Metabolome Profiling of Partial and Fully Reprogrammed Induced Pluripotent Stem Cells.

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Park, Soon-Jung; Lee, Sang A; Prasain, Nutan; Bae, Daekyeong; Kang, Hyunsu; Ha, Taewon; Kim, Jong Soo; Hong, Ki-Sung; Mantel, Charlie; Moon, Sung-Hwan; Broxmeyer, Hal E; Lee, Man Ryul

2017-05-15

Acquisition of proper metabolomic fate is required to convert somatic cells toward fully reprogrammed pluripotent stem cells. The majority of induced pluripotent stem cells (iPSCs) are partially reprogrammed and have a transcriptome different from that of the pluripotent stem cells. The metabolomic profile and mitochondrial metabolic functions required to achieve full reprogramming of somatic cells to iPSC status have not yet been elucidated. Clarification of the metabolites underlying reprogramming mechanisms should enable further optimization to enhance the efficiency of obtaining fully reprogrammed iPSCs. In this study, we characterized the metabolites of human fully reprogrammed iPSCs, partially reprogrammed iPSCs, and embryonic stem cells (ESCs). Using capillary electrophoresis time-of-flight mass spectrometry-based metabolomics, we found that 89% of analyzed metabolites were similarly expressed in fully reprogrammed iPSCs and human ESCs (hESCs), whereas partially reprogrammed iPSCs shared only 74% similarly expressed metabolites with hESCs. Metabolomic profiling analysis suggested that converting mitochondrial respiration to glycolytic flux is critical for reprogramming of somatic cells into fully reprogrammed iPSCs. This characterization of metabolic reprogramming in iPSCs may enable the development of new reprogramming parameters for enhancing the generation of fully reprogrammed human iPSCs.

Metabolome and proteome profiling of complex I deficiency induced by rotenone.

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Gielisch, Ina; Meierhofer, David

2015-01-02

Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

Biomarker discovery in neurological diseases: a metabolomic approach

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Afaf El-Ansary

2009-12-01

Full Text Available Afaf El-Ansary, Nouf Al-Afaleg, Yousra Al-YafaeeBiochemistry Department, Science College, King Saud University, Riyadh, Saudi ArabiaAbstract: Biomarkers are pharmacological and physiological measurements or specific biochemicals in the body that have a particular molecular feature that makes them useful for measuring the progress of disease or the effects of treatment. Due to the complexity of neurological disorders, it is very difficult to have perfect markers. Brain diseases require plenty of markers to reflect the metabolic impairment of different brain cells. The recent introduction of the metabolomic approach helps the study of neurological diseases based on profiling a multitude of biochemical components related to brain metabolism. This review is a trial to elucidate the possibility to use this approach to identify plasma metabolic markers related to neurological disorders. Previous trials using different metabolomic analyses including nuclear magnetic resonance spectroscopy, gas chromatography combined with mass spectrometry, liquid chromatography combined with mass spectrometry, and capillary electrophoresis will be traced.Keywords: metabolic biomarkers, neurological disorders. metabolome, nuclear magnetic resonance, mass spectrometry, chromatography

Real-time metabolome profiling of the metabolic switch between starvation and growth.

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Link, Hannes; Fuhrer, Tobias; Gerosa, Luca; Zamboni, Nicola; Sauer, Uwe

2015-11-01

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

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

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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.

Metabolomics of Small Numbers of Cells: Metabolomic Profiling of 100, 1000, and 10000 Human Breast Cancer Cells.

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Luo, Xian; Li, Liang

2017-11-07

In cellular metabolomics, it is desirable to carry out metabolomic profiling using a small number of cells in order to save time and cost. In some applications (e.g., working with circulating tumor cells in blood), only a limited number of cells are available for analysis. In this report, we describe a method based on high-performance chemical isotope labeling (CIL) nanoflow liquid chromatography mass spectrometry (nanoLC-MS) for high-coverage metabolomic analysis of small numbers of cells (i.e., ≤10000 cells). As an example, 12 C-/ 13 C-dansyl labeling of the metabolites in lysates of 100, 1000, and 10000 MCF-7 breast cancer cells was carried out using a new labeling protocol tailored to handle small amounts of metabolites. Chemical-vapor-assisted ionization in a captivespray interface was optimized for improving metabolite ionization and increasing robustness of nanoLC-MS. Compared to microflow LC-MS, the nanoflow system provided much improved metabolite detectability with a significantly reduced sample amount required for analysis. Experimental duplicate analyses of biological triplicates resulted in the detection of 1620 ± 148, 2091 ± 89 and 2402 ± 80 (n = 6) peak pairs or metabolites in the amine/phenol submetabolome from the 12 C-/ 13 C-dansyl labeled lysates of 100, 1000, and 10000 cells, respectively. About 63-69% of these peak pairs could be either identified using dansyl labeled standard library or mass-matched to chemical structures in human metabolome databases. We envisage the routine applications of this method for high-coverage quantitative cellular metabolomics using a starting material of 10000 cells. Even for analyzing 100 or 1000 cells, although the metabolomic coverage is reduced from the maximal coverage, this method can still detect thousands of metabolites, allowing the analysis of a large fraction of the metabolome and focused analysis of the detectable metabolites.

Accurate, fully-automated NMR spectral profiling for metabolomics.

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Siamak Ravanbakhsh

Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra

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Mercier, Pascal; Lewis, Michael J.; Chang, David; Baker, David; Wishart, David S.

2011-01-01

Nuclear magnetic resonance (NMR) and Mass Spectroscopy (MS) are the two most common spectroscopic analytical techniques employed in metabolomics. The large spectral datasets generated by NMR and MS are often analyzed using data reduction techniques like Principal Component Analysis (PCA). Although rapid, these methods are susceptible to solvent and matrix effects, high rates of false positives, lack of reproducibility and limited data transferability from one platform to the next. Given these limitations, a growing trend in both NMR and MS-based metabolomics is towards targeted profiling or “quantitative” metabolomics, wherein compounds are identified and quantified via spectral fitting prior to any statistical analysis. Despite the obvious advantages of this method, targeted profiling is hindered by the time required to perform manual or computer-assisted spectral fitting. In an effort to increase data analysis throughput for NMR-based metabolomics, we have developed an automatic method for identifying and quantifying metabolites in one-dimensional (1D) proton NMR spectra. This new algorithm is capable of using carefully constructed reference spectra and optimizing thousands of variables to reconstruct experimental NMR spectra of biofluids using rules and concepts derived from physical chemistry and NMR theory. The automated profiling program has been tested against spectra of synthetic mixtures as well as biological spectra of urine, serum and cerebral spinal fluid (CSF). Our results indicate that the algorithm can correctly identify compounds with high fidelity in each biofluid sample (except for urine). Furthermore, the metabolite concentrations exhibit a very high correlation with both simulated and manually-detected values.

Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra

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Mercier, Pascal; Lewis, Michael J.; Chang, David, E-mail: dchang@chenomx.com [Chenomx Inc (Canada); Baker, David [Pfizer Inc (United States); Wishart, David S. [University of Alberta, Department of Computing Science and Biological Sciences (Canada)

2011-04-15

Nuclear magnetic resonance (NMR) and Mass Spectroscopy (MS) are the two most common spectroscopic analytical techniques employed in metabolomics. The large spectral datasets generated by NMR and MS are often analyzed using data reduction techniques like Principal Component Analysis (PCA). Although rapid, these methods are susceptible to solvent and matrix effects, high rates of false positives, lack of reproducibility and limited data transferability from one platform to the next. Given these limitations, a growing trend in both NMR and MS-based metabolomics is towards targeted profiling or 'quantitative' metabolomics, wherein compounds are identified and quantified via spectral fitting prior to any statistical analysis. Despite the obvious advantages of this method, targeted profiling is hindered by the time required to perform manual or computer-assisted spectral fitting. In an effort to increase data analysis throughput for NMR-based metabolomics, we have developed an automatic method for identifying and quantifying metabolites in one-dimensional (1D) proton NMR spectra. This new algorithm is capable of using carefully constructed reference spectra and optimizing thousands of variables to reconstruct experimental NMR spectra of biofluids using rules and concepts derived from physical chemistry and NMR theory. The automated profiling program has been tested against spectra of synthetic mixtures as well as biological spectra of urine, serum and cerebral spinal fluid (CSF). Our results indicate that the algorithm can correctly identify compounds with high fidelity in each biofluid sample (except for urine). Furthermore, the metabolite concentrations exhibit a very high correlation with both simulated and manually-detected values.

Serum metabolomic profiling in acute alcoholic hepatitis identifies multiple dysregulated pathways.

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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

Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders.

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Luan, Hemi; Wang, Xian; Cai, Zongwei

2017-11-12

Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the

Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile.

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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.

Metabolomic approach to human brain spectroscopy identifies associations between clinical features and the frontal lobe metabolome in multiple sclerosis

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Vingara, Lisa K.; Yu, Hui Jing; Wagshul, Mark E.; Serafin, Dana; Christodoulou, Christopher; Pelczer, István; Krupp, Lauren B.; Maletić-Savatić, Mirjana

2013-01-01

Proton magnetic resonance spectroscopy (1H-MRS) is capable of noninvasively detecting metabolic changes that occur in the brain tissue in vivo. Its clinical utility has been limited so far, however, by analytic methods that focus on independently evaluated metabolites and require prior knowledge about which metabolites to examine. Here, we applied advanced computational methodologies from the field of metabolomics, specifically partial least squares discriminant analysis and orthogonal partial least squares, to in vivo 1H-MRS from frontal lobe white matter of 27 patients with relapsing–remitting multiple sclerosis (RRMS) and 14 healthy controls. We chose RRMS, a chronic demyelinating disorder of the central nervous system, because its complex pathology and variable disease course make the need for reliable biomarkers of disease progression more pressing. We show that in vivo MRS data, when analyzed by multivariate statistical methods, can provide reliable, distinct profiles of MRS-detectable metabolites in different patient populations. Specifically, we find that brain tissue in RRMS patients deviates significantly in its metabolic profile from that of healthy controls, even though it appears normal by standard MRI techniques. We also identify, using statistical means, the metabolic signatures of certain clinical features common in RRMS, such as disability score, cognitive impairments, and response to stress. This approach to human in vivo MRS data should promote understanding of the specific metabolic changes accompanying disease pathogenesis, and could provide biomarkers of disease progression that would be useful in clinical trials. PMID:23751863

Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

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Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

2014-07-01

Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

Informatics for Metabolomics.

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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.

Metabolomic profiling in blood from umbilical cords of low birth weight newborns

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Ivorra Carmen

2012-07-01

Full Text Available Abstract Background Low birth weight has been linked to an increased risk to develop obesity, type 2 diabetes, and hypertension in adult life, although the mechanisms underlying the association are not well understood. The objective was to determine whether the metabolomic profile of plasma from umbilical cord differs between low and normal birth weight newborns. Methods Fifty healthy pregnant women and their infants were selected. The eligibility criteria were being born at term and having a normal pregnancy. Pairs were grouped according to their birth weight: low birth weight (LBW, birth weight th percentile, n = 20 and control (control, birth weight between the 75th-90th percentiles, n = 30. Nuclear Magnetic Resonance (NMR was used to generate metabolic fingerprints of umbilical cord plasma samples. Simultaneously, the metabolomic profiles of the mothers were analysed. The resulting data were subjected to chemometric, principal component and partial least squares discriminant analyses. Results Umbilical cord plasma from LBW and control newborns displayed a clearly differentiated metabolic profile. Seven metabolites were identified that discriminate the LBW from the control group. LBW newborns had lower levels of choline, proline, glutamine, alanine and glucose than did the control newborns, while plasma levels of phenylalanine and citrulline were higher in LBW newborns (p Conclusions Low birth weight newborns display a differential metabolomic profile than those of normal birth weight, a finding not present in the mothers. The meaning and the potential utility of the findings as biomarkers of risk need to be addressed in future studies.

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

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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.

Metabolomic profiles as reliable biomarkers of dietary composition123

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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

Development of high-performance chemical isotope labeling LC-MS for profiling the human fecal metabolome.

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Xu, Wei; Chen, Deying; Wang, Nan; Zhang, Ting; Zhou, Ruokun; Huan, Tao; Lu, Yingfeng; Su, Xiaoling; Xie, Qing; Li, Liang; Li, Lanjuan

2015-01-20

Human fecal samples contain endogenous human metabolites, gut microbiota metabolites, and other compounds. Profiling the fecal metabolome can produce metabolic information that may be used not only for disease biomarker discovery, but also for providing an insight about the relationship of the gut microbiome and human health. In this work, we report a chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS) method for comprehensive and quantitative analysis of the amine- and phenol-containing metabolites in fecal samples. Differential (13)C2/(12)C2-dansyl labeling of the amines and phenols was used to improve LC separation efficiency and MS detection sensitivity. Water, methanol, and acetonitrile were examined as an extraction solvent, and a sequential water-acetonitrile extraction method was found to be optimal. A step-gradient LC-UV setup and a fast LC-MS method were evaluated for measuring the total concentration of dansyl labeled metabolites that could be used for normalizing the sample amounts of individual samples for quantitative metabolomics. Knowing the total concentration was also useful for optimizing the sample injection amount into LC-MS to maximize the number of metabolites detectable while avoiding sample overloading. For the first time, dansylation isotope labeling LC-MS was performed in a simple time-of-flight mass spectrometer, instead of high-end equipment, demonstrating the feasibility of using a low-cost instrument for chemical isotope labeling metabolomics. The developed method was applied for profiling the amine/phenol submetabolome of fecal samples collected from three families. An average of 1785 peak pairs or putative metabolites were found from a 30 min LC-MS run. From 243 LC-MS runs of all the fecal samples, a total of 6200 peak pairs were detected. Among them, 67 could be positively identified based on the mass and retention time match to a dansyl standard library, while 581 and 3197 peak pairs could be putatively

Metabolite Profiling in the Pursuit of Biomarkers for IVF Outcome: The Case for Metabolomics Studies

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C. McRae

2013-01-01

Full Text Available Background. This paper presents the literature on biomarkers of in vitro fertilisation (IVF outcome, demonstrating the progression of these studies towards metabolite profiling, specifically metabolomics. The need for more, and improved, metabolomics studies in the field of assisted conception is discussed. Methods. Searches were performed on ISI Web of Knowledge SM for literature associated with biomarkers of oocyte and embryo quality, and biomarkers of IVF outcome in embryo culture medium, follicular fluid (FF, and blood plasma in female mammals. Results. Metabolomics in the field of female reproduction is still in its infancy. Metabolomics investigations of embryo culture medium for embryo selection have been the most common, but only within the last five years. Only in 2012 has the first metabolomics investigation of FF for biomarkers of oocyte quality been reported. The only metabolomics studies of human blood plasma in this context have been aimed at identifying women with polycystic ovary syndrome (PCOS. Conclusions. Metabolomics is becoming more established in the field of assisted conception, but the studies performed so far have been preliminary and not all potential applications have yet been explored. With further improved metabolomics studies, the possibility of identifying a method for predicting IVF outcome may become a reality.

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

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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.

Metabolomic profiling reveals a role for CPT1c in neuronal oxidative metabolism

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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.

