hao; Li, Yuhu; Zhou, Hailong; Han, Qian; Diao, Xiaoping

    2016-02-01

    Benzo(a)pyrene (BaP) and dichlorodiphenyltrichloroethane (DDT) are persistent organic pollutants and environmental estrogens (EEs) with known toxicity towards the green mussel, Perna viridis. In this study, the toxic effects of BaP (10 µg/L) and DDT (10 µg/L) and their mixture were assessed in green mussel gills with proteomic and metabolomic approaches. Metabolic responses indicated that BaP mainly caused disturbance in osmotic regulation by significantly decrease in branched chain amino acids, dimethylamine and dimethylglycine in gills of male green mussels after exposure for 7 days. DDT mainly caused disturbance in osmotic regulation and energy metabolism by differential alteration of betaine, dimethylamine, dimethylglycine, amino acids, and succinate in gills of male green mussels. However, the mixture of BaP and DDT didn't show obvious metabolite changes. Proteomic analysis showed different protein expression profiles between different treatment groups, which demonstrated that BaP, DDT and their mixture may have different modes of action. Proteomic responses revealed that BaP induced cell apoptosis, disturbance in protein digestion and energy metabolism in gills of green mussels, whereas DDT exposure altered proteins that were associated with oxidative stress, cytoskeleton and cell structure, protein digestion and energy metabolism. However, the mixture of BaP and DDT affected proteins related to the oxidative stress, cytoskeleton and cell structure, protein biosynthesis and modification, energy metabolism, growth and apoptosis. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Systematic Assessment of Seven Solvent and Solid-Phase Extraction Methods for Metabolomics Analysis of Human Plasma by LC-MS

    Sitnikov, Dmitri G.; Monnin, Cian S.; Vuckovic, Dajana

    2016-12-01

    The comparison of extraction methods for global metabolomics is usually executed in biofluids only and focuses on metabolite coverage and method repeatability. This limits our detailed understanding of extraction parameters such as recovery and matrix effects and prevents side-by-side comparison of different sample preparation strategies. To address this gap in knowledge, seven solvent-based and solid-phase extraction methods were systematically evaluated using standard analytes spiked into both buffer and human plasma. We compared recovery, coverage, repeatability, matrix effects, selectivity and orthogonality of all methods tested for non-lipid metabolome in combination with reversed-phased and mixed-mode liquid chromatography mass spectrometry analysis (LC-MS). Our results confirmed wide selectivity and excellent precision of solvent precipitations, but revealed their high susceptibility to matrix effects. The use of all seven methods showed high overlap and redundancy which resulted in metabolite coverage increases of 34-80% depending on LC-MS method employed as compared to the best single extraction protocol (methanol/ethanol precipitation) despite 7x increase in MS analysis time and sample consumption. The most orthogonal methods to methanol-based precipitation were ion-exchange solid-phase extraction and liquid-liquid extraction using methyl-tertbutyl ether. Our results help facilitate rational design and selection of sample preparation methods and internal standards for global metabolomics.

  8. Metabolomics and Ionomics of Potato Tuber Reveals an Influence of Cultivar and Market Class on Human Nutrients and Bioactive Compounds

    Jacqueline M. Chaparro

    2018-05-01

    Full Text Available Potato (Solanum tuberosum L. is an important global food crop that contains phytochemicals with demonstrated effects on human health. Understanding sources of chemical variation of potato tuber can inform breeding for improved health attributes of the cooked food. Here, a comprehensive metabolomics (UPLC- and GC-MS and ionomics (ICP-MS analysis of raw and cooked potato tuber was performed on 60 unique potato genotypes that span 5 market classes including russet, red, yellow, chip, and specialty potatoes. The analyses detected 2,656 compounds that included known bioactives (43 compounds, nutrients (42, lipids (76, and 23 metals. Most nutrients and bioactives were partially degraded during cooking (44 out of 85; 52%, however genotypes with high quantities of bioactives remained highest in the cooked tuber. Chemical variation was influenced by genotype and market class. Specifically, ~53% of all detected compounds from cooked potato varied among market class and 40% varied by genotype. The most notable metabolite profiles were observed in yellow-flesh potato which had higher levels of carotenoids and specialty potatoes which had the higher levels of chlorogenic acid as compared to the other market classes. Variation in several molecules with known association to health was observed among market classes and included vitamins (e.g., pyridoxal, ~2-fold variation, bioactives (e.g., chlorogenic acid, ~40-fold variation, medicinals (e.g., kukoamines, ~6-fold variation, and minerals (e.g., calcium, iron, molybdenum, ~2-fold variation. Furthermore, more metabolite variation was observed within market class than among market class (e.g., α-tocopherol, ~1-fold variation among market class vs. ~3-fold variation within market class. Taken together, the analysis characterized significant metabolite and mineral variation in raw and cooked potato tuber, and support the potential to breed new cultivars for improved health traits.

  9. Metabolomics and Ionomics of Potato Tuber Reveals an Influence of Cultivar and Market Class on Human Nutrients and Bioactive Compounds

    Chaparro, Jacqueline M.; Holm, David G.; Broeckling, Corey D.; Prenni, Jessica E.; Heuberger, Adam L.

    2018-01-01

    Potato (Solanum tuberosum L.) is an important global food crop that contains phytochemicals with demonstrated effects on human health. Understanding sources of chemical variation of potato tuber can inform breeding for improved health attributes of the cooked food. Here, a comprehensive metabolomics (UPLC- and GC-MS) and ionomics (ICP-MS) analysis of raw and cooked potato tuber was performed on 60 unique potato genotypes that span 5 market classes including russet, red, yellow, chip, and specialty potatoes. The analyses detected 2,656 compounds that included known bioactives (43 compounds), nutrients (42), lipids (76), and 23 metals. Most nutrients and bioactives were partially degraded during cooking (44 out of 85; 52%), however genotypes with high quantities of bioactives remained highest in the cooked tuber. Chemical variation was influenced by genotype and market class. Specifically, ~53% of all detected compounds from cooked potato varied among market class and 40% varied by genotype. The most notable metabolite profiles were observed in yellow-flesh potato which had higher levels of carotenoids and specialty potatoes which had the higher levels of chlorogenic acid as compared to the other market classes. Variation in several molecules with known association to health was observed among market classes and included vitamins (e.g., pyridoxal, ~2-fold variation), bioactives (e.g., chlorogenic acid, ~40-fold variation), medicinals (e.g., kukoamines, ~6-fold variation), and minerals (e.g., calcium, iron, molybdenum, ~2-fold variation). Furthermore, more metabolite variation was observed within market class than among market class (e.g., α-tocopherol, ~1-fold variation among market class vs. ~3-fold variation within market class). Taken together, the analysis characterized significant metabolite and mineral variation in raw and cooked potato tuber, and support the potential to breed new cultivars for improved health traits. PMID:29876353

  10. Metabolomic and proteomic analysis of a clonal insulin-producing beta-cell line (INS-1 832/13).

    Fernandez, Céline; Fransson, Ulrika; Hallgard, Elna; Spégel, Peter; Holm, Cecilia; Krogh, Morten; Wårell, Kristofer; James, Peter; Mulder, Hindrik

    2008-01-01

    Metabolites generated from fuel metabolism in pancreatic beta-cells control exocytosis of insulin, a process which fails in type 2 diabetes. To identify and quantify these metabolites, global and unbiased analysis of cellular metabolism is required. To this end, polar metabolites, extracted from the clonal 832/13 beta-cell line cultured at 2.8 and 16.7 mM glucose for 48 h, were derivatized followed by identification and quantification, using gas chromatography (GC) and mass spectrometry (MS). After culture at 16.7 mM glucose for 48 h, 832/13 beta-cells exhibited a phenotype reminiscent of glucotoxicity with decreased content and secretion of insulin. The metabolomic analysis revealed alterations in the levels of 7 metabolites derived from glycolysis, the TCA cycle and pentose phosphate shunt, and 4 amino acids. Principal component analysis of the metabolite data showed two clusters, corresponding to the cells cultured at 2.8 and 16.7 mM glucose, respectively. Concurrent changes in protein expression were analyzed by 2-D gel electrophoresis followed by LC-MS/MS. The identities of 86 spots corresponding to 75 unique proteins that were significantly different in 832/13 beta-cells cultured at 16.7 mM glucose were established. Only 5 of these were found to be metabolic enzymes that could be involved in the metabolomic alterations observed. Anticipated changes in metabolite levels in cells exposed to increased glucose were observed, while changes in enzyme levels were much less profound. This suggests that substrate availability, allosteric regulation, and/or post-translational modifications are more important determinants of metabolite levels than enzyme expression at the protein level.

  11. Identification of putative biomarkers for prediabetes by metabolome analysis of rat models of type 2 diabetes

    Yokoi, Norihide; Beppu, Masayuki; Yoshida, Eri; Hoshikawa, Ritsuko; Hidaka, Shihomi; Matsubara, Toshiya; Shinohara, Masami; Irino, Yasuhiro; Hatano, Naoya; Seino, Susumu

    2015-01-01

    Biomarkers for the development of type 2 diabetes (T2D) are useful for prediction and intervention of the disease at earlier stages. In this study, we performed a longitudinal study of changes in metabolites using an animal model of T2D, the spontaneously diabetic Torii (SDT) rat. Fasting plasma samples of SDT and control Sprague-Dawley (SD) rats were collected from 6 to 24 weeks of age, and subjected to gas chromatography–mass spectrometry-based metabolome analysis. Fifty-nine hydrophilic me...

  12. Bioinformatics tools for the analysis of NMR metabolomics studies focused on the identification of clinically relevant biomarkers.

    Puchades-Carrasco, Leonor; Palomino-Schätzlein, Martina; Pérez-Rambla, Clara; Pineda-Lucena, Antonio

    2016-05-01

    Metabolomics, a systems biology approach focused on the global study of the metabolome, offers a tremendous potential in the analysis of clinical samples. Among other applications, metabolomics enables mapping of biochemical alterations involved in the pathogenesis of diseases, and offers the opportunity to noninvasively identify diagnostic, prognostic and predictive biomarkers that could translate into early therapeutic interventions. Particularly, metabolomics by Nuclear Magnetic Resonance (NMR) has the ability to simultaneously detect and structurally characterize an abundance of metabolic components, even when their identities are unknown. Analysis of the data generated using this experimental approach requires the application of statistical and bioinformatics tools for the correct interpretation of the results. This review focuses on the different steps involved in the metabolomics characterization of biofluids for clinical applications, ranging from the design of the study to the biological interpretation of the results. Particular emphasis is devoted to the specific procedures required for the processing and interpretation of NMR data with a focus on the identification of clinically relevant biomarkers. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  13. Genome sequencing reveals complex secondary metabolome in themarine actinomycete Salinispora tropica

    Udwary, Daniel W.; Zeigler, Lisa; Asolkar, Ratnakar; Singan,Vasanth; Lapidus, Alla; Fenical, William; Jensen, Paul R.; Moore, BradleyS.

    2007-05-01

    Recent fermentation studies have identified actinomycetes ofthe marine-dwelling genus Salinispora as prolific natural productproducers. To further evaluate their biosynthetic potential, we analyzedall identifiable secondary natural product gene clusters from therecently sequenced 5,184,724 bp S. tropica CNB-440 circular genome. Ouranalysis shows that biosynthetic potential meets or exceeds that shown byprevious Streptomyces genome sequences as well as other naturalproduct-producing actinomycetes. The S. tropica genome features ninepolyketide synthase systems of every known formally classified family,non-ribosomal peptide synthetases and several hybrid clusters. While afew clusters appear to encode molecules previously identified inStreptomyces species,the majority of the 15 biosynthetic loci are novel.Specific chemical information about putative and observed natural productmolecules is presented and discussed. In addition, our bioinformaticanalysis was critical for the structure elucidation of the novelpolyenemacrolactam salinilactam A. This study demonstrates the potentialfor genomic analysis to complement and strengthen traditional naturalproduct isolation studies and firmly establishes the genus Salinispora asa rich source of novel drug-like molecules.

  14. Metabolomics Reveals Metabolically Healthy and Unhealthy Obese Individuals Differ in their Response to a Caloric Challenge.

    Flavia Badoud

    Full Text Available To determine if metabolically healthy obese (MHO individuals have a different metabolic response to a standardized diet compared to lean healthy (LH and metabolically unhealthy obese (MUO individuals.Thirty adults (35-70 yrs were classified as LH, MHO, and MUO according to anthropometric and clinical measurements. Participants consumed a standardized high calorie meal (~1330 kcal. Blood glucose and insulin were measured at fasting, and 15, 30, 60, 90 and 120 min postprandially. Additional blood samples were collected for the targeted analysis of amino acids (AAs and derivatives, and fatty acids (FAs.The postprandial response (i.e., area under the curve, AUC for serum glucose and insulin were similar between MHO and LH individuals, and significantly lower than MUO individuals (p < 0.05. Minor differences were found in postprandial responses for AAs between MHO and MUO individuals, while three polyunsaturated FAs (linoleic acid, γ-linolenic acid, arachidonic acid showed smaller changes in serum after the meal in MHO individuals compared to MUO. Fasting levels for various AAs (notably branched-chain AA and FAs (e.g., saturated myristic and palmitic acids were found to correlate with glucose and insulin AUC.MHO individuals show preserved insulin sensitivity and a greater ability to adapt to a caloric challenge compared to MUO individuals.

  15. 1H NMR-based serum metabolomics reveals erythromycin-induced liver toxicity in albino Wistar rats

    Atul Rawat

    2016-01-01

    Full Text Available Introduction: Erythromycin (ERY is known to induce hepatic toxicity which mimics other liver diseases. Thus, ERY is often used to produce experimental models of drug-induced liver-toxicity. The serum metabolic profiles can be used to evaluate the liver-toxicity and to further improve the understanding of underlying mechanism. Objective: To establish the serum metabolic patterns of Erythromycin induced hepatotoxicity in albino wistar rats using 1H NMR based serum metabolomics. Experimental: Fourteen male rats were randomly divided into two groups (n = 7 in each group: control and ERY treated. After 28 days of intervention, the metabolic profiles of sera obtained from ERY and control groups were analyzed using high-resolution 1D 1H CPMG and diffusion-edited nuclear magnetic resonance (NMR spectra. The histopathological and SEM examinations were employed to evaluate the liver toxicity in ERY treated group. Results: The serum metabolic profiles of control and ERY treated rats were compared using multivariate statistical analysis and the metabolic patterns specific to ERY-induced liver toxicity were established. The toxic response of ERY was characterized with: (a increased serum levels of Glucose, glutamine, dimethylamine, malonate, choline, phosphocholine and phospholipids and (b decreased levels of isoleucine, leucine, valine, alanine, glutamate, citrate, glycerol, lactate, threonine, circulating lipoproteins, N-acetyl glycoproteins, and poly-unsaturated lipids. These metabolic alterations were found to be associated with (a decreased TCA cycle activity and enhanced fatty acid oxidation, (b dysfunction of lipid and amino acid metabolism and (c oxidative stress. Conclusion and Recommendations: Erythromycin is often used to produce experimental models of liver toxicity; therefore, the established NMR-based metabolic patterns will form the basis for future studies aiming to evaluate the efficacy of anti-hepatotoxic agents or the hepatotoxicity of new

  16. Biomarker Identification and Pathway Analysis by Serum Metabolomics of Lung Cancer

    Yingrong Chen

    2015-01-01

    Full Text Available Lung cancer is one of the most common causes of cancer death, for which no validated tumor biomarker is sufficiently accurate to be useful for diagnosis. Additionally, the metabolic alterations associated with the disease are unclear. In this study, we investigated the construction, interaction, and pathways of potential lung cancer biomarkers using metabolomics pathway analysis based on the Kyoto Encyclopedia of Genes and Genomes database and the Human Metabolome Database to identify the top altered pathways for analysis and visualization. We constructed a diagnostic model using potential serum biomarkers from patients with lung cancer. We assessed their specificity and sensitivity according to the area under the curve of the receiver operator characteristic (ROC curves, which could be used to distinguish patients with lung cancer from normal subjects. The pathway analysis indicated that sphingolipid metabolism was the top altered pathway in lung cancer. ROC curve analysis indicated that glycerophospho-N-arachidonoyl ethanolamine (GpAEA and sphingosine were potential sensitive and specific biomarkers for lung cancer diagnosis and prognosis. Compared with the traditional lung cancer diagnostic biomarkers carcinoembryonic antigen and cytokeratin 19 fragment, GpAEA and sphingosine were as good or more appropriate for detecting lung cancer. We report our identification of potential metabolic diagnostic and prognostic biomarkers of lung cancer and clarify the metabolic alterations in lung cancer.

  17. Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

    Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

    2016-08-12

    Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a Subcohort from the PREDIMED study.

    Madrid-Gambin, Francisco; Llorach, Rafael; Vázquez-Fresno, Rosa; Urpi-Sarda, Mireia; Almanza-Aguilera, Enrique; Garcia-Aloy, Mar; Estruch, Ramon; Corella, Dolores; Andres-Lacueva, Cristina

    2017-04-07

    Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils, and beans), spot urine samples from a subcohort from the PREDIMED study were stratified using a validated food frequency questionnaire. Urine samples of nonpulse consumers (≤4 g/day of pulse intake) and habitual pulse consumers (≥25 g/day of pulse intake) were analyzed using a 1 H nuclear magnetic resonance (NMR) metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through 16 metabolites coming from (i) choline metabolism, (ii) protein-related compounds, and (iii) energy metabolism (including lower urinary glucose). Stepwise logistic regression analysis was applied to design a combined model of pulse exposure, which resulted in glutamine, dimethylamine, and 3-methylhistidine. This model was evaluated by a receiver operating characteristic curve (AUC > 90% in both training and validation sets). The application of NMR-based metabolomics to reported pulse exposure highlighted new candidates for biomarkers of pulse consumption and the impact on energy metabolism, generating new hypotheses on energy modulation. Further intervention studies will confirm these findings.

  19. Lipidome and metabolome analysis of fresh tobacco leaves in different geographical regions using liquid chromatography-mass spectrometry.

    Li, Lili; Lu, Xin; Zhao, Jieyu; Zhang, Junjie; Zhao, Yanni; Zhao, Chunxia; Xu, Guowang

    2015-07-01

    The combination of the lipidome and the metabolome can provide much more information in plant metabolomics studies. A method for the simultaneous extraction of the lipidome and the metabolome of fresh tobacco leaves was developed. Method validation was performed on the basis of the optimal ratio of methanol to methyl tert-butyl ether to water (37:45:68) from the design of experiments. Good repeatability was obtained. We found that 92.2% and 91.6% of the peaks for the lipidome and the metabolome were within a relative standard deviation of 20%, accounting for 94.6% and 94.6% of the total abundance, respectively. The intraday and interday precisions were also satisfactory. A total of 230 metabolites, including 129 lipids, were identified. Significant differences were found in lipidomic and metabolomic profiles of fresh tobacco leaves in different geographical regions. Highly unsaturated galactolipids, phosphatidylethanolamines, predominant phosphatidylcholines, most of the polyphenols, amino acids, and polyamines had a higher content in Yunnan province, and low-unsaturation-degree galactolipids, triacylglycerols, glucosylceramides with trihydroxy long-chain bases, acylated sterol glucosides, and some organic acids were more abundant in Henan province. Correlation analysis between differential metabolites and climatic factors indicated the vital importance of temperature. The fatty acid unsaturation degree of galactolipids could be influenced by temperature. Accumulation of polyphenols and decreases in the ratios of stigmasterols to sitosterols and glucosylstigmasterols to glucosylsitosterols were also correlated with lower temperature in Yunnan province. Furthermore, lipids were more sensitive to climatic variations than other metabolites.

  20. Metabolomics Analysis of the Toxic Effects of the Production of Lycopene and Its Precursors

    April M. Miguez

    2018-05-01

    Full Text Available Using cells as microbial factories enables highly specific production of chemicals with many advantages over chemical syntheses. A number of exciting new applications of this approach are in the area of precision metabolic engineering, which focuses on improving the specificity of target production. In recent work, we have used precision metabolic engineering to design lycopene-producing Escherichia coli for use as a low-cost diagnostic biosensor. To increase precursor availability and thus the rate of lycopene production, we heterologously expressed the mevalonate pathway. We found that simultaneous induction of these pathways increases lycopene production, but induction of the mevalonate pathway before induction of the lycopene pathway decreases both lycopene production and growth rate. Here, we aim to characterize the metabolic changes the cells may be undergoing during expression of either or both of these heterologous pathways. After establishing an improved method for quenching E. coli for metabolomics analysis, we used two-dimensional gas chromatography coupled to mass spectrometry (GCxGC-MS to characterize the metabolomic profile of our lycopene-producing strains in growth conditions characteristic of our biosensor application. We found that the metabolic impacts of producing low, non-toxic levels of lycopene are of much smaller magnitude than the typical metabolic changes inherent to batch growth. We then used metabolomics to study differences in metabolism caused by the time of mevalonate pathway induction and the presence of the lycopene biosynthesis genes. We found that overnight induction of the mevalonate pathway was toxic to cells, but that the cells could recover if the lycopene pathway was not also heterologously expressed. The two pathways appeared to have an antagonistic metabolic effect that was clearly reflected in the cells’ metabolic profiles. The metabolites homocysteine and homoserine exhibited particularly interesting

  1. 1D-¹H-nuclear magnetic resonance metabolomics reveals age-related changes in metabolites associated with experimental venous thrombosis.

    Obi, Andrea T; Stringer, Kathleen A; Diaz, Jose A; Finkel, Michael A; Farris, Diana M; Yeomans, Larisa; Wakefield, Thomas; Myers, Daniel D

    2016-04-01

    Age is a significant risk factor for the development of venous thrombosis (VT), but the mechanism(s) that underlie this risk remain(s) undefined and poorly understood. Aging is known to adversely influence inflammation and affect metabolism. Untargeted metabolomics permits an agnostic assessment of the physiological landscape and lends insight into the mechanistic underpinnings of clinical phenotypes. The objective of this exploratory study was to test the feasibility of a metabolomics approach for identifying potential metabolic mechanisms of age-related VT. We subjected whole blood samples collected from young and old nonthrombosed controls and VT mice 2 days after thrombus induction using the electrolytic inferior vena cava, to a methanol:chloroform extraction and assayed the resulting aqueous fractions using 1D-(1)H- nuclear magnetic resonance. Normalized mouse metabolite data were compared across groups using analysis of variance (ANOVA) with Holm-Sidak post-testing. In addition, associations between metabolite concentrations and parameters of thrombosis such as thrombus and vein wall weights, and markers of inflammation, vein wall P- and E-selectin levels, were assessed using linear regression. The relatedness of the found significant metabolites was visually assessed using a bioinformatics tool, Metscape, which generates compound-reaction-enzyme-gene networks to aid in the interpretation of metabolomics data. Old mice with VT had a greater mean vein wall weight compared with young mice with VT (P metabolomics as a new approach to furthering knowledge about the mechanisms of age-related VT. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  2. Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

    Choi, Young Hae; Sertic, Sarah; Kim, Hye Kyong; Wilson, Erica G; Michopoulos, Filippos; Lefeber, Alfons W M; Erkelens, Cornelis; Prat Kricun, Sergio D; Verpoorte, Robert

    2005-02-23

    The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

  3. Analysis of metabolomic patterns in thoroughbreds before and after exercise

    Hyun-Jun Jang

    2017-11-01

    Full Text Available Objective Evaluation of exercise effects in racehorses is important in horseracing industry and animal health care. In this study, we compared metabolic patterns between before and after exercise to screen metabolic biomarkers for exercise effects in thoroughbreds. Methods The concentration of metabolites in muscle, plasma, and urine was measured by 1H nuclear magnetic resonance (NMR spectroscopy analysis and the relative metabolite levels in the three samples were compared between before and after exercise. Subsequently, multivariate data analysis based on the metabolic profiles was performed using orthogonal partial least square discriminant analysis (OPLS-DA and variable important plots and t-test was used for basic statistical analysis. Results From 1H NMR spectroscopy analysis, 35, 25, and 34 metabolites were detected in the muscle, plasma, and urine. Aspartate, betaine, choline, cysteine, ethanol, and threonine were increased over 2-fold in the muscle; propionate and trimethylamine were increased over 2-fold in the plasma; and alanine, glycerol, inosine, lactate, and pyruvate were increased over 2-fold whereas acetoacetate, arginine, citrulline, creatine, glutamine, glutarate, hippurate, lysine, methionine, phenylacetylglycine, taurine, trigonelline, trimethylamine, and trimethylamine N-oxide were decreased below 0.5-fold in the urine. The OPLS-DA showed clear separation of the metabolic patterns before and after exercise in the muscle, plasma, and urine. Statistical analysis showed that after exercise, acetoacetate, arginine, glutamine, hippurate, phenylacetylglycine trimethylamine, trimethylamine N-oxide, and trigonelline were significantly decreased and alanine, glycerol, inosine, lactate, and pyruvate were significantly increased in the urine (p<0.05. Conclusion In conclusion, we analyzed integrated metabolic patterns in the muscle, plasma, and urine before and after exercise in racehorses. We found changed patterns of metabolites in

  4. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

    Jumpei Washio

    2016-06-01

    Full Text Available Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

  5. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond.

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-06-02

    Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the 'Warburg effect'. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

  6. Interoperable and scalable metabolomics data analysis with microservices

    Van Vliet, Michael; Ruttkies, Christoph; Steinbeck, Christoph; Burman, Joachim; Bergmann, Sven; Moreno, Pablo; Khoonsari, Payam; Rueedi, Rico; Roger, Pierrick; Rocca-Serra, Philippe; Pireddu, Luca; Salek, Reza; Sansone, Susanna-Assunta; Schober, Daniel; Peters, Kristian

    2017-01-01

    Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed in parallel using the Kubernetes container orchestrator. The access point is a virtual research environment which can be lau...

  7. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites.

    Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C

    2016-09-30

    Fusarium head blight (FHB), primarily caused by Fusarium graminearum , is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum , such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

  8. Comparative metabolomics in vanilla pod and vanilla bean revealing the biosynthesis of vanillin during the curing process of vanilla.

    Gu, Fenglin; Chen, Yonggan; Hong, Yinghua; Fang, Yiming; Tan, Lehe

    2017-12-01

    High-performance liquid chromatography-mass spectrometry (LC-MS) was used for comprehensive metabolomic fingerprinting of vanilla fruits prepared from the curing process. In this study, the metabolic changes of vanilla pods and vanilla beans were characterized using MS-based metabolomics to elucidate the biosynthesis of vanillin. The vanilla pods were significantly different from vanilla beans. Seven pathways of vanillin biosynthesis were constructed, namely, glucovanillin, glucose, cresol, capsaicin, vanillyl alcohol, tyrosine, and phenylalanine pathways. Investigations demonstrated that glucose, cresol, capsaicin, and vanillyl alcohol pathway were detected in a wide range of distribution in microbial metabolism. Thus, microorganisms might have participated in vanillin biosynthesis during vanilla curing. Furthermore, the ion strength of glucovanillin was stable, which indicated that glucovanillin only participated in the vanillin biosynthesis during the curing of vanilla.

  9. Statistical analysis of proteomics, metabolomics, and lipidomics data using mass spectrometry

    Mertens, Bart

    2017-01-01

    This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass ...

  10. Metabolome analysis of effect of aspirin on Drosophila lifespan extension.

    Song, Chaochun; Zhu, Chenxing; Wu, Qi; Qi, Jiancheng; Gao, Yue; Zhang, Zhichao; Gaur, Uma; Yang, Deying; Fan, Xiaolan; Yang, Mingyao

    2017-09-01

    Effective approaches for drug development involve the repurposing of existing drugs which are already approved by the FDA. Aspirin has been shown to have many health benefits since its discovery as a nonsteroidal anti-inflammatory drug (NSAID) to treat pain and inflammation. Recent experiments demonstrated the longevity effects of aspirin in Drosophila, but its mechanism remains to be explored. In order to elucidate the effects of drug on metabolism, we carried out the metabolic analysis of aspirin-treated flies. The results identified 404 active metabolites in addition to the extended lifespan and improved healthspan in fly. There were 28 metabolites having significant changes between aspirin-treated group and the control group, out of which 22 compounds were found to have detailed information. These compounds are reported to have important functions in energy metabolism, amino sugar metabolism, and urea metabolism, indicating that aspirin might be playing positive roles in the fly's lifespan and healthspan improvement. Because of the conservation of major longevity pathways and mechanisms in different species, the health benefits of aspirin administration could be extended to other animals and humans as well. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Current metabolomics: technological advances.

    Putri, Sastia P; Yamamoto, Shinya; Tsugawa, Hiroshi; Fukusaki, Eiichiro

    2013-07-01

    Metabolomics, the global quantitative assessment of metabolites in a biological system, has played a pivotal role in various fields of science in the post-genomic era. Metabolites are the result of the interaction of the system's genome with its environment and are not merely the end product of gene expression, but also form part of the regulatory system in an integrated manner. Therefore, metabolomics is often considered a powerful tool to provide an instantaneous snapshot of the physiology of a cell. The power of metabolomics lies on the acquisition of analytical data in which metabolites in a cellular system are quantified, and the extraction of the most meaningful elements of the data by using various data analysis tool. In this review, we discuss the latest development of analytical techniques and data analyses methods in metabolomics study. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  12. Analysis of sequential hair segments reflects changes in the metabolome across the trimesters of pregnancy

    Delplancke, Thibaut D J; de Seymour, Jamie V; Tong, Chao

    2018-01-01

    The hair metabolome has been recognized as a valuable source of information in pregnancy research, as it provides stable metabolite information that could assist with studying biomarkers or metabolic mechanisms of pregnancy and its complications. We tested the hypothesis that hair segments could...... mellitus (p metabolome during pregnancy, as well as highlight the potential of the maternal hair metabolome to differentiate pregnancy complications from healthy pregnancies....

  13. Hierarchical cluster analysis of technical replicates to identify interferents in untargeted mass spectrometry metabolomics.

    Caesar, Lindsay K; Kvalheim, Olav M; Cech, Nadja B

    2018-08-27

    Mass spectral data sets often contain experimental artefacts, and data filtering prior to statistical analysis is crucial to extract reliable information. This is particularly true in untargeted metabolomics analyses, where the analyte(s) of interest are not known a priori. It is often assumed that chemical interferents (i.e. solvent contaminants such as plasticizers) are consistent across samples, and can be removed by background subtraction from blank injections. On the contrary, it is shown here that chemical contaminants may vary in abundance across each injection, potentially leading to their misidentification as relevant sample components. With this metabolomics study, we demonstrate the effectiveness of hierarchical cluster analysis (HCA) of replicate injections (technical replicates) as a methodology to identify chemical interferents and reduce their contaminating contribution to metabolomics models. Pools of metabolites with varying complexity were prepared from the botanical Angelica keiskei Koidzumi and spiked with known metabolites. Each set of pools was analyzed in triplicate and at multiple concentrations using ultraperformance liquid chromatography coupled to mass spectrometry (UPLC-MS). Before filtering, HCA failed to cluster replicates in the data sets. To identify contaminant peaks, we developed a filtering process that evaluated the relative peak area variance of each variable within triplicate injections. These interferent peaks were found across all samples, but did not show consistent peak area from injection to injection, even when evaluating the same chemical sample. This filtering process identified 128 ions that appear to originate from the UPLC-MS system. Data sets collected for a high number of pools with comparatively simple chemical composition were highly influenced by these chemical interferents, as were samples that were analyzed at a low concentration. When chemical interferent masses were removed, technical replicates clustered in

  14. System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism

    Lei Wang

    2017-06-01

    Full Text Available Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other

  15. System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism.

    Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

    2017-01-01

    Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed

  16. Metabolomics by proton nuclear magnetic resonance spectroscopy of the response to chloroethylnitrosourea reveals drug efficacy and tumor adaptive metabolic pathways.

    Morvan, Daniel; Demidem, Aicha

    2007-03-01

    Metabolomics of tumors may allow discovery of tumor biomarkers and metabolic therapeutic targets. Metabolomics by two-dimensional proton high-resolution magic angle spinning nuclear magnetic resonance spectroscopy was applied to investigate metabolite disorders following treatment by chloroethylnitrosourea of murine B16 melanoma (n = 33) and 3LL pulmonary carcinoma (n = 31) in vivo. Treated tumors of both types resumed growth after a delay. Nitrosoureas provoke DNA damage but the metabolic consequences of genotoxic stress are little known yet. Although some differences were observed in the metabolite profile of untreated tumor types, the prominent metabolic features of the response to nitrosourea were common to both. During the growth inhibition phase, there was an accumulation of glucose (more than x10; P < 0.05), glutamine (x3 to 4; P < 0.01), and aspartate (x2 to 5; P < 0.01). This response testified to nucleoside de novo synthesis down-regulation and drug efficacy. However, this phase also involved the increase in alanine (P < 0.001 in B16 melanoma), the decrease in succinate (P < 0.001), and the accumulation of serine-derived metabolites (glycine, phosphoethanolamine, and formate; P < 0.01). This response witnessed the activation of pathways implicated in energy production and resumption of nucleotide de novo synthesis, thus metabolic pathways of DNA repair and adaptation to treatment. During the growth recovery phase, it remained polyunsaturated fatty acid accumulation (x1.5 to 2; P < 0.05) and reduced utilization of glucose compared with glutamine (P < 0.05), a metabolic fingerprint of adaptation. Thus, this study provides the proof of principle that metabolomics of tumor response to an anticancer agent may help discover metabolic pathways of drug efficacy and adaptation to treatment.