Alterations in urine, serum and brain metabolomic profiles exhibit sexual dimorphism during malaria disease progression

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Sharma Shobhona

2010-04-01

Full Text Available Abstract Background Metabolic changes in the host in response to Plasmodium infection play a crucial role in the pathogenesis of malaria. Alterations in metabolism of male and female mice infected with Plasmodium berghei ANKA are reported here. Methods 1H NMR spectra of urine, sera and brain extracts of these mice were analysed over disease progression using Principle Component Analysis and Orthogonal Partial Least Square Discriminant Analysis. Results Analyses of overall changes in urinary profiles during disease progression demonstrate that females show a significant early post-infection shift in metabolism as compared to males. In contrast, serum profiles of female mice remain unaltered in the early infection stages; whereas that of the male mice changed. Brain metabolite profiles do not show global changes in the early stages of infection in either sex. By the late stages urine, serum and brain profiles of both sexes are severely affected. Analyses of individual metabolites show significant increase in lactate, alanine and lysine, kynurenic acid and quinolinic acid in sera of both males and females at this stage. Early changes in female urine are marked by an increase of ureidopropionate, lowering of carnitine and transient enhancement of asparagine and dimethylglycine. Several metabolites when analysed individually in sera and brain reveal significant changes in their levels in the early phase of infection mainly in female mice. Asparagine and dimethylglycine levels decrease and quinolinic acid increases early in sera of infected females. In brain extracts of females, an early rise in levels is also observed for lactate, alanine and glycerol, kynurenic acid, ureidopropionate and 2-hydroxy-2-methylbutyrate. Conclusions These results suggest that P. berghei infection leads to impairment of glycolysis, lipid metabolism, metabolism of tryptophan and degradation of uracil. Characterization of early changes along these pathways may be crucial for

Metabolomics by Gas Chromatography-Mass Spectrometry: the combination of targeted and untargeted profiling

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Fiehn, Oliver

2016-01-01

Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small molecular metabolites (metabolomics easily allows integrating targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated, standardized standard operating procedures, GC-MS can identify and semi-quantify over 200 compounds per study in human body fluids (e.g., plasma, urine or stool) samples. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to liquid chromatography-MS untargeted profiling (LC-MS). Hence, GC-MS is a mature technology that not only uses classic detectors (‘quadrupole’) but also target mass spectrometers (‘triple quadrupole’) and accurate mass instruments (‘quadrupole-time of flight’). This unit covers the following aspects of GC-MS-based metabolomics: (i) sample preparation from mammalian samples, (ii) acquisition of data, (iii) quality control, and (iv) data processing. PMID:27038389

NMR and MS Methods for Metabolomics.

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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.

Novel biomarker identification using metabolomic profiling to differentiate radiation necrosis and recurrent tumor following Gamma Knife radiosurgery.

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Lu, Alex Y; Turban, Jack L; Damisah, Eyiyemisi C; Li, Jie; Alomari, Ahmed K; Eid, Tore; Vortmeyer, Alexander O; Chiang, Veronica L

2017-08-01

OBJECTIVE Following an initial response of brain metastases to Gamma Knife radiosurgery, regrowth of the enhancing lesion as detected on MRI may represent either radiation necrosis (a treatment-related inflammatory change) or recurrent tumor. Differentiation of radiation necrosis from tumor is vital for management decision making but remains difficult by imaging alone. In this study, gas chromatography with time-of-flight mass spectrometry (GC-TOF) was used to identify differential metabolite profiles of the 2 tissue types obtained by surgical biopsy to find potential targets for noninvasive imaging. METHODS Specimens of pure radiation necrosis and pure tumor obtained from patient brain biopsies were flash-frozen and validated histologically. These formalin-free tissue samples were then analyzed using GC-TOF. The metabolite profiles of radiation necrosis and tumor samples were compared using multivariate and univariate statistical analysis. Statistical significance was defined as p ≤ 0.05. RESULTS For the metabolic profiling, GC-TOF was performed on 7 samples of radiation necrosis and 7 samples of tumor. Of the 141 metabolites identified, 17 (12.1%) were found to be statistically significantly different between comparison groups. Of these metabolites, 6 were increased in tumor, and 11 were increased in radiation necrosis. An unsupervised hierarchical clustering analysis found that tumor had elevated levels of metabolites associated with energy metabolism, whereas radiation necrosis had elevated levels of metabolites that were fatty acids and antioxidants/cofactors. CONCLUSIONS To the authors' knowledge, this is the first tissue-based metabolomics study of radiation necrosis and tumor. Radiation necrosis and recurrent tumor following Gamma Knife radiosurgery for brain metastases have unique metabolite profiles that may be targeted in the future to develop noninvasive metabolic imaging techniques.

Brain nonoxidative carbohydrate consumption is not explained by export of an unknown carbon source: evaluation of the arterial and jugular venous metabolome

DEFF Research Database (Denmark)

Rasmussen, Peter; Nyberg, Nils; Jaroszewski, Jerzy W.

2010-01-01

uptake is unknown, but it may be that brain metabolism is balanced by a yet-unidentified substance(s). This study used a nuclear magnetic resonance-based metabolomics approach to plasma samples obtained from the brachial artery and the right internal jugular vein in 16 healthy young males to identify...... be accounted for by changes in the NMR-derived plasma metabolome across the brain....

Cerebrospinal Fluid Metabolomics After Natural Product Treatment in an Experimental Model of Cerebral Ischemia.

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Huan, Tao; Xian, Jia Wen; Leung, Wing Nang; Li, Liang; Chan, Chun Wai

2016-11-01

Cerebrospinal fluid (CSF) is an important biofluid for diagnosis of and research on neurological diseases. However, in-depth metabolomic profiling of CSF remains an analytical challenge due to the small volume of samples, particularly in small animal models. In this work, we report the application of a high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) workflow for CSF metabolomics in Gastrodia elata and Uncaria rhynchophylla water extract (GUW)-treated experimental cerebral ischemia model of rat. The GUW is a commonly used Traditional Chinese Medicine (TCM) for hypertension and brain disease. This study investigated the amine- and phenol-containing biomarkers in the CSF metabolome. After GUW treatment for 7 days, the neurological deficit score was significantly improved with infarct volume reduction, while the integrity of brain histological structure was preserved. Over 1957 metabolites were quantified in CSF by dansylation LC-MS. The analysis of this comprehensive list of metabolites suggests that metabolites associated with oxidative stress, inflammatory response, and excitotoxicity change during GUW-induced alleviation of ischemic injury. This work is significant in that (1) it shows CIL LC-MS can be used for in-depth profiling of the CSF metabolome in experimental ischemic stroke and (2) identifies several potential molecular targets (that might mediate the central nervous system) and associate with pharmacodynamic effects of some frequently used TCMs.

NMR-based metabolomic profiling of overweight adolescents

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Zheng, Hong; Yde, Christian C; Arnberg, Karina

2014-01-01

The plasma and urine metabolome of 192 overweight 12-15-year-old adolescents (BMI of 25.4 ± 2.3 kg/m(2)) were examined in order to elucidate gender, pubertal development measured as Tanner stage, physical activity measured as number of steps taken daily, and intra-/interindividual differences...... and the metabolome could be identified. The present study for the first time provides comprehensive information about associations between the metabolome and gender, pubertal development, and physical activity in overweight adolescents, which is an important subject group to approach in the prevention of obesity...... affecting the metabolome detected by proton NMR spectroscopy. Higher urinary excretion of citrate, creatinine, hippurate, and phenylacetylglutamine and higher plasma level of phosphatidylcholine and unsaturated lipid were found for girls compared with boys. The results suggest that gender differences...

Untargeted mass spectrometry-based metabolomic profiling of pleural effusions: fatty acids as novel cancer biomarkers for malignant pleural effusions.

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Lam, Ching-Wan; Law, Chun-Yiu

2014-09-05

Untargeted mass spectrometry-based metabolomic profiling is a powerful analytical method used for broad-spectrum identification and quantification of metabolites in biofluids in human health and disease states. In this study, we exploit metabolomic profiling for cancer biomarker discovery for diagnosis of malignant pleural effusions. We envisage the result will be clinically useful since currently there are no cancer biomarkers that are accurate enough for the diagnosis of malignant pleural effusions. Metabolomes of 32 malignant pleural effusions from lung cancer patients and 18 benign effusions from patients with pulmonary tuberculosis were analyzed using reversed-phase liquid chromatography tandem mass spectrometry (LC-MS/MS) using AB SCIEX TripleTOF 5600. MS spectra were analyzed using XCMS, PeakView, and LipidView. Metabolome-Wide Association Study (MWAS) was performed by Receiver Operating Characteristic Curve Explorer and Tester (ROCCET). Insignificant markers were filtered out using a metabolome-wide significance level (MWSL) with p-value pleural effusions. Using a ratio of FFA 18:1-to-ceramide (d18:1/16:0), the area-under-ROC was further increased to 0.99 (95% CI = 0.91-1.00) with sensitivity 93.8% and specificity 100.0%. Using untargeted metabolomic profiling, the diagnostic cancer biomarker with the largest area-under-ROC can be determined objectively. This lipogenic phenotype could be explained by overexpression of fatty acid synthase (FASN) in cancer cells. The diagnostic performance of FFA 18:1-to-ceramide (d18:1/16:0) ratio supports its use for diagnosis of malignant pleural effusions.

Vitamin D prenatal programming of childhood metabolomics profiles at age 3 y.

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Blighe, Kevin; Chawes, Bo L; Kelly, Rachel S; Mirzakhani, Hooman; McGeachie, Michael; Litonjua, Augusto A; Weiss, Scott T; Lasky-Su, Jessica A

2017-10-01

Background: Vitamin D deficiency is implicated in a range of common complex diseases that may be prevented by gestational vitamin D repletion. Understanding the metabolic mechanisms related to in utero vitamin D exposure may therefore shed light on complex disease susceptibility. Objective: The goal was to analyze the programming role of in utero vitamin D exposure on children's metabolomics profiles. Design: First, unsupervised clustering was done with plasma metabolomics profiles from a case-control subset of 245 children aged 3 y with and without asthma from the Vitamin D Antenatal Asthma Reduction Trial (VDAART), in which pregnant women were randomly assigned to vitamin D supplementation or placebo. Thereafter, we analyzed the influence of maternal pre- and postsupplement vitamin D concentrations on cluster membership. Finally, we used the metabolites driving the clustering of children to identify the dominant metabolic pathways that were influential in each cluster. Results: We identified 3 clusters of children characterized by 1 ) high concentrations of fatty acids and amines and low maternal postsupplement vitamin D (mean ± SD; 27.5 ± 11.0 ng/mL), 2 ) high concentrations of amines, moderate concentrations of fatty acids, and normal maternal postsupplement vitamin D (34.0 ± 14.1 ng/mL), and 3 ) low concentrations of fatty acids, amines, and normal maternal postsupplement vitamin D (35.2 ± 15.9 ng/mL). Adjusting for sample storage time, maternal age and education, and both child asthma and vitamin D concentration at age 3 y did not modify the association between maternal postsupplement vitamin D and cluster membership ( P = 0.0014). Maternal presupplement vitamin D did not influence cluster membership, whereas the combination of pre- and postsupplement concentrations did ( P = 0.03). Conclusions: Young children can be clustered into distinct biologically meaningful groups by their metabolomics profiles. The clusters differed in concentrations of

Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

NARCIS (Netherlands)

Graham, S.F.; Ruiz Aracama, A.; Lommen, A.; Cannizzo, F.T.; Biolatti, B.; Elliott, C.T.; Mooney, M.H.

2012-01-01

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with

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

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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.

Liquid–liquid extraction combined with differential isotope dimethylaminophenacyl labeling for improved metabolomic profiling of organic acids

International Nuclear Information System (INIS)

Peng, Jun; Li, Liang

2013-01-01

Graphical abstract: -- Highlights: •An improved method for profiling the carboxylic acid sub-metabolome is reported. •Liquid–liquid extraction was used for separating the organic acids from the amines. • 12 C/ 13 C-p-dimethylaminophenacyl (DmPA) labeling of the organic acids was carried out on the extract. •Detection interference by amines and labeling efficiency reduction by water were reduced. •About 2500 12 C/ 13 C-peak pairs or putative metabolites could be detected from 20 μL of human urine. -- Abstract: A large fraction of the known human metabolome belong to organic acids. However, comprehensive profiling of the organic acid sub-metabolome is a major analytical challenge. In this work, we report an improved method for detecting organic acid metabolites. This method is based on the use of liquid–liquid extraction (LLE) to selectively extract the organic acids, followed by using differential isotope p-dimethylaminophenacyl (DmPA) labeling of the acid metabolites. The 12 C-/ 13 C-labeled samples are analyzed by liquid chromatography Fourier-transform ion cyclotron resonance mass spectrometry (LC–FTICR–MS). It is shown that this LLE DmPA labeling method offers superior performance over the method of direct DmPA labeling of biofluids such as human urine. LLE of organic acids reduces the interference of amine-containing metabolites that may also react with DmPA. It can also remove water in a biofluid that can reduce the labeling efficiency. Using human urine as an example, it is demonstrated that about 2500 peak pairs or putative metabolites could be detected in a 30-min gradient LC–MS run, which is about 3 times more than that detected in a sample prepared using direct DmPA labeling. About 95% of the 1000 or so matched metabolites to the Human Metabolome Database (HMDB) are organic acids. It is further shown that this method can be used to handle as small as 10 μL of urine. We believe that this method opens the possibility of generating a

Liquid–liquid extraction combined with differential isotope dimethylaminophenacyl labeling for improved metabolomic profiling of organic acids

Energy Technology Data Exchange (ETDEWEB)

Peng, Jun; Li, Liang, E-mail: Liang.Li@ualberta.ca

2013-11-25

Graphical abstract: -- Highlights: •An improved method for profiling the carboxylic acid sub-metabolome is reported. •Liquid–liquid extraction was used for separating the organic acids from the amines. •{sup 12}C/{sup 13}C-p-dimethylaminophenacyl (DmPA) labeling of the organic acids was carried out on the extract. •Detection interference by amines and labeling efficiency reduction by water were reduced. •About 2500 {sup 12}C/{sup 13}C-peak pairs or putative metabolites could be detected from 20 μL of human urine. -- Abstract: A large fraction of the known human metabolome belong to organic acids. However, comprehensive profiling of the organic acid sub-metabolome is a major analytical challenge. In this work, we report an improved method for detecting organic acid metabolites. This method is based on the use of liquid–liquid extraction (LLE) to selectively extract the organic acids, followed by using differential isotope p-dimethylaminophenacyl (DmPA) labeling of the acid metabolites. The {sup 12}C-/{sup 13}C-labeled samples are analyzed by liquid chromatography Fourier-transform ion cyclotron resonance mass spectrometry (LC–FTICR–MS). It is shown that this LLE DmPA labeling method offers superior performance over the method of direct DmPA labeling of biofluids such as human urine. LLE of organic acids reduces the interference of amine-containing metabolites that may also react with DmPA. It can also remove water in a biofluid that can reduce the labeling efficiency. Using human urine as an example, it is demonstrated that about 2500 peak pairs or putative metabolites could be detected in a 30-min gradient LC–MS run, which is about 3 times more than that detected in a sample prepared using direct DmPA labeling. About 95% of the 1000 or so matched metabolites to the Human Metabolome Database (HMDB) are organic acids. It is further shown that this method can be used to handle as small as 10 μL of urine. We believe that this method opens the

Cardioprotective and Metabolomic Profiling of Selected Medicinal Plants against Oxidative Stress

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Nadia Afsheen

2018-01-01

Full Text Available In this research work, the antioxidant and metabolomic profiling of seven selected medicinally important herbs including Rauvolfia serpentina, Terminalia arjuna, Coriandrum sativum, Elettaria cardamom, Piper nigrum, Allium sativum, and Crataegus oxyacantha was performed. The in vivo cardioprotective potential of these medicinal plants was evaluated against surgically induced oxidative stress through left anterior descending coronary artery ligation (LADCA in dogs. The antioxidant profiling of these plants was done through DPPH and DNA protection assay. The C. oxyacantha and T. arjuna showed maximum antioxidant potential, while the E. cardamom showed poor antioxidative strength even at its high concentration. Different concentrations of extracts of the said plants exhibited the protection of plasmid DNA against H2O2 damage as compared to the plasmid DNA merely treated with H2O2. The metabolomic profiling through LC-MS analysis of these antioxidants revealed the presence of active secondary metabolites responsible for their antioxidant potential. During in vivo analysis, blood samples of all treatment groups were drawn at different time intervals to analyze the cardiac and hemodynamic parameters. The results depicted that the group pretreated with HC4 significantly sustained the level of CK-MB, SGOT, and LDH as well as hemodynamic parameters near to normal. The histopathological examination also confirmed the cardioprotective potential of HC4. Thus, the HC4 being safe and inexpensive cardioprotective herbal combination could be considered as an alternate of synthetic drugs.

Cardioprotective and Metabolomic Profiling of Selected Medicinal Plants against Oxidative Stress

Science.gov (United States)

Afsheen, Nadia; Jahan, Nazish; Ijaz, Misbah; Manzoor, Asad; Khan, Khalid Mahmood; Hina, Saman

2018-01-01

In this research work, the antioxidant and metabolomic profiling of seven selected medicinally important herbs including Rauvolfia serpentina, Terminalia arjuna, Coriandrum sativum, Elettaria cardamom, Piper nigrum, Allium sativum, and Crataegus oxyacantha was performed. The in vivo cardioprotective potential of these medicinal plants was evaluated against surgically induced oxidative stress through left anterior descending coronary artery ligation (LADCA) in dogs. The antioxidant profiling of these plants was done through DPPH and DNA protection assay. The C. oxyacantha and T. arjuna showed maximum antioxidant potential, while the E. cardamom showed poor antioxidative strength even at its high concentration. Different concentrations of extracts of the said plants exhibited the protection of plasmid DNA against H2O2 damage as compared to the plasmid DNA merely treated with H2O2. The metabolomic profiling through LC-MS analysis of these antioxidants revealed the presence of active secondary metabolites responsible for their antioxidant potential. During in vivo analysis, blood samples of all treatment groups were drawn at different time intervals to analyze the cardiac and hemodynamic parameters. The results depicted that the group pretreated with HC4 significantly sustained the level of CK-MB, SGOT, and LDH as well as hemodynamic parameters near to normal. The histopathological examination also confirmed the cardioprotective potential of HC4. Thus, the HC4 being safe and inexpensive cardioprotective herbal combination could be considered as an alternate of synthetic drugs. PMID:29576858

Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness

DEFF Research Database (Denmark)

Bozek, Katarzyna; Wei, Yuning; Yan, Zheng

2014-01-01

Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees,...

Specific metabolomics adaptations define a differential regional vulnerability in the adult human cerebral cortex

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Rosanna Cabré

2016-12-01

Full Text Available Brain neurons offer diverse responses to stresses and detrimental factors during development and aging, and as a result of both neurodegenerative and neuropsychiatric disorders. This multiplicity of responses can be ascribed to the great diversity among neuronal populations. Here we have determined the metabolomic profile of three healthy adult human brain regions—entorhinal cortex, hippocampus, and frontal cortex—using mass spectrometry-based technologies. Our results show the existence of a lessened energy demand, mitochondrial stress, and lower one-carbon metabolism (particularly restricted to the methionine cycle specifically in frontal cortex. These findings, along with the better antioxidant capacity and lower mTOR signaling also seen in frontal cortex, suggest that this brain region is especially resistant to stress compared to the entorhinal cortex and hippocampus, which are more vulnerable regions. Globally, our results show the presence of specific metabolomics adaptations in three mature, healthy human brain regions, confirming the existence of cross-regional differences in cell vulnerability in the human cerebral cortex.

Metabolomics: A Primer.

Science.gov (United States)

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.

Maternal-fetal hepatic and placental metabolome profiles are associated with reduced fetal growth in a rat model of maternal obesity

DEFF Research Database (Denmark)

Mumme, Karen; Gray, Clint; Reynolds, Clare M.

2016-01-01

: Metabolomic profiling was used to reveal altered maternal and fetal metabolic pathways in a model of diet induced obesity during pregnancy, leading to reduced fetal growth. Methods: We examined the metabolome of maternal and fetal livers, and placenta following a high fat and salt intake. Sprague–Dawley rats...

Metabolomic Profiling in Individuals with a Failing Kidney Allograft.

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Roberto Bassi

Full Text Available Alteration of certain metabolites may play a role in the pathophysiology of renal allograft disease.To explore metabolomic abnormalities in individuals with a failing kidney allograft, we analyzed by liquid chromatography-mass spectrometry (LC-MS/MS; for ex vivo profiling of serum and urine and two dimensional correlated spectroscopy (2D COSY; for in vivo study of the kidney graft 40 subjects with varying degrees of chronic allograft dysfunction stratified by tertiles of glomerular filtration rate (GFR; T1, T2, T3. Ten healthy non-allograft individuals were chosen as controls.LC-MS/MS analysis revealed a dose-response association between GFR and serum concentration of tryptophan, glutamine, dimethylarginine isomers (asymmetric [A]DMA and symmetric [S]DMA and short-chain acylcarnitines (C4 and C12, (test for trend: T1-T3 = p<0.05; p = 0.01; p<0.001; p = 0.01; p = 0.01; p<0.05, respectively. The same association was found between GFR and urinary levels of histidine, DOPA, dopamine, carnosine, SDMA and ADMA (test for trend: T1-T3 = p<0.05; p<0.01; p = 0.001; p<0.05; p = 0.001; p<0.001; p<0.01, respectively. In vivo 2D COSY of the kidney allograft revealed significant reduction in the parenchymal content of choline, creatine, taurine and threonine (all: p<0.05 in individuals with lower GFR levels.We report an association between renal function and altered metabolomic profile in renal transplant individuals with different degrees of kidney graft function.

Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness.

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Katarzyna Bozek

2014-05-01

Full Text Available Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys.

Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

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Takao Itoi

2017-04-01

Full Text Available This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC from malignant diseases, such as biliary tract cancer (BTC, intraductal papillary mucinous carcinoma (IPMC, and various benign pancreaticobiliary diseases. Capillary electrophoresismass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41 of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140. Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test. Four multiple logistic regression models (MLR were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC of 0.970 (95% confidential interval (CI, 0.946–0.994, p < 0.0001. Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020 with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA, carbohydrate antigen 19-9 (CA19-9, pancreatic cancer-associated antigen (DUPAN2 and s-pancreas-1 antigen (SPAN1. Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.

Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.

Science.gov (United States)

Lee, Sang-Hyun; Kim, Sooah; Kwon, Min-A; Jung, Young Hoon; Shin, Yong-An; Kim, Kyoung Heon

2014-12-01

Well-established metabolome sample preparation is a prerequisite for reliable metabolomic data. For metabolome sampling of a Gram-positive strict anaerobe, Clostridium acetobutylicum, fast filtration and metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v) at -20°C under anaerobic conditions has been commonly used. This anaerobic metabolite processing method is laborious and time-consuming since it is conducted in an anaerobic chamber. Also, there have not been any systematic method evaluation and development of metabolome sample preparation for strict anaerobes and Gram-positive bacteria. In this study, metabolome sampling and extraction methods were rigorously evaluated and optimized for C. acetobutylicum by using gas chromatography/time-of-flight mass spectrometry-based metabolomics, in which a total of 116 metabolites were identified. When comparing the atmospheric (i.e., in air) and anaerobic (i.e., in an anaerobic chamber) processing of metabolome sample preparation, there was no significant difference in the quality and quantity of the metabolomic data. For metabolite extraction, pure methanol at -20°C was a better solvent than acetonitrile/methanol/water (2:2:1, v/v/v) at -20°C that is frequently used for C. acetobutylicum, and metabolite profiles were significantly different depending on extraction solvents. This is the first evaluation of metabolite sample preparation under aerobic processing conditions for an anaerobe. This method could be applied conveniently, efficiently, and reliably to metabolome analysis for strict anaerobes in air. © 2014 Wiley Periodicals, Inc.

Metabolomic profiling of heat stress: hardening and recovery of homeostasis in Drosophila

DEFF Research Database (Denmark)

Malmendal, Anders; Overgaard, Johannes; Bundy, Jacob G.

2006-01-01

Frequent exposure of terrestrial insects to temperature variation has led to the evolution of protective biochemical and physiological mechanisms, such as the heat shock response, which markedly increases the tolerance to heat stress. Insight into such mechanisms has, so far, mainly relied...... on selective studies of specific compounds or characteristics or studies at the genomic or proteomic levels. In the present study, we have used untargeted NMR metabolomic profiling to examine the biological response to heat stress in Drosophila melanogaster. The metabolite profile was analyzed during recovery...... after exposure to different thermal stress treatments and compared with untreated controls. Both moderate and severe heat stress gave clear effects on the metabolite profiles. The profiles clearly demonstrated that hardening by moderate heat stress led to a faster reestablishment of metabolite...

The Uses and Future Prospects of Metabolomics and Targeted Metabolite Profiling in Cell Factory Development

DEFF Research Database (Denmark)

Harrison, Scott James; Herrgard, Markus

2013-01-01

, these broader measurements of the cellular metabolic state are now becoming part of the toolbox used to characterize cell factories. In this review we briefly summarize the benefits and challenges of global metabolomics and targeted metabolite profiling methods and discuss the application of these methods...

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

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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.

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

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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.

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

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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.

Proteome and metabolome profiling of cytokinin action in Arabidopsis identifying both distinct and similar responses to cytokinin down- and up-regulation.

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Černý, Martin; Kuklová, Alena; Hoehenwarter, Wolfgang; Fragner, Lena; Novák, Ondrej; Rotková, Gabriela; Jedelsky, Petr L; Žáková, Katerina; Šmehilová, Mária; Strnad, Miroslav; Weckwerth, Wolfram; Brzobohaty, Bretislav

2013-11-01

In plants, numerous developmental processes are controlled by cytokinin (CK) levels and their ratios to levels of other hormones. While molecular mechanisms underlying the regulatory roles of CKs have been intensely researched, proteomic and metabolomic responses to CK deficiency are unknown. Transgenic Arabidopsis seedlings carrying inducible barley cytokinin oxidase/dehydrogenase (CaMV35S>GR>HvCKX2) and agrobacterial isopentenyl transferase (CaMV35S>GR>ipt) constructs were profiled to elucidate proteome- and metabolome-wide responses to down- and up-regulation of CK levels, respectively. Proteome profiling identified >1100 proteins, 155 of which responded to HvCKX2 and/or ipt activation, mostly involved in growth, development, and/or hormone and light signalling. The metabolome profiling covered 79 metabolites, 33 of which responded to HvCKX2 and/or ipt activation, mostly amino acids, carbohydrates, and organic acids. Comparison of the data sets obtained from activated CaMV35S>GR>HvCKX2 and CaMV35S>GR>ipt plants revealed unexpectedly extensive overlaps. Integration of the proteomic and metabolomic data sets revealed: (i) novel components of molecular circuits involved in CK action (e.g. ribosomal proteins); (ii) previously unrecognized links to redox regulation and stress hormone signalling networks; and (iii) CK content markers. The striking overlaps in profiles observed in CK-deficient and CK-overproducing seedlings might explain surprising previously reported similarities between plants with down- and up-regulated CK levels.

Specialized Information Processing Deficits and Distinct Metabolomic Profiles Following TM-Domain Disruption of Nrg1.

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O'Tuathaigh, Colm M P; Mathur, Naina; O'Callaghan, Matthew J; MacIntyre, Lynsey; Harvey, Richard; Lai, Donna; Waddington, John L; Pickard, Benjamin S; Watson, David G; Moran, Paula M

2017-09-01

Although there is considerable genetic and pathologic evidence for an association between neuregulin 1 (NRG1) dysregulation and schizophrenia, the underlying molecular and cellular mechanisms remain unclear. Mutant mice containing disruption of the transmembrane (TM) domain of the NRG1 gene constitute a heuristic model for dysregulation of NRG1-ErbB4 signaling in schizophrenia. The present study focused on hitherto uncharacterized information processing phenotypes in this mutant line. Using a mass spectrometry-based metabolomics approach, we also quantified levels of unique metabolites in brain. Across 2 different sites and protocols, Nrg1 mutants demonstrated deficits in prepulse inhibition, a measure of sensorimotor gating, that is, disrupted in schizophrenia; these deficits were partially reversed by acute treatment with second, but not first-, generation antipsychotic drugs. However, Nrg1 mutants did not show a specific deficit in latent inhibition, a measure of selective attention that is also disrupted in schizophrenia. In contrast, in a "what-where-when" object recognition memory task, Nrg1 mutants displayed sex-specific (males only) disruption of "what-when" performance, indicative of impaired temporal aspects of episodic memory. Differential metabolomic profiling revealed that these behavioral phenotypes were accompanied, most prominently, by alterations in lipid metabolism pathways. This study is the first to associate these novel physiological mechanisms, previously independently identified as being abnormal in schizophrenia, with disruption of NRG1 function. These data suggest novel mechanisms by which compromised neuregulin function from birth might lead to schizophrenia-relevant behavioral changes in adulthood. © The Author 2017. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

The metabolomic profile of umbilical cord blood in neonatal hypoxic ischaemic encephalopathy.

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Brian H Walsh

Full Text Available Hypoxic ischaemic encephalopathy (HIE in newborns can cause significant long-term neurological disability. The insult is a complex injury characterised by energy failure and disruption of cellular homeostasis, leading to mitochondrial damage. The importance of individual metabolic pathways, and their interaction in the disease process is not fully understood. The aim of this study was to describe and quantify the metabolomic profile of umbilical cord blood samples in a carefully defined population of full-term infants with HIE.The injury severity was defined using both the modified Sarnat score and continuous multichannel electroencephalogram. Using these classification systems, our population was divided into those with confirmed HIE (n = 31, asphyxiated infants without encephalopathy (n = 40 and matched controls (n = 71. All had umbilical cord blood drawn and biobanked at -80 °C within 3 hours of delivery. A combined direct injection and LC-MS/MS assay (AbsolutIDQ p180 kit, Biocrates Life Sciences AG, Innsbruck, Austria was used for the metabolomic analyses of the samples. Targeted metabolomic analysis showed a significant alteration between study groups in 29 metabolites from 3 distinct classes (Amino Acids, Acylcarnitines, and Glycerophospholipids. 9 of these metabolites were only significantly altered between neonates with Hypoxic ischaemic encephalopathy and matched controls, while 14 were significantly altered in both study groups. Multivariate Discriminant Analysis models developed showed clear multifactorial metabolite associations with both asphyxia and HIE. A logistic regression model using 5 metabolites clearly delineates severity of asphyxia and classifies HIE infants with AUC = 0.92. These data describe wide-spread disruption to not only energy pathways, but also nitrogen and lipid metabolism in both asphyxia and HIE.This study shows that a multi-platform targeted approach to metabolomic analyses using accurately phenotyped and

Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells.

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García-Cañaveras, Juan Carlos; López, Silvia; Castell, José Vicente; Donato, M Teresa; Lahoz, Agustín

2016-02-01

MS-based metabolite profiling of adherent mammalian cells comprises several challenging steps such as metabolism quenching, cell detachment, cell disruption, metabolome extraction, and metabolite measurement. In LC-MS, the final metabolome coverage is strongly determined by the separation technique and the MS conditions used. Human liver-derived cell line HepG2 was chosen as adherent mammalian cell model to evaluate the performance of several commonly used procedures in both sample processing and LC-MS analysis. In a first phase, metabolite extraction and sample analysis were optimized in a combined manner. To this end, the extraction abilities of five different solvents (or combinations) were assessed by comparing the number and the levels of the metabolites comprised in each extract. Three different chromatographic methods were selected for metabolites separation. A HILIC-based method which was set to specifically separate polar metabolites and two RP-based methods focused on lipidome and wide-ranging metabolite detection, respectively. With regard to metabolite measurement, a Q-ToF instrument operating in both ESI (+) and ESI (-) was used for unbiased extract analysis. Once metabolite extraction and analysis conditions were set up, the influence of cell harvesting on metabolome coverage was also evaluated. Therefore, different protocols for cell detachment (trypsinization or scraping) and metabolism quenching were compared. This study confirmed the inconvenience of trypsinization as a harvesting technique, and the importance of using complementary extraction solvents to extend metabolome coverage, minimizing interferences and maximizing detection, thanks to the use of dedicated analytical conditions through the combination of HILIC and RP separations. The proposed workflow allowed the detection of over 300 identified metabolites from highly polar compounds to a wide range of lipids.