  17. Metabolomics analysis and modeling suggest a lysophosphocholines-PAF receptor interaction in fibromyalgia.

    Pierluigi Caboni

    Full Text Available Fibromyalgia Syndrome (FMS is a chronic disease characterized by widespread pain, and difficult to diagnose and treat. We analyzed the plasma metabolic profile of patients with FMS by using a metabolomics approach combining Liquid Chromatography-Quadrupole-Time Of Flight/Mass Spectrometry (LC-Q-TOF/MS with multivariate statistical analysis, aiming to discriminate patients and controls. LC-Q-TOF/MS analysis of plasma (FMS patients: n = 22 and controls: n = 21 identified many lipid compounds, mainly lysophosphocholines (lysoPCs, phosphocholines and ceramides. Multivariate statistical analysis was performed to identify the discriminating metabolites. A protein docking and molecular dynamic (MD study was then performed, using the most discriminating lysoPCs, to validate the binding to Platelet Activating Factor (1-alkyl-2-acetyl-sn-glycero-3-phosphocholine, PAF Receptor (PAFr. Discriminating metabolites between FMS patients and controls were identified as 1-tetradecanoyl-sn-glycero-3-phosphocholine [PC(14:0/0:0] and 1-hexadecanoyl-sn-glycero-3-phosphocholine [PC(16:0/0:0]. MD and docking indicate that the ligands investigated have similar potentialities to activate the PAFr receptor. The application of a metabolomic approach discriminated FMS patients from controls, with an over-representation of PC(14:0/0:0 and PC(16:0/0:0 compounds in the metabolic profiles. These results and the modeling of metabolite-PAFr interaction, allowed us to hypothesize that lipids oxidative fragmentation might generate lysoPCs in abundance, that in turn will act as PAF-like bioactivators. Overall results suggest disease biomarkers and potential therapeutical targets for FMS.

  18. LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

    Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

    2012-03-01

    MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

  19. Role of metabolomics in TBI research

    Wolahan, Stephanie M.; Hirt, Daniel; Braas, Daniel; Glenn, Thomas C.

    2016-01-01

    Synopsis Metabolomics is an important member of the omics community in that it defines which small molecules may be responsible for disease states. This article reviews the essential principles of metabolomics from specimen preparation, chemical analysis, and advanced statistical methods. Metabolomics in TBI has so far been underutilized. Future metabolomics based studies focused on the diagnoses, prognoses, and treatment effects, need to be conducted across all types of TBI. PMID:27637396

  20. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods.

    Boaz, Segal M; Champagne, Cory D; Fowler, Melinda A; Houser, Dorian H; Crocker, Daniel E

    2012-02-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to 7 weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. Copyright © 2011 Elsevier Inc. All rights reserved.

  1. Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods

    Boaz, Segal M.; Champagne, Cory D.; Fowler, Melinda A.; Houser, Dorian H.; Crocker, Daniel E.

    2011-01-01

    Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to seven weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. PMID:21983145

  2. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Associations of Nasopharyngeal Metabolome and Microbiome with Severity among Infants with Bronchiolitis. A Multiomic Analysis.

    Stewart, Christopher J; Mansbach, Jonathan M; Wong, Matthew C; Ajami, Nadim J; Petrosino, Joseph F; Camargo, Carlos A; Hasegawa, Kohei

    2017-10-01

    Bronchiolitis is the most common lower respiratory infection in infants; however, it remains unclear which infants with bronchiolitis will develop severe illness. In addition, although emerging evidence indicates associations of the upper-airway microbiome with bronchiolitis severity, little is known about the mechanisms linking airway microbes and host response to disease severity. To determine the relations among the nasopharyngeal airway metabolome profiles, microbiome profiles, and severity in infants with bronchiolitis. We conducted a multicenter prospective cohort study of infants (age metabolomic and metagenomic (16S ribosomal RNA gene and whole-genome shotgun sequencing) approaches to 144 nasopharyngeal airway samples collected within 24 hours of hospitalization, we determined metabolome and microbiome profiles and their association with higher severity, defined by the use of positive pressure ventilation (i.e., continuous positive airway pressure and/or intubation). Nasopharyngeal airway metabolome profiles significantly differed by bronchiolitis severity (P metabolomics to predict bronchiolitis severity and better understand microbe-host interaction.

  4. Untargeted metabolomics of colonic digests reveals kynurenine pathway metabolites, dityrosine and 3-dehydroxycarnitine as red versus white meat discriminating metabolites

    Rombouts, Caroline; Hemeryck, Lieselot Y.; Van Hecke, Thomas; De Smet, Stefaan; De Vos, Winnok H.; Vanhaecke, Lynn

    2017-01-01

    Epidemiological research has demonstrated that the consumption of red meat is an important risk factor for the development of colorectal cancer (CRC), diabetes mellitus and cardiovascular diseases. However, there is no holistic insight in the (by-) products of meat digestion that may contribute to disease development. To address this hiatus, an untargeted mass spectrometry (MS)-based metabolomics approach was used to create red versus white meat associated metabolic fingerprints following in vitro colonic digestion using the fecal inocula of ten healthy volunteers. Twenty-two metabolites were unequivocally associated with simulated colonic digestion of red meat. Several of these metabolites could mechanistically be linked to red meat-associated pathways including N’-formylkynurenine, kynurenine and kynurenic acid (all involved in tryptophan metabolism), the oxidative stress marker dityrosine, and 3-dehydroxycarnitine. In conclusion, the used MS-based metabolomics platform proved to be a powerful platform for detection of specific metabolites that improve the understanding of the causal relationship between red meat consumption and associated diseases. PMID:28195169

  5. Comparative metabolomics reveals endogenous ligands of DAF-12, a nuclear hormone receptor regulating C. elegans development and lifespan

    Mahanti, Parag; Bose, Neelanjan; Bethke, Axel; Judkins, Joshua C.; Wollam, Joshua; Dumas, Kathleen J.; Zimmerman, Anna M.; Campbell, Sydney L.; Hu, Patrick J.; Antebi, Adam; Schroeder, Frank C.

    2014-01-01

    SUMMARY Small-molecule ligands of nuclear hormone receptors (NHRs) govern the transcriptional regulation of metazoan development, cell differentiation, and metabolism. However, the physiological ligands of many NHRs remain poorly characterized primarily due to lack of robust analytical techniques. Using comparative metabolomics, we identified endogenous steroids that act as ligands of the C. elegans NHR, DAF-12, a vitamin-D and liver-X receptor homolog regulating larval development, fat metabolism, and lifespan. The identified molecules feature unexpected chemical modifications and include only one of two DAF-12 ligands reported earlier, necessitating a revision of previously proposed ligand biosynthetic pathways. We further show that ligand profiles are regulated by a complex enzymatic network including the Rieske oxygenase DAF-36, the short-chain dehydrogenase DHS-16, and the hydroxysteroid dehydrogenase, HSD-1. Our results demonstrate the advantages of comparative metabolomics over traditional candidate-based approaches and provide a blueprint for the identification of ligands for other C. elegans and mammalian NHRs. PMID:24411940

  6. Metabolome analysis-based design and engineering of a metabolic pathway in Corynebacterium glutamicum to match rates of simultaneous utilization of D-glucose and L-arabinose.

    Kawaguchi, Hideo; Yoshihara, Kumiko; Hara, Kiyotaka Y; Hasunuma, Tomohisa; Ogino, Chiaki; Kondo, Akihiko

    2018-05-17

    L-Arabinose is the second most abundant component of hemicellulose in lignocellulosic biomass, next to D-xylose. However, few microorganisms are capable of utilizing pentoses, and catabolic genes and operons enabling bacterial utilization of pentoses are typically subject to carbon catabolite repression by more-preferred carbon sources, such as D-glucose, leading to a preferential utilization of D-glucose over pentoses. In order to simultaneously utilize both D-glucose and L-arabinose at the same rate, a modified metabolic pathway was rationally designed based on metabolome analysis. Corynebacterium glutamicum ATCC 31831 utilized D-glucose and L-arabinose simultaneously at a low concentration (3.6 g/L each) but preferentially utilized D-glucose over L-arabinose at a high concentration (15 g/L each), although L-arabinose and D-glucose were consumed at comparable rates in the absence of the second carbon source. Metabolome analysis revealed that phosphofructokinase and pyruvate kinase were major bottlenecks for D-glucose and L-arabinose metabolism, respectively. Based on the results of metabolome analysis, a metabolic pathway was engineered by overexpressing pyruvate kinase in combination with deletion of araR, which encodes a repressor of L-arabinose uptake and catabolism. The recombinant strain utilized high concentrations of D-glucose and L-arabinose (15 g/L each) at the same consumption rate. During simultaneous utilization of both carbon sources at high concentrations, intracellular levels of phosphoenolpyruvate declined and acetyl-CoA levels increased significantly as compared with the wild-type strain that preferentially utilized D-glucose. These results suggest that overexpression of pyruvate kinase in the araR deletion strain increased the specific consumption rate of L-arabinose and that citrate synthase activity becomes a new bottleneck in the engineered pathway during the simultaneous utilization of D-glucose and L-arabinose. Metabolome analysis

  7. Metabolomic Profiling of Plasma from Patients with Tuberculosis by Use of Untargeted Mass Spectrometry Reveals Novel Biomarkers for Diagnosis.

    Lau, Susanna K P; Lee, Kim-Chung; Curreem, Shirly O T; Chow, Wang-Ngai; To, Kelvin K W; Hung, Ivan F N; Ho, Deborah T Y; Sridhar, Siddharth; Li, Iris W S; Ding, Vanessa S Y; Koo, Eleanor W F; Wong, Chi-Fong; Tam, Sidney; Lam, Ching-Wan; Yuen, Kwok-Yung; Woo, Patrick C Y

    2015-12-01

    Although tuberculosis (TB) is a reemerging disease that affects people in developing countries and immunocompromised populations in developed countries, the current diagnostic methods are far from optimal. Metabolomics is increasingly being used for studies on infectious diseases. We performed metabolome profiling of plasma samples to identify potential biomarkers for diagnosing TB. We compared the plasma metabolome profiles of TB patients (n = 46) with those of community-acquired pneumonia (CAP) patients (n = 30) and controls without active infection (n = 30) using ultrahigh-performance liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (UHPLC-ESI-QTOFMS). Using multivariate and univariate analyses, four metabolites, 12R-hydroxy-5Z,8Z,10E,14Z-eicosatetraenoic acid [12(R)-HETE], ceramide (d18:1/16:0), cholesterol sulfate, and 4α-formyl-4β-methyl-5α-cholesta-8-en-3β-ol, were identified and found to have significantly higher levels in TB patients than those in CAP patients and controls. In a comparison of TB patients and controls, the four metabolites demonstrated area under the receiver operating characteristic curve (AUC) values of 0.914, 0.912, 0.905, and 0.856, sensitivities of 84.8%, 84.8%, 87.0%, and 89.1%, specificities of 90.0%, 86.7%, 86.7%, and 80.0%, and fold changes of 4.19, 26.15, 6.09, and 1.83, respectively. In a comparison of TB and CAP patients, the four metabolites demonstrated AUC values of 0.793, 0.717, 0.802, and 0.894, sensitivities of 89.1%, 71.7%, 80.4%, and 84.8%, specificities of 63.3%, 66.7%, 70.0%, and 83.3%, and fold changes of 4.69, 3.82, 3.75, and 2.16, respectively. 4α-Formyl-4β-methyl-5α-cholesta-8-en-3β-ol combined with 12(R)-HETE or cholesterol sulfate offered ≥70% sensitivity and ≥90% specificity for differentiating TB patients from controls or CAP patients. These novel plasma biomarkers, especially 12(R)-HETE and 4α-formyl-4β-methyl-5α-cholesta-8-en-3β-ol, alone or in

  8. Nanoparticle-Assisted Metabolomics

    Bo Zhang

    2018-03-01

    Full Text Available Understanding and harnessing the interactions between nanoparticles and biological molecules is at the forefront of applications of nanotechnology to modern biology. Metabolomics has emerged as a prominent player in systems biology as a complement to genomics, transcriptomics and proteomics. Its focus is the systematic study of metabolite identities and concentration changes in living systems. Despite significant progress over the recent past, important challenges in metabolomics remain, such as the deconvolution of the spectra of complex mixtures with strong overlaps, the sensitive detection of metabolites at low abundance, unambiguous identification of known metabolites, structure determination of unknown metabolites and standardized sample preparation for quantitative comparisons. Recent research has demonstrated that some of these challenges can be substantially alleviated with the help of nanoscience. Nanoparticles in particular have found applications in various areas of bioanalytical chemistry and metabolomics. Their chemical surface properties and increased surface-to-volume ratio endows them with a broad range of binding affinities to biomacromolecules and metabolites. The specific interactions of nanoparticles with metabolites or biomacromolecules help, for example, simplify metabolomics spectra, improve the ionization efficiency for mass spectrometry or reveal relationships between spectral signals that belong to the same molecule. Lessons learned from nanoparticle-assisted metabolomics may also benefit other emerging areas, such as nanotoxicity and nanopharmaceutics.

  9. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites

  10. Recent breakthroughs in metabolomics promise to reveal the cryptic chemical traits that mediate plant community composition, character evolution and lineage diversification.

    Sedio, Brian E

    2017-05-01

    Contents 952 I. 952 II. 953 III. 955 IV. 956 V. 957 957 References 957 SUMMARY: Much of our understanding of the mechanisms by which biotic interactions shape plant communities has been constrained by the methods available to study the diverse secondary chemistry that defines plant relationships with other organisms. Recent innovations in analytical chemistry and bioinformatics promise to reveal the cryptic chemical traits that mediate plant ecology and evolution by facilitating simultaneous structural comparisons of hundreds of unknown molecules to each other and to libraries of known compounds. Here, I explore the potential for mass spectrometry and nuclear magnetic resonance metabolomics to enable unprecedented tests of seminal, but largely untested hypotheses that propose a fundamental role for plant chemical defenses against herbivores and pathogens in the evolutionary origins and ecological coexistence of plant species diversity. © 2017 The Author. New Phytologist © 2017 New Phytologist Trust.

  11. Proof of concept of microbiome-metabolome analysis and delayed gluten exposure on celiac disease autoimmunity in genetically at-risk infants.

    Maria Sellitto

    Full Text Available Celiac disease (CD is a unique autoimmune disorder in which the genetic factors (DQ2/DQ8 and the environmental trigger (gluten are known and necessary but not sufficient for its development. Other environmental components contributing to CD are poorly understood. Studies suggest that aspects of gluten intake might influence the risk of CD occurrence and timing of its onset, i.e., the amount and quality of ingested gluten, together with the pattern of infant feeding and the age at which gluten is introduced in the diet. In this study, we hypothesize that the intestinal microbiota as a whole rather than specific infections dictates the switch from tolerance to immune response in genetically susceptible individuals. Using a sample of infants genetically at risk of CD, we characterized the longitudinal changes in the microbial communities that colonize infants from birth to 24 months and the impact of two patterns of gluten introduction (early vs. late on the gut microbiota and metabolome, and the switch from gluten tolerance to immune response, including onset of CD autoimmunity. We show that infants genetically susceptible to CD who are exposed to gluten early mount an immune response against gluten and develop CD autoimmunity more frequently than at-risk infants in which gluten exposure is delayed until 12 months of age. The data, while derived from a relatively small number of subjects, suggest differences between the developing microbiota of infants with genetic predisposition for CD and the microbiota from infants with a non-selected genetic background, with an overall lack of bacteria of the phylum Bacteriodetes along with a high abundance of Firmicutes and microbiota that do not resemble that of adults even at 2 years of age. Furthermore, metabolomics analysis reveals potential biomarkers for the prediction of CD. This study constitutes a definite proof-of-principle that these combined genomic and metabolomic approaches will be key to

  12. Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

    Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

    2016-05-10

    In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress.

  13. Assessment of 1H NMR-based metabolomics analysis for normalization of urinary metals against creatinine.

    Cassiède, Marc; Nair, Sindhu; Dueck, Meghan; Mino, James; McKay, Ryan; Mercier, Pascal; Quémerais, Bernadette; Lacy, Paige

    2017-01-01

    Proton nuclear magnetic resonance ( 1 H NMR, or NMR) spectroscopy and inductively coupled plasma-mass spectrometry (ICP-MS) are commonly used for metabolomics and metal analysis in urine samples. However, creatinine quantification by NMR for the purpose of normalization of urinary metals has not been validated. We assessed the validity of using NMR analysis for creatinine quantification in human urine samples in order to allow normalization of urinary metal concentrations. NMR and ICP-MS techniques were used to measure metabolite and metal concentrations in urine samples from 10 healthy subjects. For metabolite analysis, two magnetic field strengths (600 and 700MHz) were utilized. In addition, creatinine concentrations were determined by using the Jaffe method. Creatinine levels were strongly correlated (R 2 =0.99) between NMR and Jaffe methods. The NMR spectra were deconvoluted with a target database containing 151 metabolites that are present in urine. A total of 50 metabolites showed good correlation (R 2 =0.7-1.0) at 600 and 700MHz. Metal concentrations determined after NMR-measured creatinine normalization were comparable to previous reports. NMR analysis provided robust urinary creatinine quantification, and was sufficient for normalization of urinary metal concentrations. We found that NMR-measured creatinine-normalized urinary metal concentrations in our control subjects were similar to general population levels in Canada and the United Kingdom. Copyright © 2016 Elsevier B.V. All rights reserved.

  14. Optimization of the quenching method for metabolomics analysis of Lactobacillus bulgaricus.

    Chen, Ming-ming; Li, Ai-li; Sun, Mao-cheng; Feng, Zhen; Meng, Xiang-chen; Wang, Ying

    2014-04-01

    This study proposed a quenching protocol for metabolite analysis of Lactobacillus delbrueckii subsp. bulgaricus. Microbial cells were quenched with 60% methanol/water, 80% methanol/glycerol, or 80% methanol/water. The effect of the quenching process was assessed by the optical density (OD)-based method, flow cytometry, and gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed for metabolite identification. The results indicated that quenching with 80% methanol/water solution led to less damage to the L. bulgaricus cells, characterized by the lower relative fraction of prodium iodide (PI)-labeled cells and the higher OD recovery ratio. Through GC-MS analysis, higher levels of intracellular metabolites (including focal glutamic acid, aspartic acid, alanine, and AMP) and a lower leakage rate were detected in the sample quenched with 80% methanol/water compared with the others. In conclusion, we suggested a higher concentration of cold methanol quenching for L. bulgaricus metabolomics due to its decreasing metabolite leakage.

  15. Optimization of the quenching method for metabolomics analysis of Lactobacillus bulgaricus *

    Chen, Ming-ming; Li, Ai-li; Sun, Mao-cheng; Feng, Zhen; Meng, Xiang-chen; Wang, Ying

    2014-01-01

    This study proposed a quenching protocol for metabolite analysis of Lactobacillus delbrueckii subsp. bulgaricus. Microbial cells were quenched with 60% methanol/water, 80% methanol/glycerol, or 80% methanol/water. The effect of the quenching process was assessed by the optical density (OD)-based method, flow cytometry, and gas chromatography-mass spectrometry (GC-MS). The principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were employed for metabolite identification. The results indicated that quenching with 80% methanol/water solution led to less damage to the L. bulgaricus cells, characterized by the lower relative fraction of prodium iodide (PI)-labeled cells and the higher OD recovery ratio. Through GC-MS analysis, higher levels of intracellular metabolites (including focal glutamic acid, aspartic acid, alanine, and AMP) and a lower leakage rate were detected in the sample quenched with 80% methanol/water compared with the others. In conclusion, we suggested a higher concentration of cold methanol quenching for L. bulgaricus metabolomics due to its decreasing metabolite leakage. PMID:24711354

  16. Blood metabolomics analysis identifies abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism in bipolar disorder

    Yoshimi, Noriko; Futamura, Takashi; Kakumoto, Keiji; Salehi, Alireza M.; Sellgren, Carl M.; Holmén-Larsson, Jessica; Jakobsson, Joel; Pålsson, Erik; Landén, Mikael; Hashimoto, Kenji

    2016-01-01

    Background: Bipolar disorder (BD) is a severe and debilitating psychiatric disorder. However, the precise biological basis remains unknown, hampering the search for novel biomarkers. We performed a metabolomics analysis to discover novel peripheral biomarkers for BD. Methods: We quantified serum levels of 116 metabolites in mood-stabilized male BD patients (n = 54) and age-matched male healthy controls (n = 39). Results: After multivariate logistic regression, serum levels of pyruvate, N-acet...

  17. Collision energy alteration during mass spectrometric acquisition is essential to ensure unbiased metabolomic analysis

    Madala, NE

    2012-08-01

    Full Text Available Metabolomics entails identification and quantification of all metabolites within a biological system with a given physiological status; as such, it should be unbiased. A variety of techniques are used to measure the metabolite content of living...

  18. IDEOM : an Excel interface for analysis of LC-MS-based metabolomics data

    Creek, Darren J.; Jankevics, Andris; Burgess, Karl E. V.; Breitling, Rainer; Barrett, Michael P.; Wren, Jonathan

    2012-01-01

    The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates

  19. Metabolomic Analysis of the Skeletal Muscle of Mice Overexpressing PGC-1α.

    Yukino Hatazawa

    Full Text Available Peroxisome proliferator-activated receptor (PPAR γ coactivator 1α (PGC-1α is a coactivator of various nuclear receptors and other transcription factors whose expression increases in the skeletal muscle during exercise. We have previously made transgenic mice overexpressing PGC-1α in the skeletal muscle (PGC-1α-Tg mice. PGC-1α upregulates the expression of genes associated with red fibers, mitochondrial function, fatty acid oxidation, and branched chain amino acid (BCAA degradation. However, global analyses of the actual metabolic products have not been investigated. In this study, we conducted metabolomic analysis of the skeletal muscle in PGC-1α-Tg mice by capillary electrophoresis with electrospray ionization time-of-flight mass spectrometry. Principal component analysis and hierarchical cluster analysis showed clearly distinguishable changes in the metabolites between PGC-1α-Tg and wild-type control mice. Changes were observed in metabolite levels of various metabolic pathways such as the TCA cycle, pentose phosphate pathway, nucleotide synthesis, purine nucleotide cycle, and amino acid metabolism, including BCAA and β-alanine. Namely, metabolic products of the TCA cycle increased in PGC-1α-Tg mice, with increased levels of citrate (2.3-fold, succinate (2.2-fold, fumarate (2.8-fold, and malate (2.3-fold observed. Metabolic products associated with the pentose phosphate pathway and nucleotide biosynthesis also increased in PGC-1α-Tg mice. Meanwhile, BCAA levels decreased (Val, 0.7-fold; Leu, 0.8-fold; and Ile, 0.7-fold, and Glu (3.1-fold and Asp (2.2-fold levels increased. Levels of β-alanine and related metabolites were markedly decreased in PGC-1α-Tg mice. Coordinated regulation of the TCA cycle and amino acid metabolism, including BCAA, suggests that PGC-1α plays important roles in energy metabolism. Moreover, our metabolomics data showing the activation of the purine nucleotide pathway, malate-aspartate shuttle, as well as

  20. Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

    Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

    2018-01-05

    Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

  1. Metabolomics reveals dose effects of low-dose chronic exposure to uranium in rats: identification of candidate biomarkers in urine samples.

    Grison, Stéphane; Favé, Gaëlle; Maillot, Matthieu; Manens, Line; Delissen, Olivia; Blanchardon, Éric; Dublineau, Isabelle; Aigueperse, Jocelyne; Bohand, Sandra; Martin, Jean-Charles; Souidi, Maâmar

    2016-01-01

    Data are sparse about the potential health risks of chronic low-dose contamination of humans by uranium (natural or anthropogenic) in drinking water. Previous studies report some molecular imbalances but no clinical signs due to uranium intake. In a proof-of-principle study, we reported that metabolomics is an appropriate method for addressing this chronic low-dose exposure in a rat model (uranium dose: 40 mg L -1 ; duration: 9 months, n = 10). In the present study, our aim was to investigate the dose-effect pattern and identify additional potential biomarkers in urine samples. Compared to our previous protocol, we doubled the number of rats per group (n = 20), added additional sampling time points (3 and 6 months) and included several lower doses of natural uranium (doses used: 40, 1.5, 0.15 and 0.015 mg L -1 ). LC-MS metabolomics was performed on urine samples and statistical analyses were made with SIMCA-P+ and R packages. The data confirmed our previous results and showed that discrimination was both dose and time related. Uranium exposure was revealed in rats contaminated for 9 months at a dose as low as 0.15 mg L -1 . Eleven features, including the confidently identified N1-methylnicotinamide, N1-methyl-2-pyridone-5-carboxamide and 4-hydroxyphenylacetylglycine, discriminated control from contaminated rats with a specificity and a sensitivity ranging from 83 to 96 %, when combined into a composite score. These findings show promise for the elucidation of underlying radiotoxicologic mechanisms and the design of a diagnostic test to assess exposure in urine, in a dose range experimentally estimated to be above a threshold between 0.015 and 0.15 mg L -1 .

  2. Metabolomics of tomato xylem sap during bacterial wilt reveals Ralstonia solanacearum produces abundant putrescine, a metabolite that accelerates wilt disease.

    Lowe-Power, Tiffany M; Hendrich, Connor G; von Roepenack-Lahaye, Edda; Li, Bin; Wu, Dousheng; Mitra, Raka; Dalsing, Beth L; Ricca, Patrizia; Naidoo, Jacinth; Cook, David; Jancewicz, Amy; Masson, Patrick; Thomma, Bart; Lahaye, Thomas; Michael, Anthony J; Allen, Caitilyn

    2018-04-01

    Ralstonia solanacearum thrives in plant xylem vessels and causes bacterial wilt disease despite the low nutrient content of xylem sap. We found that R. solanacearum manipulates its host to increase nutrients in tomato xylem sap, enabling it to grow better in sap from infected plants than in sap from healthy plants. Untargeted GC/MS metabolomics identified 22 metabolites enriched in R. solanacearum-infected sap. Eight of these could serve as sole carbon or nitrogen sources for R. solanacearum. Putrescine, a polyamine that is not a sole carbon or nitrogen source for R. solanacearum, was enriched 76-fold to 37 µM in R. solanacearum-infected sap. R. solanacearum synthesized putrescine via a SpeC ornithine decarboxylase. A ΔspeC mutant required ≥ 15 µM exogenous putrescine to grow and could not grow alone in xylem even when plants were treated with putrescine. However, co-inoculation with wildtype rescued ΔspeC growth, indicating R. solanacearum produced and exported putrescine to xylem sap. Intriguingly, treating plants with putrescine before inoculation accelerated wilt symptom development and R. solanacearum growth and systemic spread. Xylem putrescine concentration was unchanged in putrescine-treated plants, so the exogenous putrescine likely accelerated disease indirectly by affecting host physiology. These results indicate that putrescine is a pathogen-produced virulence metabolite. © 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

  3. Perturbations in amino acids and metabolic pathways in osteoarthritis patients determined by targeted metabolomics analysis.

    Chen, Rui; Han, Su; Liu, Xuefeng; Wang, Kunpeng; Zhou, Yong; Yang, Chundong; Zhang, Xi

    2018-05-15

    Osteoarthritis (OA) is a degenerative synovial joint disease affecting people worldwide. However, the exact pathogenesis of OA remains unclear. Metabolomics analysis was performed to obtain insight into possible pathogenic mechanisms and diagnostic biomarkers of OA. Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry (UPLC-TQ-MS), followed by multivariate statistical analysis, was used to determine the serum amino acid profiles of 32 OA patients and 35 healthy controls. Variable importance for project values and Student's t-test were used to determine the metabolic abnormalities in OA. Another 30 OA patients were used as independent samples to validate the alterations in amino acids. MetaboAnalyst was used to identify the key amino acid pathways and construct metabolic networks describing their relationships. A total of 25 amino acids and four biogenic amines were detected by UPLC-TQ-MS. Differences in amino acid profiles were found between the healthy controls and OA patients. Alanine, γ-aminobutyric acid and 4-hydroxy-l-proline were important biomarkers distinguishing OA patients from healthy controls. The metabolic pathways with the most significant effects were involved in metabolism of alanine, aspartate, glutamate, arginine and proline. The results of this study improve understanding of the amino acid metabolic abnormalities and pathogenic mechanisms of OA at the molecular level. The metabolic perturbations may be important for the diagnosis and prevention of OA. Copyright © 2018 Elsevier B.V. All rights reserved.

  4. Two-Phase Extraction for Comprehensive Analysis of the Plant Metabolome by NMR.

    Schripsema, Jan; Dagnino, Denise

    2018-01-01

    Metabolomics is the area of research, which strives to obtain complete metabolic fingerprints, to detect differences between them, and to provide hypothesis to explain those differences [1]. But obtaining complete metabolic fingerprints is not an easy task. Metabolite extraction is a key step during this process, and much research has been devoted to finding the best solvent mixture to extract as much metabolites as possible.Here a procedure is described for analysis of both polar and apolar metabolites using a two-phase extraction system. D 2 O and CDCl 3 are the solvents of choice, and their major advantage is that, for the identification of the compounds, standard databases can be used because D 2 O and CDCl 3 are the solvents most commonly used for pure compound NMR spectra. The procedure enables the absolute quantification of components via the addition of suitable internal standards. The extracts are also suitable for further analysis with other systems like LC-MS or GC-MS.

  5. Intrauterine Growth Restriction Programs the Hypothalamus of Adult Male Rats: Integrated Analysis of Proteomic and Metabolomic Data.

    Pedroso, Amanda P; Souza, Adriana P; Dornellas, Ana P S; Oyama, Lila M; Nascimento, Cláudia M O; Santos, Gianni M S; Rosa, José C; Bertolla, Ricardo P; Klawitter, Jelena; Christians, Uwe; Tashima, Alexandre K; Ribeiro, Eliane B

    2017-04-07

    Programming of hypothalamic functions regulating energy homeostasis may play a role in intrauterine growth restriction (IUGR)-induced adulthood obesity. The present study investigated the effects of IUGR on the hypothalamus proteome and metabolome of adult rats submitted to 50% protein-energy restriction throughout pregnancy. Proteomic and metabolomic analyzes were performed by data independent acquisition mass spectrometry and multiple reaction monitoring, respectively. At age 4 months, the restricted rats showed elevated adiposity, increased leptin and signs of insulin resistance. 1356 proteins were identified and 348 quantified while 127 metabolites were quantified. The restricted hypothalamus showed down-regulation of 36 proteins and 5 metabolites and up-regulation of 21 proteins and 9 metabolites. Integrated pathway analysis of the proteomics and metabolomics data indicated impairment of hypothalamic glucose metabolism, increased flux through the hexosamine pathway, deregulation of TCA cycle and the respiratory chain, and alterations in glutathione metabolism. The data suggest IUGR modulation of energy metabolism and redox homeostasis in the hypothalamus of male adult rats. The present results indicated deleterious consequences of IUGR on hypothalamic pathways involved in pivotal physiological functions. These results provide guidance for future mechanistic studies assessing the role of intrauterine malnutrition in the development of metabolic diseases later in life.

  6. Comparative mass spectrometry & nuclear magnetic resonance metabolomic approaches for nutraceuticals quality control analysis: a brief review.

    Farag, Mohamed A

    2014-01-01

    The number of botanical dietary supplements in the market has recently increased primarily due to increased health awareness. Standardization and quality control of the constituents of these plant extracts is an important topic, particularly when such ingredients are used long term as dietary supplements, or in cases where higher doses are marketed as drugs. The development of fast, comprehensive, and effective untargeted analytical methods for plant extracts is of high interest. Nuclear magnetic resonance spectroscopy and mass spectrometry are the most informative tools, each of which enables high-throughput and global analysis of hundreds of metabolites in a single step. Although only one of the two techniques is utilized in the majority of plant metabolomics applications, there is a growing interest in combining the data from both platforms to effectively unravel the complexity of plant samples. The application of combined MS and NMR in the quality control of nutraceuticals forms the major part of this review. Finally I will look at the future developments and perspectives of these two technologies for the quality control of herbal materials.

  7. Metabolomic analysis of cooperative adaptation between co-cultured Bacillus cereus and Ketogulonicigenium vulgare.

    Ming-Zhu Ding

    Full Text Available The cooperative adaptation of subcultivated Bacillus cereus and Ketogulonicigenium vulgare significantly increased the productivity of 2-keto-L-gulonic acid, the precursor of vitamin C. The mechanism of cooperative adaptation of the serial subcultivated B. cereus and K. vulgare was investigated in this study by culturing the two strains orthogonally on agar plates. It was found that the swarming distance of B. cereus along the trace of K. vulgare on the plate decreased after 150 days' subcultivation. Metabolomic analysis on these co-cultured B. cereus and K. vulgare strains showed that their cooperative adaptation was accomplished by three key events: (i the ability of nutrients (e.g., amino acids and purines searching and intaking, and proteins biosynthesis is increased in the evolved B. cereus; (ii the capability of protein degradation and amino acids transportation is enhanced in evolved K. vulgare; (iii the evolved B. cereus was found to provide more nutrients (mostly amino acids and purines to K. vulgare, thus strengthening the oxidation and energy generation of K. vulgare. Our results provided novel insights into the systems-level understanding of the cooperative adaptation between strains in synergistic consortium.

  8. Biological effect of aqueous C60 aggregates on Scenedesmus obliquus revealed by transcriptomics and non-targeted metabolomics.

    Du, Chunlei; Zhang, Bo; He, Yiliang; Hu, Chaoyang; Ng, Qin Xiang; Zhang, Hui; Ong, Choon Nam; ZhifenLin

    2017-02-15

    This work evaluated biological effect of nC 60 on Scenedesmus obliquus. The cells were exposed to various concentrations of nC 60 for 7days. Low-dose of nC 60 was found to have a minor growth inhibitory effect. The transcriptomics and metabolomics were integrated to examine intricate molecular and cellular effects of nC 60 on Scenedesmus obliquus. We found that Scenedesmus obliquus cells exposed to nC 60 had several significant alterations in cellular transcription and biochemical processes. During the 7-day exposure to nC 60 , 2234 and 2,448 unigenes were differentially expressed by 0.1mg/L and 1mg/L nC 60 -treated groups compared with the control, including 2085 or 2247 up-regulated genes and 149 or 201 down-regulated genes, respectively. We successfully identified 22 metabolites, including 6 significantly changed metabolites, such as sucrose, d-glucose, and malic acid. The citrate cycle (TCA cycle) (ko00020) was the main target of both differentially expressed genes and metabolic change. However, accumulation of sucrose (end-product) could have induced feedback inhibition of photosynthesis in Scenedesmus obliquus, explaining the slight growth inhibition observed. The results provided a mechanistic understanding of the growth inhibition of nC 60 toxicity. These genes and metabolites are useful biomarkers for future studies and offer new insights into the early detectable changes in Scenedesmus obliquus with nC 60 exposure. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Serum Metabolomics Reveals Serotonin as a Predictor of Severe Dengue in the Early Phase of Dengue Fever

    Thein, Tun Linn; Fang, Jinling; Pang, Junxiong; Ooi, Eng Eong; Leo, Yee Sin; Ong, Choon Nam; Tannenbaum, Steven R.