Profiling the Oxylipin and Endocannabinoid Metabolome by UPLC-ESI-MS/MS in Human Plasma to Monitor Postprandial Inflammation.

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Gouveia-Figueira, Sandra; Späth, Jana; Zivkovic, Angela M; Nording, Malin L

2015-01-01

Bioactive lipids, including oxylipins, endocannabinoids, and related compounds may function as specific biochemical markers of certain aspects of inflammation. However, the postprandial responsiveness of these compounds is largely unknown; therefore, changes in the circulating oxylipin and endocannabinoid metabolome in response to a challenge meal were investigated at six occasions in a subject who freely modified her usual diet. The dietary change, and especially the challenge meal itself, represented a modification of precursor fatty acid status, with expectedly subtle effects on bioactive lipid levels. To detect even the slightest alteration, highly sensitive ultra-performance liquid chromatography (UPLC) coupled to electrospray ionization (ESI) tandem mass spectrometry (MS/MS) methods for bioactive lipid profiling was employed. A previously validated UPLC-ESI-MS/MS method for profiling the endocannabinoid metabolome was used, while validation of an UPLC-ESI-MS/MS method for oxylipin analysis was performed with acceptable outcomes for a majority of the parameters according to the US Food and Drug Administration guidelines for linearity (0.9938 metabolome, caused by changes in diet and ii) responsiveness to a challenge meal for a subset of the oxylipin and endocannabinoid metabolome. To summarize, we have shown proof-of-concept of our UPLC-ESI-MS/MS bioactive lipid protocols for the purpose of monitoring subtle shifts, and thereby useful to address lipid-mediated postprandial inflammation.

Metabolomics reveals distinct neurochemical profiles associated with stress resilience

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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

Management of familial Mediterranean fever by colchicine does not normalize the altered profile of microbial long chain fatty acids in the human metabolome

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Zhanna eKtsoyan

2013-01-01

Full Text Available In our previous works we established that in an autoinflammatory condition, familial Mediterranean fever, the gut microbial diversity is specifically restructured, which also results in the altered profiles of microbial long chain fatty acids (LCFAs present in the systemic metabolome. The mainstream management of the disease is based on oral administration of colchicine to suppress clinical signs and extend remission periods and our aim was to determine whether this therapy normalizes the microbial LCFA profiles in the metabolome as well. Unexpectedly, the treatment does not normalize these profiles. Moreover, it results in the formation of new distinct microbial LCFA clusters, which are well separated from the corresponding values in healthy controls and FMF patients without the therapy. We hypothesize that the therapy alters the proinflammatory network specific for the disease, with the concomitant changes in gut microbiota and the corresponding microbial LCFAs in the metabolome.

NMR-based metabolomics approach to study the toxicity of lambda-cyhalothrin to goldfish (Carassius auratus)

Energy Technology Data Exchange (ETDEWEB)

Li, Minghui [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China); Wang, Junsong, E-mail: wang.junsong@gmail.com [Center for Molecular Metabolism, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, 200 Xiao Ling Wei Street, Nanjing 210094 (China); Lu, Zhaoguang; Wei, Dandan; Yang, Minghua [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China); Kong, Lingyi, E-mail: cpu_lykong@126.com [State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, 24 Tong Jia Xiang, Nanjing 210009 (China)

2014-01-15

Highlights: •A goldfish model was established to investigate the toxicity of lambda-cyhalothrin (LCT) exposure on multiple organs. •NMR based metabolomics approach were firstly used to provide a global view of the toxicity of LCT. •LCT induced neurotransmitters and osmoregulatory imbalances, oxidative stress, energy and amino acid metabolic disorders. •Glutamate–glutamine–GABA axis as a potential target for LCT toxicity was first found. -- Abstract: In this study, a {sup 1}H nuclear magnetic resonance (NMR) based metabolomics approach was applied to investigate the toxicity of lambda-cyhalothrin (LCT) in goldfish (Carassius auratus). LCT showed tissue-specific damage to gill, heart, liver and kidney tissues of goldfish. NMR profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis (OPLS-DA) and two-dimensional statistical total correlation spectroscopy (2D-STOCSY) was developed to discern metabolite changes occurring after one week LCT exposure in brain, heart and kidney tissues of goldfish. LCT exposure influenced levels of many metabolites (e.g., leucine, isoleucine and valine in brain and kidney; lactate in brain, heart and kidney; alanine in brain and kidney; choline in brain, heart and kidney; taurine in brain, heart and kidney; N-acetylaspartate in brain; myo-inositol in brain; phosphocreatine in brain and heart; 2-oxoglutarate in brain; cis-aconitate in brain, and etc.), and broke the balance of neurotransmitters and osmoregulators, evoked oxidative stress, disturbed metabolisms of energy and amino acids. The implication of glutamate–glutamine–gamma-aminobutyric axis in LCT induced toxicity was demonstrated for the first time. Our findings demonstrated the applicability and potential of metabolomics approach for the elucidation of toxicological effects of pesticides and the underlying mechanisms, and the discovery of biomarkers for pesticide pollution in aquatic environment.

NMR-based metabolomics approach to study the toxicity of lambda-cyhalothrin to goldfish (Carassius auratus)

International Nuclear Information System (INIS)

Li, Minghui; Wang, Junsong; Lu, Zhaoguang; Wei, Dandan; Yang, Minghua; Kong, Lingyi

2014-01-01

Highlights: •A goldfish model was established to investigate the toxicity of lambda-cyhalothrin (LCT) exposure on multiple organs. •NMR based metabolomics approach were firstly used to provide a global view of the toxicity of LCT. •LCT induced neurotransmitters and osmoregulatory imbalances, oxidative stress, energy and amino acid metabolic disorders. •Glutamate–glutamine–GABA axis as a potential target for LCT toxicity was first found. -- Abstract: In this study, a 1 H nuclear magnetic resonance (NMR) based metabolomics approach was applied to investigate the toxicity of lambda-cyhalothrin (LCT) in goldfish (Carassius auratus). LCT showed tissue-specific damage to gill, heart, liver and kidney tissues of goldfish. NMR profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis (OPLS-DA) and two-dimensional statistical total correlation spectroscopy (2D-STOCSY) was developed to discern metabolite changes occurring after one week LCT exposure in brain, heart and kidney tissues of goldfish. LCT exposure influenced levels of many metabolites (e.g., leucine, isoleucine and valine in brain and kidney; lactate in brain, heart and kidney; alanine in brain and kidney; choline in brain, heart and kidney; taurine in brain, heart and kidney; N-acetylaspartate in brain; myo-inositol in brain; phosphocreatine in brain and heart; 2-oxoglutarate in brain; cis-aconitate in brain, and etc.), and broke the balance of neurotransmitters and osmoregulators, evoked oxidative stress, disturbed metabolisms of energy and amino acids. The implication of glutamate–glutamine–gamma-aminobutyric axis in LCT induced toxicity was demonstrated for the first time. Our findings demonstrated the applicability and potential of metabolomics approach for the elucidation of toxicological effects of pesticides and the underlying mechanisms, and the discovery of biomarkers for pesticide pollution in aquatic environment

Profiles of microbial fatty acids in the human metabolome are disease-specific

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Zhanna A Ktsoyan

2011-01-01

Full Text Available The human gastrointestinal tract is inhabited by a diverse and dense symbiotic microbiota, the composition of which is the result of host-microbe co-evolution and co-adaptation. This tight integration creates intense crosstalk and signalling between the host and microbiota at the cellular and metabolic levels. In many genetic or infectious diseases the balance between host and microbiota may be compromised resulting in erroneous communication. Consequently, the composition of the human metabolome, which includes the gut metabolome, may be different in health and disease states in terms of microbial products and metabolites entering systemic circulation. To test this hypothesis, we measured the level of hydroxy, branched, cyclopropyl and unsaturated fatty acids, aldehydes, and phenyl derivatives in blood of patients with a hereditary autoinflammatory disorder, familial Mediterranean fever (FMF, and in patients with peptic ulceration (PU resulting from Helicobacter pylori infection. Discriminant function analysis of a data matrix consisting of 94 cases as statistical units (37 FMF patients, 14 PU patients, and 43 healthy controls and the concentration of 35 microbial products in the blood as statistical variables revealed a high accuracy of the proposed model (all cases were correctly classified. This suggests that the profile of microbial products and metabolites in the human metabolome is specific for a given disease and may potentially serve as a biomarker for disease.

Nutritional Metabolomics

DEFF Research Database (Denmark)

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...

The Human Serum Metabolome

Science.gov (United States)

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

Metabolomics in chemical ecology.

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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.

Metabolomic Profiles of Aspergillus oryzae and Bacillus amyloliquefaciens During Rice Koji Fermentation

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Da Eun Lee

2016-06-01

Full Text Available Rice koji, used early in the manufacturing process for many fermented foods, produces diverse metabolites and enzymes during fermentation. Using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS, ultrahigh-performance liquid chromatography linear trap quadrupole ion trap tandem mass spectrometry (UHPLC-LTQ-IT-MS/MS, and multivariate analysis we generated the metabolite profiles of rice koji produced by fermentation with Aspergillus oryzae (RK_AO or Bacillus amyloliquefaciens (RK_BA for different durations. Two principal components of the metabolomic data distinguished the rice koji samples according to their fermenter species and fermentation time. Several enzymes secreted by the fermenter species, including α-amylase, protease, and β-glucosidase, were assayed to identify differences in expression levels. This approach revealed that carbohydrate metabolism, serine-derived amino acids, and fatty acids were associated with rice koji fermentation by A. oryzae, whereas aromatic and branched chain amino acids, flavonoids, and lysophospholipids were more typical in rice koji fermentation by B. amyloliquefaciens. Antioxidant activity was significantly higher for RK_BA than for RK_AO, as were the abundances of flavonoids, including tricin, tricin glycosides, apigenin glycosides, and chrysoeriol glycosides. In summary, we have used MS-based metabolomics and enzyme activity assays to evaluate the effects of using different microbial species and fermentation times on the nutritional profile of rice koji.

Long-term fertilization determines different metabolomic profiles and responses in saplings of three rainforest tree species with different adult canopy position.

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Albert Gargallo-Garriga

Full Text Available Tropical rainforests are frequently limited by soil nutrient availability. However, the response of the metabolic phenotypic plasticity of trees to an increase of soil nutrient availabilities is poorly understood. We expected that increases in the ability of a nutrient that limits some plant processes should be detected by corresponding changes in plant metabolome profile related to such processes.We studied the foliar metabolome of saplings of three abundant tree species in a 15 year field NPK fertilization experiment in a Panamanian rainforest. The largest differences were among species and explained 75% of overall metabolome variation. The saplings of the large canopy species, Tetragastris panamensis, had the lowest concentrations of all identified amino acids and the highest concentrations of most identified secondary compounds. The saplings of the "mid canopy" species, Alseis blackiana, had the highest concentrations of amino acids coming from the biosynthesis pathways of glycerate-3P, oxaloacetate and α-ketoglutarate, and the saplings of the low canopy species, Heisteria concinna, had the highest concentrations of amino acids coming from the pyruvate synthesis pathways.The changes in metabolome provided strong evidence that different nutrients limit different species in different ways. With increasing P availability, the two canopy species shifted their metabolome towards larger investment in protection mechanisms, whereas with increasing N availability, the sub-canopy species increased its primary metabolism. The results highlighted the proportional distinct use of different nutrients by different species and the resulting different metabolome profiles in this high diversity community are consistent with the ecological niche theory.

Influence of exposure to pesticide mixtures on the metabolomic profile in post-metamorphic green frogs (Lithobates clamitans)

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Pesticide use in agricultural areas requires the application of numerous chemicals to control target organisms, leaving non-target organisms at risk. The present study evaluates the hepatic metabolomic profile of one group of non-target organisms, amphibians, after exposure to a ...

Metabolomic profiling of lung and prostate tumor tissues by capillary electrophoresis time-of-flight mass spectrometry.

Science.gov (United States)

Kami, Kenjiro; Fujimori, Tamaki; Sato, Hajime; Sato, Mutsuko; Yamamoto, Hiroyuki; Ohashi, Yoshiaki; Sugiyama, Naoyuki; Ishihama, Yasushi; Onozuka, Hiroko; Ochiai, Atsushi; Esumi, Hiroyasu; Soga, Tomoyoshi; Tomita, Masaru

2013-04-01

Metabolic microenvironment of tumor cells is influenced by oncogenic signaling and tissue-specific metabolic demands, blood supply, and enzyme expression. To elucidate tumor-specific metabolism, we compared the metabolomics of normal and tumor tissues surgically resected pairwise from nine lung and seven prostate cancer patients, using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). Phosphorylation levels of enzymes involved in central carbon metabolism were also quantified. Metabolomic profiles of lung and prostate tissues comprised 114 and 86 metabolites, respectively, and the profiles not only well distinguished tumor from normal tissues, but also squamous cell carcinoma from the other tumor types in lung cancer and poorly differentiated tumors from moderately differentiated tumors in prostate cancer. Concentrations of most amino acids, especially branched-chain amino acids, were significantly higher in tumor tissues, independent of organ type, but of essential amino acids were particularly higher in poorly differentiated than moderately differentiated prostate cancers. Organ-dependent differences were prominent at the levels of glycolytic and tricarboxylic acid cycle intermediates and associated energy status. Significantly high lactate concentrations and elevated activating phosphorylation levels of phosphofructokinase and pyruvate kinase in lung tumors confirmed hyperactive glycolysis. We highlighted the potential of CE-TOFMS-based metabolomics combined with phosphorylated enzyme analysis for understanding tissue-specific tumor microenvironments, which may lead to the development of more effective and specific anticancer therapeutics.

Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins

OpenAIRE

Pallister, Tess; Jennings, Amy; Mohney, Robert P.; Yarand, Darioush; Mangino, Massimo; Cassidy, Aedin; MacGregor, Alexander; Spector, Tim D.; Menni, Cristina

2016-01-01

Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 ad...

Noninvasive metabolomic profiling as an adjunct to morphology for noninvasive embryo assessment in women undergoing single embryo transfer

NARCIS (Netherlands)

Seli, E.; Vergouw, C.G.; Morita, H.; Botros, L.; Roos, P.; Lambalk, C.B.; Yamashita, N.; Kato, O.; Sakkas, D.

2010-01-01

Objective: To determine whether metabolomic profiling of spent embryo culture media correlates with reproductive potential of human embryos. Design: Retrospective study. Setting: Academic and a private assisted reproductive technology (ART) programs. Patient(s): Women undergoing single embryo

Target and Non-target metabolomics profiling of different barley varieties affected by enhanced ultraviolet radiation and various C:N stoichiometry

Czech Academy of Sciences Publication Activity Database

Oravec, Michal; Novotná, Kateřina; Rajsnerová, P.; Veselá, B.; Urban, Otmar; Holub, Petr; Klem, Karel

2015-01-01

Roč. 29, č. 1 (2015), s. 887.7 ISSN 0892-6638 Institutional support: RVO:67179843 Keywords : metabolomic profiling * different barley varieties * ultraviolet radiation Subject RIV: EH - Ecology, Behaviour

Metabolome analysis for discovering biomarkers of gastroenterological cancer.

Science.gov (United States)

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.