    2016-01-01

    Effective triage of dengue patients early in the disease course for in- or out-patient management would be useful for optimal healthcare resource utilization while minimizing poor clinical outcome due to delayed intervention. Yet, early prognosis of severe dengue is hampered by the heterogeneity in clinical presentation and routine hematological and biochemical measurements in dengue patients that collectively correlates poorly with eventual clinical outcome. Herein, untargeted liquid-chromatography mass spectrometry metabolomics of serum from patients with dengue fever (DF) and dengue hemorrhagic fever (DHF) in the febrile phase (1.5) in the serum, among which are two products of tryptophan metabolism–serotonin and kynurenine. Serotonin, involved in platelet aggregation and activation decreased significantly, whereas kynurenine, an immunomodulator, increased significantly in patients with DHF, consistent with thrombocytopenia and immunopathology in severe dengue. To sensitively and accurately evaluate serotonin levels as prognostic biomarkers, we implemented stable-isotope dilution mass spectrometry and used convalescence samples as their own controls. DHF serotonin was significantly 1.98 fold lower in febrile compared to convalescence phase, and significantly 1.76 fold lower compared to DF in the febrile phase of illness. Thus, serotonin alone provided good prognostic utility (Area Under Curve, AUC of serotonin = 0.8). Additionally, immune mediators associated with DHF may further increase the predictive ability than just serotonin alone. Nine cytokines, including IFN-γ, IL-1β, IL-4, IL-8, G-CSF, MIP-1β, FGF basic, TNFα and RANTES were significantly different between DF and DHF, among which IFN-γ ranked top by multivariate statistics. Combining serotonin and IFN-γ improved the prognosis performance (AUC = 0.92, sensitivity = 77.8%, specificity = 95.8%), suggesting this duplex panel as accurate metrics for the early prognosis of DHF. PMID:27055163

  10. Nutritional Metabolomics

    Gürdeniz, Gözde

    strategy influences the patterns identified as important for the nutritional question under study. Therefore, in depth understanding of the study design and the specific effects of the analytical technology on the produced data is extremely important to achieve high quality data handling. Besides data......Metabolomics provides a holistic approach to investigate the perturbations in human metabolism with respect to a specific exposure. In nutritional metabolomics, the research question is generally related to the effect of a specific food intake on metabolic profiles commonly of plasma or urine....... Application of multiple analytical strategies may provide comprehensive information to reach a valid answer to these research questions. In this thesis, I investigated several analytical technologies and data handling strategies in order to evaluate their effects on the biological answer. In metabolomics, one...

  11. Analysis of stable isotope assisted metabolomics data acquired by GC-MS

    Wei, Xiaoli; Shi, Biyun; Koo, Imhoi; Yin, Xinmin; Lorkiewicz, Pawel; Suhail, Hamid; Rattan, Ramandeep; Giri, Shailendra; McClain, Craig J.

    2017-01-01

    Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., 13 C, 18 O and/or 15 N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 13 C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform 13 C-glucose and 13 C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples. - Highlights: • A signature ion approach is developed for analysis of stable isotope GC-MS data. • GC-MS data of compound standards are used for selection of the signature ion. • Linear regression model is used to deconvolute the overlapping isotopologue peaks. • The developed method was tested by known compounds and biological samples.

  12. Plant Metabolomics : the missiong link in functional genomics strategies

    Hall, R.D.; Beale, M.; Fiehn, O.; Hardy, N.; Summer, L.; Bino, R.

    2002-01-01

    After the establishment of technologies for high-throughput DNA sequencing (genomics), gene expression analysis (transcriptomics), and protein analysis (proteomics), the remaining functional genomics challenge is that of metabolomics. Metabolomics is the term coined for essentially comprehensive,

  13. Metabolomics Reveals New Mechanisms for Pathogenesis in Barth Syndrome and Introduces Novel Roles for Cardiolipin in Cellular Function.

    Yana Sandlers

    Full Text Available Barth Syndrome is the only known Mendelian disorder of cardiolipin remodeling, with characteristic clinical features of cardiomyopathy, skeletal myopathy, and neutropenia. While the primary biochemical defects of reduced mature cardiolipin and increased monolysocardiolipin are well-described, much of the downstream biochemical dysregulation has not been uncovered, and biomarkers are limited. In order to further expand upon the knowledge of the biochemical abnormalities in Barth Syndrome, we analyzed metabolite profiles in plasma from a cohort of individuals with Barth Syndrome compared to age-matched controls via 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry. A clear distinction between metabolite profiles of individuals with Barth Syndrome and controls was observed, and was defined by an array of metabolite classes including amino acids and lipids. Pathway analysis of these discriminating metabolites revealed involvement of mitochondrial and extra-mitochondrial biochemical pathways including: insulin regulation of fatty acid metabolism, lipid metabolism, biogenic amine metabolism, amino acid metabolism, endothelial nitric oxide synthase signaling, and tRNA biosynthesis. Taken together, this data indicates broad metabolic dysregulation in Barth Syndrome with wide cellular effects.

  14. LC-MS metabolomic analysis of environmental stressor impacts on the metabolite diversity in Nephthea spp.

    Hedi Indra Januar

    2012-01-01

    Full Text Available Context: The soft coral Nephthea spp. is a source of terpenoid class that potentially has pharmaceutical properties. However, metabolite diversity and cytotoxic activity of this species are varied among coral reefs from various sites. Aim: To analyze the water quality in Nephthea spp. environment as a possible factor causing a difference in its metabolite diversity. Settings and Design: Nephthea spp. from seven sites were taken in October 2010 at the Alor District of Marine Protected Area, Indonesia. Materials and Methods: Water quality assessment was analyzed in situ and indexed by Canadian Council of Ministry Environment-Water Quality Index (CCME-WQI method. Meanwhile, metabolite diversity was analyzed by a LC-MS metabolomic method, using C18 reversed phase and gradient water-acetonitrile system. Statistical Analysis Used: Spearman′s rho and regression analysis were applied to correlate the water quality index to ecological index (richness, diversity, and evenness from LC-MS results. Results: The water quality index had a significant positive correlation and strong linear regression determinant to the total metabolite (R 2 = 0.704, particularly to semipolar metabolite richness (R 2 = 0.809, the area of terpenoid class in the organism. Conclusion: It can be concluded that water quality may serve as a major factor that affects the amount of richness in Nephthea spp. metabolites. When the water quality is lower, as environment stresses increases, it may affect the metabolite richness within direct disrupt of metabolite biosynthesis or indirect ecological means. Terpenoids are known as a soft coral antipredator (coral fishes, the amount of which depends on the water quality.

  15. Plasma metabolomics reveals membrane lipids, aspartate/asparagine and nucleotide metabolism pathway differences associated with chloroquine resistance in Plasmodium vivax malaria

    Salinas, Jorge L.; Monteiro, Wuelton M.; Val, Fernando; Cordy, Regina J.; Liu, Ken; Melo, Gisely C.; Siqueira, Andre M.; Magalhaes, Belisa; Galinski, Mary R.; Lacerda, Marcus V. G.; Jones, Dean P.

    2017-01-01

    Background Chloroquine (CQ) is the main anti-schizontocidal drug used in the treatment of uncomplicated malaria caused by Plasmodium vivax. Chloroquine resistant P. vivax (PvCR) malaria in the Western Pacific region, Asia and in the Americas indicates a need for biomarkers of resistance to improve therapy and enhance understanding of the mechanisms associated with PvCR. In this study, we compared plasma metabolic profiles of P. vivax malaria patients with PvCR and chloroquine sensitive parasites before treatment to identify potential molecular markers of chloroquine resistance. Methods An untargeted high-resolution metabolomics analysis was performed on plasma samples collected in a malaria clinic in Manaus, Brazil. Male and female patients with Plasmodium vivax were included (n = 46); samples were collected before CQ treatment and followed for 28 days to determine PvCR, defined as the recurrence of parasitemia with detectable plasma concentrations of CQ ≥100 ng/dL. Differentially expressed metabolic features between CQ-Resistant (CQ-R) and CQ-Sensitive (CQ-S) patients were identified using partial least squares discriminant analysis and linear regression after adjusting for covariates and multiple testing correction. Pathway enrichment analysis was performed using Mummichog. Results Linear regression and PLS-DA methods yielded 69 discriminatory features between CQ-R and CQ-S groups, with 10-fold cross-validation classification accuracy of 89.6% using a SVM classifier. Pathway enrichment analysis showed significant enrichment (p<0.05) of glycerophospholipid metabolism, glycosphingolipid metabolism, aspartate and asparagine metabolism, purine and pyrimidine metabolism, and xenobiotics metabolism. Glycerophosphocholines levels were significantly lower in the CQ-R group as compared to CQ-S patients and also to independent control samples. Conclusions The results show differences in lipid, amino acids, and nucleotide metabolism pathways in the plasma of CQ-R versus

  16. An initial non-targeted analysis of the peanut seed metabolome

    There are likely a large number of compounds that constitute the peanut seed metabolome that have yet to be elucidated. Although the proximate composition and nutrients such as vitamins and minerals are well known, the composition of many other small molecule metabolites present have not been syste...

  17. Real-life metabolomics data analysis: how to deal with complex data?

    Rubingh, C.M.

    2010-01-01

    Door de grote datasets die gegenereerd worden in metabolomics studies, in combinatie met de ingewikkelde studiedesigns die vaak nodig zijn om subtiele verschillen in metabolietprofielen te kunnen detecteren, zijn standaard multivariate technieken niet meer afdoende. Dit geldt voor alle fasen van de

  18. Metabolomic analysis for combined hepatotoxicity of chlorpyrifos and cadmium in rats

    Xu, Ming-Yuan; Wang, Pan; Sun, Ying-Jian; Wu, Yi-Jun

    2017-01-01

    Pesticides and heavy metals are widespread environmental pollutants. Although the acute toxicity of organophosphorus pesticide chlorpyrifos (CPF) and toxic heavy metal cadmium (Cd) is well characterized, the combined toxicity of CPF and Cd, especially the hepatotoxicity of the two chemicals with long-term exposure at a low dose, remained unclear. In this study, we investigated the toxicity in the liver of rats upon subchronic exposure to CPF and Cd at environmentally relevant doses. Rats were given three different doses (1/135 LD 50 , 1/45 LD 50 and 1/15 LD 50 ) of CPF and Cd as well as their mixtures by oral gavage for 90 days. After treatment, the liver tissues were subjected to histopathological examination and biochemical analysis. Gas chromatography-mass spectrometry (GC–MS) was used to analyze the metabolomic changes in the rat liver upon CPF, Cd and their mixtures treatment. The results showed that CPF and Cd-induced oxidative damage and disrupted energy, amino acid, and fatty acid metabolism in the liver. Eleven biomarkers in liver were identified for CPF-, Cd-, and their mixture-treated rats. Three metabolites, i.e., butanedioic acid, myo-inositol, and urea, were identified as unique biomarkers for the mixture-treated rats. Moreover, we found that Cd could accelerate the metabolism of CPF in the liver when given together to the rats, which may lead to the potential antagonistic interaction between CPF and Cd. In conclusion, our results indicated that even at environmentally relevant doses, CPF and Cd could disrupt the liver metabolism. In addition, the accelerated metabolism of CPF by Cd may lead to their potential antagonistic interaction.

  19. Physiological and metabolomic analysis of Punica granatum (L.) under drought stress.

    Catola, Stefano; Marino, Giovanni; Emiliani, Giovanni; Huseynova, Taravat; Musayev, Mirza; Akparov, Zeynal; Maserti, Bianca Elena

    2016-02-01

    Punica granatum has a noticeable adaptation to drought stress. The levels of the green leaf volatile trans-2-hexenal increased in response to drought stress suggesting a possible role of this compound in drought stress response in pomegranate. Punica granatum (L.) is a highly valued fruit crop for its health-promoting effects and it is mainly cultivated in semi-arid areas. Thus, understanding the response mechanisms to drought stress is of great importance. In the present research, a metabolomics analysis was performed to evaluate the effects of drought stress on volatile organic compounds extracted from the leaves of pomegranate plants grown under water shortage conditions. The time course experiment (7 days of water deprivation and 24-h recovery) consisted of three treatments (control, drought stress, and rehydration of drought-stressed plants). Plant weights were recorded and control plants were irrigated daily at pot capacity to provide the lost water. Fraction of transpirable soil water has been evaluated as indicator of soil water availability in stressed plants. The levels of proline, hydrogen peroxide and lipid peroxidation as well as of the photosynthetic parameters such as photosynthesis rate (A), stomatal conductance (g s), photosynthetic efficiency of photosystem II, and photochemical quenching were monitored after the imposition of drought stress and recovery as markers of plant stress. Constitutive carbon volatile components were analyzed in the leaf of control and drought-stressed leaves using Head Space Solid Phase Micro Extraction sampling coupled with Gas Chromatography Mass Spectrometry. A total of 12 volatile compounds were found in pomegranate leaf profiles, mainly aldehydes, alcohols, and organic acids. Among them, the trans-2-hexenal showed a significant increase in water-stressed and recovered leaves respect to the well-watered ones. These data evidence a possible role of the oxylipin pathway in the response to water stress in pomegranate

  20. Urinary Loss of Tricarboxylic Acid Cycle Intermediates As Revealed by Metabolomics Studies: An Underlying Mechanism to Reduce Lipid Accretion by Whey Protein Ingestion?

    2015-01-01

    Whey protein intake is associated with the modulation of energy metabolism and altered body composition both in human subjects and in animals, but the underlying mechanisms are not yet elucidated. We fed obesity-prone C57BL/6J mice high-fat diets with either casein (HF casein) or whey (HF whey) for 6 weeks. At equal energy intake and apparent fat and nitrogen digestibility, mice fed HF whey stored less energy as lipids, evident both as lower white adipose tissue mass and as reduced liver lipids, compared with HF-casein-fed mice. Explorative analyses of 48 h urine, both by 1H NMR and LC–MS metabolomic platforms, demonstrated higher urinary excretion of tricarboxylic acid (TCA) cycle intermediates citric acid and succinic acid (identified by both platforms), and cis-aconitic acid and isocitric acid (identified by LC–MS platform) in the HF whey, relative to in the HF-casein-fed mice. Targeted LC–MS analyses revealed higher citric acid and cis-aconitic acid concentrations in fed state plasma, but not in liver of HF-whey-fed mice. We propose that enhanced urinary loss of TCA cycle metabolites drain available substrates for anabolic processes, such as lipogenesis, thereby leading to reduced lipid accretion in HF-whey-fed compared to HF-casein-fed mice. PMID:24702026

  1. Metabolomic Profiling of Post-Mortem Brain Reveals Changes in Amino Acid and Glucose Metabolism in Mental Illness Compared with Controls

    Rong Zhang

    2016-01-01

    Full Text Available Metabolomic profiling was carried out on 53 post-mortem brain samples from subjects diagnosed with schizophrenia, depression, bipolar disorder (SDB, diabetes, and controls. Chromatography on a ZICpHILIC column was used with detection by Orbitrap mass spectrometry. Data extraction was carried out with m/z Mine 2.14 with metabolite searching against an in-house database. There was no clear discrimination between the controls and the SDB samples on the basis of a principal components analysis (PCA model of 755 identified or putatively identified metabolites. Orthogonal partial least square discriminant analysis (OPLSDA produced clear separation between 17 of the controls and 19 of the SDB samples (R2CUM 0.976, Q2 0.671, p-value of the cross-validated ANOVA score 0.0024. The most important metabolites producing discrimination were the lipophilic amino acids leucine/isoleucine, proline, methionine, phenylalanine, and tyrosine; the neurotransmitters GABA and NAAG and sugar metabolites sorbitol, gluconic acid, xylitol, ribitol, arabinotol, and erythritol. Eight samples from diabetic brains were analysed, six of which grouped with the SDB samples without compromising the model (R2 CUM 0.850, Q2 CUM 0.534, p-value for cross-validated ANOVA score 0.00087. There appears on the basis of this small sample set to be some commonality between metabolic perturbations resulting from diabetes and from SDB.

  2. Pathway Analysis and Metabolites Identification by Metabolomics of Etiolation Substrate from Fresh-Cut Chinese Water Chestnut (Eleocharis tuberosa

    Yi-Xiao Li

    2016-12-01

    Full Text Available Fresh-cut Chinese water chestnuts (CWC turn yellow after being peeled, reducing their shelf life and commercial value. Metabolomics, the systematic study of the full complement of small molecular metabolites, was useful for clarifying the mechanism of fresh-cut CWC etiolation and developing methods to inhibit yellowing. In this study, metabolic alterations associated with etiolation at different growth stages (0 day, 2 days, 3 days, 4 days, 5 days from fresh-cut CWC were investigated using LC–MS and analyzed by pattern recognition methods (principal component analysis (PCA, partial least squares-discriminant analysis (PLS-DA, and orthogonal projection to latent structures-discriminant analysis (OPLS-DA. The metabolic pathways of the etiolation molecules were elucidated. The main metabolic pathway appears to be the conversion of phenylalanine to p-coumaroyl-CoA, followed by conversion to naringenin chalcone, to naringenin, and naringenin then following different pathways. Firstly, it can transform into apigenin and its derivatives; secondly, it can produce eriodictyol and its derivatives; and thirdly it can produce dihydrokaempferol, quercetin, and myricetin. The eriodictyol can be further transformed to luteolin, cyanidin, dihydroquercetin, dihydrotricetin, and others. This is the first reported use of metabolomics to study the metabolic pathways of the etiolation of fresh-cut CWC.

  3. Metabolomics in Toxicology and Preclinical Research

    Ramirez, Tzutzuy; Daneshian, Mardas; Kamp, Hennicke; Bois, Frederic Y.; Clench, Malcolm R.; Coen, Muireann; Donley, Beth; Fischer, Steven M.; Ekman, Drew R.; Fabian, Eric; Guillou, Claude; Heuer, Joachim; Hogberg, Helena T.; Jungnickel, Harald; Keun, Hector C.; Krennrich, Gerhard; Krupp, Eckart; Luch, Andreas; Noor, Fozia; Peter, Erik; Riefke, Bjoern; Seymour, Mark; Skinner, Nigel; Smirnova, Lena; Verheij, Elwin; Wagner, Silvia; Hartung, Thomas; van Ravenzwaay, Bennard; Leist, Marcel

    2013-01-01

    Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context. PMID:23665807

  4. Quantitative analysis of relationships between fluxome and metabolome in Escherichia coli

    Taymaz Nikerel, H.

    2010-01-01

    Kinetic models, which predict the behaviour of metabolic reaction networks under different conditions, are indispensible to fully and quantitatively understand the relation between a product pathway and connected central metabolism. In this thesis the focus was to develop tools for future in vivo kinetic modeling in Escherichia coli. The relations between fluxome and metabolome at steady-state or transient state but where enzyme levels can be assumed constant are investigated. In addition, we...

  5. Blood metabolomics analysis identifies abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism in bipolar disorder.

    Yoshimi, Noriko; Futamura, Takashi; Kakumoto, Keiji; Salehi, Alireza M; Sellgren, Carl M; Holmén-Larsson, Jessica; Jakobsson, Joel; Pålsson, Erik; Landén, Mikael; Hashimoto, Kenji

    2016-06-01

    Bipolar disorder (BD) is a severe and debilitating psychiatric disorder. However, the precise biological basis remains unknown, hampering the search for novel biomarkers. We performed a metabolomics analysis to discover novel peripheral biomarkers for BD. We quantified serum levels of 116 metabolites in mood-stabilized male BD patients (n = 54) and age-matched male healthy controls (n = 39). After multivariate logistic regression, serum levels of pyruvate, N-acetylglutamic acid, α-ketoglutarate, and arginine were significantly higher in BD patients than in healthy controls. Conversely, serum levels of β-alanine, and serine were significantly lower in BD patients than in healthy controls. Chronic (4-weeks) administration of lithium or valproic acid to adult male rats did not alter serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, or arginine, but lithium administration significantly increased serum levels of α-ketoglutarate. The metabolomics analysis demonstrated altered serum levels of pyruvate, N-acetylglutamic acid, β-alanine, serine, and arginine in BD patients. The present findings suggest that abnormalities in the citric acid cycle, urea cycle, and amino acid metabolism play a role in the pathogenesis of BD.

  6. Metabolomic analysis of urine samples by UHPLC-QTOF-MS: Impact of normalization strategies.

    Gagnebin, Yoric; Tonoli, David; Lescuyer, Pierre; Ponte, Belen; de Seigneux, Sophie; Martin, Pierre-Yves; Schappler, Julie; Boccard, Julien; Rudaz, Serge

    2017-02-22

    Among the various biological matrices used in metabolomics, urine is a biofluid of major interest because of its non-invasive collection and its availability in large quantities. However, significant sources of variability in urine metabolomics based on UHPLC-MS are related to the analytical drift and variation of the sample concentration, thus requiring normalization. A sequential normalization strategy was developed to remove these detrimental effects, including: (i) pre-acquisition sample normalization by individual dilution factors to narrow the concentration range and to standardize the analytical conditions, (ii) post-acquisition data normalization by quality control-based robust LOESS signal correction (QC-RLSC) to correct for potential analytical drift, and (iii) post-acquisition data normalization by MS total useful signal (MSTUS) or probabilistic quotient normalization (PQN) to prevent the impact of concentration variability. This generic strategy was performed with urine samples from healthy individuals and was further implemented in the context of a clinical study to detect alterations in urine metabolomic profiles due to kidney failure. In the case of kidney failure, the relation between creatinine/osmolality and the sample concentration is modified, and relying only on these measurements for normalization could be highly detrimental. The sequential normalization strategy was demonstrated to significantly improve patient stratification by decreasing the unwanted variability and thus enhancing data quality. Copyright © 2016 Elsevier B.V. All rights reserved.

  7. GC-MS analysis of headspace and liquid extracts for metabolomic differentiation of citrus Huanglongbing and zinc deficiency in leaves of 'Valencia' sweet orange from commercial groves.

    Cevallos-Cevallos, Juan Manuel; García-Torres, Rosalía; Etxeberria, Edgardo; Reyes-De-Corcuera, José Ignacio

    2011-01-01

    Citrus Huanglongbing (HLB) is considered the most destructive citrus disease worldwide. Symptoms-based detection of HLB is difficult due to similarities with zinc deficiency. To find metabolic differences between leaves from HLB-infected, zinc-deficient, and healthy 'Valencia' orange trees by using GC-MS based metabolomics. Analysis based on GC-MS methods for untargeted metabolite analysis of citrus leaves was developed and optimized. Sample extracts from healthy, zinc deficient, or HLB-infected sweet orange leaves were submitted to headspace solid phase micro-extraction (SPME) and derivatization treatments prior to GC-MS analysis. Principal components analysis achieved correct classification of all the derivatized liquid extracts. Analysis of variance revealed 6 possible biomarkers for HLB, of which 5 were identified as proline, β-elemene, (-)trans- caryophyllene, and α-humulene. Significant (P < 0.05) differences in oxo-butanedioic acid, arabitol, and neo-inositol were exclusively detected in samples from plants with zinc deficiency. Levels of isocaryophyllen, α-selinene, β-selinene, and fructose were significantly (P < 0.05) different in healthy leaves only. Results suggest the potential of using identified HLB biomarkers for rapid differentiation of HLB from zinc deficiency. Copyright © 2010 John Wiley & Sons, Ltd.

  8. Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis

    Emwas, Abdul-Hamid M.

    2016-01-08

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to non-destructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Indeed, precise metabolite quantification is a necessary prerequisite to move any chemical biomarker or biomarker panel from the lab into the clinic. Among the many biofluids (urine, serum, plasma, cerebrospinal fluid and saliva) commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, easily obtained, needs little sample preparation and does not require any invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, thereby providing a rich source of potentially useful disease biomarkers. However, the incredible variation in urine chemical concentrations due to effects such as gender, age, diet, life style, health conditions, and physical activity make the analysis of urine and the identification of useful urinary biomarkers by NMR quite challenging. In this review, we discuss a number of the most significant issues regarding NMR-based urinary metabolomics with a specific emphasis on metabolite quantification for disease biomarker applications. We also propose a number of data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, as well as recommendations regarding sample preparation and biomarker assessment.

  9. Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis

    Emwas, Abdul-Hamid M.; Roy, Raja; McKay, Ryan T.; Ryan, Danielle; Brennan, Lorraine; Tenori, Leonardo; Luchinat, Claudio; Gao, Xin; Zeri, Ana Carolina; Gowda, G. A. Nagana; Raftery, Daniel; Steinbeck, Christoph; Salek, Reza M; Wishart, David S.

    2016-01-01

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to non-destructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Indeed, precise metabolite quantification is a necessary prerequisite to move any chemical biomarker or biomarker panel from the lab into the clinic. Among the many biofluids (urine, serum, plasma, cerebrospinal fluid and saliva) commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, easily obtained, needs little sample preparation and does not require any invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, thereby providing a rich source of potentially useful disease biomarkers. However, the incredible variation in urine chemical concentrations due to effects such as gender, age, diet, life style, health conditions, and physical activity make the analysis of urine and the identification of useful urinary biomarkers by NMR quite challenging. In this review, we discuss a number of the most significant issues regarding NMR-based urinary metabolomics with a specific emphasis on metabolite quantification for disease biomarker applications. We also propose a number of data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, as well as recommendations regarding sample preparation and biomarker assessment.

  10. Lysosomal metabolomics reveals V-ATPase- and mTOR-dependent regulation of amino acid efflux from lysosomes.

    Abu-Remaileh, Monther; Wyant, Gregory A; Kim, Choah; Laqtom, Nouf N; Abbasi, Maria; Chan, Sze Ham; Freinkman, Elizaveta; Sabatini, David M

    2017-11-10

    The lysosome degrades and recycles macromolecules, signals to the cytosol and nucleus, and is implicated in many diseases. Here, we describe a method for the rapid isolation of mammalian lysosomes and use it to quantitatively profile lysosomal metabolites under various cell states. Under nutrient-replete conditions, many lysosomal amino acids are in rapid exchange with those in the cytosol. Loss of lysosomal acidification through inhibition of the vacuolar H + -adenosine triphosphatase (V-ATPase) increased the luminal concentrations of most metabolites but had no effect on those of the majority of essential amino acids. Instead, nutrient starvation regulates the lysosomal concentrations of these amino acids, an effect we traced to regulation of the mechanistic target of rapamycin (mTOR) pathway. Inhibition of mTOR strongly reduced the lysosomal efflux of most essential amino acids, converting the lysosome into a cellular depot for them. These results reveal the dynamic nature of lysosomal metabolites and that V-ATPase- and mTOR-dependent mechanisms exist for controlling lysosomal amino acid efflux. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  11. Metabolomic biosignature differentiates melancholic depressive patients from healthy controls.

    Liu, Yashu; Yieh, Lynn; Yang, Tao; Drinkenburg, Wilhelmus; Peeters, Pieter; Steckler, Thomas; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

    2016-08-23

    Major depressive disorder (MDD) is a heterogeneous disease at the level of clinical symptoms, and this heterogeneity is likely reflected at the level of biology. Two clinical subtypes within MDD that have garnered interest are "melancholic depression" and "anxious depression". Metabolomics enables us to characterize hundreds of small molecules that comprise the metabolome, and recent work suggests the blood metabolome may be able to inform treatment decisions for MDD, however work is at an early stage. Here we examine a metabolomics data set to (1) test whether clinically homogenous MDD subtypes are also more biologically homogeneous, and hence more predictiable, (2) devise a robust machine learning framework that preserves biological meaning, and (3) describe the metabolomic biosignature for melancholic depression. With the proposed computational system we achieves around 80 % classification accuracy, sensitivity and specificity for melancholic depression, but only ~72 % for anxious depression or MDD, suggesting the blood metabolome contains more information about melancholic depression.. We develop an ensemble feature selection framework (EFSF) in which features are first clustered, and learning then takes place on the cluster centroids, retaining information about correlated features during the feature selection process rather than discarding them as most machine learning methods will do. Analysis of the most discriminative feature clusters revealed differences in metabolic classes such as amino acids and lipids as well as pathways studied extensively in MDD such as the activation of cortisol in chronic stress. We find the greater clinical homogeneity does indeed lead to better prediction based on biological measurements in the case of melancholic depression. Melancholic depression is shown to be associated with changes in amino acids, catecholamines, lipids, stress hormones, and immune-related metabolites. The proposed computational framework can be adapted

  12. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure.

    McClay, Joseph L; Adkins, Daniel E; Vunck, Sarah A; Batman, Angela M; Vann, Robert E; Clark, Shaunna L; Beardsley, Patrick M; van den Oord, Edwin J C G

    2013-04-01

    Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate ( p = 4.4 × 10 -5 , q = 0.013), tryptophan ( p = 7.0 × 10 -4 , q = 0.035) and 2-hydroxyglutarate ( p = 1.1 × 10 -4 , q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate ( p = 3.8 × 10 -7 ). Associations specific to repeated (5 day) MA exposure included phosphocholine ( p = 4.0 × 10 -4 , q = 0.087) and ergothioneine ( p = 3.0 × 10 -4 , q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects.

  13. {sup 1}H NMR-based metabolomics reveals sub-lethal toxicity of a mixture of diabetic and lipid-regulating pharmaceuticals on amphibian larvae

    Melvin, Steven D., E-mail: s.melvin@griffith.edu.au [Australian Rivers Institute, Griffith University, Southport, QLD 4222 (Australia); Habener, Leesa J. [Griffith School of Environment, Griffith University, Southport, QLD 4222 (Australia); Leusch, Frederic D.L. [Australian Rivers Institute, Griffith University, Southport, QLD 4222 (Australia); Griffith School of Environment, Griffith University, Southport, QLD 4222 (Australia); Carroll, Anthony R. [Griffith School of Environment, Griffith University, Southport, QLD 4222 (Australia)

    2017-03-15

    Highlights: • Pharmaceutical pollutants are a concern for eliciting adverse effects in wildlife. • Diabetes and lipid regulating drugs are widely used and poorly removed from sewage. • We explored the toxicity of a mixture of metformin, atorvastatin and bezafibrate on tadpoles. • Exposure caused increased growth and development but no effects on lipids or cholesterol. • {sup 1}H NMR-based metabolomics reveal increased lactic acid and BCAAs in exposed animals. - Abstract: Pharmaceuticals are widely used for the treatment of various physical and psychological ailments. Due to incomplete removal during sewage treatment many pharmaceuticals are frequently detected in aquatic waterways at trace concentrations. The diversity of pharmaceutical contaminants and potential for complex mixtures to occur makes it very difficult to predict the toxicity of these compounds on wildlife, and robust methods are therefore needed to explore sub-lethal effects. Metabolic syndrome is one of the most widespread health concerns currently facing the human population, and various drugs, including anti-diabetic medications and lipid- and cholesterol-lowering fibrates and statins, are widely prescribed as treatment. In this study, we exposed striped marsh frog (Limnodynastes peronii) tadpoles to a mixture of the drugs metformin, atorvastatin and bezafibrate at 0.5, 5, 50 and 500 μg/L to explore possible effects on growth and development, energy reserves (triglycerides and cholesterol), and profiles of small polar metabolites extracted from hepatic tissues. It was hypothesised that exposure would result in a general reduction in energy reserves, and that this would subsequently correspond with reduced growth and development. Responses differed from expected outcomes based on the known mechanisms of these compounds in humans, with no changes to hepatic triglycerides or cholesterol and a general increase in mass and condition with increasing exposure concentration. Deviation from the

  14. "1H NMR-based metabolomics reveals sub-lethal toxicity of a mixture of diabetic and lipid-regulating pharmaceuticals on amphibian larvae

    Melvin, Steven D.; Habener, Leesa J.; Leusch, Frederic D.L.; Carroll, Anthony R.

    2017-01-01

    Highlights: • Pharmaceutical pollutants are a concern for eliciting adverse effects in wildlife. • Diabetes and lipid regulating drugs are widely used and poorly removed from sewage. • We explored the toxicity of a mixture of metformin, atorvastatin and bezafibrate on tadpoles. • Exposure caused increased growth and development but no effects on lipids or cholesterol. • "1H NMR-based metabolomics reveal increased lactic acid and BCAAs in exposed animals. - Abstract: Pharmaceuticals are widely used for the treatment of various physical and psychological ailments. Due to incomplete removal during sewage treatment many pharmaceuticals are frequently detected in aquatic waterways at trace concentrations. The diversity of pharmaceutical contaminants and potential for complex mixtures to occur makes it very difficult to predict the toxicity of these compounds on wildlife, and robust methods are therefore needed to explore sub-lethal effects. Metabolic syndrome is one of the most widespread health concerns currently facing the human population, and various drugs, including anti-diabetic medications and lipid- and cholesterol-lowering fibrates and statins, are widely prescribed as treatment. In this study, we exposed striped marsh frog (Limnodynastes peronii) tadpoles to a mixture of the drugs metformin, atorvastatin and bezafibrate at 0.5, 5, 50 and 500 μg/L to explore possible effects on growth and development, energy reserves (triglycerides and cholesterol), and profiles of small polar metabolites extracted from hepatic tissues. It was hypothesised that exposure would result in a general reduction in energy reserves, and that this would subsequently correspond with reduced growth and development. Responses differed from expected outcomes based on the known mechanisms of these compounds in humans, with no changes to hepatic triglycerides or cholesterol and a general increase in mass and condition with increasing exposure concentration. Deviation from the

  15. Metabolomics reveals distinct, antibody-independent, molecular signatures of MS, AQP4-antibody and MOG-antibody disease.

    Jurynczyk, Maciej; Probert, Fay; Yeo, Tianrong; Tackley, George; Claridge, Tim D W; Cavey, Ana; Woodhall, Mark R; Arora, Siddharth; Winkler, Torsten; Schiffer, Eric; Vincent, Angela; DeLuca, Gabriele; Sibson, Nicola R; Isabel Leite, M; Waters, Patrick; Anthony, Daniel C; Palace, Jacqueline

    2017-12-06

    The overlapping clinical features of relapsing remitting multiple sclerosis (RRMS), aquaporin-4 (AQP4)-antibody (Ab) neuromyelitis optica spectrum disorder (NMOSD), and myelin oligodendrocyte glycoprotein (MOG)-Ab disease mean that detection of disease specific serum antibodies is the gold standard in diagnostics. However, antibody levels are not prognostic and may become undetectable after treatment or during remission. Therefore, there is still a need to discover antibody-independent biomarkers. We sought to discover whether plasma metabolic profiling could provide biomarkers of these three diseases and explore if the metabolic differences are independent of antibody titre. Plasma samples from 108 patients (34 RRMS, 54 AQP4-Ab NMOSD, and 20 MOG-Ab disease) were analysed by nuclear magnetic resonance spectroscopy followed by lipoprotein profiling. Orthogonal partial-least squares discriminatory analysis (OPLS-DA) was used to identify significant differences in the plasma metabolite concentrations and produce models (mathematical algorithms) capable of identifying these diseases. In all instances, the models were highly discriminatory, with a distinct metabolite pattern identified for each disease. In addition, OPLS-DA identified AQP4-Ab NMOSD patient samples with low/undetectable antibody levels with an accuracy of 92%. The AQP4-Ab NMOSD metabolic profile was characterised by decreased levels of scyllo-inositol and small high density lipoprotein particles along with an increase in large low density lipoprotein particles relative to both RRMS and MOG-Ab disease. RRMS plasma exhibited increased histidine and glucose, along with decreased lactate, alanine, and large high density lipoproteins while MOG-Ab disease plasma was defined by increases in formate and leucine coupled with decreased myo-inositol. Despite overlap in clinical measures in these three diseases, the distinct plasma metabolic patterns support their distinct serological profiles and confirm that these

  16. Dynamic Maize Responses to Aphid Feeding Are Revealed by a Time Series of Transcriptomic and Metabolomic Assays1[OPEN

    Tzin, Vered; Fernandez-Pozo, Noe; Richter, Annett; Schmelz, Eric A.; Schoettner, Matthias; Schäfer, Martin; Ahern, Kevin R.; Meihls, Lisa N.; Kaur, Harleen; Huffaker, Alisa; Mori, Naoki; Degenhardt, Joerg; Mueller, Lukas A.; Jander, Georg

    2015-01-01

    As a response to insect attack, maize (Zea mays) has inducible defenses that involve large changes in gene expression and metabolism. Piercing/sucking insects such as corn leaf aphid (Rhopalosiphum maidis) cause direct damage by acquiring phloem nutrients as well as indirect damage through the transmission of plant viruses. To elucidate the metabolic processes and gene expression changes involved in maize responses to aphid attack, leaves of inbred line B73 were infested with corn leaf aphids for 2 to 96 h. Analysis of infested maize leaves showed two distinct response phases, with the most significant transcriptional and metabolic changes occurring in the first few hours after the initiation of aphid feeding. After 4 d, both gene expression and metabolite profiles of aphid-infested maize reverted to being more similar to those of control plants. Although there was a predominant effect of salicylic acid regulation, gene expression changes also indicated prolonged induction of oxylipins, although not necessarily jasmonic acid, in aphid-infested maize. The role of specific metabolic pathways was confirmed using Dissociator transposon insertions in maize inbred line W22. Mutations in three benzoxazinoid biosynthesis genes, Bx1, Bx2, and Bx6, increased aphid reproduction. In contrast, progeny production was greatly decreased by a transposon insertion in the single W22 homolog of the previously uncharacterized B73 terpene synthases TPS2 and TPS3. Together, these results show that maize leaves shift to implementation of physical and chemical defenses within hours after the initiation of aphid feeding and that the production of specific metabolites can have major effects in maize-aphid interactions. PMID:26378100

  17. Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis.

    Hamerly, Timothy; Tripet, Brian P; Tigges, Michelle; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

    2015-08-01

    Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans , including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans 's consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans . Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.

  18. Metabolomics Analysis of Health Functions of Physalis Pubescens L. using by Ultra-performance Liquid Chromatography/Electrospray Ionization Quadruple Time-of-Flight Mass Spectrometry

    Hang Chu; Hui Sun; Guang-Li Yan; Ai-Hua Zhang; Chang Liu; Hui Dong; Xiang-Cai Meng; Xi-Jun Wang

    2015-01-01

    Herbal medicines may benefit from metabolomics studies, and applying metabolomics may provide answers about which herbal interventions may be effective for individuals, which metabolic processes are triggered, and the subsequent chemical pathways of activity. Physalis pubescens L (PPL) is an herbal fruit for one year living plant and has been developed into healthy function’s food. However, the mechanisms of health functions are still unclear. To comprehensively and holistically assess its anti-fatigue and antioxidant effects, a novel integrative metabolomics approach was applied. In this study, we present metabolomics analysis applying ultra performance liquid chromatography coupled to quadrupole with time-of-flight mass spectrometry (UPLC-Q/TOF-MS) to determine metabolite alterations after oral administration PPL to rats. Fifteen metabolites in urine were identified as potential biomarkers. Pattern analysis of the UPLC-Q/TOF-MS data disclosed that PPL could relieve fatigue rats by ameliorating the disturbance in amino acids metabolism and energy metabolism, alleviating the oxidative stress from reactive oxygen species and the inflammatory damage, and recovering the destructed regulation. Based on these results, we demonstrated that PPL is a promising source of natural anti-fatigue and antioxidants material for use in functional foods and medicines.

  19. Metabolomics coupled with multivariate data and pathway analysis on potential biomarkers in cholestasis and intervention effect of Paeonia lactiflora Pall.

    Xiao eMa

    2016-02-01

    Full Text Available Background: The dried root of Paeonia lactiflora Pall. (PLP is a classical Chinese herbal medicine that has been used to treat hepatic disease for thousands of years. Our previous work suggested that PLP can be used to treat hepatitis with severe cholestasis. This study explored the mechanism by which PLP affects ANIT-induced cholestasis in rats using a metabolomics approach.Methods: The effects of PLP on serum indices (TBIL, DBIL, AST, ALT, ALP and TBA and the histopathology of the liver were analyzed. Moreover, UHPLC-Q-TOF was performed to identify the possible effect of PLP on metabolites. The pathway analysis was conducted to illustrate the pathways and network by which PLP treats cholestasis. Result: High-dose PLP remarkably down-regulated the serum indices and alleviated histological damage to the liver. Metabolomics analyses showed that the therapeutic effect of high-dose PLP is mainly associated with the regulation of several metabolites, such as glycocholic acid, taurocholic acid, glycochenodeoxycholic acid, L(D-arginine and L-tryptophan. A pathway analysis showed that the metabolites were related to bile acid secretion and amino acid metabolism. In addition, the significant changes in bile acid transporters also indicated that bile acid metabolism might be involved in the therapeutic effect of PLP on cholestasis. Moreover, a principal component analysis indicated that the metabolites in the high-dose PLP group were closer to those of the control, whereas those of the moderate dose or low-dose PLP group were closer to those of the ANIT group. This finding indicated that metabolites may be responsible for the differences between the effects of low-dose and moderate-dose PLP. Conclusions: The therapeutic effect of high-dose PLP on cholestasis is possibly related to regulation of bile acid secretion and amino acid metabolism. Moreover, these findings may help better understand the mechanisms of disease and provide a potential therapy for

  20. Metabolome Comparison of Transgenic and Non-transgenic Rice by Statistical Analysis of FTIR and NMR Spectra

    Keykhosrow Keymanesh

    2009-06-01

    Full Text Available Modern biotechnology, based on recombinant DNA techniques, has made it possible to introduce new traits with great potential for crop improvement. However, concerns about unintended effects of gene transformation that possibly threaten environment or consumer health have persuaded scientists to set up pre-release tests on genetically modified organisms. Assessment of ‘substantial equivalence’ concept that established by comparison of genetically modified organism with a comparator with a history of safe use could be the first step of a comprehensive risk assessment. Metabolite level is the richest in performance of changes which stem from genetic or environmental factors. Since assessment of all metabolites in detail is very costly and practically impossible, statistical evaluation of processed data of grain spectroscopic values could be a time and cost effective substitution for complex chemical analysis. To investigate the ability of multivariate statistical techniques in comparison of metabolomes as well as testing a method for such comparisons with available tools, a transgenic rice in combination with its traditionally bred parent were used as test material, and the discriminant analysis were applied as supervised method and principal component analysis as unsupervised classification method on the processed data which were extracted from Fourier transform infrared spectroscopy and nuclear magnetic resonance spectral data of powdered rice and rice extraction and barley grain samples, of which the latter was considered as control. The results confirmed the capability of statistics, even with initial data processing applications in metabolome studies. Meanwhile, this study confirms that the supervised method results in more distinctive results.

  1. Normalization to specific gravity prior to analysis improves information recovery from high resolution mass spectrometry metabolomic profiles of human urine.

    Edmands, William M B; Ferrari, Pietro; Scalbert, Augustin

    2014-11-04

    Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets.

  2. Systematic analysis of the polyphenol metabolome using the Phenol-Explorer database.

    Rothwell, Joseph A; Urpi-Sarda, Mireia; Boto-Ordoñez, Maria; Llorach, Rafael; Farran-Codina, Andreu; Barupal, Dinesh Kumar; Neveu, Vanessa; Manach, Claudine; Andres-Lacueva, Cristina; Scalbert, Augustin

    2016-01-01

    The Phenol-Explorer web database details 383 polyphenol metabolites identified in human and animal biofluids from 221 publications. Here, we exploit these data to characterize and visualize the polyphenol metabolome, the set of all metabolites derived from phenolic food components. Qualitative and quantitative data on 383 polyphenol metabolites as described in 424 human and animal intervention studies were systematically analyzed. Of these metabolites, 301 were identified without prior enzymatic hydrolysis of biofluids, and included glucuronide and sulfate esters, glycosides, aglycones, and O-methyl ethers. Around one-third of these compounds are also known as food constituents and corresponded to polyphenols absorbed without further metabolism. Many ring-cleavage metabolites formed by gut microbiota were noted, mostly derived from hydroxycinnamates, flavanols, and flavonols. Median maximum plasma concentrations (C(max)) of all human metabolites were 0.09 and 0.32 μM when consumed from foods or dietary supplements, respectively. Median time to reach maximum plasma concentration in humans (T(max)) was 2.18 h. These data show the complexity of the polyphenol metabolome and the need to take into account biotransformations to understand in vivo bioactivities and the role of dietary polyphenols in health and disease. © 2015 The Authors. Molecular Nutrition & Food Research published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. A data preprocessing strategy for metabolomics to reduce the mask effect in data analysis

    Jun eYang

    2015-02-01

    Full Text Available Metabolomics is a booming research field. Its success highly relies on the discovery of differential metabolites by comparing different data sets (for example, patients vs. controls. One of the challenges is that differences of the low abundant metabolites between groups are often masked by the high variation of abundant metabolites -. In order to solve this challenge, a novel data preprocessing strategy consisting of 3 steps was proposed in this study. In step 1, a ‘modified 80%’ rule was used to reduce effect of missing values; in step 2, unit-variance and Pareto scaling methods were used to reduce the mask effect from the abundant metabolites. In step 3, in order to fix the adverse effect of scaling, stability information of the variables deduced from intensity information and the class information, was used to assign suitable weights to the variables. When applying to an LC/MS based metabolomics dataset from chronic hepatitis B patients study and two simulated datasets, the mask effect was found to be partially eliminated and several new low abundant differential metabolites were rescued.

  4. Metabolomics and bioactive substances in plants

    Khakimov, Bekzod

    Metabolomic analysis of plants broadens understanding of how plants may benefit humans, animals and the environment, provide sustainable food and energy, and improve current agricultural, pharmacological and medicinal practices in order to bring about healthier and longer life. The quality...... and amount of the extractible biological information is largely determined by data acquisition, data processing and analysis methodologies of the plant metabolomics studies. This PhD study focused mainly on the development and implementation of new metabolomics methodologies for improved data acquisition...... and data processing. The study mainly concerned the three most commonly applied analytical techniques in plant metabolomics, GC-MS, LC-MS and NMR. In addition, advanced chemometrics methods e.g. PARAFAC2 and ASCA have been extensively used for development of complex metabolomics data processing...

  5. Applied metabolomics in drug discovery.

    Cuperlovic-Culf, M; Culf, A S

    2016-08-01

    The metabolic profile is a direct signature of phenotype and biochemical activity following any perturbation. Metabolites are small molecules present in a biological system including natural products as well as drugs and their metabolism by-products depending on the biological system studied. Metabolomics can provide activity information about possible novel drugs and drug scaffolds, indicate interesting targets for drug development and suggest binding partners of compounds. Furthermore, metabolomics can be used for the discovery of novel natural products and in drug development. Metabolomics can enhance the discovery and testing of new drugs and provide insight into the on- and off-target effects of drugs. This review focuses primarily on the application of metabolomics in the discovery of active drugs from natural products and the analysis of chemical libraries and the computational analysis of metabolic networks. Metabolomics methodology, both experimental and analytical is fast developing. At the same time, databases of compounds are ever growing with the inclusion of more molecular and spectral information. An increasing number of systems are being represented by very detailed metabolic network models. Combining these experimental and computational tools with high throughput drug testing and drug discovery techniques can provide new promising compounds and leads.

  6. Comparative Analysis of Compatibility Effects on Invigorating Blood Circulation for Cyperi Rhizoma Series of Herb Pairs Using Untargeted Metabolomics

    Pei Liu

    2017-09-01

    Full Text Available The mutual-assistance compatibility of Cyperi Rhizoma (Xiangfu, XF and Angelicae Sinensis Radix (Danggui, DG, Chuanxiong Rhizoma (Chuanxiong, CX, Paeoniae Radix Alba (Baishao, BS, or Corydalis Rhizoma (Yanhusuo, YH, found in a traditional Chinese medicine (TCM named Xiang-Fu-Si-Wu Decoction (XFSWD, can produce synergistic and promoting blood effects. Nowadays, XFSWD has been proved to be effective in activating blood circulation and dissipating blood stasis. However, the role of the herb pairs synergistic effects in the formula were poorly understood. In order to quantitatively assess the compatibility effects of herb pairs, mass spectrometry-based untargeted metabolomics studies were performed. The plasma and urine metabolic profiles of acute blood stasis rats induced by adrenaline hydrochloride and ice water and administered with Cyperi Rhizoma—Angelicae Sinensis Radix (XD, Cyperi Rhizoma—Chuanxiong Rhizoma (XC, Cyperi Rhizoma—Paeoniae Radix Alba (XB, Cyperi Rhizoma—Corydalis Rhizoma (XY were compared. Relative peak area of identified metabolites was calculated and principal component analysis (PCA score plot from the potential markers was used to visualize the overall differences. Then, the metabolites results were used with biochemistry indicators and genes expression values as parameters to quantitatively evaluate the compatibility effects of XF series of herb pairs by PCA and correlation analysis. The collective results indicated that the four XF herb pairs regulated glycerophospholipid metabolism, steroid hormone biosynthesis and arachidonic acid metabolism pathway. XD was more prominent in regulating the blood stasis during the four XF herb pairs. This study demonstrated that metabolomics was a useful tool to efficacy evaluation and compatibility effects of TCM elucidation.

  7. The future of metabolomics in ELIXIR

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B.; Ebbels, Timothy M. D.; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L.; Jimenez, Rafael C.; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I.; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K.; Neumann, Steffen; O’Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M.; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A.; Spjuth, Ola; Thévenot, Etienne A.; Viant, Mark R.; Weber, Ralf J. M.; Willighagen, Egon L.; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases. PMID:29043062

  8. The future of metabolomics in ELIXIR.

    van Rijswijk, Merlijn; Beirnaert, Charlie; Caron, Christophe; Cascante, Marta; Dominguez, Victoria; Dunn, Warwick B; Ebbels, Timothy M D; Giacomoni, Franck; Gonzalez-Beltran, Alejandra; Hankemeier, Thomas; Haug, Kenneth; Izquierdo-Garcia, Jose L; Jimenez, Rafael C; Jourdan, Fabien; Kale, Namrata; Klapa, Maria I; Kohlbacher, Oliver; Koort, Kairi; Kultima, Kim; Le Corguillé, Gildas; Moreno, Pablo; Moschonas, Nicholas K; Neumann, Steffen; O'Donovan, Claire; Reczko, Martin; Rocca-Serra, Philippe; Rosato, Antonio; Salek, Reza M; Sansone, Susanna-Assunta; Satagopam, Venkata; Schober, Daniel; Shimmo, Ruth; Spicer, Rachel A; Spjuth, Ola; Thévenot, Etienne A; Viant, Mark R; Weber, Ralf J M; Willighagen, Egon L; Zanetti, Gianluigi; Steinbeck, Christoph

    2017-01-01

    Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the "Future of metabolomics in ELIXIR" was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.

  9. An overview of renal metabolomics.

    Kalim, Sahir; Rhee, Eugene P

    2017-01-01

    The high-throughput, high-resolution phenotyping enabled by metabolomics has been applied increasingly to a variety of questions in nephrology research. This article provides an overview of current metabolomics methodologies and nomenclature, citing specific considerations in sample preparation, metabolite measurement, and data analysis that investigators should understand when examining the literature or designing a study. Furthermore, we review several notable findings that have emerged in the literature that both highlight some of the limitations of current profiling approaches, as well as outline specific strengths unique to metabolomics. More specifically, we review data on the following: (i) tryptophan metabolites and chronic kidney disease onset, illustrating the interpretation of metabolite data in the context of established biochemical pathways; (ii) trimethylamine-N-oxide and cardiovascular disease in chronic kidney disease, illustrating the integration of exogenous and endogenous inputs to the blood metabolome; and (iii) renal mitochondrial function in diabetic kidney disease and acute kidney injury, illustrating the potential for rapid translation of metabolite data for diagnostic or therapeutic aims. Finally, we review future directions, including the need to better characterize interperson and intraperson variation in the metabolome, pool existing data sets to identify the most robust signals, and capitalize on the discovery potential of emerging nontargeted methods. Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

  10. The Human Urine Metabolome

    Bouatra, Souhaila; Aziat, Farid; Mandal, Rupasri; Guo, An Chi; Wilson, Michael R.; Knox, Craig; Bjorndahl, Trent C.; Krishnamurthy, Ramanarayan; Saleem, Fozia; Liu, Philip; Dame, Zerihun T.; Poelzer, Jenna; Huynh, Jessica; Yallou, Faizath S.; Psychogios, Nick; Dong, Edison; Bogumil, Ralf; Roehring, Cornelia; Wishart, David S.

    2013-01-01

    Urine has long been a “favored” biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing

  11. Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

    Ida, Megumi; Kosaka, Reia; Miura, Daisuke; Wariishi, Hiroyuki; Maeda-Yamamoto, Mari; Nesumi, Atsushi; Saito, Takeshi; Kanda, Tomomasa; Yamada, Koji; Tachibana, Hirofumi

    2011-01-01

    Background Green tea has various health promotion effects. Although there are numerous tea cultivars, little is known about the differences in their nutraceutical properties. Metabolic profiling techniques can provide information on the relationship between the metabolome and factors such as phenotype or quality. Here, we performed metabolomic analyses to explore the relationship between the metabolome and health-promoting attributes (bioactivity) of diverse Japanese green tea cultivars. Methodology/Principal Findings We investigated the ability of leaf extracts from 43 Japanese green tea cultivars to inhibit thrombin-induced phosphorylation of myosin regulatory light chain (MRLC) in human umbilical vein endothelial cells (HUVECs). This thrombin-induced phosphorylation is a potential hallmark of vascular endothelial dysfunction. Among the tested cultivars, Cha Chuukanbohon Nou-6 (Nou-6) and Sunrouge (SR) strongly inhibited MRLC phosphorylation. To evaluate the bioactivity of green tea cultivars using a metabolomics approach, the metabolite profiles of all tea extracts were determined by high-performance liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses, principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA), revealed differences among green tea cultivars with respect to their ability to inhibit MRLC phosphorylation. In the SR cultivar, polyphenols were associated with its unique metabolic profile and its bioactivity. In addition, using partial least-squares (PLS) regression analysis, we succeeded in constructing a reliable bioactivity-prediction model to predict the inhibitory effect of tea cultivars based on their metabolome. This model was based on certain identified metabolites that were associated with bioactivity. When added to an extract from the non-bioactive cultivar Yabukita, several metabolites enriched in SR were able to transform the extract into a bioactive extract

  12. Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress

    Malmendal, Anders; Sørensen, Jesper Givskov; Overgaard, Johannes

    2013-01-01

    -regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level......We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene...... expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic (1)H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led...

  13. An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection.

    Vijay C Antharam

    Full Text Available Clostridium difficile infection (CDI is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7 and healthy controls (n = 6. From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA, 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.

  14. Quantitative Metabolomic Analysis of Urinary Citrulline and Calcitroic Acid in Mice after Exposure to Various Types of Ionizing Radiation

    Maryam Goudarzi

    2016-05-01

    Full Text Available With the safety of existing nuclear power plants being brought into question after the Fukushima disaster and the increased level of concern over terrorism-sponsored use of improvised nuclear devices, it is more crucial to develop well-defined radiation injury markers in easily accessible biofluids to help emergency-responders with injury assessment during patient triage. Here, we focused on utilizing ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS to identify and quantitate the unique changes in the urinary excretion of two metabolite markers, calcitroic acid and citrulline, in mice induced by different forms of irradiation; X-ray irradiation at a low dose rate (LDR of 3.0 mGy/min and a high dose rate (HDR of 1.1 Gy/min, and internal exposure to Cesium-137 (137Cs and Strontium-90 (90Sr. The multiple reaction monitoring analysis showed that, while exposure to 137Cs and 90Sr induced a statistically significant and persistent decrease, similar doses of X-ray beam at the HDR had the opposite effect, and the LDR had no effect on the urinary levels of these two metabolites. This suggests that the source of exposure and the dose rate strongly modulate the in vivo metabolomic injury responses, which may have utility in clinical biodosimetry assays for the assessment of exposure in an affected population. This study complements our previous investigations into the metabolomic profile of urine from mice internally exposed to 90Sr and 137Cs and to X-ray beam radiation.

  15. An Integrated Metabolomic and Microbiome Analysis Identified Specific Gut Microbiota Associated with Fecal Cholesterol and Coprostanol in Clostridium difficile Infection.

    Antharam, Vijay C; McEwen, Daniel C; Garrett, Timothy J; Dossey, Aaron T; Li, Eric C; Kozlov, Andrew N; Mesbah, Zhubene; Wang, Gary P

    2016-01-01

    Clostridium difficile infection (CDI) is characterized by dysbiosis of the intestinal microbiota and a profound derangement in the fecal metabolome. However, the contribution of specific gut microbes to fecal metabolites in C. difficile-associated gut microbiome remains poorly understood. Using gas-chromatography mass spectrometry (GC-MS) and 16S rRNA deep sequencing, we analyzed the metabolome and microbiome of fecal samples obtained longitudinally from subjects with Clostridium difficile infection (n = 7) and healthy controls (n = 6). From 155 fecal metabolites, we identified two sterol metabolites at >95% match to cholesterol and coprostanol that significantly discriminated C. difficile-associated gut microbiome from healthy microbiota. By correlating the levels of cholesterol and coprostanol in fecal extracts with 2,395 bacterial operational taxonomic units (OTUs) determined by 16S rRNA sequencing, we identified 63 OTUs associated with high levels of coprostanol and 2 OTUs correlated with low coprostanol levels. Using indicator species analysis (ISA), 31 of the 63 coprostanol-associated bacteria correlated with health, and two Veillonella species were associated with low coprostanol levels that correlated strongly with CDI. These 65 bacterial taxa could be clustered into 12 sub-communities, with each community containing a consortium of organisms that co-occurred with one another. Our studies identified 63 human gut microbes associated with cholesterol-reducing activities. Given the importance of gut bacteria in reducing and eliminating cholesterol from the GI tract, these results support the recent finding that gut microbiome may play an important role in host lipid metabolism.

  16. Quantitative Metabolomic Analysis of Urinary Citrulline and Calcitroic Acid in Mice after Exposure to Various Types of Ionizing Radiation.

    Goudarzi, Maryam; Chauthe, Siddheshwar; Strawn, Steven J; Weber, Waylon M; Brenner, David J; Fornace, Albert J

    2016-05-20

    With the safety of existing nuclear power plants being brought into question after the Fukushima disaster and the increased level of concern over terrorism-sponsored use of improvised nuclear devices, it is more crucial to develop well-defined radiation injury markers in easily accessible biofluids to help emergency-responders with injury assessment during patient triage. Here, we focused on utilizing ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to identify and quantitate the unique changes in the urinary excretion of two metabolite markers, calcitroic acid and citrulline, in mice induced by different forms of irradiation; external γ irradiation at a low dose rate (LDR) of 3.0 mGy/min and a high dose rate (HDR) of 1.1 Gy/min, and internal exposure to Cesium-137 ((137)Cs) and Strontium-90 ((90)Sr). The multiple reaction monitoring analysis showed that, while exposure to (137)Cs and (90)Sr induced a statistically significant and persistent decrease, similar doses of external γ beam at the HDR had the opposite effect, and the LDR had no effect on the urinary levels of these two metabolites. This suggests that the source of exposure and the dose rate strongly modulate the in vivo metabolomic injury responses, which may have utility in clinical biodosimetry assays for the assessment of exposure in an affected population. This study complements our previous investigations into the metabolomic profile of urine from mice internally exposed to (90)Sr and (137)Cs and to external γ beam radiation.

  17. Untargeted metabolomic analysis using liquid chromatography quadrupole time-of-flight mass spectrometry for non-volatile profiling of wines

    Arbulu, M.; Sampedro, M.C.; Gómez-Caballero, A.; Goicolea, M.A.; Barrio, R.J.

    2015-01-01

    Highlights: • An untargeted metabolomic method for the non-volatile profile of the Graciano wine was developed. • 411 different metabolites in Graciano Vitis vinifera red wine were identified. • 15 compounds could serve to differentiate Graciano and Tempranillo wines. • An enological database (WinMet) with 2080 compounds was constructed. - Abstract: The current study presents a method for comprehensive untargeted metabolomic fingerprinting of the non-volatile profile of the Graciano Vitis vinifera wine variety, using liquid chromatography/electrospray ionization time of flight mass spectrometry (LC–ESI-QTOF). Pre-treatment of samples, chromatographic columns, mobile phases, elution gradients and ionization sources, were evaluated for the extraction of the maximum number of metabolites in red wine. Putative compounds were extracted from the raw data using the extraction algorithm, molecular feature extractor (MFE). For the metabolite identification the WinMet database was designed based on electronic databases and literature research and includes only the putative metabolites reported to be present in oenological matrices. The results from WinMet were compared with those in the METLIN database to evaluate how much the databases overlap for performing identifications. The reproducibility of the analysis was assessed using manual processing following replicate injections of Vitis vinifera cv. Graciano wine spiked with external standards. In the present work, 411 different metabolites in Graciano Vitis vinifera red wine were identified, including primary wine metabolites such as sugars (4%), amino acids (23%), biogenic amines (4%), fatty acids (2%), and organic acids (32%) and secondary metabolites such as phenols (27%) and esters (8%). Significant differences between varieties Tempranillo and Graciano were related to the presence of fifteen specific compounds

  18. Untargeted metabolomic analysis using liquid chromatography quadrupole time-of-flight mass spectrometry for non-volatile profiling of wines

    Arbulu, M. [Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain); Sampedro, M.C. [Central Service of Analysis, SGIker, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain); Gómez-Caballero, A.; Goicolea, M.A. [Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain); Barrio, R.J., E-mail: r.barrio@ehu.es [Department of Analytical Chemistry, Faculty of Pharmacy, University of the Basque Country, 01006 Vitoria-Gasteiz (Spain)

    2015-02-09

    Highlights: • An untargeted metabolomic method for the non-volatile profile of the Graciano wine was developed. • 411 different metabolites in Graciano Vitis vinifera red wine were identified. • 15 compounds could serve to differentiate Graciano and Tempranillo wines. • An enological database (WinMet) with 2080 compounds was constructed. - Abstract: The current study presents a method for comprehensive untargeted metabolomic fingerprinting of the non-volatile profile of the Graciano Vitis vinifera wine variety, using liquid chromatography/electrospray ionization time of flight mass spectrometry (LC–ESI-QTOF). Pre-treatment of samples, chromatographic columns, mobile phases, elution gradients and ionization sources, were evaluated for the extraction of the maximum number of metabolites in red wine. Putative compounds were extracted from the raw data using the extraction algorithm, molecular feature extractor (MFE). For the metabolite identification the WinMet database was designed based on electronic databases and literature research and includes only the putative metabolites reported to be present in oenological matrices. The results from WinMet were compared with those in the METLIN database to evaluate how much the databases overlap for performing identifications. The reproducibility of the analysis was assessed using manual processing following replicate injections of Vitis vinifera cv. Graciano wine spiked with external standards. In the present work, 411 different metabolites in Graciano Vitis vinifera red wine were identified, including primary wine metabolites such as sugars (4%), amino acids (23%), biogenic amines (4%), fatty acids (2%), and organic acids (32%) and secondary metabolites such as phenols (27%) and esters (8%). Significant differences between varieties Tempranillo and Graciano were related to the presence of fifteen specific compounds.

  19. The Chemistry of Plant–Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance

    Mhlongo, Msizi I.; Piater, Lizelle A.; Madala, Ntakadzeni E.; Labuschagne, Nico; Dubery, Ian A.

    2018-01-01

    Plant roots communicate with microbes in a sophisticated manner through chemical communication within the rhizosphere, thereby leading to biofilm formation of beneficial microbes and, in the case of plant growth-promoting rhizomicrobes/-bacteria (PGPR), resulting in priming of defense, or induced resistance in the plant host. The knowledge of plant–plant and plant–microbe interactions have been greatly extended over recent years; however, the chemical communication leading to priming is far from being well understood. Furthermore, linkage between below- and above-ground plant physiological processes adds to the complexity. In metabolomics studies, the main aim is to profile and annotate all exo- and endo-metabolites in a biological system that drive and participate in physiological processes. Recent advances in this field has enabled researchers to analyze 100s of compounds in one sample over a short time period. Here, from a metabolomics viewpoint, we review the interactions within the rhizosphere and subsequent above-ground ‘signalomics’, and emphasize the contributions that mass spectrometric-based metabolomic approaches can bring to the study of plant-beneficial – and priming events. PMID:29479360

  20. Comparison of quenching and extraction methodologies for metabolome analysis of Lactobacillus plantarum

    Faijes Magda

    2007-08-01

    Full Text Available Abstract Background A reliable quenching and metabolite extraction method has been developed for Lactobacillus plantarum. The energy charge value was used as a critical indicator for fixation of metabolism. Results Four different aqueous quenching solutions, all containing 60% of methanol, were compared for their efficiency. Only the solutions containing either 70 mM HEPES or 0.85% (w/v ammonium carbonate (pH 5.5 caused less than 10% cell leakage and the energy charge of the quenched cells was high, indicating rapid inactivation of the metabolism. The efficiency of extraction of intracellular metabolites from cell cultures depends on the extraction methods, and is expected to vary between micro-organisms. For L. plantarum, we have compared five different extraction methodologies based on (i cold methanol, (ii perchloric acid, (iii boiling ethanol, (iv chloroform/methanol (1:1 and (v chloroform/water (1:1. Quantification of representative intracellular metabolites showed that the best extraction efficiencies were achieved with cold methanol, boiling ethanol and perchloric acid. Conclusion The ammonium carbonate solution was selected as the most suitable quenching buffer for metabolomics studies in L. plantarum because (i leakage is minimal, (ii the energy charge indicates good fixation of metabolism, and (iii all components are easily removed during freeze-drying. A modified procedure based on cold methanol extraction combined good extractability with mild extraction conditions and high enzymatic inactivation. These features make the combination of these quenching and extraction protocols very suitable for metabolomics studies with L. plantarum.

  1. Quality Variation of Goji (Fruits of Lycium spp. in China: A Comparative Morphological and Metabolomic Analysis

    Ruyu Yao

    2018-02-01

    Full Text Available Goji (fruits of Lycium barbarum L. and L. chinense Mill. has been used in China as food and medicine for millennia, and globally has been consumed increasingly as a healthy food. Ningxia, with a semi-arid climate, always had the reputation of producing best goji quality (daodi area. Recently, the increasing market demand pushed the cultivation into new regions with different climates. We therefore ask: How does goji quality differ among production areas of various climatic regions? Historical records are used to trace the spread of goji production in China over time. Quality measurements of 51 samples were correlated with the four main production areas in China: monsoon (Hebei, semi-arid (Ningxia, Gansu, and Inner Mongolia, plateau (Qinghai and arid regions (Xinjiang. We include morphological characteristics, sugar and polysaccharide content, antioxidant activity, and metabolomic profiling to compare goji among climatic regions. Goji cultivation probably began in the East (Hebei of China around 100 CE and later shifted westward to the semi-arid regions. Goji from monsoon, plateau and arid regions differ according to its fruit morphology, whereas semi-arid goji cannot be separated from the other regions. L. chinense fruits, which are exclusively cultivated in Hebei (monsoon, are significantly lighter, smaller and brighter in color, while the heaviest and largest fruits (L. barbarum stem from the plateau. The metabolomic profiling separates the two species but not the regions of cultivation. Lycium chinense and samples from the semi-arid regions have significantly (p < 0.01 lower sugar contents and L. chinense shows the highest antioxidant activity. Our results do not justify superiority of a specific production area over other areas. Instead it will be essential to distinguish goji from different regions based on the specific morphological and chemical traits with the aim to understand what its intended uses are.

  2. The influence of different diets on metabolism and atherosclerosis processes-A porcine model: Blood serum, urine and tissues 1H NMR metabolomics targeted analysis.