Metabolomic Profiles of a Midge (Procladius villosimanus, Kieffer Are Associated with Sediment Contamination in Urban Wetlands

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Katherine J. Jeppe

2017-12-01

Full Text Available Metabolomic techniques are powerful tools for investigating organism-environment interactions. Metabolite profiles have the potential to identify exposure or toxicity before populations are disrupted and can provide useful information for environmental assessment. However, under complex environmental scenarios, metabolomic responses to exposure can be distorted by background and/or organismal variation. In the current study, we use LC-MS (liquid chromatography-mass spectrometry and GC-MS (gas chromatography-mass spectrometry to measure metabolites of the midge Procladius villosimanus inhabiting 21 urban wetlands. These metabolites were tested against common sediment contaminants using random forest models and metabolite enrichment analysis. Sediment contaminant concentrations in the field correlated with several P. villosimanus metabolites despite natural environmental and organismal variation. Furthermore, enrichment analysis indicated that metabolite sets implicated in stress responses were enriched, pointing to specific cellular functions affected by exposure. Methionine metabolism, sugar metabolism and glycerolipid metabolism associated with total petroleum hydrocarbon and metal concentrations, while mitochondrial electron transport and urea cycle sets associated only with bifenthrin. These results demonstrate the potential for metabolomics approaches to provide useful information in field-based environmental assessments.

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

Science.gov (United States)

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

Metabolomics: beyond biomarkers and towards mechanisms

Science.gov (United States)

Johnson, Caroline H.; Ivanisevic, Julijana; Siuzdak, Gary

2017-01-01

Metabolomics, which is the profiling of metabolites in biofluids, cells and tissues, is routinely applied as a tool for biomarker discovery. Owing to innovative developments in informatics and analytical technologies, and the integration of orthogonal biological approaches, it is now possible to expand metabolomic analyses to understand the systems-level effects of metabolites. Moreover, because of the inherent sensitivity of metabolomics, subtle alterations in biological pathways can be detected to provide insight into the mechanisms that underlie various physiological conditions and aberrant processes, including diseases. PMID:26979502

Vitamins, metabolomics, and prostate cancer.

Science.gov (United States)

Mondul, Alison M; Weinstein, Stephanie J; Albanes, Demetrius

2017-06-01

How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms through which vitamins influence prostate cancer risk. Prostate cancer risk data related to vitamins E, A, and D and metabolomic profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have had mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomic profiling of fasting serum collected 1-20 years prior to clinical diagnoses found reduced lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with lower risk of aggressive disease. Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study.

Metabolomics (liver and blood profiling) in a mouse model in response to fasting: A study of hepatic steatosis

NARCIS (Netherlands)

Ginneken, V. van; Verhey, E.; Poelmann, R.; Ramakers, R.; Dijk, K.W. van; Ham, L.; Voshol, P.; Havekes, L.; Eck, M. van; Greef, J. van der

2007-01-01

A metabolomic approach was applied to a mouse model of starvation-induced hepatic steatosis. After 24 h of fasting it appears that starvation reduced the phospholipids (PL), free cholesterol (FC), and cholesterol esters (CE) content of low-density lipoproteins (LDL). In liver lipid profiles major

Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry

International Nuclear Information System (INIS)

Spur, Eva-Margarete; Decelle, Emily A.; Cheng, Leo L.

2013-01-01

Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases. (orig.)

Metabolomic imaging of prostate cancer with magnetic resonance spectroscopy and mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Spur, Eva-Margarete [Massachusetts General Hospital, Harvard Medical School, Department of Pathology, Boston, MA (United States); Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Boston, MA (United States); Charite Universitaetsmedizin, Berlin (Germany); Decelle, Emily A.; Cheng, Leo L. [Massachusetts General Hospital, Harvard Medical School, Department of Pathology, Boston, MA (United States); Massachusetts General Hospital, Harvard Medical School, Department of Radiology, Boston, MA (United States)

2013-07-15

Metabolomic imaging of prostate cancer (PCa) aims to improve in vivo imaging capability so that PCa tumors can be localized noninvasively to guide biopsy and evaluated for aggressiveness prior to prostatectomy, as well as to assess and monitor PCa growth in patients with asymptomatic PCa newly diagnosed by biopsy. Metabolomics studies global variations of metabolites with which malignancy conditions can be evaluated by profiling the entire measurable metabolome, instead of focusing only on certain metabolites or isolated metabolic pathways. At present, PCa metabolomics is mainly studied by magnetic resonance spectroscopy (MRS) and mass spectrometry (MS). With MRS imaging, the anatomic image, obtained from magnetic resonance imaging, is mapped with values of disease condition-specific metabolomic profiles calculated from MRS of each location. For example, imaging of removed whole prostates has demonstrated the ability of metabolomic profiles to differentiate cancerous foci from histologically benign regions. Additionally, MS metabolomic imaging of prostate biopsies has uncovered metabolomic expression patterns that could discriminate between PCa and benign tissue. Metabolomic imaging offers the potential to identify cancer lesions to guide prostate biopsy and evaluate PCa aggressiveness noninvasively in vivo, or ex vivo to increase the power of pathology analysis. Potentially, this imaging ability could be applied not only to PCa, but also to different tissues and organs to evaluate other human malignancies and metabolic diseases. (orig.)

Using Metabolomic Profiles as Biomarkers for Insulin Resistance in Childhood Obesity: A Systematic Review

Directory of Open Access Journals (Sweden)

Xue Zhao

2016-01-01

Full Text Available A growing body of evidence has shown the intimate relationship between metabolomic profiles and insulin resistance (IR in obese adults, while little is known about childhood obesity. In this review, we searched available papers addressing metabolomic profiles and IR in obese children from inception to February 2016 on MEDLINE, Web of Science, the Cochrane Library, ClinicalTrials.gov, and EMASE. HOMA-IR was applied as surrogate markers of IR and related metabolic disorders at both baseline and follow-up. To minimize selection bias, two investigators independently completed this work. After critical selection, 10 studies (including 2,673 participants were eligible and evaluated by using QUADOMICS for quality assessment. Six of the 10 studies were classified as “high quality.” Then we generated all the metabolites identified in each study and found amino acid metabolism and lipid metabolism were the main affected metabolic pathways in obese children. Among identified metabolites, branched-chain amino acids (BCAAs, aromatic amino acids (AAAs, and acylcarnitines were reported to be associated with IR as biomarkers most frequently. Additionally, BCAAs and tyrosine seemed to be relevant to future metabolic risk in the long-term follow-up cohorts, emphasizing the importance of early diagnosis and prevention strategy. Because of limited scale and design heterogeneity of existing studies, future studies might focus on validating above findings in more large-scale and longitudinal studies with elaborate design.

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

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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.

Metabolomic profiling to characterize acute intestinal ischemia/reperfusion injury.

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Rachel G Khadaroo

Full Text Available Sepsis and septic shock are the leading causes of death in critically ill patients. Acute intestinal ischemia/reperfusion (AII/R is an adaptive response to shock. The high mortality rate from AII/R is due to the severity of the disease and, more importantly, the failure of timely diagnosis. The objective of this investigation is to use nuclear magnetic resonance (NMR analysis to characterize urine metabolomic profile of AII/R injury in a mouse model. Animals were exposed to sham, early (30 min or late (60 min acute intestinal ischemia by complete occlusion of the superior mesenteric artery, followed by 2 hrs of reperfusion. Urine was collected and analyzed by NMR spectroscopy. Urinary metabolite concentrations demonstrated that different profiles could be delineated based on the duration of the intestinal ischemia. Metabolites such as allantoin, creatinine, proline, and methylamine could be predictive of AII/R injury. Lactate, currently used for clinical diagnosis, was found not to significantly contribute to the classification model for either early or late ischemia. This study demonstrates that patterns of changes in urinary metabolites are effective at distinguishing AII/R progression in an animal model. This is a proof-of-concept study to further support examination of metabolites in the clinical diagnosis of intestinal ischemia reperfusion injury in patients. The discovery of a fingerprint metabolite profile of AII/R will be a major advancement in the diagnosis, treatment, and prevention of systemic injury in critically ill patients.

Metabolomic profiling of faecal extracts from Cryptosporidium parvum infection in experimental mouse models.

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Josephine S Y Ng Hublin

Full Text Available Cryptosporidiosis is a gastrointestinal disease in humans and animals caused by infection with the protozoan parasite Cryptosporidium. In healthy individuals, the disease manifests mainly as acute self-limiting diarrhoea, but may be chronic and life threatening for those with compromised immune systems. Control and treatment of the disease is challenged by the lack of sensitive diagnostic tools and broad-spectrum chemotherapy. Metabolomics, or metabolite profiling, is an emerging field of study, which enables characterisation of the end products of regulatory processes in a biological system. Analysis of changes in metabolite patterns reflects changes in biochemical regulation, production and control, and may contribute to understanding the effects of Cryptosporidium infection in the host environment. In the present study, metabolomic analysis of faecal samples from experimentally infected mice was carried out to assess metabolite profiles pertaining to the infection. Gas-chromatography mass spectrometry (GC-MS carried out on faecal samples from a group of C. parvum infected mice and a group of uninfected control mice detected a mean total of 220 compounds. Multivariate analyses showed distinct differences between the profiles of C. parvum infected mice and uninfected control mice,identifying a total of 40 compounds, or metabolites that contributed most to the variance between the two groups. These metabolites consisted of amino acids (n = 17, carbohydrates (n = 8, lipids (n = 7, organic acids (n = 3 and other various metabolites (n = 5, which showed significant differences in levels of metabolite abundance between the infected and uninfected mice groups (p < 0.05. The metabolites detected in this study as well as the differences in abundance between the C. parvum infected and the uninfected control mice, highlights the effects of the infection on intestinal permeability and the fate of the metabolites as a result of nutrient scavenging by the

Analytical methods in untargeted metabolomics: state of the art in 2015

Directory of Open Access Journals (Sweden)

Arnald eAlonso

2015-03-01

Full Text Available Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile –the metabolome- has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance (NMR and mass spectrometry (MS are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high throughput biotechnologies is also reviewed.

Challenges of metabolomics in human gut microbiota research.

Science.gov (United States)

Smirnov, Kirill S; Maier, Tanja V; Walker, Alesia; Heinzmann, Silke S; Forcisi, Sara; Martinez, Inés; Walter, Jens; Schmitt-Kopplin, Philippe

2016-08-01

The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine. Copyright © 2016 Elsevier GmbH. All rights reserved.

Gut metabolome meets microbiome

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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.

1HNMR-Based metabolomic profiling method to develop plasma biomarkers for sensitivity to chronic heat stress in growing pigs.

Directory of Open Access Journals (Sweden)

Samir Dou

Full Text Available The negative impact of heat stress (HS on the production performances in pig faming is of particular concern. Novel diagnostic methods are needed to predict the robustness of pigs to HS. Our study aimed to assess the reliability of blood metabolome to predict the sensitivity to chronic HS of 10 F1 (Large White × Creole sire families (SF reared in temperate (TEMP and in tropical (TROP regions (n = 56±5 offsprings/region/SF. Live body weight (BW and rectal temperature (RT were recorded at 23 weeks of age. Average daily feed intake (AFDI and average daily gain were calculated from weeks 11 to 23 of age, together with feed conversion ratio. Plasma blood metabolome profiles were obtained by Nuclear Magnetic Resonance spectroscopy (1HNMR from blood samples collected at week 23 in TEMP. The sensitivity to hot climatic conditions of each SF was estimated by computing a composite index of sensitivity (Isens derived from a linear combination of t statistics applied to familial BW, ADFI and RT in TEMP and TROP climates. A model of prediction of sensitivity was established with sparse Partial Least Square Discriminant Analysis (sPLS-DA between the two most robust SF (n = 102 and the two most sensitive ones (n = 121 using individual metabolomic profiles measured in TEMP. The sPLS-DA selected 29 buckets that enabled 78% of prediction accuracy by cross-validation. On the basis of this training, we predicted the proportion of sensitive pigs within the 6 remaining families (n = 337. This proportion was defined as the predicted membership of families to the sensitive category. The positive correlation between this proportion and Isens (r = 0.97, P < 0.01 suggests that plasma metabolome can be used to predict the sensitivity of pigs to hot climate.

Applied metabolomics in drug discovery.

Science.gov (United States)

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.

Metabolome analysis of Drosophila melanogaster during embryogenesis.

Science.gov (United States)

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.

Radiation metabolomics : a window to high throughput radiation biodosimetry

International Nuclear Information System (INIS)

Rana, Poonam

2016-01-01

In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for radiation exposure is critical. In particular, a significant number of victims may sustain radiation injury, which increases mortality and worsens the overall prognosis of victims from radiation trauma. Availability of a high-throughput noninvasive in vivo biodosimetry tool for assessing the radiation exposure is of particular importance for timely diagnosis of radiation injury. In this study, we describe the potential NMR techniques in evaluating the radiation injury. NMR is the most versatile technique that has been extensively used in the diverse fields of science since its discovery. NMR and biomedical sciences have been going hand in hand since its application in clinical imaging as MRI and metabolic profiling of biofluids was identified. We have established an NMR based metabonomic and in vivo spectroscopy approach to analyse and identify metabolic profile to measure metabolic fingerprint for radiation exposure. NMR spectroscopy experiments were conducted on urine and serum samples collected from mice irradiated with different doses of radiation. Additionally, in vivo NMR spectroscopy was also performed in different region of brains post irradiation in animal model. A number of metabolites associated with energy metabolism, gut flora metabolites, osmolytes, amino acids and membrane metabolism were identified in serum and urine metabolome. Our results illustrated a metabolic fingerprint for radiation exposure that elucidates perturbed physiological functions. Quantitative as well as multivariate analysis/assessment of these metabolites demonstrated dose and time dependent toxicological effect. In vivo spectroscopy from brain showed radiation induced changes in hippocampus region indicating whole body radiation had striking effect on brain metabolism as well. The results of the present work lay a

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

Energy Technology Data Exchange (ETDEWEB)

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

2015-12-22

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in

Impact of Intestinal Microbiota on Intestinal Luminal Metabolome

Science.gov (United States)

Matsumoto, Mitsuharu; Kibe, Ryoko; Ooga, Takushi; Aiba, Yuji; Kurihara, Shin; Sawaki, Emiko; Koga, Yasuhiro; Benno, Yoshimi

2012-01-01

Low–molecular-weight metabolites produced by intestinal microbiota play a direct role in health and disease. In this study, we analyzed the colonic luminal metabolome using capillary electrophoresis mass spectrometry with time-of-flight (CE-TOFMS) —a novel technique for analyzing and differentially displaying metabolic profiles— in order to clarify the metabolite profiles in the intestinal lumen. CE-TOFMS identified 179 metabolites from the colonic luminal metabolome and 48 metabolites were present in significantly higher concentrations and/or incidence in the germ-free (GF) mice than in the Ex-GF mice (p metabolome and a comprehensive understanding of intestinal luminal metabolome is critical for clarifying host-intestinal bacterial interactions. PMID:22724057

Highlights of the 2012 Research Workshop: Using nutrigenomics and metabolomics in clinical nutrition research.

Science.gov (United States)

Zeisel, Steven H; Waterland, Robert A; Ordovás, José M; Muoio, Deborah M; Jia, Wei; Fodor, Anthony

2013-03-01

The American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Research Workshop, "Using Nutrigenomics and Metabolomics in Clinical Nutrition Research," was held on January 21, 2012, in Orlando, Florida. The conference brought together experts in human nutrition who use nutrigenomic and metabolomic methods to better understand metabolic individuality and nutrition effects on health. We are beginning to understand how genetic variation and epigenetic events alter requirements for and responses to foods in our diet (the field of nutrigenetics/nutrigenomics and epigenetics). At the same time, methods for profiling almost all of the products of metabolism in plasma, urine, and tissues (metabolomics) are being refined. The relationships between diet and nutrigenomic-metabolomic profiles, as well as between these profiles and health, are being elucidated, and this will dramatically alter clinical practice in nutrition.