    Adam Zabek

    Full Text Available The global epidemic of cardiovascular diseases leads to increased morbidity and mortality caused mainly by myocardial infarction and stroke. Atherosclerosis is the major pathological process behind this epidemic. We designed a novel model of atherosclerosis in swine. Briefly, the first group (11 pigs received normal pig feed (balanced diet group-BDG for 12 months, the second group (9 pigs was fed a Western high-calorie diet (unbalanced diet group-UDG for 12 months, the third group (8 pigs received a Western type high-calorie diet for 9 months later replaced by a normal diet for 3 months (regression group-RG. Clinical measurements included zoometric data, arterial blood pressure, heart rate and ultrasonographic evaluation of femoral arteries. Then, the animals were sacrificed and the blood serum, urine and skeletal muscle tissue were collected and 1H NMR based metabolomics studies with the application of fingerprinting PLS-DA and univariate analysis were done. Our results have shown that the molecular disturbances might overlap with other diseases such as onset of diabetes, sleep apnea and other obesity accompanied diseases. Moreover, we revealed that once initiated, molecular changes did not return to homeostatic equilibrium, at least for the duration of this experiment.

  3. Investigation of the preventive effect of Sijunzi decoction on mitomycin C-induced immunotoxicity in rats by 1H NMR and MS-based untargeted metabolomic analysis.

    Guan, Zhibo; Wu, Juan; Wang, Cancan; Zhang, Fang; Wang, Yinan; Wang, Miao; Zhao, Min; Zhao, Chunjie

    2018-01-10

    Sijunzi decoction (SJZD) is a well known traditional Chinese prescription used for the treatment of gastrointestinal disorders and immunity enhancement. It has been found to indeed improve life quality of chemotherapy patients and extensive used in clinical conbined with chemotherapeutics for the treatment of cancer. The aim of this study was to investigate the preventive effect of the immunotoxicity of SJZD on mitomycin C (MMC) and the metabolic mechanism of action. NMR and MS-based metabolomics approaches were combined for monitoring MMC-induced immunotoxicity and the protective effect of SJZD. Body weight change and mortality, histopathological observations and relative viscera weight determinations of spleen and thymus, sternum micronucleus assay and hematological analysis were used to confirm the immunotoxicity and attenuation effects. An OPLS-DA approach was used to screen potential biomarkers of immunotoxicity and the MetaboAnalyst and KEGG PATHWAY Database were used to investigate the metabolic pathways. 8 biomarkers in plasma samples, 19 in urine samples and 10 in spleen samples were identified as being primarily involved in amino acid metabolism, carbohydrate metabolism and lipid metabolism. The most critical pathway was alanine, aspartate and glutamate metabolism. The variations in biomarkers revealed the preventive effect of the immunotoxicity of SJZD on MMC and significant for speculating the possible metabolic mechanism. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  4. The Human Blood Metabolome-Transcriptome Interface

    Schramm, Katharina; Adamski, Jerzy; Gieger, Christian; Herder, Christian; Carstensen, Maren; Peters, Annette; Rathmann, Wolfgang; Roden, Michael; Strauch, Konstantin; Suhre, Karsten; Kastenmüller, Gabi; Prokisch, Holger; Theis, Fabian J.

    2015-01-01

    Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the ‘human blood metabolome-transcriptome interface’ (BMTI). Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease. PMID:26086077

  5. The Human Blood Metabolome-Transcriptome Interface.

    Jörg Bartel

    2015-06-01

    Full Text Available Biological systems consist of multiple organizational levels all densely interacting with each other to ensure function and flexibility of the system. Simultaneous analysis of cross-sectional multi-omics data from large population studies is a powerful tool to comprehensively characterize the underlying molecular mechanisms on a physiological scale. In this study, we systematically analyzed the relationship between fasting serum metabolomics and whole blood transcriptomics data from 712 individuals of the German KORA F4 cohort. Correlation-based analysis identified 1,109 significant associations between 522 transcripts and 114 metabolites summarized in an integrated network, the 'human blood metabolome-transcriptome interface' (BMTI. Bidirectional causality analysis using Mendelian randomization did not yield any statistically significant causal associations between transcripts and metabolites. A knowledge-based interpretation and integration with a genome-scale human metabolic reconstruction revealed systematic signatures of signaling, transport and metabolic processes, i.e. metabolic reactions mainly belonging to lipid, energy and amino acid metabolism. Moreover, the construction of a network based on functional categories illustrated the cross-talk between the biological layers at a pathway level. Using a transcription factor binding site enrichment analysis, this pathway cross-talk was further confirmed at a regulatory level. Finally, we demonstrated how the constructed networks can be used to gain novel insights into molecular mechanisms associated to intermediate clinical traits. Overall, our results demonstrate the utility of a multi-omics integrative approach to understand the molecular mechanisms underlying both normal physiology and disease.

  6. Disruption of TCA Cycle and Glutamate Metabolism Identified by Metabolomics in an In Vitro Model of Amyotrophic Lateral Sclerosis.

    Veyrat-Durebex, Charlotte; Corcia, Philippe; Piver, Eric; Devos, David; Dangoumau, Audrey; Gouel, Flore; Vourc'h, Patrick; Emond, Patrick; Laumonnier, Frédéric; Nadal-Desbarats, Lydie; Gordon, Paul H; Andres, Christian R; Blasco, Hélène

    2016-12-01

    This study aims to develop a cellular metabolomics model that reproduces the pathophysiological conditions found in amyotrophic lateral sclerosis in order to improve knowledge of disease physiology. We used a co-culture model combining the motor neuron-like cell line NSC-34 and the astrocyte clone C8-D1A, with each over-expressing wild-type or G93C mutant human SOD1, to examine amyotrophic lateral sclerosis (ALS) physiology. We focused on the effects of mutant human SOD1 as well as oxidative stress induced by menadione on intracellular metabolism using a metabolomics approach through gas chromatography coupled with mass spectrometry (GC-MS) analysis. Preliminary non-supervised analysis by Principal Component Analysis (PCA) revealed that cell type, genetic environment, and time of culture influenced the metabolomics profiles. Supervised analysis using orthogonal partial least squares discriminant analysis (OPLS-DA) on data from intracellular metabolomics profiles of SOD1 G93C co-cultures produced metabolites involved in glutamate metabolism and the tricarboxylic acid cycle (TCA) cycle. This study revealed the feasibility of using a metabolomics approach in a cellular model of ALS. We identified potential disruption of the TCA cycle and glutamate metabolism under oxidative stress, which is consistent with prior research in the disease. Analysis of metabolic alterations in an in vitro model is a novel approach to investigation of disease physiology.

  7. Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

    Hruby, Adela; Toledo, Estefanía; Clish, Clary B.; Martínez-González, Miguel A.

    2016-01-01

    OBJECTIVE To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. RESEARCH DESIGN AND METHODS We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite. RESULTS We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24–1.48]; I2 = 9.5%), 36% for leucine (1.36 [1.17–1.58]; I2 = 37.4%), 35% for valine (1.35 [1.19–1.53]; I2 = 45.8%), 36% for tyrosine (1.36 [1.19–1.55]; I2 = 51.6%), and 26% for phenylalanine (1.26 [1.10–1.44]; I2 = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81–0.96] and 0

  8. Comparative genomic analysis of the microbiome [corrected] of herbivorous insects reveals eco-environmental adaptations: biotechnology applications.

    Weibing Shi

    Full Text Available Metagenome analysis of the gut symbionts of three different insects was conducted as a means of comparing taxonomic and metabolic diversity of gut microbiomes to diet and life history of the insect hosts. A second goal was the discovery of novel biocatalysts for biorefinery applications. Grasshopper and cutworm gut symbionts were sequenced and compared with the previously identified metagenome of termite gut microbiota. These insect hosts represent three different insect orders and specialize on different food types. The comparative analysis revealed dramatic differences among the three insect species in the abundance and taxonomic composition of the symbiont populations present in the gut. The composition and abundance of symbionts was correlated with their previously identified capacity to degrade and utilize the different types of food consumed by their hosts. The metabolic reconstruction revealed that the gut metabolome of cutworms and grasshoppers was more enriched for genes involved in carbohydrate metabolism and transport than wood-feeding termite, whereas the termite gut metabolome was enriched for glycosyl hydrolase (GH enzymes relevant to lignocellulosic biomass degradation. Moreover, termite gut metabolome was more enriched with nitrogen fixation genes than those of grasshopper and cutworm gut, presumably due to the termite's adaptation to the high fiber and less nutritious food types. In order to evaluate and exploit the insect symbionts for biotechnology applications, we cloned and further characterized four biomass-degrading enzymes including one endoglucanase and one xylanase from both the grasshopper and cutworm gut symbionts. The results indicated that the grasshopper symbiont enzymes were generally more efficient in biomass degradation than the homologous enzymes from cutworm symbionts. Together, these results demonstrated a correlation between the composition and putative metabolic functionality of the gut microbiome and host

  9. System-Level and Granger Network Analysis of Integrated Proteomic and Metabolomic Dynamics Identifies Key Points of Grape Berry Development at the Interface of Primary and Secondary Metabolism

    Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram

    2017-01-01

    Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major d...

  10. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors

    Vázquez Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez Martínez, Miguel Ángel; Vinaixa Crevillent, Maria; Chiva Blanch, Gemma; Estruch Riba, Ramon; Correig Blanchar, Xavier; Andrés Lacueva, Ma. Cristina

    2012-01-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100m...

  11. Comprehensive analysis of the tryptophan metabolome in urine of patients with acute intermittent porphyria.

    Gomez-Gomez, Alex; Marcos, Josep; Aguilera, Paula; To-Figueras, Jordi; Pozo, Oscar J

    2017-08-15

    Acute intermittent porphyria (AIP) is a rare metabolic disorder due to a deficiency of porphobilinogen deaminase, the third enzyme of the heme biosynthetic pathway. This low enzymatic activity may predispose to the appearance of acute neurological attacks. Seminal studies suggested that AIP was associated with changes in tryptophan homeostasis with inconclusive results. Therefore, the aim of this study was to analyze the urinary metabolome of AIP patients focusing on tryptophan metabolism using state-of-the-art technology. This was a case-control study including a group of 25 AIP patients with active biochemical disease and increased excretion of heme-precursors and 25 healthy controls. Tryptophan and related compounds and metabolites including: large neutral amino acids (LNAAs), serotonin, kynurenine, kynurenic acid and anthranilic acid were quantified in urine by liquid chromatography tandem-mass spectrometry (LC-MS/MS). Twenty-nine biological markers (including metabolic ratios and absolute concentrations) were compared between patients and controls. Significant differences were found in the tryptophan-kynurenine metabolic pathway. Compared to controls, AIP patients showed: (a) increased urinary excretion of kynurenine and anthranilic acid (Pmetabolome of hepatic porphyrias. Copyright © 2017. Published by Elsevier B.V.

  12. Metabolomics analysis of TiO2 nanoparticles induced toxicological effects on rice (Oryza sativa L.).

    Wu, Biying; Zhu, Lizhong; Le, X Chris

    2017-11-01

    The wide occurrence and high environmental concentration of titanium dioxide nanoparticles (nano-TiO 2 ) have raised concerns about their potential toxic effects on crops. In this study, we employed a GC-MS-based metabolomic approach to investigate the potential toxicity of nano-TiO 2 on hydroponically-cultured rice (Oryza sativa L.) after exposed to 0, 100, 250 or 500 mg/L of nano-TiO 2 for fourteen days. Results showed that the biomass of rice was significantly decreased and the antioxidant defense system was significantly disturbed after exposure to nano-TiO 2 . One hundred and five identified metabolites showed significant difference compared to the control, among which the concentrations of glucose-6-phosphate, glucose-1-phosphate, succinic and isocitric acid were increased most, while the concentrations of sucrose, isomaltulose, and glyoxylic acid were decreased most. Basic energy-generating ways including tricarboxylic acid cycle and the pentose phosphate pathway, were elevated significantly while the carbohydrate synthesis metabolism including starch and sucrose metabolism, and glyoxylate and dicarboxylate metabolism were inhibited. However, the biosynthetic formation of most of the identified fatty acids, amino acids and secondary metabolites which correlated to crop quality, were increased. The results suggest that the metabolism of rice plants is distinctly disturbed after exposure to nano-TiO 2 , and nano-TiO 2 would have a mixed effect on the yield and quality of rice. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. H-1 Nuclear Magnetic Resonance Metabolomics Analysis Identifies Novel Urinary Biomarkers for Lung Function

    McClay, Joseph L.; Adkins, Daniel E.; Isern, Nancy G.; O'Connell, Thomas M.; Wooten, Jan B.; Zedler, Barbara K.; Dasika, Madhukar S.; Webb, B.T.; Webb-Robertson, Bobbie-Jo M.; Pounds, Joel G.; Murrelle, Edward L.; Leppert, Mark F.; van den Oord, Edwin J.

    2010-01-01

    Chronic obstructive pulmonary disease (COPD), characterized by chronic airflow limitation, is a serious and growing public health concern. The major environmental risk factor for COPD is tobacco smoking, but the biological mechanisms underlying COPD are not well understood. In this study, we used proton nuclear magnetic resonance (1H-NMR) spectroscopy to identify and quantify metabolites associated with lung function in COPD. Plasma and urine were collected from 197 adults with COPD and from 195 adults without COPD. Samples were assayed using a 600 MHz NMR spectrometer, and the resulting spectra were analyzed against quantitative spirometric measures of lung function. After correcting for false discoveries and adjusting for covariates (sex, age, smoking) several spectral regions in urine were found to be significantly associated with baseline lung function. These regions correspond to the metabolites trigonelline, hippurate and formate. Concentrations of each metabolite, standardized to urinary creatinine, were associated with baseline lung function (minimum p-value = 0.0002 for trigonelline). No significant associations were found with plasma metabolites. Two of the three urinary metabolites positively associated with baseline lung function, i.e. hippurate and formate, are often related to gut microflora. This suggests that the microbiome composition is variable between individuals with different lung function. Alternatively, the nature and origins of all three associated metabolites may reflect lifestyle differences affecting overall health. Our results will require replication and validation, but demonstrate the utility of NMR metabolomics as a screening tool for identifying novel biomarkers of lung disease or disease risk.

  14. Metabolomics analysis identifies sex-associated metabotypes of oxidative stress and the autotaxin–lysoPA axis in COPD

    Naz, Shama; Kolmert, Johan; Yang, Mingxing; Reinke, Stacey N.; Kamleh, Muhammad Anas; Snowden, Stuart; Heyder, Tina; Levänen, Bettina; Erle, David J.; Sköld, C. Magnus; Wheelock, Åsa M.; Wheelock, Craig E.

    2017-01-01

    Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and a leading cause of mortality and morbidity worldwide. The aim of this study was to investigate the sex dependency of circulating metabolic profiles in COPD. Serum from healthy never-smokers (healthy), smokers with normal lung function (smokers), and smokers with COPD (COPD; Global Initiative for Chronic Obstructive Lung Disease stages I–II/A–B) from the Karolinska COSMIC cohort (n=116) was analysed using our nontargeted liquid chromatography–high resolution mass spectrometry metabolomics platform. Pathway analyses revealed that several altered metabolites are involved in oxidative stress. Supervised multivariate modelling showed significant classification of smokers from COPD (p=2.8×10−7). Sex stratification indicated that the separation was driven by females (p=2.4×10−7) relative to males (p=4.0×10−4). Significantly altered metabolites were confirmed quantitatively using targeted metabolomics. Multivariate modelling of targeted metabolomics data confirmed enhanced metabolic dysregulation in females with COPD (p=3.0×10−3) relative to males (p=0.10). The autotaxin products lysoPA (16:0) and lysoPA (18:2) correlated with lung function (forced expiratory volume in 1 s) in males with COPD (r=0.86; pCOPD, and suggest that sex-enhanced dysregulation in oxidative stress, and potentially the autotaxin–lysoPA axis, are associated with disease mechanisms and/or prevalence. PMID:28642310

  15. Women with preterm birth have a distinct cervicovaginal metabolome.

    Ghartey, Jeny; Bastek, Jamie A; Brown, Amy G; Anglim, Laura; Elovitz, Michal A

    2015-06-01

    Metabolomics has the potential to reveal novel pathways involved in the pathogenesis of preterm birth (PTB). The objective of this study was to investigate whether the cervicovaginal (CV) metabolome was different in asymptomatic women destined to have a PTB compared with term birth. A nested case-control study was performed using CV fluid collected from a larger prospective cohort. The CV fluid was collected between 20-24 weeks (V1) and 24-28 weeks (V2). The metabolome was compared between women with a spontaneous PTB (n = 10) to women who delivered at term (n = 10). Samples were extracted and prepared for analysis using a standard extraction solvent method. Global biochemical profiles were determined using gas chromatography/mass spectrometry and ultra-performance liquid chromatography/tandem mass spectrometry. An ANOVA was used to detect differences in biochemical compounds between the groups. A false discovery rate was estimated to account for multiple comparisons. A total of 313 biochemicals were identified in CV fluid. Eighty-two biochemicals were different in the CV fluid at V1 in those destined to have a PTB compared with term birth, whereas 48 were different at V2. Amino acid, carbohydrate, and peptide metabolites were distinct between women with and without PTB. These data suggest that the CV space is metabolically active during pregnancy. Changes in the CV metabolome may be observed weeks, if not months, prior to any clinical symptoms. Understanding the CV metabolome may hold promise for unraveling the pathogenesis of PTB and may provide novel biomarkers to identify women most at risk. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Quantitative Clinical Diagnostic Analysis of Acetone in Human Blood by HPLC: A Metabolomic Search for Acetone as Indicator

    Esin Akgul Kalkan

    2016-01-01

    Full Text Available Using high-performance liquid chromatography (HPLC and 2,4-dinitrophenylhydrazine (2,4-DNPH as a derivatizing reagent, an analytical method was developed for the quantitative determination of acetone in human blood. The determination was carried out at 365 nm using an ultraviolet-visible (UV-Vis diode array detector (DAD. For acetone as its 2,4-dinitrophenylhydrazone derivative, a good separation was achieved with a ThermoAcclaim C18 column (15 cm × 4.6 mm × 3 μm at retention time (tR 12.10 min and flowrate of 1 mL min−1 using a (methanol/acetonitrile water elution gradient. The methodology is simple, rapid, sensitive, and of low cost, exhibits good reproducibility, and allows the analysis of acetone in biological fluids. A calibration curve was obtained for acetone using its standard solutions in acetonitrile. Quantitative analysis of acetone in human blood was successfully carried out using this calibration graph. The applied method was validated in parameters of linearity, limit of detection and quantification, accuracy, and precision. We also present acetone as a useful tool for the HPLC-based metabolomic investigation of endogenous metabolism and quantitative clinical diagnostic analysis.

  17. Metabolomics Analysis of Hormone-Responsive and Triple-Negative Breast Cancer Cell Responses to Paclitaxel Identify Key Metabolic Differences.

    Stewart, Delisha A; Winnike, Jason H; McRitchie, Susan L; Clark, Robert F; Pathmasiri, Wimal W; Sumner, Susan J

    2016-09-02

    To date, no targeted therapies are available to treat triple negative breast cancer (TNBC), while other breast cancer subtypes are responsive to current therapeutic treatment. Metabolomics was conducted to reveal differences in two hormone receptor-negative TNBC cell lines and two hormone receptor-positive Luminal A cell lines. Studies were conducted in the presence and absence of paclitaxel (Taxol). TNBC cell lines had higher levels of amino acids, branched-chain amino acids, nucleotides, and nucleotide sugars and lower levels of proliferation-related metabolites like choline compared with Luminal A cell lines. In the presence of paclitaxel, each cell line showed unique metabolic responses, with some similarities by type. For example, in the Luminal A cell lines, levels of lactate and creatine decreased while certain choline metabolites and myo-inositol increased with paclitaxel. In the TNBC cell lines levels of glutamine, glutamate, and glutathione increased, whereas lysine, proline, and valine decreased in the presence of drug. Profiling secreted inflammatory cytokines in the conditioned media demonstrated a greater response to paclitaxel in the hormone-positive Luminal cells compared with a secretion profile that suggested greater drug resistance in the TNBC cells. The most significant differences distinguishing the cell types based on pathway enrichment analyses were related to amino acid, lipid and carbohydrate metabolism pathways, whereas several biological pathways were differentiated between the cell lines following treatment.

  18. Mathematical Modeling Approaches in Plant Metabolomics.

    Fürtauer, Lisa; Weiszmann, Jakob; Weckwerth, Wolfram; Nägele, Thomas

    2018-01-01

    The experimental analysis of a plant metabolome typically results in a comprehensive and multidimensional data set. To interpret metabolomics data in the context of biochemical regulation and environmental fluctuation, various approaches of mathematical modeling have been developed and have proven useful. In this chapter, a general introduction to mathematical modeling is presented and discussed in context of plant metabolism. A particular focus is laid on the suitability of mathematical approaches to functionally integrate plant metabolomics data in a metabolic network and combine it with other biochemical or physiological parameters.

  19. A model‐driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K‐12 MG1655 that is biochemically and thermodynamically consistent

    McCloskey, Douglas; Gangoiti, Jon A.; King, Zachary A.

    2014-01-01

    in metabolomes between anaerobic and aerobic growth of Escherichia coli. Constraint‐based modeling was utilized to deduce a target list of compounds for downstream method development. An analytical and experimental methodology was developed and tailored to the compound chemistry and growth conditions of interest....... This included the construction of a rapid sampling apparatus for use with anaerobic cultures. The resulting genome‐scale data sets for anaerobic and aerobic growth were validated by comparison to previous small‐scale studies comparing growth of E. coli under the same conditions. The metabolomics data were......‐oxidation pathway for synthesis of fatty acids. This analysis also identified enzyme promiscuity for the pykA gene, that is critical for anaerobic growth, and which has not been previously incorporated into metabolic models of E coli. Biotechnol....

  20. Metabolomics Study of Resina Draconis on Myocardial Ischemia Rats Using Ultraperformance Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry Combined with Pattern Recognition Methods and Metabolic Pathway Analysis

    Yunpeng Qi

    2013-01-01

    Full Text Available Resina draconis (bright red resin isolated from Dracaena cochinchinensis, RD has been clinically used for treatment of myocardial ischemia (MI for many years. However, the mechanisms of its pharmacological action on MI are still poorly understood. This study aimed to characterize the plasma metabolic profiles of MI and investigate the mechanisms of RD on MI using ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry-based metabolomics combined with pattern recognition methods and metabolic pathway analysis. Twenty metabolite markers characterizing metabolic profile of MI were revealed, which were mainly involved in aminoacyl-tRNA biosynthesis, phenylalanine, tyrosine, and tryptophan biosynthesis, vascular smooth muscle contraction, sphingolipid metabolism, and so forth. After RD treatment, however, levels of seven MI metabolite markers, including phytosphingosine, sphinganine, acetylcarnitine, cGMP, cAMP, L-tyrosine, and L-valine, were turned over, indicating that RD is likely to alleviate MI through regulating the disturbed vascular smooth muscle contraction, sphingolipid metabolism, phenylalanine metabolism, and BCAA metabolism. To our best knowledge, this is the first comprehensive study to investigate the mechanisms of RD for treating MI, from a metabolomics point of view. Our findings are very valuable to gain a better understanding of MI metabolic profiles and provide novel insights for exploring the mechanisms of RD on MI.

  1. Qualitative Metabolome Analysis of Human Cerebrospinal Fluid by 13C-/12C-Isotope Dansylation Labeling Combined with Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

    Guo, Kevin; Bamforth, Fiona; Li, Liang

    2011-02-01

    Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by 13C-dansyl and 12C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner.

  2. Qualitative metabolome analysis of human cerebrospinal fluid by 13C-/12C-isotope dansylation labeling combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry.

    Guo, Kevin; Bamforth, Fiona; Li, Liang

    2011-02-01

    Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by (13)C-dansyl and (12)C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner. © American Society for Mass Spectrometry, 2011

  3. Sulfites and the wine metabolome.

    Roullier-Gall, Chloé; Hemmler, Daniel; Gonsior, Michael; Li, Yan; Nikolantonaki, Maria; Aron, Alissa; Coelho, Christian; Gougeon, Régis D; Schmitt-Kopplin, Philippe

    2017-12-15

    In a context of societal concern about food preservation, the reduction of sulfite input plays a major role in the wine industry. To improve the understanding of the chemistry involved in the SO 2 protection, a series of bottle aged Chardonnay wines made from the same must, but with different concentrations of SO 2 added at pressing were analyzed by ultrahigh resolution mass spectrometry (FT-ICR-MS) and excitation emission matrix fluorescence (EEMF). Metabolic fingerprints from FT-ICR-MS data could discriminate wines according to the added concentration to the must but they also revealed chemistry-related differences according to the type of stopper, providing a wine metabolomics picture of the impact of distinct stopping strategies. Spearman rank correlation was applied to link the statistically modeled EEMF components (parallel factor analysis (PARAFAC)) and the exact mass information from FT-ICR-MS, and thus revealing the extent of sulfur-containing compounds which could show some correlation with fluorescence fingerprints. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Metabolomic analysis of marine and mud crabs based on antibacterial activity

    A.A. Laith

    2017-08-01

    Full Text Available Isolated compounds from marine invertebrates are being increasingly known to possess various pharmacological activities with which many useful drugs have been developed. Crabs contain bioactive compounds including antibacterial, antifungal and antiviral metabolites, isolated from various tissues and organs that have revolutionized treatment of serious diseases. The present study represents the first attempt to investigate and compare the natural antibacterial properties from whole extract of marine blue swimmer crab, Portunus pelagicus, and mud crab, Scylla tranquebarica, against fish pathogenic bacteria. Liquid chromatography/mass spectrometry utilizing a time-of-flight (TOF mass analyser (LC/MS-QTOF based metabolomics approach was used to characterize the variation in secondary metabolite production in P. pelagicus and S. tranquebarica crab habitats in Malaysia. Different metabolites are evaluated in both crab species using LC/MS-QTOF. Initially a total of 75 metabolites were identified and only 19 metabolites satisfied the P-Corr cut-off point of less than 0.01 and at least 2-fold change. These metabolites, which contain anti-inflammatory and antibacterial properties, were down regulated in S. tranquebarica samples and up regulated in P. pelagicus samples. In vitro bioassay of methanolic P. pelagicus extracts showed the best antimicrobial response against Gram positive bacteria, Streptococcus agalactiae, and Gram negative bacteria, Vibrio alginolyticus, Klebsiella pneumoniae, and Escherichia coli, with a statistically significant difference (P < 0.05 of P. pelagicus extracts as compared to S. tranquebarica. The results indicate that both types of crab extracts are bactericidal at higher concentrations and bacteriostatic at lower concentrations. This manuscript reports the role of marine and mud crabs with specific emphasis on their secondary metabolites, and discusses current and future developments in both the production of desired crab

  5. Metabolomics and Epidemiology Working Group

    The Metabolomics and Epidemiology (MetEpi) Working Group promotes metabolomics analyses in population-based studies, as well as advancement in the field of metabolomics for broader biomedical and public health research.

  6. Quantitative 1H NMR metabolomics reveals extensive metabolic reprogramming of primary and secondary metabolism in elicitor-treated opium poppy cell cultures

    Vogel Hans J

    2008-01-01

    Full Text Available Abstract Background Opium poppy (Papaver somniferum produces a diverse array of bioactive benzylisoquinoline alkaloids and has emerged as a model system to study plant alkaloid metabolism. The plant is cultivated as the only commercial source of the narcotic analgesics morphine and codeine, but also produces many other alkaloids including the antimicrobial agent sanguinarine. Modulations in plant secondary metabolism as a result of environmental perturbations are often associated with the altered regulation of other metabolic pathways. As a key component of our functional genomics platform for opium poppy we have used proton nuclear magnetic resonance (1H NMR metabolomics to investigate the interplay between primary and secondary metabolism in cultured opium poppy cells treated with a fungal elicitor. Results Metabolite fingerprinting and compound-specific profiling showed the extensive reprogramming of primary metabolic pathways in association with the induction of alkaloid biosynthesis in response to elicitor treatment. Using Chenomx NMR Suite v. 4.6, a software package capable of identifying and quantifying individual compounds based on their respective signature spectra, the levels of 42 diverse metabolites were monitored over a 100-hour time course in control and elicitor-treated opium poppy cell cultures. Overall, detectable and dynamic changes in the metabolome of elicitor-treated cells, especially in cellular pools of carbohydrates, organic acids and non-protein amino acids were detected within 5 hours after elicitor treatment. The metabolome of control cultures also showed substantial modulations 80 hours after the start of the time course, particularly in the levels of amino acids and phospholipid pathway intermediates. Specific flux modulations were detected throughout primary metabolism, including glycolysis, the tricarboxylic acid cycle, nitrogen assimilation, phospholipid/fatty acid synthesis and the shikimate pathway, all of which

  7. Study of exhaled breath condensate sample preparation for metabolomics analysis by LC-MS/MS in high resolution mode.

    Fernández-Peralbo, M A; Calderón Santiago, M; Priego-Capote, F; Luque de Castro, M D

    2015-11-01

    Metabolomic analysis of exhaled breath condensate (EBC) requires an unavoidable sample preparation step because of the low concentration of its components, and potential cleanup for possible interferents. Sample preparation based on protein precipitation (PP), solid-phase extraction (SPE) by hydrophilic and lipophilic sorbents or lyophilization has demonstrated that the analytical sample from the last is largely the best because lyophilization allows reconstitution in a volume as small as required (preconcentration factors up to 80-times with respect to the original sample), thus doubling the number of detected compounds as compared with the other alternatives (47 versus 25). In addition, PP and/or SPE cleanup are unnecessary as no effect from the EBC components removed by these steps appears in the chromatograms. The total 49 EBC compounds tentatively identified and confirmed by MS/MS in this research include amino acids, fatty acids, fatty amides, fatty aldehydes, sphingoid bases, oxoanionic compounds, imidazoles, hydroxy acids and aliphatic acyclic acids. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Supervised Semi-Automated Data Analysis Software for Gas Chromatography / Differential Mobility Spectrometry (GC/DMS) Metabolomics Applications.

    Peirano, Daniel J; Pasamontes, Alberto; Davis, Cristina E

    2016-09-01

    Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities.

  9. Metabolomics coupled with similarity analysis advances the elucidation of the cold/hot properties of traditional Chinese medicines.

    Jia, Yan; Zhang, Zheng-Zheng; Wei, Yu-Hai; Xue-Mei, Qin; Li, Zhen-Yu

    2017-08-01

    It recently becomes an important and urgent mission for modern scientific research to identify and explain the theory of traditional Chinese medicine (TCM), which has been utilized in China for more than four millennia. Since few works have been contributed to understanding the TCM theory, the mechanism of actions of drugs with cold/hot properties remains unclear. In the present study, six kinds of typical herbs with cold or hot properties were orally administered into mice, and serum and liver samples were analyzed using an untargeted nuclear magnetic resonance (NMR) based metabolomics approach coupled with similarity analysis. This approach was performed to identify and quantify changes in metabolic pathways to elucidate drug actions on the treated mice. Our results showed that those drugs with same property exerted similar effects on the metabolic alterations in mouse serum and liver samples, while drugs with different property showed different effects. The effects of herbal medicines with cold/hot properties were exerted by regulating the pathways linked to glycometabolism, lipid metabolism, amino acids metabolism and other metabolic pathways. The results elucidated the differences and similarities of drugs with cold/hot properties, providing useful information on the explanation of medicinal properties of these TCMs. Copyright © 2017 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

  10. (1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors.

    Vázquez-Fresno, Rosa; Llorach, Rafael; Alcaro, Francesca; Rodríguez, Miguel Ángel; Vinaixa, Maria; Chiva-Blanch, Gemma; Estruch, Ramon; Correig, Xavier; Andrés-Lacueva, Cristina

    2012-08-01

    Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100mL/day, alcohol control). After each period, 24-h urine samples were collected and analyzed by (1) H-NMR. According to the results of a one-way ANOVA, significant markers were grouped in four categories: alcohol-related markers (ethanol); gin-related markers; wine-related markers; and gut microbiota markers (hippurate and 4-hydroxphenylacetic acid). Wine metabolites were classified into two groups; first, metabolites of food metabolome: tartrate (RWA and RWD), ethanol, and mannitol (RWA); and second, biomarkers that relates to endogenous modifications after wine consumption, comprising branched-chain amino acid (BCAA) metabolite (3-methyl-oxovalerate). Additionally, a possible interaction between alcohol and gut-related biomarkers has been identified. To our knowledge, this is the first time that this approach has been applied in a nutritional intervention with red wine. The results show the capacity of this approach to obtain a comprehensive metabolome picture including food metabolome and endogenous biomarkers of moderate wine intake. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Metabolic pathways of lung inflammation revealed by high-resolution metabolomics (HRM) of H1N1 influenza virus infection in mice.

    Chandler, Joshua D; Hu, Xin; Ko, Eun-Ju; Park, Soojin; Lee, Young-Tae; Orr, Michael; Fernandes, Jolyn; Uppal, Karan; Kang, Sang-Moo; Jones, Dean P; Go, Young-Mi

    2016-11-01

    Influenza is a significant health concern worldwide. Viral infection induces local and systemic activation of the immune system causing attendant changes in metabolism. High-resolution metabolomics (HRM) uses advanced mass spectrometry and computational methods to measure thousands of metabolites inclusive of most metabolic pathways. We used HRM to identify metabolic pathways and clusters of association related to inflammatory cytokines in lungs of mice with H1N1 influenza virus infection. Infected mice showed progressive weight loss, decreased lung function, and severe lung inflammation with elevated cytokines [interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ] and increased oxidative stress via cysteine oxidation. HRM showed prominent effects of influenza virus infection on tryptophan and other amino acids, and widespread effects on pathways including purines, pyrimidines, fatty acids, and glycerophospholipids. A metabolome-wide association study (MWAS) of the aforementioned inflammatory cytokines was used to determine the relationship of metabolic responses to inflammation during infection. This cytokine-MWAS (cMWAS) showed that metabolic associations consisted of distinct and shared clusters of 396 metabolites highly correlated with inflammatory cytokines. Strong negative associations of selected glycosphingolipid, linoleate, and tryptophan metabolites with IFN-γ contrasted strong positive associations of glycosphingolipid and bile acid metabolites with IL-1β, TNF-α, and IL-10. Anti-inflammatory cytokine IL-10 had strong positive associations with vitamin D, purine, and vitamin E metabolism. The detailed metabolic interactions with cytokines indicate that targeted metabolic interventions may be useful during life-threatening crises related to severe acute infection and inflammation. Copyright © 2016 the American Physiological Society.

  12. Metabolomics reveals that vine tea (Ampelopsis grossedentata prevents high-fat-diet-induced metabolism disorder by improving glucose homeostasis in rats.

    Wenting Wan

    Full Text Available Vine tea (VT, derived from Ampelopsis grossedentata (Hand.-Mazz. W.T. Wang, is an alternative tea that has been consumed widely in south China for hundreds of years. It has been shown that drinking VT on a daily basis improves hyperlipidemia and hyperglycemia. However, little is known about the preventive functions of VT for metabolic dysregulation and the potential pathological mechanisms involved. This paper elucidates the preventive effects of VT on the dysregulation of lipid and glucose metabolism using rats maintained on a high-fat-diet (HFD in an attempt to explain the potential mechanisms involved.Sprague Dawley (SD rats were divided into five groups: a group given normal rat chow and water (control group; a group given an HFD and water (HFD group; a group given an HFD and Pioglitazone (PIO group, 5 mg /kg; and groups given an HFD and one of two doses of VT: 500 mg/L or 2000 mg/L. After 8 weeks, changes in food intake, tea consumption, body weight, serum and hepatic biochemical parameters were determined. Moreover, liver samples were isolated for pathology histology and liquid chromatography-mass spectrometry (LC-MS-based metabolomic research.VT reduced the serum levels of glucose and total cholesterol, decreased glucose area under the curve in the insulin tolerance test and visibly impaired hepatic lipid accumulation. Metabolomics showed that VT treatment modulated the contents of metabolic intermediates linked to glucose metabolism (including gluconeogenesis and glycolysis, the TCA cycle, purine metabolism and amino acid metabolism.The current results demonstrate that VT may prevent metabolic impairments induced by the consumption of an HFD. These effects may be caused by improved energy-related metabolism (including gluconeogenesis, glycolysis and TCA cycle, purine metabolism and amino acid metabolism, and reduced lipid levels in the HFD-fed rats.

  13. NMR-based Metabolomics Analysis of Liver from C57BL/6 Mouse Exposed to Ionizing Radiation

    Xiao, Xiongjie [Pacific Northwest National Laboratory, Richland, Washington 99352; State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, the Chinese Academy of Sciences, Wuhan, 430071, PR China; University of Chinese Academy of Sciences, Beijing 100049, China; Hu, Mary [Pacific Northwest National Laboratory, Richland, Washington 99352; Zhang, Xu [State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, the Chinese Academy of Sciences, Wuhan, 430071, PR China; Hu, Jian Zhi [Pacific Northwest National Laboratory, Richland, Washington 99352

    2017-07-01

    The health effects of exposing to ionizing radiation are attracting great interest in the space exploration community and patients considering radiotherapy. However, the impact to metabolism after exposure to high dose radiation has not yet been clearly defined in livers. In the present study, 1H nuclear magnetic resonance (NMR) based metabolomics combined with multivariate data analysis are applied to study the changes of metabolism in the liver of C57BL/6 mouse after whole body exposure to either gamma (3.0 and 7.8 Gy) or proton (3.0 Gy) radiation. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification of potential biomarkers associated with gamma and proton irradiation. The results show that the radiation exposed groups can be well separated from the control group. At the same radiation dosage, the group exposed to proton radiation is well separated from the group exposed to gamma radiation, indicating different radiation sources induce different alterations based on metabolic profiling. Common to both gamma and proton radiation at the high radiation doses studied in this work, compared with the control groups the concentrations of choline, O-phosphocholine and trimethylamine N-oxide are decreased statistically, while those of glutamine, glutathione, malate, creatinine, phosphate, betaine and 4-hydroxyphenylacetate are statistically and significantly elevated after exposure to radiation. Since these altered metabolites are associated with multiple biological pathways, the changes suggest that the exposure to radiation induce abnormality in multiple biological pathways. In particular, metabolites such as 4-hydroxyphenylacetate, betaine, glutamine, choline and trimethylamine N-oxide may be good candidates of pre-diagnose biomarkers for ionizing radiation in liver.

  14. Proteomic and metabolomic approaches to biomarker discovery

    Issaq, Haleem J

    2013-01-01

    Proteomic and Metabolomic Approaches to Biomarker Discovery demonstrates how to leverage biomarkers to improve accuracy and reduce errors in research. Disease biomarker discovery is one of the most vibrant and important areas of research today, as the identification of reliable biomarkers has an enormous impact on disease diagnosis, selection of treatment regimens, and therapeutic monitoring. Various techniques are used in the biomarker discovery process, including techniques used in proteomics, the study of the proteins that make up an organism, and metabolomics, the study of chemical fingerprints created from cellular processes. Proteomic and Metabolomic Approaches to Biomarker Discovery is the only publication that covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution.  The book describes methods, and presents a standard operating procedure for sample selection, preparation, and storage, as well as data analysis...

  15. Metabolomics window into diabetic complications.

    Wu, Tao; Qiao, Shuxuan; Shi, Chenze; Wang, Shuya; Ji, Guang

    2018-03-01

    Diabetes has become a major global health problem. The elucidation of characteristic metabolic alterations during the diabetic progression is critical for better understanding its pathogenesis, and identifying potential biomarkers and drug targets. Metabolomics is a promising tool to reveal the metabolic changes and the underlying mechanism involved in the pathogenesis of diabetic complications. The present review provides an update on the application of metabolomics in diabetic complications, including diabetic coronary artery disease, diabetic nephropathy, diabetic retinopathy and diabetic neuropathy, and this review provides notes on the prevention and prediction of diabetic complications. © 2017 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

  16. Increased serum bile acid concentration following low-dose chronic administration of thioacetamide in rats, as evidenced by metabolomic analysis

    Jeong, Eun Sook; Kim, Gabin; Shin, Ho Jung [Department of Pharmacology and Pharmacogenomics Research Center, Inje University, College of Medicine, Bokjiro 75, Busanjin-Gu, Busan 614-735 (Korea, Republic of); Park, Se-Myo; Oh, Jung-Hwa; Kim, Yong-Bum; Moon, Kyoung-Sik [Korea Institute of Toxicology, 141 Gajeong-ro, Yuseong-gu, Daejeon 305-343 (Korea, Republic of); Choi, Hyung-Kyoon [College of Pharmacy, Chung-Ang University, Seoul (Korea, Republic of); Jeong, Jayoung [Ministry of Food and Drug Safety, Osong-eup, Heungdeok-gu, Cheongju-si, Chungcheongbuk-do 361-951 (Korea, Republic of); Shin, Jae-Gook [Department of Pharmacology and Pharmacogenomics Research Center, Inje University, College of Medicine, Bokjiro 75, Busanjin-Gu, Busan 614-735 (Korea, Republic of); Kim, Dong Hyun, E-mail: dhkim@inje.ac.kr [Department of Pharmacology and Pharmacogenomics Research Center, Inje University, College of Medicine, Bokjiro 75, Busanjin-Gu, Busan 614-735 (Korea, Republic of)

    2015-10-15

    A liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS)-based metabolomics approach was employed to identify endogenous metabolites as potential biomarkers for thioacetamide (TAA)-induced liver injury. TAA (10 and 30 mg/kg), a well-known hepatotoxic agent, was administered daily to male Sprague–Dawley (SD) rats for 28 days. We then conducted untargeted analyses of endogenous serum and liver metabolites. Partial least squares discriminant analysis (PLS-DA) was performed on serum and liver samples to evaluate metabolites associated with TAA-induced perturbation. TAA administration resulted in altered levels of bile acids, acyl carnitines, and phospholipids in serum and in the liver. We subsequently demonstrated and confirmed the occurrence of compromised bile acid homeostasis. TAA treatment significantly increased serum levels of conjugated bile acids in a dose-dependent manner, which correlated well with toxicity. However, hepatic levels of these metabolites were not substantially changed. Gene expression profiling showed that the hepatic mRNA levels of Ntcp, Bsep, and Oatp1b2 were significantly suppressed, whereas those of basolateral Mrp3 and Mrp4 were increased. Decreased levels of Ntcp, Oatp1b2, and Ostα proteins in the liver were confirmed by western blot analysis. These results suggest that serum bile acids might be increased due to the inhibition of bile acid enterohepatic circulation rather than increased endogenous bile acid synthesis. Moreover, serum bile acids are a good indicator of TAA-induced hepatotoxicity. - Highlights: • Endogenous metabolic profiles were assessed in rat after treatment of thioacetamide. • It significantly increased the levels of bile acids in serum but not in the liver. • Expression of the genes related to bile acid secretion and reuptake was decreased. • Increased serum bile acids result from block of enterohepatic circulation of bile acids.

  17. Increased serum bile acid concentration following low-dose chronic administration of thioacetamide in rats, as evidenced by metabolomic analysis

    Jeong, Eun Sook; Kim, Gabin; Shin, Ho Jung; Park, Se-Myo; Oh, Jung-Hwa; Kim, Yong-Bum; Moon, Kyoung-Sik; Choi, Hyung-Kyoon; Jeong, Jayoung; Shin, Jae-Gook; Kim, Dong Hyun

    2015-01-01

    A liquid chromatography/time-of-flight mass spectrometry (LC/TOF-MS)-based metabolomics approach was employed to identify endogenous metabolites as potential biomarkers for thioacetamide (TAA)-induced liver injury. TAA (10 and 30 mg/kg), a well-known hepatotoxic agent, was administered daily to male Sprague–Dawley (SD) rats for 28 days. We then conducted untargeted analyses of endogenous serum and liver metabolites. Partial least squares discriminant analysis (PLS-DA) was performed on serum and liver samples to evaluate metabolites associated with TAA-induced perturbation. TAA administration resulted in altered levels of bile acids, acyl carnitines, and phospholipids in serum and in the liver. We subsequently demonstrated and confirmed the occurrence of compromised bile acid homeostasis. TAA treatment significantly increased serum levels of conjugated bile acids in a dose-dependent manner, which correlated well with toxicity. However, hepatic levels of these metabolites were not substantially changed. Gene expression profiling showed that the hepatic mRNA levels of Ntcp, Bsep, and Oatp1b2 were significantly suppressed, whereas those of basolateral Mrp3 and Mrp4 were increased. Decreased levels of Ntcp, Oatp1b2, and Ostα proteins in the liver were confirmed by western blot analysis. These results suggest that serum bile acids might be increased due to the inhibition of bile acid enterohepatic circulation rather than increased endogenous bile acid synthesis. Moreover, serum bile acids are a good indicator of TAA-induced hepatotoxicity. - Highlights: • Endogenous metabolic profiles were assessed in rat after treatment of thioacetamide. • It significantly increased the levels of bile acids in serum but not in the liver. • Expression of the genes related to bile acid secretion and reuptake was decreased. • Increased serum bile acids result from block of enterohepatic circulation of bile acids.

  18. Gas chromatography mass spectrometry : key technology in metabolomics

    Koek, Maud Marijtje

    2009-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues. Gas chromatography coupled to mass spectrometry (GC-MS) is very suitable for metabolomics analysis, as it combines high separation power with

  19. Gas Chromatography/Mass Spectrometry-Based Metabolomic Profiling Reveals Alterations in Mouse Plasma and Liver in Response to Fava Beans.

    Xiao, Man; Du, Guankui; Zhong, Guobing; Yan, Dongjing; Zeng, Huazong; Cai, Wangwei

    2016-01-01

    Favism is a life-threatening hemolytic anemia resulting from the intake of fava beans by susceptible individuals with low erythrocytic glucose 6-phosphate dehydrogenase (G6PD) activity. However, little is known about the metabolomic changes in plasma and liver after the intake of fava beans in G6PD normal and deficient states. In this study, gas chromatography/mass spectrometry was used to analyze the plasma and liver metabolic alterations underlying the effects of fava beans in C3H- and G6PD-deficient (G6PDx) mice, and to find potential biomarkers and metabolic changes associated with favism. Our results showed that fava beans induced oxidative stress in both C3H and G6PDx mice. Significantly, metabolomic differences were observed in plasma and liver between the control and fava bean treated groups of both C3H and G6PDx mice. The levels of 7 and 21 metabolites in plasma showed significant differences between C3H-control (C3H-C)- and C3H fava beans-treated (C3H-FB) mice, and G6PDx-control (G6PDx-C)- and G6PDx fava beans-treated (G6PDx-FB) mice, respectively. Similarly, the levels of 7 and 25 metabolites in the liver showed significant differences between C3H and C3H-FB, and G6PDx and G6PDx-FB, respectively. The levels of oleic acid, linoleic acid, and creatinine were significantly increased in the plasma of both C3H-FB and G6PDx-FB mice. In the liver, more metabolic alterations were observed in G6PDx-FB mice than in C3H-FB mice, and were involved in a sugar, fatty acids, amino acids, cholesterol biosynthesis, the urea cycle, and the nucleotide metabolic pathway. These findings suggest that oleic acid, linoleic acid, and creatinine may be potential biomarkers of the response to fava beans in C3H and G6PDx mice and therefore that oleic acid and linoleic acid may be involved in oxidative stress induced by fava beans. This study demonstrates that G6PD activity in mice can affect their metabolic pathways in response to fava beans.

  20. Gas Chromatography/Mass Spectrometry-Based Metabolomic Profiling Reveals Alterations in Mouse Plasma and Liver in Response to Fava Beans.

    Man Xiao

    Full Text Available Favism is a life-threatening hemolytic anemia resulting from the intake of fava beans by susceptible individuals with low erythrocytic glucose 6-phosphate dehydrogenase (G6PD activity. However, little is known about the metabolomic changes in plasma and liver after the intake of fava beans in G6PD normal and deficient states. In this study, gas chromatography/mass spectrometry was used to analyze the plasma and liver metabolic alterations underlying the effects of fava beans in C3H- and G6PD-deficient (G6PDx mice, and to find potential biomarkers and metabolic changes associated with favism. Our results showed that fava beans induced oxidative stress in both C3H and G6PDx mice. Significantly, metabolomic differences were observed in plasma and liver between the control and fava bean treated groups of both C3H and G6PDx mice. The levels of 7 and 21 metabolites in plasma showed significant differences between C3H-control (C3H-C- and C3H fava beans-treated (C3H-FB mice, and G6PDx-control (G6PDx-C- and G6PDx fava beans-treated (G6PDx-FB mice, respectively. Similarly, the levels of 7 and 25 metabolites in the liver showed significant differences between C3H and C3H-FB, and G6PDx and G6PDx-FB, respectively. The levels of oleic acid, linoleic acid, and creatinine were significantly increased in the plasma of both C3H-FB and G6PDx-FB mice. In the liver, more metabolic alterations were observed in G6PDx-FB mice than in C3H-FB mice, and were involved in a sugar, fatty acids, amino acids, cholesterol biosynthesis, the urea cycle, and the nucleotide metabolic pathway. These findings suggest that oleic acid, linoleic acid, and creatinine may be potential biomarkers of the response to fava beans in C3H and G6PDx mice and therefore that oleic acid and linoleic acid may be involved in oxidative stress induced by fava beans. This study demonstrates that G6PD activity in mice can affect their metabolic pathways in response to fava beans.

  1. Application of a novel metabolomic approach based on atmospheric pressure photoionization mass spectrometry using flow injection analysis for the study of Alzheimer's disease.

    González-Domínguez, Raúl; García-Barrera, Tamara; Gómez-Ariza, José Luis

    2015-01-01

    The use of atmospheric pressure photoionization is not widespread in metabolomics, despite its considerable potential for the simultaneous analysis of compounds with diverse polarities. This work considers the development of a novel analytical approach based on flow injection analysis and atmospheric pressure photoionization mass spectrometry for rapid metabolic screening of serum samples. Several experimental parameters were optimized, such as type of dopant, flow injection solvent, and their flows, given that a careful selection of these variables is mandatory for a comprehensive analysis of metabolites. Toluene and methanol were the most suitable dopant and flow injection solvent, respectively. Moreover, analysis in negative mode required higher solvent and dopant flows (100 µl min(-1) and 40 µl min(-1), respectively) compared to positive mode (50 µl min(-1) and 20 µl min(-1)). Then, the optimized approach was used to elucidate metabolic alterations associated with Alzheimer's disease. Thereby, results confirm the increase of diacylglycerols, ceramides, ceramide-1-phosphate and free fatty acids, indicating membrane destabilization processes, and reduction of fatty acid amides and several neurotransmitters related to impairments in neuronal transmission, among others. Therefore, it could be concluded that this metabolomic tool presents a great potential for analysis of biological samples, considering its high-throughput screening capability, fast analysis and comprehensive metabolite coverage. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Of monkeys and men: A metabolomic analysis of static and dynamic urinary metabolic phenotypes in two species

    Saccenti, E.; Tenori, L.; Verbruggen, P.; Timmerman, M.E.; Bouwman, J.; Greef, J. van der; Luchinat, C.; Smilde, A.K.

    2014-01-01

    Background: Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the

  3. Of Monkeys and Men: A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

    Saccenti, E.; Tenori, L.; Verbruggen, P.; Timmerman, M.E.; Bouwman, J.; Greef, de J.; Luchinat, C.; Smilde, A.K.

    2014-01-01

    Background Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the

  4. Of Monkeys and Men : A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

    Saccenti, E.; Tenori, L.; Verbruggen, P.; Timmerman, Marieke; Bouwman, J.; van der Greef, J.; Luchinat, C.; Smilde, Age K.

    2014-01-01

    Background Metabolomics has attracted the interest of the medical community for its potential in predicting early derangements from a healthy to a diseased metabolic phenotype. One key issue is the diversity observed in metabolic profiles of different healthy individuals, commonly attributed to the

  5. Metabolomics: A Primer.

    Liu, Xiaojing; Locasale, Jason W

    2017-04-01

    Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Impact of a western diet on the ovarian and serum metabolome.

    Dhungana, Suraj; Carlson, James E; Pathmasiri, Wimal; McRitchie, Susan; Davis, Matt; Sumner, Susan; Appt, Susan E

    2016-10-01

    The objective of this investigation was to determine differences in the profiles of endogenous metabolites (metabolomics) among ovaries and serum derived from Old World nonhuman primates fed prudent or Western diets. A retrospective, observational study was done using archived ovarian tissue and serum from midlife cynomolgus monkeys (Macaca fasicularis). Targeted and broad spectrum metabolomics analysis was used to compare ovarian tissue and serum from monkeys that had been exposed to a prudent diet or a Western diet. Monkeys in the prudent diet group (n=13) were research naïve and had been exposed only to a commercial monkey chow diet (low in cholesterol and saturated fats, high in complex carbohydrates). Western diet monkeys (n=8) had consumed a diet that was high in cholesterol, saturated animal fats and soluble carbohydrates for 2 years prior to ovarian tissue and serum collection. Metabolomic analyses were done on extracts of homogenized ovary tissue samples, and extracts of serum. Targeted analysis was conducted using the Biocrates p180 kit and broad spectrum analysis was conducted using UPLC-TOF-MS, resulting in the detection of 3500 compound ions. Using metabolomics methods, which capture thousands of signals for metabolites, 64 metabolites were identified in serum and 47 metabolites were identified in ovarian tissue that differed by diet. Quantitative targeted analysis revealed 13 amino acids, 6 acrylcarnitines, and 2 biogenic amines that were significantly (pmetabolome, and demonstrated perturbation in carnitine, lipids/fatty acid, and amino acid metabolic pathways. Published by Elsevier Ireland Ltd.

  7. Causal Genetic Variation Underlying Metabolome Differences.

    Swain-Lenz, Devjanee; Nikolskiy, Igor; Cheng, Jiye; Sudarsanam, Priya; Nayler, Darcy; Staller, Max V; Cohen, Barak A

    2017-08-01

    An ongoing challenge in biology is to predict the phenotypes of individuals from their genotypes. Genetic variants that cause disease often change an individual's total metabolite profile, or metabolome. In light of our extensive knowledge of metabolic pathways, genetic variants that alter the metabolome may help predict novel phenotypes. To link genetic variants to changes in the metabolome, we studied natural variation in the yeast Saccharomyces cerevisiae We used an untargeted mass spectrometry method to identify dozens of metabolite Quantitative Trait Loci (mQTL), genomic regions containing genetic variation that control differences in metabolite levels between individuals. We mapped differences in urea cycle metabolites to genetic variation in specific genes known to regulate amino acid biosynthesis. Our functional assays reveal that genetic variation in two genes, AUA1 and ARG81 , cause the differences in the abundance of several urea cycle metabolites. Based on knowledge of the urea cycle, we predicted and then validated a new phenotype: sensitivity to a particular class of amino acid isomers. Our results are a proof-of-concept that untargeted mass spectrometry can reveal links between natural genetic variants and metabolome diversity. The interpretability of our results demonstrates the promise of using genetic variants underlying natural differences in the metabolome to predict novel phenotypes from genotype. Copyright © 2017 by the Genetics Society of America.

  8. Metabolomics study of human urinary metabolome modifications after intake of almond (Prunus dulcis (Mill.) D.A. Webb) skin polyphenols.

    Llorach, Rafael; Garrido, Ignacio; Monagas, Maria; Urpi-Sarda, Mireia; Tulipani, Sara; Bartolome, Begona; Andres-Lacueva, Cristina

    2010-11-05

    Almond, as a part of the nut family, is an important source of biological compounds, and specifically, almond skins have been considered an important source of polyphenols, including flavan-3-ols and flavonols. Polyphenol metabolism may produce several classes of metabolites that could often be more biologically active than their dietary precursor and could also become a robust new biomarker of almond polyphenol intake. In order to study urinary metabolome modifications during the 24 h after a single dose of almond skin extract, 24 volunteers (n = 24), who followed a polyphenol-free diet for 48 h before and during the study, ingested a dietary supplement of almond skin phenolic compounds (n = 12) or a placebo (n = 12). Urine samples were collected before ((-2)-0 h) and after (0-2 h, 2-6 h, 6-10 h, and 10-24 h) the intake and were analyzed by liquid chromatography-mass spectrometry (LC-q-TOF) and multivariate statistical analysis (principal component analysis (PCA) and orthogonal projection to latent structures (OPLS)). Putative identification of relevant biomarkers revealed a total of 34 metabolites associated with the single dose of almond extract, including host and, in particular, microbiota metabolites. As far as we know, this is the first time that conjugates of hydroxyphenylvaleric, hydroxyphenylpropionic, and hydroxyphenylacetic acids have been identified in human samples after the consumption of flavan-3-ols through a metabolomic approach. The results showed that this non-targeted approach could provide new intake biomarkers, contributing to the development of the food metabolome as an important part of the human urinary metabolome.

  9. Impact of red meat consumption on the metabolome of rats.

    Jakobsen, Louise M A; Yde, Christian C; Van Hecke, Thomas; Jessen, Randi; Young, Jette F; De Smet, Stefaan; Bertram, Hanne Christine

    2017-03-01

    The scope of the present study was to investigate the effects of red versus white meat intake on the metabolome of rats. Twenty-four male Sprague-Dawley rats were randomly assigned to 15 days of ad libitum feeding of one of four experimental diets: (i) lean chicken, (ii) chicken with lard, (iii) lean beef, and (iv) beef with lard. Urine, feces, plasma, and colon tissue samples were analyzed using 1 H NMR-based metabolomics and real-time PCR was performed on colon tissue to examine the expression of specific genes. Urinary excretion of acetate and anserine was higher after chicken intake, while carnosine, fumarate, and trimethylamine N-oxide excretion were higher after beef intake. In colon tissue, higher choline levels and lower lipid levels were found after intake of chicken compared to beef. Expression of the apc gene was higher in response to the lean chicken and beef with lard diets. Correlation analysis revealed that intestinal apc gene expression was correlated with fecal lactate content (R 2 = 0.65). This study is the first to identify specific differences in the metabolome related to the intake of red and white meat. These differences may reflect perturbations in endogenous metabolism that can be linked to the proposed harmful effects associated with intake of red meat. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Metabolomic analysis of 92 pulmonary embolism patients from a nested case-control study identifies metabolites associated with adverse clinical outcomes.

    Zeleznik, O A; Poole, E M; Lindstrom, S; Kraft, P; Van Hylckama Vlieg, A; Lasky-Su, J A; Harrington, L B; Hagan, K; Kim, J; Parry, B A; Giordano, N; Kabrhel, C

    2018-03-01

    Essentials Risk-stratification often fails to predict clinical deterioration in pulmonary embolism (PE). First-ever high-throughput metabolomics analysis of risk-stratified PE patients. Changes in circulating metabolites reflect a compromised energy metabolism in PE. Metabolites play a key role in the pathophysiology and risk stratification of PE. Background Patients with acute pulmonary embolism (PE) exhibit wide variation in clinical presentation and outcomes. Our understanding of the pathophysiologic mechanisms differentiating low-risk and high-risk PE is limited, so current risk-stratification efforts often fail to predict clinical deterioration and are insufficient to guide management. Objectives To improve our understanding of the physiology differentiating low-risk from high-risk PE, we conducted the first-ever high-throughput metabolomics analysis (843 named metabolites) comparing PE patients across risk strata within a nested case-control study. Patients/methods We enrolled 92 patients diagnosed with acute PE and collected plasma within 24 h of PE diagnosis. We used linear regression and pathway analysis to identify metabolites and pathways associated with PE risk-strata. Results When we compared 46 low-risk with 46 intermediate/high-risk PEs, 50 metabolites were significantly different after multiple testing correction. These metabolites were enriched in the following pathways: tricarboxylic acid (TCA) cycle, fatty acid metabolism (acyl carnitine) and purine metabolism, (hypo)xanthine/inosine containing. Additionally, energy, nucleotide and amino acid pathways were downregulated in intermediate/high-risk PE patients. When we compared 28 intermediate-risk with 18 high-risk PE patients, 41 metabolites differed at a nominal P-value level. These metabolites were enriched in fatty acid metabolism (acyl cholines), and hemoglobin and porphyrin metabolism. Conclusion Our results suggest that high-throughput metabolomics can provide insight into the

  11. Diurnal effects of anoxia on the metabolome of the seagrass Zostera marina

    Hasler-Sheetal, Harald; Holmer, Marianne; Weckwerth, Wolfram

    2014-01-01

    Environmental metabolomics has become interesting in marine ecological studies. One example is the revealing of new insights in stress response of Zostera marina. This is essential to understand how, at which level and to what extend aquatic plants adapt, tolerate and react to environmental...... stressors. We exposed Z. marina to water column anoxia and assessed the diurnal metabolomic response by GC-TOF-MS based metabolomics identifying 109 known and 217 unknown metabolites. During day time photosynthetic oxygen production prevents severe effects of anoxia on the metabolome (complete set of small...... the applicability of metabolomics to assess environmental stress responses of Zostera marina....

  12. Plasma metabolomics reveal alterations of sphingo- and glycerophospholipid levels in non-diabetic carriers of the transcription factor 7-like 2 polymorphism rs7903146.

    Then, Cornelia; Wahl, Simone; Kirchhofer, Anna; Grallert, Harald; Krug, Susanne; Kastenmüller, Gabi; Römisch-Margl, Werner; Claussnitzer, Melina; Illig, Thomas; Heier, Margit; Meisinger, Christa; Adamski, Jerzy; Thorand, Barbara; Huth, Cornelia; Peters, Annette; Prehn, Cornelia; Heukamp, Ina; Laumen, Helmut; Lechner, Andreas; Hauner, Hans; Seissler, Jochen

    2013-01-01

    Polymorphisms in the transcription factor 7-like 2 (TCF7L2) gene have been shown to display a powerful association with type 2 diabetes. The aim of the present study was to evaluate metabolic alterations in carriers of a common TCF7L2 risk variant. Seventeen non-diabetic subjects carrying the T risk allele at the rs7903146 TCF7L2 locus and 24 subjects carrying no risk allele were submitted to intravenous glucose tolerance test and euglycemic-hyperinsulinemic clamp. Plasma samples were analysed for concentrations of 163 metabolites through targeted mass spectrometry. TCF7L2 risk allele carriers had a reduced first-phase insulin response and normal insulin sensitivity. Under fasting conditions, carriers of TCF7L2 rs7903146 exhibited a non-significant increase of plasma sphingomyelins (SMs), phosphatidylcholines (PCs) and lysophosphatidylcholines (lysoPCs) species. A significant genotype effect was detected in response to challenge tests in 6 SMs (C16:0, C16:1, C18:0, C18:1, C24:0, C24:1), 5 hydroxy-SMs (C14:1, C16:1, C22:1, C22:2, C24:1), 4 lysoPCs (C14:0, C16:0, C16:1, C17:0), 3 diacyl-PCs (C28:1, C36:6, C40:4) and 4 long-chain acyl-alkyl-PCs (C40:2, C40:5, C44:5, C44:6). Plasma metabolomic profiling identified alterations of phospholipid metabolism in response to challenge tests in subjects with TCF7L2 rs7903146 genotype. This may reflect a genotype-mediated link to early metabolic abnormalities prior to the development of disturbed glucose tolerance.

  13. The Human Serum Metabolome

    Psychogios, Nikolaos; Hau, David D.; Peng, Jun; Guo, An Chi; Mandal, Rupasri; Bouatra, Souhaila; Sinelnikov, Igor; Krishnamurthy, Ramanarayan; Eisner, Roman; Gautam, Bijaya; Young, Nelson; Xia, Jianguo; Knox, Craig; Dong, Edison; Huang, Paul; Hollander, Zsuzsanna; Pedersen, Theresa L.; Smith, Steven R.; Bamforth, Fiona; Greiner, Russ; McManus, Bruce; Newman, John W.; Goodfriend, Theodore; Wishart, David S.

    2011-01-01

    Continuing improvements in analytical technology along with an increased interest in performing comprehensive, quantitative metabolic profiling, is leading to increased interest pressures within the metabolomics community to develop centralized metabolite reference resources for certain clinically important biofluids, such as cerebrospinal fluid, urine and blood. As part of an ongoing effort to systematically characterize the human metabolome through the Human Metabolome Project, we have undertaken the task of characterizing the human serum metabolome. In doing so, we have combined targeted and non-targeted NMR, GC-MS and LC-MS methods with computer-aided literature mining to identify and quantify a comprehensive, if not absolutely complete, set of metabolites commonly detected and quantified (with today's technology) in the human serum metabolome. Our use of multiple metabolomics platforms and technologies allowed us to substantially enhance the level of metabolome coverage while critically assessing the relative strengths and weaknesses of these platforms or technologies. Tables containing the complete set of 4229 confirmed and highly probable human serum compounds, their concentrations, related literature references and links to their known disease associations are freely available at http://www.serummetabolome.ca. PMID:21359215

  14. Metabolomics in chemical ecology.

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

    Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

  15. Tailored liquid chromatography-mass spectrometry analysis improves the coverage of the intracellular metabolome of HepaRG cells.

    Cuykx, Matthias; Negreira, Noelia; Beirnaert, Charlie; Van den Eede, Nele; Rodrigues, Robim; Vanhaecke, Tamara; Laukens, Kris; Covaci, Adrian

    2017-03-03

    Metabolomics protocols are often combined with Liquid Chromatography-Mass Spectrometry (LC-MS) using mostly reversed phase chromatography coupled to accurate mass spectrometry, e.g. quadrupole time-of-flight (QTOF) mass spectrometers to measure as many metabolites as possible. In this study, we optimised the LC-MS separation of cell extracts after fractionation in polar and non-polar fractions. Both phases were analysed separately in a tailored approach in four different runs (two for the non-polar and two for the polar-fraction), each of them specifically adapted to improve the separation of the metabolites present in the extract. This approach improves the coverage of a broad range of the metabolome of the HepaRG cells and the separation of intra-class metabolites. The non-polar fraction was analysed using a C18-column with end-capping, mobile phase compositions were specifically adapted for each ionisation mode using different co-solvents and buffers. The polar extracts were analysed with a mixed mode Hydrophilic Interaction Liquid Chromatography (HILIC) system. Acidic metabolites from glycolysis and the Krebs cycle, together with phosphorylated compounds, were best detected with a method using ion pairing (IP) with tributylamine and separation on a phenyl-hexyl column. Accurate mass detection was performed with the QTOF in MS-mode only using an extended dynamic range to improve the quality of the dataset. Parameters with the greatest impact on the detection were the balance between mass accuracy and linear range, the fragmentor voltage, the capillary voltage, the nozzle voltage, and the nebuliser pressure. By using a tailored approach for the intracellular HepaRG metabolome, consisting of three different LC techniques, over 2200 metabolites can be measured with a high precision and acceptable linear range. The developed method is suited for qualitative untargeted LC-MS metabolomics studies. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Metabolomic Analysis of Differential Changes in Metabolites during ATP Oscillations in Chondrogenesis

    Hyuck Joon Kwon

    2013-01-01

    Full Text Available Prechondrogenic condensation is a critical step for skeletal pattern formation. Recent studies reported that ATP oscillations play an essential role in prechondrogenic condensation. However, the molecular mechanism to underlie ATP oscillations remains poorly understood. In the present study, it was investigated how changes in metabolites are implicated in ATP oscillations during chondrogenesis by using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS. CE-TOF-MS detected 93 cationic and 109 anionic compounds derived from known metabolic pathways. 15 cationic and 18 anionic compounds revealed significant change between peak and trough of ATP oscillations. These results implicate that glycolysis, mitochondrial respiration and uronic acid pathway oscillate in phase with ATP oscillations, while PPRP and nucleotides synthesis pathways oscillate in antiphase with ATP oscillations. This suggests that the ATP-producing glycolysis and mitochondrial respiration oscillate in antiphase with the ATP-consuming PPRP/nucleotide synthesis pathway during chondrogenesis.