Metabolomic Profiles of Dinophysis acuminata and Dinophysis acuta Using Non-Targeted High-Resolution Mass Spectrometry: Effect of Nutritional Status and Prey

Directory of Open Access Journals (Sweden)

María García-Portela

2018-04-01

Full Text Available Photosynthetic species of the genus Dinophysis are obligate mixotrophs with temporary plastids (kleptoplastids that are acquired from the ciliate Mesodinium rubrum, which feeds on cryptophytes of the Teleaulax-Plagioselmis-Geminigera clade. A metabolomic study of the three-species food chain Dinophysis-Mesodinium-Teleaulax was carried out using mass spectrometric analysis of extracts of batch-cultured cells of each level of that food chain. The main goal was to compare the metabolomic expression of Galician strains of Dinophysis acuminata and D. acuta that were subjected to different feeding regimes (well-fed and prey-limited and feeding on two Mesodinium (Spanish and Danish strains. Both Dinophysis species were able to grow while feeding on both Mesodinium strains, although differences in growth rates were observed. Toxin and metabolomic profiles of the two Dinophysis species were significantly different, and also varied between different feeding regimes and different prey organisms. Furthermore, significantly different metabolomes were expressed by a strain of D. acuminata that was feeding on different strains of the ciliate Mesodinium rubrum. Both species-specific metabolites and those common to D. acuminata and D. acuta were tentatively identified by screening of METLIN and Marine Natural Products Dictionary databases. This first metabolomic study applied to Dinophysis acuminata and D.acuta in culture establishes a basis for the chemical inventory of these species.

Metabolomic Profiles of Dinophysis acuminata and Dinophysis acuta Using Non-Targeted High-Resolution Mass Spectrometry: Effect of Nutritional Status and Prey.

Science.gov (United States)

García-Portela, María; Reguera, Beatriz; Sibat, Manoella; Altenburger, Andreas; Rodríguez, Francisco; Hess, Philipp

2018-04-26

Photosynthetic species of the genus Dinophysis are obligate mixotrophs with temporary plastids (kleptoplastids) that are acquired from the ciliate Mesodinium rubrum , which feeds on cryptophytes of the Teleaulax-Plagioselmis-Geminigera clade. A metabolomic study of the three-species food chain Dinophysis-Mesodinium-Teleaulax was carried out using mass spectrometric analysis of extracts of batch-cultured cells of each level of that food chain. The main goal was to compare the metabolomic expression of Galician strains of Dinophysis acuminata and D. acuta that were subjected to different feeding regimes (well-fed and prey-limited) and feeding on two Mesodinium (Spanish and Danish) strains. Both Dinophysis species were able to grow while feeding on both Mesodinium strains, although differences in growth rates were observed. Toxin and metabolomic profiles of the two Dinophysis species were significantly different, and also varied between different feeding regimes and different prey organisms. Furthermore, significantly different metabolomes were expressed by a strain of D. acuminata that was feeding on different strains of the ciliate Mesodinium rubrum . Both species-specific metabolites and those common to D. acuminata and D. acuta were tentatively identified by screening of METLIN and Marine Natural Products Dictionary databases. This first metabolomic study applied to Dinophysis acuminata and D.acuta in culture establishes a basis for the chemical inventory of these species.

Leucine-rich diet alters the 1H-NMR based metabolomic profile without changing the Walker-256 tumour mass in rats.

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Viana, Laís Rosa; Canevarolo, Rafael; Luiz, Anna Caroline Perina; Soares, Raquel Frias; Lubaczeuski, Camila; Zeri, Ana Carolina de Mattos; Gomes-Marcondes, Maria Cristina Cintra

2016-10-03

Cachexia is one of the most important causes of cancer-related death. Supplementation with branched-chain amino acids, particularly leucine, has been used to minimise loss of muscle tissue, although few studies have examined the effect of this type of nutritional supplementation on the metabolism of the tumour-bearing host. Therefore, the present study evaluated whether a leucine-rich diet affects metabolomic derangements in serum and tumour tissues in tumour-bearing Walker-256 rats (providing an experimental model of cachexia). After 21 days feeding Wistar female rats a leucine-rich diet, distributed in L-leucine and LW-leucine Walker-256 tumour-bearing groups, we examined the metabolomic profile of serum and tumour tissue samples and compared them with samples from tumour-bearing rats fed a normal protein diet (C - control; W - tumour-bearing groups). We utilised 1 H-NMR as a means to study the serum and tumour metabolomic profile, tumour proliferation and tumour protein synthesis pathway. Among the 58 serum metabolites examined, we found that 12 were altered in the tumour-bearing group, reflecting an increase in activity of some metabolic pathways related to energy production, which diverted many nutrients toward tumour growth. Despite displaying increased tumour cell activity (i.e., higher Ki-67 and mTOR expression), there were no differences in tumour mass associated with changes in 23 metabolites (resulting from valine, leucine and isoleucine synthesis and degradation, and from the synthesis and degradation of ketone bodies) in the leucine-tumour group. This result suggests that the majority of nutrients were used for host maintenance. A leucine rich-diet, largely used to prevent skeletal muscle loss, did not affect Walker 256 tumour growth and led to metabolomic alterations that may partially explain the positive effects of leucine for the whole tumour-bearing host.

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

International Nuclear Information System (INIS)

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

Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

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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

Metabolomic Profiling as a Possible Reverse Engineering Tool for Estimating Processing Conditions of Dry-Cured Hams.

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Sugimoto, Masahiro; Obiya, Shinichi; Kaneko, Miku; Enomoto, Ayame; Honma, Mayu; Wakayama, Masataka; Soga, Tomoyoshi; Tomita, Masaru

2017-01-18

Dry-cured hams are popular among consumers. To increase the attractiveness of the product, objective analytical methods and algorithms to evaluate the relationship between observable properties and consumer acceptability are required. In this study, metabolomics, which is used for quantitative profiling of hundreds of small molecules, was applied to 12 kinds of dry-cured hams from Japan and Europe. In total, 203 charged metabolites, including amino acids, organic acids, nucleotides, and peptides, were successfully identified and quantified. Metabolite profiles were compared for the samples with different countries of origin and processing methods (e.g., smoking or use of a starter culture). Principal component analysis of the metabolite profiles with sensory properties revealed significant correlations for redness, homogeneity, and fat whiteness. This approach could be used to design new ham products by objective evaluation of various features.

Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS Magnetic Resonance Spectroscopy (MRS

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Taylor L. Fuss

2016-03-01

Full Text Available According to World Health Organization (WHO estimates, cancer is responsible for more deaths than all coronary heart disease or stroke worldwide, serving as a major public health threat around the world. High resolution magic angle spinning (HRMAS magnetic resonance spectroscopy (MRS has demonstrated its usefulness in the identification of cancer metabolic markers with the potential to improve diagnosis and prognosis for the oncology clinic, due partially to its ability to preserve tissue architecture for subsequent histological and molecular pathology analysis. Capable of the quantification of individual metabolites, ratios of metabolites, and entire metabolomic profiles, HRMAS MRS is one of the major techniques now used in cancer metabolomic research. This article reviews and discusses literature reports of HRMAS MRS studies of cancer metabolomics published between 2010 and 2015 according to anatomical origins, including brain, breast, prostate, lung, gastrointestinal, and neuroendocrine cancers. These studies focused on improving diagnosis and understanding patient prognostication, monitoring treatment effects, as well as correlating with the use of in vivo MRS in cancer clinics.

CE-MS for metabolomics: developments and applications in the period 2012-2014.

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Ramautar, Rawi; Somsen, Govert W; de Jong, Gerhardus J

2015-01-01

In the field of metabolomics, CE-MS is now regarded as a useful complementary analytical technique for the profiling of (highly) polar ionogenic metabolites in biological samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolic profiling studies. This paper, which is a follow-up of three previous review papers covering the years 2000-2012 [Electrophoresis 2009, 30, 276-291; Electrophoresis 2011, 32, 52-65; Electrophoresis 2013, 34, 86-98], provides an update of these developments covering the scientific literature from July 2012 to June 2014. Attention will be paid to novel interfacing techniques for coupling CE to MS and their implications for metabolomics studies. The potential of CEC-MS and MEKC-MS are also considered, and CE-MS systems for high-throughput metabolic profiling are discussed. The applicability of CE-MS for metabolomics studies is demonstrated by representative examples in the fields of biomedical, clinical, microbial, plant, environmental, and food metabolomics. An overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metabolomic profiling identifies potential pathways involved in the interaction of iron homeostasis with glucose metabolism

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Lars Stechemesser

2017-01-01

Full Text Available Objective: Elevated serum ferritin has been linked to type 2 diabetes (T2D and adverse health outcomes in subjects with the Metabolic Syndrome (MetS. As the mechanisms underlying the negative impact of excess iron have so far remained elusive, we aimed to identify potential links between iron homeostasis and metabolic pathways. Methods: In a cross-sectional study, data were obtained from 163 patients, allocated to one of three groups: (1 lean, healthy controls (n = 53, (2 MetS without hyperferritinemia (n = 54 and (3 MetS with hyperferritinemia (n = 56. An additional phlebotomy study included 29 patients with biopsy-proven iron overload before and after iron removal. A detailed clinical and biochemical characterization was obtained and metabolomic profiling was performed via a targeted metabolomics approach. Results: Subjects with MetS and elevated ferritin had higher fasting glucose (p < 0.001, HbA1c (p = 0.035 and 1 h glucose in oral glucose tolerance test (p = 0.002 compared to MetS subjects without iron overload, whereas other clinical and biochemical features of the MetS were not different. The metabolomic study revealed significant differences between MetS with high and low ferritin in the serum concentrations of sarcosine, citrulline and particularly long-chain phosphatidylcholines. Methionine, glutamate, and long-chain phosphatidylcholines were significantly different before and after phlebotomy (p < 0.05 for all metabolites. Conclusions: Our data suggest that high serum ferritin concentrations are linked to impaired glucose homeostasis in subjects with the MetS. Iron excess is associated to distinct changes in the serum concentrations of phosphatidylcholine subsets. A pathway involving sarcosine and citrulline also may be involved in iron-induced impairment of glucose metabolism. Author Video: Author Video Watch what authors say about their articles Keywords: Metabolomics, Hyperferritinemia, Iron overload, Metabolic

Metabolomics-based promising candidate biomarkers and pathways in Alzheimer's disease.

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Kang, Jian; Lu, Jingli; Zhang, Xiaojian

2015-05-01

Pathologically, loss of synapses and neurons, extracellular senile plaques and intracellular neurofibrillary tangles (NFTs) are observed in the brains of patients with Alzheimer's disease (AD). These features are associated with changes Aβ (amyloid β) 40, Aβ42, total tau and phosphorylated tau (p-tau), which are as definitely biomarkers for severe AD state. However, biomarkers for effectively diagnosing AD in the pre-clinical state for directing therapeutic strategies are lacking. Metabolic profiling as a powerful tool to identify new biomarkers is receiving increasing attention in AD. This review will focus on metabolomics-based detection of promising candidate biomarkers and pathways in AD to facilitate the discovery of new medicines and disease pathways.

Microextraction by Packed Sorbent (MEPS and Solid-Phase Microextraction (SPME as Sample Preparation Procedures for the Metabolomic Profiling of Urine

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Catarina Silva

2014-01-01

Full Text Available For a long time, sample preparation was unrecognized as a critical issue in the analytical methodology, thus limiting the performance that could be achieved. However, the improvement of microextraction techniques, particularly microextraction by packed sorbent (MEPS and solid-phase microextraction (SPME, completely modified this scenario by introducing unprecedented control over this process. Urine is a biological fluid that is very interesting for metabolomics studies, allowing human health and disease characterization in a minimally invasive form. In this manuscript, we will critically review the most relevant and promising works in this field, highlighting how the metabolomic profiling of urine can be an extremely valuable tool for the early diagnosis of highly prevalent diseases, such as cardiovascular, oncologic and neurodegenerative ones.

Metabolomic NMR fingerprinting: an exploratory and predictive tool

OpenAIRE

Lauri, Ilaria

2014-01-01

Metabolomics is the comprehensive assessment of low molecular weight organic metabolites within biological system. The identification and characterization of several chemical species, or metabolic fingerprinting, is an emergent approach in metabolomics field that provides a valuable “snapshot” of metabolic profiles. This approach is finding an increasing number of applications in many areas including cancer research, drug discovery and food science. The combined use of NMR spectroscopy, data ...

An overview of renal metabolomics.

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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.

Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics.

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Gika, Helen G; Theodoridis, Georgios A; Plumb, Robert S; Wilson, Ian D

2014-01-01

Based on publication and citation numbers liquid chromatography (LC-MS) has become the major analytical technology in the field of global metabolite profiling. This dominance reflects significant investments from both the research community and instrument manufacturers. Here an overview of the approaches taken for LC-MS-based metabolomics research is given, describing critical steps in the realisation of such studies: study design and its needs, specific technological problems to be addressed and major obstacles in data treatment and biomarker identification. The current state of the art for LC-MS-based analysis in metabonomics/metabolomics is described including recent developments in liquid chromatography, mass spectrometry and data treatment as these are applied in metabolomics underlining the challenges, limitations and prospects for metabolomics research. Examples of the application of metabolite profiling in the life sciences focusing on disease biomarker discovery are highlighted. In addition, new developments and future prospects are described. Copyright © 2013 Elsevier B.V. All rights reserved.

Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

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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

Nutritional impact on the plasma metabolome of rats.

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Mellert, W; Kapp, M; Strauss, V; Wiemer, J; Kamp, H; Walk, T; Looser, R; Prokoudine, A; Fabian, E; Krennrich, G; Herold, M; van Ravenzwaay, B

2011-11-30

Metabolite profiling (metabolomics) elucidates changes in biochemical pathways under various conditions, e.g., different nutrition scenarios or compound administration. BASF and metanomics have obtained plasma metabolic profiles of approximately 500 compounds (agrochemicals, chemicals and pharmaceuticals) from 28-day rat studies. With these profiles the establishment of a database (MetaMap(®)Tox) containing specific metabolic patterns associated with many toxicological modes of action was achieved. To evaluate confounding factors influencing metabolome patterns, the effect of fasting vs. non-fasting prior to blood sampling, the influence of high caloric diet and caloric restriction as well as the administration of corn oil and olive oil was studied for its influence on the metabolome. All mentioned treatments had distinct effects: triacylglycerol, phospholipids and their degradation product levels (fatty acids, glycerol, lysophosphatidylcholine) were often altered depending on the nutritional status. Also some amino acid and related compounds were changed. Some metabolites derived from food (e.g. alpha-tocopherol, ascorbic acid, beta-sitosterol, campesterol) were biomarkers related to food consumption, whereas others indicated a changed energy metabolism (e.g. hydroxybutyrate, pyruvate). Strikingly, there was a profound difference in the metabolite responses to diet restriction in male and female rats. Consequently, when evaluating the metabolic profile of a compound, the effect of nutritional status should be taken into account. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Identification of Plasma Metabolomic Profiling for Diagnosis of Esophageal Squamous-Cell Carcinoma Using an UPLC/TOF/MS Platform

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Lihong Yin

2013-04-01

Full Text Available Epidemiological studies indicated that esophageal squamous-cell carcinoma (ESCC is still one of the most common causes of cancer incidence in the world. Searching for valuable markers including circulating endogenous metabolites associated with the risk of esophageal cancer, is extremely important A comparative metabolomics study was performed by using ultraperformance liquid chromatography-electrospray ionization-accurate mass time-of-flight mass spectrometry to analyze 53 pairs of plasma samples from ESCC patients and healthy controls recruited in Huaian, China. The result identified a metabolomic profiling of plasma including 25 upregulated metabolites and five downregulated metabolites, for early diagnosis of ESCC. With a database-based verification protocol, 11 molecules were identified, and six upregulated molecules of interest in ESCC were found to belong to phospholipids as follows: phosphatidylserine, phosphatidic acid, phosphatidyl choline, phosphatidylinositol, phosphatidyl ethanolamine, and sphinganine 1-phosphate. Clinical estimation of metabolic biomarkers through hierarchical cluster analysis in plasma samples from 17 ESCC patients and 29 healthy volunteers indicated that the present metabolite profile could distinguish ESCC patients from healthy individuals. The cluster of aberrant expression of these metabolites in ESCC indicates the critical role of phospholipid metabolism in the oncogenesis of ESCC and suggests its potential ability to assess the risk of ESCC development in addition to currently used risk factors.