  17. Application of Metabolomics in Thyroid Cancer Research

    Anna Wojakowska

    2015-01-01

    Full Text Available Thyroid cancer is the most common endocrine malignancy with four major types distinguished on the basis of histopathological features: papillary, follicular, medullary, and anaplastic. Classification of thyroid cancer is the primary step in the assessment of prognosis and selection of the treatment. However, in some cases, cytological and histological patterns are inconclusive; hence, classification based on histopathology could be supported by molecular biomarkers, including markers identified with the use of high-throughput “omics” techniques. Beside genomics, transcriptomics, and proteomics, metabolomic approach emerges as the most downstream attitude reflecting phenotypic changes and alterations in pathophysiological states of biological systems. Metabolomics using mass spectrometry and magnetic resonance spectroscopy techniques allows qualitative and quantitative profiling of small molecules present in biological systems. This approach can be applied to reveal metabolic differences between different types of thyroid cancer and to identify new potential candidates for molecular biomarkers. In this review, we consider current results concerning application of metabolomics in the field of thyroid cancer research. Recent studies show that metabolomics can provide significant information about the discrimination between different types of thyroid lesions. In the near future, one could expect a further progress in thyroid cancer metabolomics leading to development of molecular markers and improvement of the tumor types classification and diagnosis.

  18. Metabolomics enables precision medicine: "A White Paper, Community Perspective".

    Beger, Richard D; Dunn, Warwick; Schmidt, Michael A; Gross, Steven S; Kirwan, Jennifer A; Cascante, Marta; Brennan, Lorraine; Wishart, David S; Oresic, Matej; Hankemeier, Thomas; Broadhurst, David I; Lane, Andrew N; Suhre, Karsten; Kastenmüller, Gabi; Sumner, Susan J; Thiele, Ines; Fiehn, Oliver; Kaddurah-Daouk, Rima

    stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our

  19. Metabolomic differentiation of maca (Lepidium meyenii) accessions cultivated under different conditions using NMR and chemometric analysis.

    Zhao, Jianping; Avula, Bharathi; Chan, Michael; Clément, Céline; Kreuzer, Michael; Khan, Ikhlas A

    2012-01-01

    To gain insights on the effects of color type, cultivation history, and growing site on the composition alterations of maca (Lepidium meyenii Walpers) hypocotyls, NMR profiling combined with chemometric analysis was applied to investigate the metabolite variability in different maca accessions. Maca hypocotyls with different colors (yellow, pink, violet, and lead-colored) cultivated at different geographic sites and different areas were examined for differences in metabolite expression. Differentiations of the maca accessions grown under the different cultivation conditions were determined by principle component analyses (PCAs) which were performed on the datasets derived from their ¹H NMR spectra. A total of 16 metabolites were identified by NMR analysis, and the changes in metabolite levels in relation to the color types and growing conditions of maca hypocotyls were evaluated using univariate statistical analysis. In addition, the changes of the correlation pattern among the metabolites identified in the maca accessions planted at the two different sites were examined. The results from both multivariate and univariate analysis indicated that the planting site was the major determining factor with regards to metabolite variations in maca hypocotyls, while the color of maca accession seems to be of minor importance in this respect. © Georg Thieme Verlag KG Stuttgart · New York.

  20. Changes in the Metabolome in Response to Low-Dose Exposure to Environmental Chemicals Used in Personal Care Products during Different Windows of Susceptibility.

    Houten, Sander M; Chen, Jia; Belpoggi, Fiorella; Manservisi, Fabiana; Sánchez-Guijo, Alberto; Wudy, Stefan A; Teitelbaum, Susan L

    2016-01-01

    The consequences of ubiquitous exposure to environmental chemicals remain poorly defined. Non-targeted metabolomic profiling is an emerging method to identify biomarkers of the physiological response to such exposures. We investigated the effect of three commonly used ingredients in personal care products, diethyl phthalate (DEP), methylparaben (MPB) and triclosan (TCS), on the blood metabolome of female Sprague-Dawley rats. Animals were treated with low levels of these chemicals comparable to human exposures during prepubertal and pubertal windows as well as chronically from birth to adulthood. Non-targeted metabolomic profiling revealed that most of the variation in the metabolites was associated with developmental stage. The low-dose exposure to DEP, MPB and TCS had a relatively small, but detectable impact on the metabolome. Multiple metabolites that were affected by chemical exposure belonged to the same biochemical pathways including phenol sulfonation and metabolism of pyruvate, lyso-plasmalogens, unsaturated fatty acids and serotonin. Changes in phenol sulfonation and pyruvate metabolism were most pronounced in rats exposed to DEP during the prepubertal period. Our metabolomics analysis demonstrates that human level exposure to personal care product ingredients has detectable effects on the rat metabolome. We highlight specific pathways such as sulfonation that warrant further study.

  1. Phenotyping of Chronic Obstructive Pulmonary Disease Based on the Integration of Metabolomes and Clinical Characteristics

    Kalle Kilk

    2018-02-01

    Full Text Available Apart from the refined management-oriented clinical stratification of chronic obstructive pulmonary disease (COPD, the molecular pathologies behind this highly prevalent disease have remained obscure. The aim of this study was the characterization of patients with COPD, based on the metabolomic profiling of peripheral blood and exhaled breath condensate (EBC within the context of defined clinical and demographic variables. Mass-spectrometry-based targeted analysis of serum metabolites (mainly amino acids and lipid species, untargeted profiles of serum and EBC of patients with COPD of different clinical characteristics (n = 25 and control individuals (n = 21 were performed. From the combined clinical/demographic and metabolomics data, associations between clinical/demographic and metabolic parameters were searched and a de novo phenotyping for COPD was attempted. Adjoining the clinical parameters, sphingomyelins were the best to differentiate COPD patients from controls. Unsaturated fatty acid-containing lipids, ornithine metabolism and plasma protein composition-associated signals from the untargeted analysis differentiated the Global Initiative for COPD (GOLD categories. Hierarchical clustering did not reveal a clinical-metabolomic stratification superior to the strata set by the GOLD consensus. We conclude that while metabolomics approaches are good for finding biomarkers and clarifying the mechanism of the disease, there are no distinct co-variate independent clinical-metabolic phenotypes.

  2. Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile.

    Nobuyuki Okuma

    Full Text Available This study characterized the changes in quality and quantity of saliva, and changes in the salivary metabolomic profile, to understand the effects of masticatory stimulation.Stimulated and unstimulated saliva samples were collected from 55 subjects and salivary hydrophilic metabolites were comprehensively quantified using capillary electrophoresis-time-of-flight mass spectrometry.In total, 137 metabolites were identified and quantified. The concentrations of 44 metabolites in stimulated saliva were significantly higher than those in unstimulated saliva. Pathway analysis identified the upregulation of the urea cycle and synthesis and degradation pathways of glycine, serine, cysteine and threonine in stimulated saliva. A principal component analysis revealed that the effect of masticatory stimulation on salivary metabolomic profiles was less dependent on sample population sex, age, and smoking. The concentrations of only 1 metabolite in unstimulated saliva, and of 3 metabolites stimulated saliva, showed significant correlation with salivary secretion volume, indicating that the salivary metabolomic profile and salivary secretion volume were independent factors.Masticatory stimulation affected not only salivary secretion volume, but also metabolite concentration patterns. A low correlation between the secretion volume and these patterns supports the conclusion that the salivary metabolomic profile may be a new indicator to characterize masticatory stimulation.

  3. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

    Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

    2015-05-01

    Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  4. Tools for the functional interpretation of metabolomic experiments.

    Chagoyen, Monica; Pazos, Florencio

    2013-11-01

    The so-called 'omics' approaches used in modern biology aim at massively characterizing the molecular repertories of living systems at different levels. Metabolomics is one of the last additions to the 'omics' family and it deals with the characterization of the set of metabolites in a given biological system. As metabolomic techniques become more massive and allow characterizing larger sets of metabolites, automatic methods for analyzing these sets in order to obtain meaningful biological information are required. Only recently the first tools specifically designed for this task in metabolomics appeared. They are based on approaches previously used in transcriptomics and other 'omics', such as annotation enrichment analysis. These, together with generic tools for metabolic analysis and visualization not specifically designed for metabolomics will for sure be in the toolbox of the researches doing metabolomic experiments in the near future.

  5. Compliance with minimum information guidelines in public metabolomics repositories.

    Spicer, Rachel A; Salek, Reza; Steinbeck, Christoph

    2017-09-26

    The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

  6. Plasma sample based analysis of gastric cancer progression using targeted metabolomics.

    Lario, Sergio; Ramírez-Lázaro, Maria José; Sanjuan-Herráez, Daniel; Brunet-Vega, Anna; Pericay, Carles; Gombau, Lourdes; Junquera, Félix; Quintás, Guillermo; Calvet, Xavier

    2017-12-19

    Gastric carcinogenesis is a multifactorial process described as a stepwise progression from non-active gastritis (NAG), chronic active gastritis (CAG), precursor lesions of gastric cancer (PLGC) and gastric adenocarcinoma. Gastric cancer (GC) 5-year survival rate is highly dependent upon stage of disease at diagnosis, which is based on endoscopy, biopsy and pathological examinations. Non-invasive GC biomarkers would facilitate its diagnosis at early stages leading to improved GC prognosis. We analyzed plasma samples collected from 80 patients diagnosed with NAG without H. pylori infection (NAG-), CAG with H. pylori infection (CAG+), PLGC and GC. A panel of 208 metabolites including acylcarnitines, amino acids and biogenic amines, sphingolipids, glycerophospholipids, hexoses, and tryptophan and phenylalanine metabolites were quantified using two complementary quantitative approaches: Biocrates AbsoluteIDQ®p180 kit and a LC-MS method designed for the analysis of 29 tryptophan pathway and phenylalanine metabolites. Significantly altered metabolic profiles were found in GC patients that allowing discrimination from NAG-, CAG+ and PLGC patients. Pathway analysis showed significantly altered tryptophan and nitrogen metabolic pathways (FDR P < 0.01). Three metabolites (histidine, tryprophan and phenylacetylglutamine) discriminated between non-GC and GC groups. These metabolic signatures open new possibilities to improve surveillance of PLGC patients using a minimally invasive blood analysis.

  7. RepExplore: addressing technical replicate variance in proteomics and metabolomics data analysis.

    Glaab, Enrico; Schneider, Reinhard

    2015-07-01

    High-throughput omics datasets often contain technical replicates included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses.We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ranking tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. Freely available at http://www.repexplore.tk enrico.glaab@uni.lu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  8. Alanine Enhances Aminoglycosides-Induced ROS Production as Revealed by Proteomic Analysis

    Jin-zhou Ye

    2018-01-01

    Full Text Available Metabolite-enabled killing of antibiotic-resistant pathogens by antibiotics is an attractive strategy to manage antibiotic resistance. Our previous study demonstrated that alanine or/and glucose increased the killing efficacy of kanamycin on antibiotic-resistant bacteria, whose action is through up-regulating TCA cycle, increasing proton motive force and enhancing antibiotic uptake. Despite the fact that alanine altered several metabolic pathways, other mechanisms could be potentially involved in alanine-mediated kanamycin killing of bacteria which remains to be explored. In the present study, we adopted proteomic approach to analyze the proteome changes induced by exogenous alanine. Our results revealed that the expression of three outer membrane proteins was altered and the deletion of nagE and fadL decreased the intracellular kanamycin concentration, implying their possible roles in mediating kanamycin transport. More importantly, the integrated analysis of proteomic and metabolomic data pointed out that alanine metabolism could connect to riboflavin metabolism that provides the source for reactive oxygen species (ROS production. Functional studies confirmed that alanine treatment together with kanamycin could promote ROS production that in turn potentiates the killing of antibiotic-resistant bacteria. Further investigation showed that alanine repressed the transcription of antioxidant-encoding genes, and alanine metabolism to riboflavin metabolism connected with riboflavin metabolism through TCA cycle, glucogenesis pathway and pentose phosphate pathway. Our results suggest a novel mechanism by which alanine facilitates kanamycin killing of antibiotic-resistant bacteria via promoting ROS production.

  9. Metabolomics data normalization with EigenMS.

    Yuliya V Karpievitch

    Full Text Available Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases. These include batch effects, day-to-day variations in instrument performance, signal intensity loss due to time-dependent effects of the LC column performance, accumulation of contaminants in the MS ion source and MS sensitivity among others. In this study we aimed to test a singular value decomposition-based method, called EigenMS, for normalization of metabolomics data. We analyzed a clinical human dataset where LC-MS serum metabolomics data and physiological measurements were collected from thirty nine healthy subjects and forty with type 2 diabetes and applied EigenMS to detect and correct for any systematic bias. EigenMS works in several stages. First, EigenMS preserves the treatment group differences in the metabolomics data by estimating treatment effects with an ANOVA model (multiple fixed effects can be estimated. Singular value decomposition of the residuals matrix is then used to determine bias trends in the data. The number of bias trends is then estimated via a permutation test and the effects of the bias trends are eliminated. EigenMS removed bias of unknown complexity from the LC-MS metabolomics data, allowing for increased sensitivity in differential analysis. Moreover, normalized samples better correlated with both other normalized samples and corresponding physiological data, such as blood glucose level, glycated haemoglobin, exercise central augmentation pressure normalized to heart rate of 75, and total cholesterol. We were able to report 2578 discriminatory metabolite peaks in the normalized data (p<0.05 as compared to only 1840 metabolite signals in the raw data. Our results support the use of singular value decomposition-based normalization for metabolomics data.

  10. Metabolomics as a tool to identify biomarkers to predict and improve outcomes in reproductive medicine: a systematic review.

    Bracewell-Milnes, Timothy; Saso, Srdjan; Abdalla, Hossam; Nikolau, Dimitrios; Norman-Taylor, Julian; Johnson, Mark; Holmes, Elaine; Thum, Meen-Yau

    2017-11-01

    reproductive tract, with a summary of the current findings, promise and pitfalls in metabolomic techniques. The approaches discussed can be adapted by other metabolomic studies. A range of sophisticated modern metabolomic techniques are now more widely available and have been applied to the analysis of the female reproductive tract. However, this review has revealed the paucity of metabolomic studies in the field of fertility and the inconsistencies of findings between different studies, as well as a lack of research examining the metabolic effects of various gynecological diseases. By incorporating metabolomic technology into an increased number of well designed studies, a much greater understanding of infertility at a molecular level could be achieved. However, there is currently no evidence for the use of metabolomics in clinical practice to improve fertility outcomes. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  11. Metabolomic studies in pulmonology

    R. R. Furina

    2015-01-01

    Full Text Available The review shows the results of metabolomic studies in pulmonology. The key idea of metabolomics is to detect specific biomarkers in a biological sample for the diagnosis of diseases of the bronchi and lung. Main methods for the separation and identification of volatile organic substances as biomarkers (gas chromatography, mass spectrometry, and nuclear magnetic resonance spectrometry used in metabolomics are given. A solid-phase microextraction method used to pre-prepare a sample is also covered. The results of laboratory tests for biomarkers for lung cancer, acute respiratory distress syndrome, chronic obstructive pulmonary disease, cystic fibrosis, chronic infections, and pulmonary tuberculosis are presented. In addition, emphasis is placed on the possibilities of metabolomics used in experimental medicine, including to the study of asthma. The information is of interest to both theorists and practitioners.

  12. The food metabolome

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine

    2014-01-01

    to the diet. By its very nature it represents a considerable and still largely unexploited source of novel dietary biomarkers that could be used to measure dietary exposures with a high level of detail and precision. Most dietary biomarkers currently have been identified on the basis of our knowledge of food......The food metabolome is defined as the part of the human metabolome directly derived from the digestion and biotransformation of foods and their constituents. With >25,000 compounds known in various foods, the food metabolome is extremely complex, with a composition varying widely according...... by the recent identification of novel biomarkers of intakes for fruit, vegetables, beverages, meats, or complex diets. Moreover, examples also show how the scrutiny of the food metabolome can lead to the discovery of bioactive molecules and dietary factors associated with diseases. However, researchers still...

  13. Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids

    Sandusky, Peter; Appiah-Amponsah, Emmanuel; Raftery, Daniel

    2011-01-01

    One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.

  14. Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids

    Sandusky, Peter [Eckerd College, Department of Chemistry (United States); Appiah-Amponsah, Emmanuel; Raftery, Daniel, E-mail: raftery@purdue.edu [Purdue University, Department of Chemistry (United States)

    2011-04-15

    One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.

  15. Metabolomics er fremtiden

    Pedersern, Birger

    2010-01-01

    Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet......Forskningen i fødevarer har fået et potent redskab i hånden. Metabolomics er vejen frem, mener professor Søren Balling Engelsen fra Københavns Universitet...

  16. Discriminative Analysis of Different Grades of Gaharu (Aquilaria malaccensis Lamk. via 1H-NMR-Based Metabolomics Using PLS-DA and Random Forests Classification Models

    Siti Nazirah Ismail

    2017-09-01

    Full Text Available Gaharu (agarwood, Aquilaria malaccensis Lamk. is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using 1H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a ‘high grade’ group (samples A, B and D, characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an ‘intermediate grade’ group (samples C, F and G, dominated by fatty acid and vanillic acid; and a ‘low grade’ group (sample E and H, which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that 1H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents.

  17. Quality assurance of metabolomics.

    Bouhifd, Mounir; Beger, Richard; Flynn, Thomas; Guo, Lining; Harris, Georgina; Hogberg, Helena; Kaddurah-Daouk, Rima; Kamp, Hennicke; Kleensang, Andre; Maertens, Alexandra; Odwin-DaCosta, Shelly; Pamies, David; Robertson, Donald; Smirnova, Lena; Sun, Jinchun; Zhao, Liang; Hartung, Thomas

    2015-01-01

    Metabolomics promises a holistic phenotypic characterization of biological responses to toxicants. This technology is based on advanced chemical analytical tools with reasonable throughput, including mass-spectroscopy and NMR. Quality assurance, however - from experimental design, sample preparation, metabolite identification, to bioinformatics data-mining - is urgently needed to assure both quality of metabolomics data and reproducibility of biological models. In contrast to microarray-based transcriptomics, where consensus on quality assurance and reporting standards has been fostered over the last two decades, quality assurance of metabolomics is only now emerging. Regulatory use in safety sciences, and even proper scientific use of these technologies, demand quality assurance. In an effort to promote this discussion, an expert workshop discussed the quality assurance needs of metabolomics. The goals for this workshop were 1) to consider the challenges associated with metabolomics as an emerging science, with an emphasis on its application in toxicology and 2) to identify the key issues to be addressed in order to establish and implement quality assurance procedures in metabolomics-based toxicology. Consensus has still to be achieved regarding best practices to make sure sound, useful, and relevant information is derived from these new tools.

  18. In-silico Metabolome Target Analysis Towards PanC-based Antimycobacterial Agent Discovery.

    Khoshkholgh-Sima, Baharak; Sardari, Soroush; Izadi Mobarakeh, Jalal; Khavari-Nejad, Ramezan Ali

    2015-01-01

    Mycobacterium tuberculosis, the main cause of tuberculosis (TB), has still remained a global health crisis especially in developing countries. Tuberculosis treatment is a laborious and lengthy process with high risk of noncompliance, cytotoxicity adverse events and drug resistance in patient. Recently, there has been an alarming rise of drug resistant in TB. In this regard, it is an unmet need to develop novel antitubercular medicines that target new or more effective biochemical pathways to prevent drug resistant Mycobacterium. Integrated study of metabolic pathways through in-silico approach played a key role in antimycobacterial design process in this study. Our results suggest that pantothenate synthetase (PanC), anthranilate phosphoribosyl transferase (TrpD) and 3-isopropylmalate dehydratase (LeuD) might be appropriate drug targets. In the next step, in-silico ligand analysis was used for more detailed study of chemical tractability of targets. This was helpful to identify pantothenate synthetase (PanC, Rv3602c) as the best target for antimycobacterial design procedure. Virtual library screening on the best ligand of PanC was then performed for inhibitory ligand design. At the end, five chemical intermediates showed significant inhibition of Mycobacterium bovis with good selectivity indices (SI) ≥10 according to Tuberculosis Antimicrobial Acquisition & Coordinating Facility of US criteria for antimycobacterial screening programs.

  19. Metabolomic analysis and phenylpropanoid biosynthesis in hairy root culture of tartary buckwheat cultivars.

    Aye Aye Thwe

    Full Text Available Buckwheat, Fagopyrum tataricum Gaertn., is an important medicinal plant, which contains several phenolic compounds, including one of the highest content of rutin, a phenolic compound with anti-inflammatory properties. An experiment was conducted to investigate the level of expression of various genes in the phenylpropanoid biosynthetic pathway to analyze in vitro production of anthocyanin and phenolic compounds from hairy root cultures derived from 2 cultivars of tartary buckwheat (Hokkai T8 and T10. A total of 47 metabolites were identified by gas chromatography-time-of-flight mass spectrometry (GC-TOFMS and subjected to principal component analysis (PCA in order to fully distinguish between Hokkai T8 and T10 hairy roots. The expression levels of phenylpropanoid biosynthetic pathway genes, through qRT-PCR, showed higher expression for almost all the genes in T10 than T8 hairy root except for FtF3'H-2 and FtFLS-2. Rutin, quercetin, gallic acid, caffeic acid, ferulic acid, 4-hydroxybenzoic acid, and 2 anthocyanin compounds were identified in Hokkai T8 and T10 hairy roots. The concentration of rutin and anthocyanin in Hokkai T10 hairy roots of tartary buckwheat was several-fold higher compared with that obtained from Hokkai T8 hairy root. This study provides useful information on the molecular and physiological dynamic processes that are correlated with phenylpropanoid biosynthetic gene expression and phenolic compound content in F. tataricum species.

  20. Microbial metabolomics with gas chromatography/mass spectrometry

    Koek, M.M.; Muilwijk, B.; Werf, M.J. van der; Hankemeier, T.

    2006-01-01

    An analytical method was set up suitable for the analysis of microbial metabolomes, consisting of an oximation and silylation derivatization reaction and subsequent analysis by gas chromatography coupled to mass spectrometry. Microbial matrixes contain many compounds that potentially interfere with

  1. Metabolomics analysis and biosynthesis of rosmarinic acid in Agastache rugosa Kuntze treated with methyl jasmonate.

    Yeon Bok Kim

    Full Text Available This study investigated the effect of methyl jasmonate (MeJA on metabolic profiles and rosmarinic acid (RA biosynthesis in cell cultures of Agastache rugosa Kuntze. Transcript levels of phenylpropanoid biosynthetic genes, i.e., ArPAL, Ar4CL, and ArC4H, maximally increased 4.5-fold, 3.4-fold, and 3.5-fold, respectively, compared with the untreated controls, and the culture contained relatively high amounts of RA after exposure of cells to 50 µM MeJA. RA levels were 2.1-, 4.7-, and 3.9-fold higher after exposure to 10, 50, and 100 µM MeJA, respectively, than those in untreated controls. In addition, the transcript levels of genes attained maximum levels at different time points after the initial exposure. The transcript levels of ArC4H and Ar4CL were transiently induced by MeJA, and reached a maximum of up to 8-fold at 3 hr and 6 hr, respectively. The relationships between primary metabolites and phenolic acids in cell cultures of A. rugosa treated with MeJA were analyzed by gas chromatography coupled with time-of-flight mass spectrometry. In total, 45 metabolites, including 41 primary metabolites and 4 phenolic acids, were identified from A. rugosa. Metabolite profiles were subjected to partial least square-discriminate analysis to evaluate the effects of MeJA. The results indicate that both phenolic acids and precursors for the phenylpropanoid biosynthetic pathway, such as aromatic amino acids and shikimate, were induced as a response to MeJA treatment. Therefore, MeJA appears to have an important impact on RA accumulation, and the increased RA accumulation in the treated cells might be due to activation of the phenylpropanoid genes ArPAL, ArC4H, and Ar4CL.

  2. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang; Gouveia-Figueira, Sandra; Pinto, Rui; Trygg, Johan; Zivkovic, Angela M.; Nording, Malin L.

    2016-01-01

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a

  3. Postprandial metabolomics: A pilot mass spectrometry and NMR study of the human plasma metabolome in response to a challenge meal

    Karimpour, Masoumeh; Surowiec, Izabella; Wu, Junfang [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Gouveia-Figueira, Sandra [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Department of Pharmacology and Clinical Neuroscience, Umeå University, Umeå (Sweden); Pinto, Rui [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Bioinformatics Infrastructure for Life Sciences (Sweden); Trygg, Johan [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden); Zivkovic, Angela M. [Department of Nutrition, University of California, Davis, One Shields Ave, CA 95616 (United States); Nording, Malin L., E-mail: malin.nording@umu.se [Computational Life Science Cluster (CLiC), Department of Chemistry, Umeå University, 90187 Umeå (Sweden)

    2016-02-18

    The study of postprandial metabolism is relevant for understanding metabolic diseases and characterizing personal responses to diet. We combined three analytical platforms – gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) – to validate a multi-platform approach for characterizing individual variation in the postprandial state. We analyzed the postprandial plasma metabolome by introducing, at three occasions, meal challenges on a usual diet, and 1.5 years later, on a modified background diet. The postprandial response was stable over time and largely independent of the background diet as revealed by all three analytical platforms. Coverage of the metabolome between NMR and GC-MS included more polar metabolites detectable only by NMR and more hydrophobic compounds detected by GC-MS. The variability across three separate testing occasions among the identified metabolites was in the range of 1.1–86% for GC-MS and 0.9–42% for NMR in the fasting state at baseline. For the LC-MS analysis, the coefficients of variation of the detected compounds in the fasting state at baseline were in the range of 2–97% for the positive and 4–69% for the negative mode. Multivariate analysis (MVA) of metabolites detected with GC-MS revealed that for both background diets, levels of postprandial amino acids and sugars increased whereas those of fatty acids decreased at 0.5 h after the meal was consumed, reflecting the expected response to the challenge meal. MVA of NMR data revealed increasing postprandial levels of amino acids and other organic acids together with decreasing levels of acetoacetate and 3-hydroxybutanoic acid, also independent of the background diet. Together these data show that the postprandial response to the same challenge meal was stable even though it was tested 1.5 years apart, and that it was largely independent of background diet. This work demonstrates the efficacy of a

  4. Metabolomics of Clostridial Biofuel Production

    Rabinowitz, Joshua D [Princeton Univ., NJ (United States); Aristilde, Ludmilla [Cornell Univ., Ithaca, NY (United States); Amador-Noguez, Daniel [Univ. of Wisconsin, Madison, WI (United States)

    2015-09-08

    Members of the genus Clostridium collectively have the ideal set of the metabolic capabilities for fermentative biofuel production: cellulose degradation, hydrogen production, and solvent excretion. No single organism, however, can effectively convert cellulose into biofuels. Here we developed, using metabolomics and isotope tracers, basic science knowledge of Clostridial metabolism of utility for future efforts to engineer such an organism. In glucose fermentation carried out by the biofuel producer Clostridium acetobutylicum, we observed a remarkably ordered series of metabolite concentration changes as the fermentation progressed from acidogenesis to solventogenesis. In general, high-energy compounds decreased while low-energy species increased during solventogenesis. These changes in metabolite concentrations were accompanied by large changes in intracellular metabolic fluxes, with pyruvate directed towards acetyl-CoA and solvents instead of oxaloacetate and amino acids. Thus, the solventogenic transition involves global remodeling of metabolism to redirect resources from biomass production into solvent production. In contrast to C. acetobutylicum, which is an avid fermenter, C. cellulolyticum metabolizes glucose only slowly. We find that glycolytic intermediate concentrations are radically different from fast fermenting organisms. Associated thermodynamic and isotope tracer analysis revealed that the full glycolytic pathway in C. cellulolyticum is reversible. This arises from changes in cofactor utilization for phosphofructokinase and an alternative pathway from phosphoenolpyruvate to pyruvate. The net effect is to increase the high-energy phosphate bond yield of glycolysis by 150% (from 2 to 5) at the expense of lower net flux. Thus, C. cellulolyticum prioritizes glycolytic energy efficiency over speed. Degradation of cellulose results in other sugars in addition to glucose. Simultaneous feeding of stable isotope-labeled glucose and unlabeled pentose sugars

  5. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    2016-12-01

    Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chemical reactions and are essential for cellular function. Upstream biological disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample preparation and instrument methodology along with myriad data processing and analysis approaches. Research focuses have now shifted toward a fundamental understanding of the biology responsible for metabolomic changes. There are several types of metabolomics experiments including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Critical Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies—specifically in mammalian systems. Biological interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence associated with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

  6. New tools and resources in metabolomics: 2016-2017.

    Misra, Biswapriya B

    2018-04-01

    Rapid advances in mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based platforms for metabolomics have led to an upsurge of data every single year. Newer high-throughput platforms, hyphenated technologies, miniaturization, and tool kits in data acquisition efforts in metabolomics have led to additional challenges in metabolomics data pre-processing, analysis, interpretation, and integration. Thanks to the informatics, statistics, and computational community, new resources continue to develop for metabolomics researchers. The purpose of this review is to provide a summary of the metabolomics tools, software, and databases that were developed or improved during 2016-2017, thus, enabling readers, developers, and researchers access to a succinct but thorough list of resources for further improvisation, implementation, and application in due course of time. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  7. Systematic Applications of Metabolomics in Metabolic Engineering

    Robert A. Dromms

    2012-12-01

    Full Text Available The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

  8. NMR and MS Methods for Metabolomics.

    Amberg, Alexander; Riefke, Björn; Schlotterbeck, Götz; Ross, Alfred; Senn, Hans; Dieterle, Frank; Keck, Matthias

    2017-01-01

    Metabolomics, also often referred as "metabolic profiling," is the systematic profiling of metabolites in biofluids or tissues of organisms and their temporal changes. In the last decade, metabolomics has become more and more popular in drug development, molecular medicine, and other biotechnology fields, since it profiles directly the phenotype and changes thereof in contrast to other "-omics" technologies. The increasing popularity of metabolomics has been possible only due to the enormous development in the technology and bioinformatics fields. In particular, the analytical technologies supporting metabolomics, i.e., NMR, UPLC-MS, and GC-MS, have evolved into sensitive and highly reproducible platforms allowing the determination of hundreds of metabolites in parallel. This chapter describes the best practices of metabolomics as seen today. All important steps of metabolic profiling in drug development and molecular medicine are described in great detail, starting from sample preparation to determining the measurement details of all analytical platforms, and finally to discussing the corresponding specific steps of data analysis.

  9. Linking metabolomics data to underlying metabolic regulation

    Thomas eNägele

    2014-11-01

    Full Text Available The comprehensive experimental analysis of a metabolic constitution plays a central role in approaches of organismal systems biology.Quantifying the impact of a changing environment on the homeostasis of cellular metabolism has been the focus of numerous studies applying various metabolomics techniques. It has been proven that approaches which integrate different analytical techniques, e.g. LC-MS, GC-MS, CE-MS and H-NMR, can provide a comprehensive picture of a certain metabolic homeostasis. Identification of metabolic compounds and quantification of metabolite levels represent the groundwork for the analysis of regulatory strategies in cellular metabolism. This significantly promotes our current understanding of the molecular organization and regulation of cells, tissues and whole organisms.Nevertheless, it is demanding to elicit the pertinent information which is contained in metabolomics data sets.Based on the central dogma of molecular biology, metabolite levels and their fluctuations are the result of a directed flux of information from gene activation over transcription to translation and posttranslational modification.Hence, metabolomics data represent the summed output of a metabolic system comprising various levels of molecular organization.As a consequence, the inverse assignment of metabolomics data to underlying regulatory processes should yield information which-if deciphered correctly-provides comprehensive insight into a metabolic system.Yet, the deduction of regulatory principles is complex not only due to the high number of metabolic compounds, but also because of a high level of cellular compartmentalization and differentiation.Motivated by the question how metabolomics approaches can provide a representative view on regulatory biochemical processes, this article intends to present and discuss current metabolomics applications, strategies of data analysis and their limitations with respect to the interpretability in context of

  10. Strategy for NMR metabolomic analysis of urine in mouse models of obesity- from sample collection to interpretation of acquired data

    Pelantová, Helena; Bugáňová, Martina; Anýž, J.; Železná, Blanka; Maletínská, Lenka; Novák, D.; Haluzík, M.; Kuzma, Marek

    2015-01-01

    Roč. 115, NOV 10 (2015), s. 225-235 ISSN 0731-7085 R&D Projects: GA ČR GA13-14105S; GA MŠk LO1509 Grant - others:OPPC(XE) CZ.2.16/3.1.00/24023 Institutional support: RVO:61388971 ; RVO:61388963 Keywords : NMR metabolomics * Mouse * Obesity Subject RIV: CB - Analytical Chemistry, Separation; CB - Analytical Chemistry, Separation (UOCHB-X) OBOR OECD: Analytical chemistry; Analytical chemistry (UOCHB-X) Impact factor: 3.169, year: 2015

  11. Blood transcriptomics and metabolomics for personalized medicine.

    Li, Shuzhao; Todor, Andrei; Luo, Ruiyan

    2016-01-01

    Molecular analysis of blood samples is pivotal to clinical diagnosis and has been intensively investigated since the rise of systems biology. Recent developments have opened new opportunities to utilize transcriptomics and metabolomics for personalized and precision medicine. Efforts from human immunology have infused into this area exquisite characterizations of subpopulations of blood cells. It is now possible to infer from blood transcriptomics, with fine accuracy, the contribution of immune activation and of cell subpopulations. In parallel, high-resolution mass spectrometry has brought revolutionary analytical capability, detecting > 10,000 metabolites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus, the re-examination of blood chemicals by metabolomics is in order. Transcriptomics and metabolomics can be integrated to provide a more comprehensive understanding of the human biological states. We will review these new data and methods and discuss how they can contribute to personalized medicine.

  12. Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: Application to the detection of breast cancer

    Gu Haiwei; Pan Zhengzheng; Xi Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

    2011-01-01

    Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, 1 H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology.

  13. Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer.

    Gu, Haiwei; Pan, Zhengzheng; Xi, Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

    2011-02-07

    Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology. Copyright © 2010 Elsevier B.V. All rights reserved.

  14. Effect of High-Carbohydrate Diet on Plasma Metabolome in Mice with Mitochondrial Respiratory Chain Complex III Deficiency

    Jayasimman Rajendran

    2016-11-01

    Full Text Available Mitochondrial disorders cause energy failure and metabolic derangements. Metabolome profiling in patients and animal models may identify affected metabolic pathways and reveal new biomarkers of disease progression. Using liver metabolomics we have shown a starvation-like condition in a knock-in (Bcs1lc.232A>G mouse model of GRACILE syndrome, a neonatal lethal respiratory chain complex III dysfunction with hepatopathy. Here, we hypothesized that a high-carbohydrate diet (HCD, 60% dextrose will alleviate the hypoglycemia and promote survival of the sick mice. However, when fed HCD the homozygotes had shorter survival (mean ± SD, 29 ± 2.5 days, n = 21 than those on standard diet (33 ± 3.8 days, n = 30, and no improvement in hypoglycemia or liver glycogen depletion. We investigated the plasma metabolome of the HCD- and control diet-fed mice and found that several amino acids and urea cycle intermediates were increased, and arginine, carnitines, succinate, and purine catabolites decreased in the homozygotes. Despite reduced survival the increase in aromatic amino acids, an indicator of liver mitochondrial dysfunction, was normalized on HCD. Quantitative enrichment analysis revealed that glycine, serine and threonine metabolism, phenylalanine and tyrosine metabolism, and urea cycle were also partly normalized on HCD. This dietary intervention revealed an unexpected adverse effect of high-glucose diet in complex III deficiency, and suggests that plasma metabolomics is a valuable tool in evaluation of therapies in mitochondrial disorders.

  15. Circadian Metabolomics in Time and Space

    Kenneth A. Dyar

    2017-07-01

    Full Text Available Circadian rhythms are widely known to govern human health and disease, but specific pathogenic mechanisms linking circadian disruption to metabolic diseases are just beginning to come to light. This is thanks in part to the development and application of various “omics”-based tools in biology and medicine. Current high-throughput technologies allow for the simultaneous monitoring of multiple dynamic cellular events over time, ranging from gene expression to metabolite abundance and sub-cellular localization. These fundamental temporal and spatial perspectives have allowed for a more comprehensive understanding of how various dynamic cellular events and biochemical processes are related in health and disease. With advances in technology, metabolomics has become a more routine “omics” approach for studying metabolism, and “circadian metabolomics” (i.e., studying the 24-h metabolome has recently been undertaken by several groups. To date, circadian metabolomes have been reported for human serum, saliva, breath, and urine, as well as tissues from several species under specific disease or mutagenesis conditions. Importantly, these studies have consistently revealed that 24-h rhythms are prevalent in almost every tissue and metabolic pathway. Furthermore, these circadian rhythms in tissue metabolism are ultimately linked to and directed by internal 24-h biological clocks. In this review, we will attempt to put these data-rich circadian metabolomics experiments into perspective to find out what they can tell us about metabolic health and disease, and what additional biomarker potential they may reveal.

  16. Towards the Fecal Metabolome Derived from Moderate Red Wine Intake

    Ana Jiménez-Girón

    2014-12-01

    Full Text Available Dietary polyphenols, including red wine phenolic compounds, are extensively metabolized during their passage through the gastrointestinal tract; and their biological effects at the gut level (i.e., anti-inflammatory activity, microbiota modulation, interaction with cells, among others seem to be due more to their microbial-derived metabolites rather than to the original forms found in food. In an effort to improve our understanding of the biological effects that phenolic compounds exert at the gut level, this paper summarizes the changes observed in the human fecal metabolome after an intervention study consisting of a daily consumption of 250 mL of wine during four weeks by healthy volunteers (n = 33. It assembles data from two analytical approaches: (1 UPLC-ESI-MS/MS analysis of phenolic metabolites in fecal solutions (targeted analysis; and (2 UHPLC-TOF MS analysis of the fecal solutions (non-targeted analysis. Both approaches revealed statistically-significant changes in the concentration of several metabolites as a consequence of the wine intake. Similarity and complementarity between targeted and non-targeted approaches in the analysis of the fecal metabolome are discussed. Both strategies allowed the definition of a complex metabolic profile derived from wine intake. Likewise, the identification of endogenous markers could lead to new hypotheses to unravel the relationship between moderate wine consumption and the metabolic functionality of gut microbiota.

  17. New Nordic Diet versus Average Danish Diet: A Randomized Controlled Trial Revealed Healthy Long-Term Effects of the New Nordic Diet by GC-MS Blood Plasma Metabolomics.

    Khakimov, Bekzod; Poulsen, Sanne Kellebjerg; Savorani, Francesco; Acar, Evrim; Gürdeniz, Gözde; Larsen, Thomas M; Astrup, Arne; Dragsted, Lars O; Engelsen, Søren Balling

    2016-06-03

    A previous study has shown effects of the New Nordic Diet (NND) to stimulate weight loss and lower systolic and diastolic blood pressure in obese Danish women and men in a randomized, controlled dietary intervention study. This work demonstrates long-term metabolic effects of the NND as compared with an Average Danish Diet (ADD) in blood plasma and reveals associations between metabolic changes and health beneficial effects of the NND including weight loss. A total of 145 individuals completed the intervention and blood samples were taken along with clinical examinations before the intervention started (week 0) and after 12 and 26 weeks. The plasma metabolome was measured using GC-MS, and the final metabolite table contained 144 variables. Significant and novel metabolic effects of the diet, resulting weight loss, gender, and intervention study season were revealed using PLS-DA and ASCA. Several metabolites reflecting specific differences in the diets, especially intake of plant foods and seafood, and in energy metabolism related to ketone bodies and gluconeogenesis formed the predominant metabolite pattern discriminating the intervention groups. Among NND subjects, higher levels of vaccenic acid and 3-hydroxybutanoic acid were related to a higher weight loss, while higher concentrations of salicylic, lactic, and N-aspartic acids and 1,5-anhydro-d-sorbitol were related to a lower weight loss. Specific gender and seasonal differences were also observed. The study strongly indicates that healthy diets high in fish, vegetables, fruit, and whole grain facilitated weight loss and improved insulin sensitivity by increasing ketosis and gluconeogenesis in the fasting state.

  18. Clinical Metabolomics and Glaucoma.

    Barbosa-Breda, João; Himmelreich, Uwe; Ghesquière, Bart; Rocha-Sousa, Amândio; Stalmans, Ingeborg

    2018-01-01

    Glaucoma is one of the leading causes of irreversible blindness worldwide. However, there are no biomarkers that accurately help clinicians perform an early diagnosis or detect patients with a high risk of progression. Metabolomics is the study of all metabolites in an organism, and it has the potential to provide a biomarker. This review summarizes the findings of metabolomics in glaucoma patients and explains why this field is promising for new research. We identified published studies that focused on metabolomics and ophthalmology. After providing an overview of metabolomics in ophthalmology, we focused on human glaucoma studies. Five studies have been conducted in glaucoma patients and all compared patients to healthy controls. Using mass spectrometry, significant differences were found in blood plasma in the metabolic pathways that involve palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors. For nuclear magnetic resonance spectroscopy, a high glutamine-glutamate/creatine ratio was found in the vitreous and lateral geniculate body; no differences were detected in the optic radiations, and a lower N-acetylaspartate/choline ratio was observed in the geniculocalcarine and striate areas. Metabolomics can move glaucoma care towards a personalized approach and provide new knowledge concerning the pathophysiology of glaucoma, which can lead to new therapeutic options. © 2017 S. Karger AG, Basel.

  19. The acute metabolic response to breads with contrasting content and composition of arabinoxylans and ß-glucan - metabolomics analysis of plasma from porto-arterial catheterized pigs

    Nielsen, Kirstine Lykke; Hedemann, Mette Skou; Lærke, Helle Nygaard

    2014-01-01

    A liquid chromatography–MS (LC-MS) metabolomics analysis of plasma from portal–arterial catheterised pigs fed breads prepared with whole-grain rye or wheat flour with added concentrated arabinoxylan (AX) or β-glucan (BG) was conducted. Comparison of the effects of concentrated fibres with whole...... of available carbohydrate was similar for the five breads but varied in the content of protein. Plasma was collected continuously for 4 h after feeding. Glucose levels in the portal vein were reduced postprandially in response to the AX, GR and RK breads that had high contents of AX compared with WF bread (P...... contents in the breads and leucine uptake significantly affected insulin secretion in the mesenteric artery...

  20. Gut metabolome meets microbiome

    Lamichhane, Santosh; Sen, Partho; Dickens, Alex M

    2018-01-01

    It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We...... highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding...

  1. Metabolomic profiles as reliable biomarkers of dietary composition123

    Esko, Tõnu; Hirschhorn, Joel N; Feldman, Henry A; Hsu, Yu-Han H; Deik, Amy A; Clish, Clary B; Ebbeling, Cara B; Ludwig, David S

    2017-01-01

    Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects. Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol. Design: Twenty-one adults with a high body mass index (in kg/m2; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10–15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography–tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons. Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors. Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in

  2. Effects of sample injection amount and time-of-flight mass spectrometric detection dynamic range on metabolome analysis by high-performance chemical isotope labeling LC-MS.

    Zhou, Ruokun; Li, Liang

    2015-04-06

    The effect of sample injection amount on metabolome analysis in a chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) platform was investigated. The performance of time-of-flight (TOF) mass spectrometers with and without a high-dynamic-range (HD) detection system was compared in the analysis of (12)C2/(13)C2-dansyl labeled human urine samples. An average of 1635 ± 21 (n = 3) peak pairs or putative metabolites was detected using the HD-TOF-MS, compared to 1429 ± 37 peak pairs from a conventional or non-HD TOF-MS. In both instruments, signal saturation was observed. However, in the HD-TOF-MS, signal saturation was mainly caused by the ionization process, while in the non-HD TOF-MS, it was caused by the detection process. To extend the MS detection range in the non-HD TOF-MS, an automated switching from using (12)C to (13)C-natural abundance peaks for peak ratio calculation when the (12)C peaks are saturated has been implemented in IsoMS, a software tool for processing CIL LC-MS data. This work illustrates that injecting an optimal sample amount is important to maximize the metabolome coverage while avoiding the sample carryover problem often associated with over-injection. A TOF mass spectrometer with an enhanced detection dynamic range can also significantly increase the number of peak pairs detected. In chemical isotope labeling (CIL) LC-MS, relative metabolite quantification is done by measuring the peak ratio of a (13)C2-/(12)C2-labeled peak pair for a given metabolite present in two comparative samples. The dynamic range of peak ratio measurement does not need to be very large, as only subtle changes of metabolite concentrations are encountered in most metabolomic studies where relative metabolome quantification of different groups of samples is performed. However, the absolute concentrations of different metabolites can be very different, requiring a technique to provide a wide detection dynamic range to allow the detection of as

  3. Metabolomic Analysis and Mode of Action of Metabolites of Tea Tree Oil Involved in the Suppression of Botrytis cinerea

    Jiayu Xu

    2017-06-01

    Full Text Available Tea tree oil (TTO, a volatile essential oil, has been widely used as an antimicrobial agent. However, the mechanism underlying TTO antifungal activity is not fully understood. In this study, a comprehensive metabolomics survey was undertaken to identify changes in metabolite production in Botrytis cinerea cells treated with TTO. Significant differences in 91 metabolites were observed, including 8 upregulated and 83 downregulated metabolites in TTO-treated cells. The results indicate that TTO inhibits primary metabolic pathways through the suppression of the tricarboxylic acid (TCA cycle and fatty acid metabolism. Further experiments show that TTO treatment decreases the activities of key enzymes in the TCA cycle and increases the level of hydrogen peroxide (H2O2. Membrane damage is also induced by TTO treatment. We hypothesize that the effect of TTO on B. cinerea is achieved mainly by disruption of the TCA cycle and fatty acid metabolism, resulting in mitochondrial dysfunction and oxidative stress.

  4. Analysis of spatiotemporal metabolomic dynamics for sensitively monitoring biological alterations in cisplatin-induced acute kidney injury.

    Irie, Miho; Hayakawa, Eisuke; Fujimura, Yoshinori; Honda, Youhei; Setoyama, Daiki; Wariishi, Hiroyuki; Hyodo, Fuminori; Miura, Daisuke

    2018-01-29

    Clinical application of the major anticancer drug, cisplatin, is limited by severe side effects, especially acute kidney injury (AKI) caused by nephrotoxicity. The detailed metabolic mechanism is still largely unknown. Here, we used an integrated technique combining mass spectrometry imaging (MSI) and liquid chromatography-mass spectrometry (LC-MS) to visualize the diverse spatiotemporal metabolic dynamics in the mouse kidney after cisplatin dosing. Biological responses to cisplatin was more sensitively detected within 24 h as a metabolic alteration, which is much earlier than possible with the conventional clinical chemistry method of blood urea nitrogen (BUN) measurement. Region-specific changes (e.g., medulla and cortex) in metabolites related to DNA damage and energy generation were observed over the 72-h exposure period. Therefore, this metabolomics approach may become a novel strategy for elucidating early renal responses to cisplatin, prior to the detection of kidney damage evaluated by conventional method. Copyright © 2018. Published by Elsevier Inc.

  5. Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

    Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

    2017-05-02

    Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

  6. Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats.

    Tranchida, Fabrice; Shintu, Laetitia; Rakotoniaina, Zo; Tchiakpe, Léopold; Deyris, Valérie; Hiol, Abel; Caldarelli, Stefano

    2015-01-01

    We explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and glycoproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR.

  7. Comparative metabolomics analysis for the compatibility and incompatibility of kansui and licorice with different ratios by UHPLC-QTOF/MS and multivariate data analysis.

    Shen, Juan; Pu, Zong-Jin; Kai, Jun; Kang, An; Tang, Yu-Ping; Shang, Li-Li; Zhou, Gui-Sheng; Zhu, Zhen-Hua; Shang, Er-Xin; Li, Shao-Ping; Cao, Yu-Jie; Tao, Wei-Wei; Su, Shu-Lan; Zhang, Li; Zhou, Huiping; Qian, Da-Wei; Duan, Jin-Ao

    2017-07-01

    Kansui, the root of Euphorbia kansui T.N. Liou ex T.P. Wang (Euphorbiaceae), is a well-known poisonous traditional Chinese medicine (TCM). However, many monographs of TCM indicated that it cannot be co-used with licorice, as kansui-licorice is a typical "eighteen incompatible" medicaments. Our previous studies have indicated that kansui was effective in treating malignant pleural effusion (MPE), and the efficacy could be weakened by the co-use of licorice, even causing serious toxicity at the given ratio. Nevertheless, the actual mechanisms of their dosage-toxicity-efficacy relationship need to be well clarified. The present study aimed to investigate the effect of individual and combined use of kansui and licorice on MPE rats, and explain the underlying mechanisms from a metabolomic perspective. Urine samples were analyzed by ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS). Partial least-squares discriminate analysis (PLS-DA) models were built to evaluate the interaction between kansui and licorice. Seven potential biomarkers contribute to the separation of model group and control group were tentatively identified. And selenoamino acid metabolism and nicotinate and nicotinamide metabolism with the impact-value 0.31 and 0.24, respectively, were filtered out as the most important metabolic pathways. Kansui and kansui-licorice at a ratio of 4:1 can treat MPE rats by adjusting abnormal metabolic pathways to the normal state, while it may have opposite result with kansui-licorice 1:4. The different influences to the two metabolic pathways may partially explain the dosage-toxicity-efficacy relationship of kansui-licorice with different ratios. The results could offer valuable insights into the compatibility property changes for the two herbs. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. Global Metabolomics of the Placenta Reveals Distinct Metabolic Profiles between Maternal and Fetal Placental Tissues Following Delivery in Non-Labored Women

    Jacquelyn M. Walejko

    2018-01-01

    Full Text Available We evaluated the metabolic alterations in maternal and fetal placental tissues from non-labored women undergoing cesarean section using samples collected from 5 min to 24 h following delivery. Using 1H-NMR, we identified 14 metabolites that significantly differed between maternal and fetal placental tissues (FDR-corrected p-value < 0.05, with 12 metabolites elevated in the maternal tissue, reflecting the flux of these metabolites from mother to fetus. In the maternal tissue, 4 metabolites were significantly altered at 15 min, 10 metabolites at 30 min, and 16 metabolites at 1 h postdelivery, while 11 metabolites remained stable over 24 h. In contrast, in the fetal placenta tissue, 1 metabolite was significantly altered at 15 min, 2 metabolites at 30 min, and 4 metabolites at 1 h postdelivery, while 22 metabolites remained stable over 24 h. Our study provides information on the metabolic profiles of maternal and fetal placental tissues delivered by cesarean section and reveals that there are different metabolic alterations in the maternal and fetal tissues of the placenta following delivery.

  9. Comparative physiological, metabolomic, and transcriptomic analyses reveal mechanisms of improved abiotic stress resistance in bermudagrass [Cynodon dactylon (L). Pers.] by exogenous melatonin

    Shi, Haitao; Jiang, Chuan; Ye, Tiantian; Tan, Dun-xian; Reiter, Russel J.; Zhang, Heng; Liu, Renyi; Chan, Zhulong

    2015-01-01

    Melatonin (N-acetyl-5-methoxytryptamine), a well-known animal hormone, is also involved in plant development and abiotic stress responses. In this study, it is shown that exogenous application of melatonin conferred improved salt, drought, and cold stress resistances in bermudagrass. Moreover, exogenous melatonin treatment alleviated reactive oxygen species (ROS) burst and cell damage induced by abiotic stress; this involved activation of several antioxidants. Additionally, melatonin-pre-treated plants exhibited higher concentrations of 54 metabolites, including amino acids, organic acids, sugars, and sugar alcohols, than non-treated plants under abiotic stress conditions. Genome-wide transcriptomic profiling identified 3933 transcripts (2361 up-regulated and 1572 down-regulated) that were differentially expressed in melatonin-treated plants versus controls. Pathway and gene ontology (GO) term enrichment analyses revealed that genes involved in nitrogen metabolism, major carbohydrate metabolism, tricarboxylic acid (TCA)/org transformation, transport, hormone metabolism, metal handling, redox, and secondary metabolism were over-represented after melatonin pre-treatment. Taken together, this study provides the first evidence of the protective roles of exogenous melatonin in the bermudagrass response to abiotic stresses, partially via activation of antioxidants and modulation of metabolic homeostasis. Notably, metabolic and transcriptomic analyses showed that the underlying mechanisms of melatonin could involve major reorientation of photorespiratory and carbohydrate and nitrogen metabolism. PMID:25225478

  10. Comparative physiological, metabolomic, and transcriptomic analyses reveal mechanisms of improved abiotic stress resistance in bermudagrass [Cynodon dactylon (L). Pers.] by exogenous melatonin.

    Shi, Haitao; Jiang, Chuan; Ye, Tiantian; Tan, Dun-Xian; Reiter, Russel J; Zhang, Heng; Liu, Renyi; Chan, Zhulong

    2015-02-01

    Melatonin (N-acetyl-5-methoxytryptamine), a well-known animal hormone, is also involved in plant development and abiotic stress responses. In this study, it is shown that exogenous application of melatonin conferred improved salt, drought, and cold stress resistances in bermudagrass. Moreover, exogenous melatonin treatment alleviated reactive oxygen species (ROS) burst and cell damage induced by abiotic stress; this involved activation of several antioxidants. Additionally, melatonin-pre-treated plants exhibited higher concentrations of 54 metabolites, including amino acids, organic acids, sugars, and sugar alcohols, than non-treated plants under abiotic stress conditions. Genome-wide transcriptomic profiling identified 3933 transcripts (2361 up-regulated and 1572 down-regulated) that were differentially expressed in melatonin-treated plants versus controls. Pathway and gene ontology (GO) term enrichment analyses revealed that genes involved in nitrogen metabolism, major carbohydrate metabolism, tricarboxylic acid (TCA)/org transformation, transport, hormone metabolism, metal handling, redox, and secondary metabolism were over-represented after melatonin pre-treatment. Taken together, this study provides the first evidence of the protective roles of exogenous melatonin in the bermudagrass response to abiotic stresses, partially via activation of antioxidants and modulation of metabolic homeostasis. Notably, metabolic and transcriptomic analyses showed that the underlying mechanisms of melatonin could involve major reorientation of photorespiratory and carbohydrate and nitrogen metabolism. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  11. Updates in metabolomics tools and resources: 2014-2015.

    Misra, Biswapriya B; van der Hooft, Justin J J

    2016-01-01

    Data processing and interpretation represent the most challenging and time-consuming steps in high-throughput metabolomic experiments, regardless of the analytical platforms (MS or NMR spectroscopy based) used for data acquisition. Improved machinery in metabolomics generates increasingly complex datasets that create the need for more and better processing and analysis software and in silico approaches to understand the resulting data. However, a comprehensive source of information describing the utility of the most recently developed and released metabolomics resources--in the form of tools, software, and databases--is currently lacking. Thus, here we provide an overview of freely-available, and open-source, tools, algorithms, and frameworks to make both upcoming and established metabolomics researchers aware of the recent developments in an attempt to advance and facilitate data processing workflows in their metabolomics research. The major topics include tools and researches for data processing, data annotation, and data visualization in MS and NMR-based metabolomics. Most in this review described tools are dedicated to untargeted metabolomics workflows; however, some more specialist tools are described as well. All tools and resources described including their analytical and computational platform dependencies are summarized in an overview Table. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. Serum metabolomic profiling in acute alcoholic hepatitis identifies multiple dysregulated pathways.

    Rachakonda, Vikrant; Gabbert, Charles; Raina, Amit; Bell, Lauren N; Cooper, Sara; Malik, Shahid; Behari, Jaideep

    2014-01-01

    While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH), the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA) cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. Severe AAH is characterized by a distinct metabolic phenotype spanning

  13. Metabolomics and Personalized Medicine.

    Koen, Nadia; Du Preez, Ilse; Loots, Du Toit

    2016-01-01

    Current clinical practice strongly relies on the prognosis, diagnosis, and treatment of diseases using methods determined and averaged for the specific diseased cohort/population. Although this approach complies positively with most patients, misdiagnosis, treatment failure, relapse, and adverse drug effects are common occurrences in many individuals, which subsequently hamper the control and eradication of a number of diseases. These incidences can be explained by individual variation in the genome, transcriptome, proteome, and metabolome of a patient. Various "omics" approaches have investigated the influence of these factors on a molecular level, with the intention of developing personalized approaches to disease diagnosis and treatment. Metabolomics, the newest addition to the "omics" domain and the closest to the observed phenotype, reflects changes occurring at all molecular levels, as well as influences resulting from other internal and external factors. By comparing the metabolite profiles of two or more disease phenotypes, metabolomics can be applied to identify biomarkers related to the perturbation being investigated. These biomarkers can, in turn, be used to develop personalized prognostic, diagnostic, and treatment approaches, and can also be applied to the monitoring of disease progression, treatment efficacy, predisposition to drug-related side effects, and potential relapse. In this review, we discuss the contributions that metabolomics has made, and can potentially still make, towards the field of personalized medicine. © 2016 Elsevier Inc. All rights reserved.

  14. Single cell metabolomics

    Heinemann, Matthias; Zenobi, Renato

    Recent discoveries suggest that cells of a clonal population often display multiple metabolic phenotypes at the same time. Motivated by the success of mass spectrometry (MS) in the investigation of population-level metabolomics, the analytical community has initiated efforts towards MS-based single

  15. Possible contribution of taurine to distorted glucagon secretion in intra-islet insulin deficiency: a metabolome analysis using a novel α-cell model of insulin-deficient diabetes.

    Megumi Bessho

    Full Text Available Glycemic instability is a serious problem in patients with insulin-deficient diabetes, and it may be due in part to abnormal endogenous glucagon secretion. However, the intracellular metabolic mechanism(s involved in the aberrant glucagon response under the condition of insulin deficiency has not yet been elucidated. To investigate the metabolic traits that underlie the distortion of glucagon secretion under insulin deficient conditions, we generated an αTC1-6 cell line with stable knockdown of the insulin receptor (IRKD, i.e., an in vitro α-cell model for insulin-deficient diabetes, which exhibits an abnormal glucagon response to glucose. A comprehensive metabolomic analysis of the IRKD αTC1-6 cells (IRKD cells revealed some candidate metabolites whose levels differed markedly compared to those in control αTC1-6 cells, but also which could affect the glucagon release in IRKD cells. Of these candidates, taurine was remarkably increased in the IRKD cells and was identified as a stimulator of glucagon in αTC1-6 cells. Taurine also paradoxically exaggerated the glucagon secretion at a high glucose concentration in IRKD cells and islets with IRKD. These results indicate that the metabolic alterations induced by IRKD in α-cells, especially the increase of taurine, may lead to the distorted glucagon response in IRKD cells, suggesting the importance of taurine in the paradoxical glucagon response and the resultant glucose instability in insulin-deficient diabetes.

  16. Characteristics of the tomato chromoplast revealed by proteomic analysis

    Barsan, Cristina; Sanchez-Bel, Paloma; Rombaldi, César Valmor; Egea, Isabel; Rossignol, Michel; Kuntz, Marcel; Zouine, Mohamed; Latché, Alain; Bouzayen, Mondher; Pech, Jean-Claude

    2010-01-01

    Chromoplasts are non-photosynthetic specialized plastids that are important in ripening tomato fruit (Solanum lycopersicum) since, among other functions, they are the site of accumulation of coloured compounds. Analysis of the proteome of red fruit chromoplasts revealed the presence of 988 proteins corresponding to 802 Arabidopsis unigenes, among which 209 had not been listed so far in plastidial databanks. These data revealed several features of the chromoplast. Proteins of lipid metabolism ...

  17. Metabolomic biomarkers in serum and urine in women with preeclampsia.

    Marie Austdal

    Full Text Available To explore the potential of magnetic resonance (MR metabolomics for study of preeclampsia, for improved phenotyping and elucidating potential clues to etiology and pathogenesis.Urine and serum samples from pregnant women with preeclampsia (n = 10, normal pregnancies (n = 10 and non-pregnant women (n = 10 matched by age and gestational age were analyzed with MR spectroscopy and subjected to multivariate analysis. Metabolites were then quantified and compared between groups.Urine and serum samples revealed clear differences between women with preeclampsia and both control groups (normal pregnant and non-pregnant women. Nine urine metabolites were significantly different between preeclampsia and the normal pregnant group. Urine samples from women with early onset preeclampsia clustered together in the multivariate analysis. The preeclampsia serum spectra showed higher levels of low and very-low density lipoproteins and lower levels of high-density lipoproteins when compared to both non-pregnant and normal pregnant women.The MR determined metabolic profiles in urine and serum from women with preeclampsia are clearly different from normal pregnant women. The observed differences represent a potential to examine mechanisms underlying different preeclampsia phenotypes in urine and serum samples in larger studies. In addition, similarities between preeclampsia and cardiovascular disease in metabolomics are demonstrated.

  18. Blood Transcriptomics and Metabolomics for Personalized Medicine

    2015-10-31

    involved in rheumatoid arthritis . PLoS Comput Biol 2011;7. [100] Zhu J. Stitching together multiple data dimensions reveals interacting metabolomic...capability, detecting N10,000 metabo- lites, together with environmental exposure, dietary intake, microbial activity, and pharmaceutical drugs. Thus...research to clinical care has constantly seen huge disap- pointments. With the accumulation of detailed, information-rich data, human subjects start to

  19. Comparative proteomic and metabolomic analyses reveal mechanisms of improved cold stress tolerance in bermudagrass (Cynodon dactylon (L.) Pers.) by exogenous calcium.

    Shi, Haitao; Ye, Tiantian; Zhong, Bao; Liu, Xun; Chan, Zhulong

    2014-11-01

    As an important second messenger, calcium is involved in plant cold stress response, including chilling (Cynodon dactylon (L.) Pers.). Physiological analyses showed that CaCl2 treatment alleviated the reactive oxygen species (ROS) burst and cell damage triggered by chilling stress, via activating antioxidant enzymes, non-enzymatic glutathione antioxidant pool, while EGTA treatment had the opposite effects. Additionally, comparative proteomic analysis identified 51 differentially expressed proteins that were enriched in redox, tricarboxylicacid cycle, glycolysis, photosynthesis, oxidative pentose phosphate pathway, and amino acid metabolisms. Consistently, 42 metabolites including amino acids, organic acids, sugars, and sugar alcohols were regulated by CaCl2 treatment under control and cold stress conditions, further confirming the common modulation of CaCl2 treatment in carbon metabolites and amino acid metabolism. Taken together, this study reported first evidence of the essential and protective roles of endogenous and exogenous calcium in bermudagrass response to cold stress, partially via activation of the antioxidants and modulation of several differentially expressed proteins and metabolic homeostasis in the process of cold acclimation. © 2014 Institute of Botany, Chinese Academy of Sciences.

  20. Investigation of the effect of genotype and agronomic conditions on metabolomic profiles of selected strawberry cultivars with different sensitivity to environmental stress.

    Akhatou, Ikram; González-Domínguez, Raúl; Fernández-Recamales, Ángeles

    2016-04-01

    Strawberry is one of the most economically important and widely cultivated fruit crops across the world, so that there is a growing need to develop new analytical methodologies for the authentication of variety and origin, as well as the assessment of agricultural and processing practices. In this work, an untargeted metabolomic strategy based on gas chromatography mass spectrometry (GC-MS) combined with multivariate statistical techniques was used for the first time to characterize the primary metabolome of different strawberry cultivars and to study metabolite alterations in response to multiple agronomic conditions. For this purpose, we investigated three varieties of strawberries with different sensitivity to environmental stress (Camarosa, Festival and Palomar), cultivated in soilless systems using various electrical conductivities, types of coverage and substrates. Metabolomic analysis revealed significant alterations in primary metabolites between the three strawberry cultivars grown under different crop conditions, including sugars (fructose, glucose), organic acids (malic acid, citric acid) and amino acids (alanine, threonine, aspartic acid), among others. Therefore, it could be concluded that GC-MS based metabolomics is a suitable tool to differentiate strawberry cultivars and characterize metabolomic changes associated with environmental and agronomic conditions. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

  1. Microbial metabolomics in open microscale platforms

    Barkal, Layla J.; Theberge, Ashleigh B.; Guo, Chun-Jun; Spraker, Joe; Rappert, Lucas; Berthier, Jean; Brakke, Kenneth A.; Wang, Clay C. C.; Beebe, David J.; Keller, Nancy P.; Berthier, Erwin

    2016-01-01

    The microbial secondary metabolome encompasses great synthetic diversity, empowering microbes to tune their chemical responses to changing microenvironments. Traditional metabolomics methods are ill-equipped to probe a wide variety of environments or environmental dynamics. Here we introduce a class of microscale culture platforms to analyse chemical diversity of fungal and bacterial secondary metabolomes. By leveraging stable biphasic interfaces to integrate microculture with small molecule isolation via liquid–liquid extraction, we enable metabolomics-scale analysis using mass spectrometry. This platform facilitates exploration of culture microenvironments (including rare media typically inaccessible using established methods), unusual organic solvents for metabolite isolation and microbial mutants. Utilizing Aspergillus, a fungal genus known for its rich secondary metabolism, we characterize the effects of culture geometry and growth matrix on secondary metabolism, highlighting the potential use of microscale systems to unlock unknown or cryptic secondary metabolites for natural products discovery. Finally, we demonstrate the potential for this class of microfluidic systems to study interkingdom communication between fungi and bacteria. PMID:26842393

  2. NMR metabolomic analysis of dairy cows reveals milk glycerophosphocholine to phosphocholine ratio as prognostic biomarker for risk of ketosis.

    Klein, Matthias S; Buttchereit, Nina; Miemczyk, Sebastian P; Immervoll, Ann-Kathrin; Louis, Caridad; Wiedemann, Steffi; Junge, Wolfgang; Thaller, Georg; Oefner, Peter J; Gronwald, Wolfram

    2012-02-03

    Ketosis is a common metabolic disease in dairy cows. Diagnostic markers for ketosis such as acetone and beta-hydroxybutyric acid (BHBA) are known, but disease prediction remains an unsolved challenge. Milk is a steadily available biofluid and routinely collected on a daily basis. This high availability makes milk superior to blood or urine samples for diagnostic purposes. In this contribution, we show that high milk glycerophosphocholine (GPC) levels and high ratios of GPC to phosphocholine (PC) allow for the reliable selection of healthy and metabolically stable cows for breeding purposes. Throughout lactation, high GPC values are connected with a low ketosis incidence. During the first month of lactation, molar GPC/PC ratios equal or greater than 2.5 indicate a very low risk for developing ketosis. This threshold was validated for different breeds (Holstein-Friesian, Brown Swiss, and Simmental Fleckvieh) and for animals in different lactations, with observed odds ratios between 1.5 and 2.38. In contrast to acetone and BHBA, these measures are independent of the acute disease status. A possible explanation for the predictive effect is that GPC and PC are measures for the ability to break down phospholipids as a fatty acid source to meet the enhanced energy requirements of early lactation.

  3. Metabolomics approach for discovering disease biomarkers and understanding metabolic pathway

    Jeeyoun Jung

    2011-12-01

    Full Text Available Metabolomics, the multi-targeted analysis of endogenous metabolites from biological samples, can be efficiently applied to screen disease biomarkers and investigate pathophysiological processes. Metabolites change rapidly in response to physiological perturbations, making them the closest link to disease phenotypes. This study explored the role of metabolomics in gaining mechanistic insight into disease processes and in searching for novel biomarkers of human diseases

  4. Metabolomics through the lens of precision cardiovascular medicine.

    Lam, Sin Man; Wang, Yuan; Li, Bowen; Du, Jie; Shui, Guanghou

    2017-03-20

    Metabolomics, which targets at the extensive characterization and quantitation of global metabolites from both endogenous and exogenous sources, has emerged as a novel technological avenue to advance the field of precision medicine principally driven by genomics-oriented approaches. In particular, metabolomics has revealed the cardinal roles that the environment exerts in driving the progression of major diseases threatening public health. Herein, the existent and potential applications of metabolomics in two key areas of precision cardiovascular medicine will be critically discussed: 1) the use of metabolomics in unveiling novel disease biomarkers and pathological pathways; 2) the contribution of metabolomics in cardiovascular drug development. Major issues concerning the statistical handling of big data generated by metabolomics, as well as its interpretation, will be briefly addressed. Finally, the need for integration of various omics branches and adopting a multi-omics approach to precision medicine will be discussed. Copyright © 2017 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.

  5. NMR-based milk metabolomics

    Sundekilde, Ulrik; Larsen, Lotte Bach; Bertram, Hanne Christine S.

    2013-01-01

    and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weig