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

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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.

Metabolomics and Metabolic Diseases: Where Do We Stand?

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Newgard, Christopher B

2017-01-10

Metabolomics, or the comprehensive profiling of small molecule metabolites in cells, tissues, or whole organisms, has undergone a rapid technological evolution in the past two decades. These advances have led to the application of metabolomics to defining predictive biomarkers for incident cardiometabolic diseases and, increasingly, as a blueprint for understanding those diseases' pathophysiologic mechanisms. Progress in this area and challenges for the future are reviewed here. Copyright © 2017 Elsevier Inc. All rights reserved.

Metabolomics

DEFF Research Database (Denmark)

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...

Profiling the metabolome changes caused by cranberry procyanidins in plasma of female rats using (1) H NMR and UHPLC-Q-Orbitrap-HRMS global metabolomics approaches.

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Liu, Haiyan; Garrett, Timothy J; Tayyari, Fariba; Gu, Liwei

2015-11-01

The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using (1) H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Twenty-four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for three times using a 250 mg extracts/kg body weight dose. Plasma was collected 6 h after the last gavage and analyzed using (1) H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using (1) H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in the plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulphate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4'-O-methyl-(-)-epicatechin-3'-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(-)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-ϒ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Profiling the Metabolome Changes Caused by Cranberry Procyanidins in Plasma of Female Rats using 1H NMR and UHPLC-Q-Orbitrap-HRMS Global Metabolomics Approaches

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Liu, Haiyan; Garrett, Timothy J.; Tayyari, Fariba; Gu, Liwei

2015-01-01

Scope The objective was to investigate the metabolome changes in female rats gavaged with partially purified cranberry procyanidins (PPCP) using 1H NMR and UHPLC-Q-Orbitrap-HRMS metabolomics approaches, and to identify the contributing metabolites. Methods and results Twenty four female Sprague-Dawley rats were randomly separated into two groups and administered PPCP or partially purified apple procyanidins (PPAP) for 3 times using a 250 mg extracts/kg body weight dose. Plasma were collected six hours after the last gavage and analyzed using 1H NMR and UHPLC-Q-Orbitrap-HRMS. No metabolome difference was observed using 1H NMR metabolomics approach. However, LC-HRMS metabolomics data show that metabolome in plasma of female rats administered PPCP differed from those gavaged with PPAP. Eleven metabolites were tentatively identified from a total of 36 discriminant metabolic features based on accurate masses and/or product ion spectra. PPCP caused a greater increase of exogenous metabolites including p-hydroxybenzoic acid, phenol, phenol-sulfate, catechol sulphate, 3, 4-dihydroxyphenylvaleric acid, and 4′-O-methyl-(−)-epicatechin-3′-O-beta-glucuronide in rat plasma. Furthermore, the plasma level of O-methyl-(−)-epicatechin-O-glucuronide, 4-hydroxy-5-(hydroxyphenyl)-valeric acid-O-sulphate, 5-(hydroxyphenyl)-γ-valerolactone-O-sulphate, 4-hydroxydiphenylamine, and peonidin-3-O-hexose were higher in female rats administered with PPAP. Conclusion The metabolome changes caused by cranberry procyanidins were revealed using an UHPLC-Q-Orbitrap-HRMS global metabolomics approach. Exogenous and microbial metabolites were the major identified discriminate biomarkers. PMID:26264887

Metabolomics and Personalized Medicine.

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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.

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

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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

Expanded metabolomics approach to profiling endogenous carbohydrates in the serum of ovarian cancer patients.

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Cheng, Yu; Li, Li; Zhu, Bangjie; Liu, Feng; Wang, Yan; Gu, Xue; Yan, Chao

2016-01-01

We applied hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry to the quantitative analysis of serum from 58 women, including ovarian cancer patients, ovarian benign tumor patients, and healthy controls. All of these ovarian cancer and ovarian benign tumor patients have elevated cancer antigen 125, which makes them clinically difficult to differentiate the malignant from the benign. All of the 16 endogenous carbohydrates were quantitatively detected in the human sera, of which, eight endogenous carbohydrates were significantly different (P-value carbohydrates in the expanded metabolomics approach after the global metabolic profiling are characterized and are potential biomarkers for the early diagnosis of ovarian cancer. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterization of rheumatoid arthritis subtypes using symptom profiles, clinical chemistry and metabolomics measurements.

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Herman A van Wietmarschen

Full Text Available OBJECTIVE: The aim is to characterize subgroups or phenotypes of rheumatoid arthritis (RA patients using a systems biology approach. The discovery of subtypes of rheumatoid arthritis patients is an essential research area for the improvement of response to therapy and the development of personalized medicine strategies. METHODS: In this study, 39 RA patients are phenotyped using clinical chemistry measurements, urine and plasma metabolomics analysis and symptom profiles. In addition, a Chinese medicine expert classified each RA patient as a Cold or Heat type according to Chinese medicine theory. Multivariate data analysis techniques are employed to detect and validate biochemical and symptom relationships with the classification. RESULTS: The questionnaire items 'Red joints', 'Swollen joints', 'Warm joints' suggest differences in the level of inflammation between the groups although c-reactive protein (CRP and rheumatoid factor (RHF levels were equal. Multivariate analysis of the urine metabolomics data revealed that the levels of 11 acylcarnitines were lower in the Cold RA than in the Heat RA patients, suggesting differences in muscle breakdown. Additionally, higher dehydroepiandrosterone sulfate (DHEAS levels in Heat patients compared to Cold patients were found suggesting that the Cold RA group has a more suppressed hypothalamic-pituitary-adrenal (HPA axis function. CONCLUSION: Significant and relevant biochemical differences are found between Cold and Heat RA patients. Differences in immune function, HPA axis involvement and muscle breakdown point towards opportunities to tailor disease management strategies to each of the subgroups RA patient.

Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review.

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Li, Bingbing; He, Xuyun; Jia, Wei; Li, Houkai

2017-07-13

Interindividual variability in drug responses and disease susceptibility is common in the clinic. Currently, personalized medicine is highly valued, the idea being to prescribe the right medicine to the right patient. Metabolomics has been increasingly applied in evaluating the therapeutic outcomes of clinical drugs by correlating the baseline metabolic profiles of patients with their responses, i.e., pharmacometabonomics, as well as prediction of disease susceptibility among population in advance, i.e., patient stratification. The accelerated advance in metabolomics technology pinpoints the huge potential of its application in personalized medicine. In current review, we discussed the novel applications of metabolomics with typical examples in evaluating drug therapy and patient stratification, and underlined the potential of metabolomics in personalized medicine in the future.

Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

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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.

Causal Genetic Variation Underlying Metabolome Differences.

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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.

Metabolomic Profiling of Statin Use and Genetic Inhibition of HMG-CoA Reductase.

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Würtz, Peter; Wang, Qin; Soininen, Pasi; Kangas, Antti J; Fatemifar, Ghazaleh; Tynkkynen, Tuulia; Tiainen, Mika; Perola, Markus; Tillin, Therese; Hughes, Alun D; Mäntyselkä, Pekka; Kähönen, Mika; Lehtimäki, Terho; Sattar, Naveed; Hingorani, Aroon D; Casas, Juan-Pablo; Salomaa, Veikko; Kivimäki, Mika; Järvelin, Marjo-Riitta; Davey Smith, George; Vanhala, Mauno; Lawlor, Debbie A; Raitakari, Olli T; Chaturvedi, Nish; Kettunen, Johannes; Ala-Korpela, Mika

2016-03-15

Statins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized. This study sought to determine the molecular effects of statin therapy on multiple metabolic pathways. Metabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts. Starting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R(2) = 0.94, slope 1.00 ± 0.03). Statin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug targets can inform indications, pleiotropic effects

Application of Metabolomics in Thyroid Cancer Research

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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.

A LC-MS metabolomics approach to investigate the effect of raw apple intake in the rat plasma metabolome

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Rago, Daniela; Kristensen, Mette; Gürdeniz, Gözde

2013-01-01

Fruit and vegetable consumption has been associated with several health benefits; however the mechanisms are largely unknown at the biochemical level. Our research aims to investigate whether plasma metabolome profiling can reflect biological effects after feeding rats with raw apple by using...... an untargeted UPLC–ESI– TOF–MS based metabolomics approach in both positive and negative mode. Eighty young male rats were randomised into groups receiving daily 0, 5 or 10 g fresh apple slices, respectively, for 13 weeks. During weeks 3–6 some of the animals were receiving 4 mg/ml 1,2-dimethylhydrazine...

Conventional and accelerated-solvent extractions of green tea (camellia sinensis) for metabolomics-based chemometrics.

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Kellogg, Joshua J; Wallace, Emily D; Graf, Tyler N; Oberlies, Nicholas H; Cech, Nadja B

2017-10-25

Metabolomics has emerged as an important analytical technique for multiple applications. The value of information obtained from metabolomics analysis depends on the degree to which the entire metabolome is present and the reliability of sample treatment to ensure reproducibility across the study. The purpose of this study was to compare methods of preparing complex botanical extract samples prior to metabolomics profiling. Two extraction methodologies, accelerated solvent extraction and a conventional solvent maceration, were compared using commercial green tea [Camellia sinensis (L.) Kuntze (Theaceae)] products as a test case. The accelerated solvent protocol was first evaluated to ascertain critical factors influencing extraction using a D-optimal experimental design study. The accelerated solvent and conventional extraction methods yielded similar metabolite profiles for the green tea samples studied. The accelerated solvent extraction yielded higher total amounts of extracted catechins, was more reproducible, and required less active bench time to prepare the samples. This study demonstrates the effectiveness of accelerated solvent as an efficient methodology for metabolomics studies. Copyright © 2017. Published by Elsevier B.V.

Statistical methods for the analysis of high-throughput metabolomics data

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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.

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

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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.

Tissue Multiplatform-Based Metabolomics/Metabonomics for Enhanced Metabolome Coverage.

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Vorkas, Panagiotis A; Abellona U, M R; Li, Jia V

2018-01-01

The use of tissue as a matrix to elucidate disease pathology or explore intervention comes with several advantages. It allows investigation of the target alteration directly at the focal location and facilitates the detection of molecules that could become elusive after secretion into biofluids. However, tissue metabolomics/metabonomics comes with challenges not encountered in biofluid analyses. Furthermore, tissue heterogeneity does not allow for tissue aliquoting. Here we describe a multiplatform, multi-method workflow which enables metabolic profiling analysis of tissue samples, while it can deliver enhanced metabolome coverage. After applying a dual consecutive extraction (organic followed by aqueous), tissue extracts are analyzed by reversed-phase (RP-) and hydrophilic interaction liquid chromatography (HILIC-) ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) and nuclear magnetic resonance (NMR) spectroscopy. This pipeline incorporates the required quality control features, enhances versatility, allows provisional aliquoting of tissue extracts for future guided analyses, expands the range of metabolites robustly detected, and supports data integration. It has been successfully employed for the analysis of a wide range of tissue types.

Plasma metabolomic profiles of breast cancer patients after short-term limonene intervention.

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Miller, Jessica A; Pappan, Kirk; Thompson, Patricia A; Want, Elizabeth J; Siskos, Alexandros P; Keun, Hector C; Wulff, Jacob; Hu, Chengcheng; Lang, Julie E; Chow, H-H Sherry

2015-01-01

Limonene is a lipophilic monoterpene found in high levels in citrus peel. Limonene demonstrates anticancer properties in preclinical models with effects on multiple cellular targets at varying potency. While of interest as a cancer chemopreventive, the biologic activity of limonene in humans is poorly understood. We conducted metabolite profiling in 39 paired (pre/postintervention) plasma samples from early-stage breast cancer patients receiving limonene treatment (2 g QD) before surgical resection of their tumor. Metabolite profiling was conducted using ultra-performance liquid chromatography coupled to a linear trap quadrupole system and gas chromatography-mass spectrometry. Metabolites were identified by comparison of ion features in samples to a standard reference library. Pathway-based interpretation was conducted using the human metabolome database and the MetaCyc database. Of the 397 named metabolites identified, 72 changed significantly with limonene intervention. Class-based changes included significant decreases in adrenal steroids (P limonene resulted in significant changes in several metabolic pathways. Furthermore, pathway-based changes were related to the change in tissue level cyclin D1 expression. Future controlled clinical trials with limonene are necessary to determine the potential role and mechanisms of limonene in the breast cancer prevention setting. ©2014 American Association for Cancer Research.

UPLC-Q-TOF/MS based metabolomic profiling of serum and urine of hyperlipidemic rats induced by high fat diet

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Qiong Wu

2014-12-01

Full Text Available Hyperlipidemia is considered to be a high lipid level in blood, can induce metabolic disorders and dysfunctions of the body, and results in some severe complications. Therefore, hunting for some metabolite markers and clarifying the metabolic pathways in vivo will be an important strategy in the treatment and prevention of hyperlipidemia. In this study, a rat model of hyperlipidemia was constructed according to histopathological data and biochemical parameters, and the metabolites of serum and urine were analyzed by UPLC-Q-TOF/MS. Combining pattern recognition and statistical analysis, 19 candidate biomarkers were screened and identified. These changed metabolites indicated that during the development and progression of hyperlipidemia, energy metabolism, lipid metabolism, amino acid metabolism and nucleotide metabolism were mainly disturbed, which are reported to be closely related to diabetes, cardiovascular diseases, etc. This study demonstrated that a UPLC-Q-TOF/MS based metabolomic approach is useful to profile the alternation of endogenous metabolites of hyperlipidemia. Keywords: UPLC-Q-TOF/MS, Hyperlipidemia, Metabolomic, Pattern recognition

Arbuscular Mycorrhizal Fungi and Plant Chemical Defence: Effects of Colonisation on Aboveground and Belowground Metabolomes.

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Hill, Elizabeth M; Robinson, Lynne A; Abdul-Sada, Ali; Vanbergen, Adam J; Hodge, Angela; Hartley, Sue E

2018-02-01

Arbuscular mycorrhizal fungal (AMF) colonisation of plant roots is one of the most ancient and widespread interactions in ecology, yet the systemic consequences for plant secondary chemistry remain unclear. We performed the first metabolomic investigation into the impact of AMF colonisation by Rhizophagus irregularis on the chemical defences, spanning above- and below-ground tissues, in its host-plant ragwort (Senecio jacobaea). We used a non-targeted metabolomics approach to profile, and where possible identify, compounds induced by AMF colonisation in both roots and shoots. Metabolomics analyses revealed that 33 compounds were significantly increased in the root tissue of AMF colonised plants, including seven blumenols, plant-derived compounds known to be associated with AMF colonisation. One of these was a novel structure conjugated with a malonyl-sugar and uronic acid moiety, hitherto an unreported combination. Such structural modifications of blumenols could be significant for their previously reported functional roles associated with the establishment and maintenance of AM colonisation. Pyrrolizidine alkaloids (PAs), key anti-herbivore defence compounds in ragwort, dominated the metabolomic profiles of root and shoot extracts. Analyses of the metabolomic profiles revealed an increase in four PAs in roots (but not shoots) of AMF colonised plants, with the potential to protect colonised plants from below-ground organisms.

Metabolomics techniques for nanotoxicity investigations.

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Lv, Mengying; Huang, Wanqiu; Chen, Zhipeng; Jiang, Hulin; Chen, Jiaqing; Tian, Yuan; Zhang, Zunjian; Xu, Fengguo

2015-01-01

Nanomaterials are commonly defined as engineered structures with at least one dimension of 100 nm or less. Investigations of their potential toxicological impact on biological systems and the environment have yet to catch up with the rapid development of nanotechnology and extensive production of nanoparticles. High-throughput methods are necessary to assess the potential toxicity of nanoparticles. The omics techniques are well suited to evaluate toxicity in both in vitro and in vivo systems. Besides genomic, transcriptomic and proteomic profiling, metabolomics holds great promises for globally evaluating and understanding the molecular mechanism of nanoparticle-organism interaction. This manuscript presents a general overview of metabolomics techniques, summarizes its early application in nanotoxicology and finally discusses opportunities and challenges faced in nanotoxicology.

SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

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Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

2018-03-20

The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

Potential Anticancer Effects of Polyphenols from Chestnut Shell Extracts: Modulation of Cell Growth, and Cytokinomic and Metabolomic Profiles

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Angela Sorice

2016-10-01

Full Text Available In this study, a hydroalcoholic chestnut shell extract was characterized and tested on six different human cell lines. Gallic, ellagic, and syringic acids were the most abundant non-condensed compounds in the chestnut extract, as determined by high performance liquid chromatography (HPLC. Tannins were mainly represented by condensed monomeric units of epigallocatechin and catechin/epicatechin. After 48 h of treatment, only the human hepatoblastoma HepG2 cells reached an inhibition corresponding to IC50 with an increase of apoptosis and mitochondrial depolarization. The cytokinome evaluation before and after treatment revealed that the vascular endothelial growth factor (VEGF and the tumor necrosis factor (TNF-α decreased after the treatment, suggesting a potential anti-angiogenic and anti-inflammatory effect of this extract. Moreover, the metabolome evaluation by 1H-NMR evidenced that the polyphenols extracted from chestnut shell (PECS treatment affected the levels of some amino acids and other metabolites. Overall, these data highlight the effects of biomolecules on cell proliferation, apoptosis, cell cycle and mitochondrial depolarization, and on cytokinomics and metabolomics profiles.

Livestock metabolomics and the livestock metabolome: A systematic review

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Guo, An Chi; Sajed, Tanvir; Steele, Michael A.; Plastow, Graham S.; Wishart, David S.

2017-01-01

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed. PMID:28531195

Livestock metabolomics and the livestock metabolome: A systematic review.

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Goldansaz, Seyed Ali; Guo, An Chi; Sajed, Tanvir; Steele, Michael A; Plastow, Graham S; Wishart, David S

2017-01-01

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular "omics" approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

LC-QTOF/MS metabolomic profiles in human plasma after a 5-week high dietary fiber intake

DEFF Research Database (Denmark)

Johansson-Persson, Anna; Barri, Thaer; Ulmius, Matilda

2013-01-01

, in a 5-week randomized controlled crossover intervention. The HF diet consisted of oat bran, rye bran, and sugar beet fiber incorporated into test food products, whereas the LF diet was made of equivalent food products to the HF diet, but without adding fibers. Blood plasma samples were collected......The objective was to investigate the alterations of plasma metabolome profiles to identify exposure and effect markers of dietary fiber intake. Subjects (n¿=¿25) aged 58.6 (1.1)¿years (mean and SD) with a body mass index of 26.6 (0.5)¿kg/m(2) were given a high fiber (HF) and a low fiber (LF) diet...

Stable isotope-resolved metabolomics and applications for drug development

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Fan, Teresa W-M.; Lorkiewicz, Pawel; Sellers, Katherine; Moseley, Hunter N.B.; Higashi, Richard M.; Lane, Andrew N.

2012-01-01

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), during the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly cancer. The metabolome is the functional readout of the genome, functional genome, and proteome; it is also an integral partner in molecular regulations for homeostasis. The interrogation of the metabolome, or metabolomics, is now being applied to numerous diseases, largely by metabolite profiling for biomarker discovery, but also in pharmacology and therapeutics. Recent advances in stable isotope tracer-based metabolomic approaches enable unambiguous tracking of individual atoms through compartmentalized metabolic networks directly in human subjects, which promises to decipher the complexity of the human metabolome at an unprecedented pace. This knowledge will revolutionize our understanding of complex human diseases, clinical diagnostics, as well as individualized therapeutics and drug response. In this review, we focus on the use of stable isotope tracers with metabolomics technologies for understanding metabolic network dynamics in both model systems and in clinical applications. Atom-resolved isotope tracing via the two major analytical platforms, NMR and MS, has the power to determine novel metabolic reprogramming in diseases, discover new drug targets, and facilitates ADME studies. We also illustrate new metabolic tracer-based imaging technologies, which enable direct visualization of metabolic processes in vivo. We further outline current practices and future requirements for biochemoinformatics development, which is an integral part of translating stable isotope-resolved metabolomics into clinical reality. PMID:22212615

Cerebral biochemical pathways in experimental autoimmune encephalomyelitis and adjuvant arthritis: a comparative metabolomic study.

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Norbert W Lutz

Full Text Available Many diseases, including brain disorders, are associated with perturbations of tissue metabolism. However, an often overlooked issue is the impact that inflammations outside the brain may have on brain metabolism. Our main goal was to study similarities and differences between brain metabolite profiles of animals suffering from experimental autoimmune encephalomyelitis (EAE and adjuvant arthritis (AA in Lewis rat models. Our principal objective was the determination of molecular protagonists involved in the metabolism underlying these diseases. EAE was induced by intraplantar injection of complete Freund's adjuvant (CFA and spinal-cord homogenate (SC-H, whereas AA was induced by CFA only. Naive rats served as controls (n = 9 for each group. Two weeks after inoculation, animals were sacrificed, and brains were removed and processed for metabolomic analysis by NMR spectroscopy or for immunohistochemistry. Interestingly, both inflammatory diseases caused similar, though not identical, changes in metabolites involved in regulation of brain cell size and membrane production: among the osmolytes, taurine and the neuronal marker, N-acetylaspartate, were decreased, and the astrocyte marker, myo-inositol, slightly increased in both inoculated groups compared with controls. Also ethanolamine-containing phospholipids, sources of inflammatory agents, and several glycolytic metabolites were increased in both inoculated groups. By contrast, the amino acids, aspartate and isoleucine, were less concentrated in CFA/SC-H and control vs. CFA rats. Our results suggest that inflammatory brain metabolite profiles may indicate the existence of either cerebral (EAE or extra-cerebral (AA inflammation. These inflammatory processes may act through distinct pathways that converge toward similar brain metabolic profiles. Our findings open new avenues for future studies aimed at demonstrating whether brain metabolic effects provoked by AA are pain/stress-mediated and

Cerebral biochemical pathways in experimental autoimmune encephalomyelitis and adjuvant arthritis: a comparative metabolomic study.

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Lutz, Norbert W; Fernandez, Carla; Pellissier, Jean-François; Cozzone, Patrick J; Béraud, Evelyne

2013-01-01

Many diseases, including brain disorders, are associated with perturbations of tissue metabolism. However, an often overlooked issue is the impact that inflammations outside the brain may have on brain metabolism. Our main goal was to study similarities and differences between brain metabolite profiles of animals suffering from experimental autoimmune encephalomyelitis (EAE) and adjuvant arthritis (AA) in Lewis rat models. Our principal objective was the determination of molecular protagonists involved in the metabolism underlying these diseases. EAE was induced by intraplantar injection of complete Freund's adjuvant (CFA) and spinal-cord homogenate (SC-H), whereas AA was induced by CFA only. Naive rats served as controls (n = 9 for each group). Two weeks after inoculation, animals were sacrificed, and brains were removed and processed for metabolomic analysis by NMR spectroscopy or for immunohistochemistry. Interestingly, both inflammatory diseases caused similar, though not identical, changes in metabolites involved in regulation of brain cell size and membrane production: among the osmolytes, taurine and the neuronal marker, N-acetylaspartate, were decreased, and the astrocyte marker, myo-inositol, slightly increased in both inoculated groups compared with controls. Also ethanolamine-containing phospholipids, sources of inflammatory agents, and several glycolytic metabolites were increased in both inoculated groups. By contrast, the amino acids, aspartate and isoleucine, were less concentrated in CFA/SC-H and control vs. CFA rats. Our results suggest that inflammatory brain metabolite profiles may indicate the existence of either cerebral (EAE) or extra-cerebral (AA) inflammation. These inflammatory processes may act through distinct pathways that converge toward similar brain metabolic profiles. Our findings open new avenues for future studies aimed at demonstrating whether brain metabolic effects provoked by AA are pain/stress-mediated and/or due to the

Untargeted Metabolomics Profiling of an 80.5 km Simulated Treadmill Ultramarathon

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Christopher C. F. Howe

2018-02-01

Full Text Available Metabolomic profiling of nine trained ultramarathon runners completing an 80.5 km self-paced treadmill-based time trial was carried out. Plasma samples were obtained from venous whole blood, collected at rest and on completion of the distance (post-80.5 km. The samples were analyzed by using high-resolution mass spectrometry in combination with both hydrophilic interaction (HILIC and reversed phase (RP chromatography. The extracted putatively identified features were modeled using Simca P 14.1 software (Umetrics, Umea, Sweden. A large number of amino acids decreased post-80.5 km and fatty acid metabolism was affected with an increase in the formation of medium-chain unsaturated and partially oxidized fatty acids and conjugates of fatty acids with carnitines. A possible explanation for the complex pattern of medium-chain and oxidized fatty acids formed is that the prolonged exercise provoked the proliferation of peroxisomes. The peroxisomes may provide a readily utilizable form of energy through formation of acetyl carnitine and other acyl carnitines for export to mitochondria in the muscles; and secondly may serve to regulate the levels of oxidized metabolites of long-chain fatty acids. This is the first study to provide evidence of the metabolic profile in response to prolonged ultramarathon running using an untargeted approach. The findings provide an insight to the effects of ultramarathon running on the metabolic specificities and alterations that may demonstrate cardio-protective effects.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study.

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Austdal, Marie; Tangerås, Line H; Skråstad, Ragnhild B; Salvesen, Kjell; Austgulen, Rigmor; Iversen, Ann-Charlotte; Bathen, Tone F

2015-09-08

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study

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Marie Austdal

2015-09-01

Full Text Available Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension. Preeclampsia developed in 26 (4.3% and gestational hypertension in 21 (3.5% women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

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

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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.

Day-3 embryo metabolomics in the spent culture media is altered in obese women undergoing in vitro fertilization.

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Bellver, José; De Los Santos, María J; Alamá, Pilar; Castelló, Damià; Privitera, Laura; Galliano, Daniela; Labarta, Elena; Vidal, Carmen; Pellicer, Antonio; Domínguez, Francisco

2015-06-01

To determine whether the global metabolomic profile of the spent culture media (SCM) of day-3 embryos is different in obese and normoweight women undergoing in vitro fertilization (IVF). Prospective cohort analysis. IVF clinic. Twenty-eight young, nonsmoking women with normoweight, nonsmoking male partners with mild/normal sperm factors undergoing a first IVF attempt for idiopathic infertility, tubal factor infertility, or failed ovulation induction: obese ovulatory women (n = 12); obese women with polycystic ovary syndrome (PCOS; n = 4); normoweight ovulatory women (n = 12). Fifty μl of SCM collected from two day-3 embryos of each cohort. Metabolomic profiling via ultrahigh performance liquid chromatography coupled to mass spectrometry of SCM from a total of 56 embryos. The untargeted metabolomic profile was different in obese and normoweight women. Partial least squares discriminant analysis resulted in a clear separation of samples when a total of 551 differential metabolites were considered. A prediction model was generated using the most consistent metabolites. Most of the metabolites identified were saturated fatty acids, which were detected in lower concentrations in the SCM of embryos from obese women. The metabolomic profile was similar in obese women with or without PCOS. The metabolomic profile in the SCM of day-3 embryos is different in normoweight and obese women. Saturated fatty acids seem to be reduced when embryos from obese patients are present. NCT01448863. Copyright © 2015 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Non-invasive metabolomic profiling of embryo culture media and morphology grading to predict implantation outcome in frozen-thawed embryo transfer cycles.

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Li, Xiong; Xu, Yan; Fu, Jing; Zhang, Wen-Bi; Liu, Su-Ying; Sun, Xiao-Xi

2015-11-01

Assessment of embryo viability is a crucial component of in vitro fertilization and currently relies largely on embryo morphology and cleavage rate. Because morphological assessment remains highly subjective, it can be unreliable in predicting embryo viability. This study investigated the metabolomic profiling of embryo culture media using near-infrared (NIR) spectroscopy for predicting the implantation potential of human embryos in frozen-thawed embryo transfer (FET) cycles. Spent embryo culture media was collected on day 4 after thawed embryo transfer (n = 621) and analysed using NIR spectroscopy. Viability scores were calculated using a predictive multivariate algorithm of fresh embryos with known pregnancy outcomes. The mean viability indices of embryos resulting in clinical pregnancy following FET were significantly higher than those of non-implanted embryos and differed between the 0, 50, and 100 % implantation groups. Notably, the 0 % group index was significantly lower than the 100 % implantation group index (-0.787 ± 0.382 vs. 1.064 ± 0.331, P  0.05). NIR metabolomic profiling of thawed embryo culture media is independent of morphology and correlates with embryo implantation potential in FET cycles. The viability score alone or in conjunction with morphologic grading is a more objective marker for implantation outcome in FET cycles than morphology alone.

Exploring the Inflammatory Metabolomic Profile to Predict Response to TNF-α Inhibitors in Rheumatoid Arthritis.

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Bart V J Cuppen

Full Text Available In clinical practice, approximately one-third of patients with rheumatoid arthritis (RA respond insufficiently to TNF-α inhibitors (TNFis. The aim of the study was to explore the use of a metabolomics to identify predictors for the outcome of TNFi therapy, and study the metabolomic fingerprint in active RA irrespective of patients' response. In the metabolomic profiling, lipids, oxylipins, and amines were measured in serum samples of RA patients from the observational BiOCURA cohort, before start of biological treatment. Multivariable logistic regression models were established to identify predictors for good- and non-response in patients receiving TNFi (n = 124. The added value of metabolites over prediction using clinical parameters only was determined by comparing the area under receiver operating characteristic curve (AUC-ROC, sensitivity, specificity, positive- and negative predictive value and by the net reclassification index (NRI. The models were further validated by 10-fold cross validation and tested on the complete TNFi treatment cohort including moderate responders. Additionally, metabolites were identified that cross-sectionally associated with the RA disease activity score based on a 28-joint count (DAS28, erythrocyte sedimentation rate (ESR or C-reactive protein (CRP. Out of 139 metabolites, the best-performing predictors were sn1-LPC(18:3-ω3/ω6, sn1-LPC(15:0, ethanolamine, and lysine. The model that combined the selected metabolites with clinical parameters showed a significant larger AUC-ROC than that of the model containing only clinical parameters (p = 0.01. The combined model was able to discriminate good- and non-responders with good accuracy and to reclassify non-responders with an improvement of 30% (total NRI = 0.23 and showed a prediction error of 0.27. For the complete TNFi cohort, the NRI was 0.22. In addition, 88 metabolites were associated with DAS28, ESR or CRP (p<0.05. Our study established an accurate

Fecal Microbiota and Metabolome in a Mouse Model of Spontaneous Chronic Colitis: Relevance to Human Inflammatory Bowel Disease.

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Robinson, Ainsley M; Gondalia, Shakuntla V; Karpe, Avinash V; Eri, Rajaraman; Beale, David J; Morrison, Paul D; Palombo, Enzo A; Nurgali, Kulmira

2016-12-01

Dysbiosis of the gut microbiota may be involved in the pathogenesis of inflammatory bowel disease (IBD). However, the mechanisms underlying the role of the intestinal microbiome and metabolome in IBD onset and its alteration during active treatment and recovery remain unknown. Animal models of chronic intestinal inflammation with similar microbial and metabolomic profiles would enable investigation of these mechanisms and development of more effective treatments. Recently, the Winnie mouse model of colitis closely representing the clinical symptoms and characteristics of human IBD has been developed. In this study, we have analyzed fecal microbial and metabolomic profiles in Winnie mice and discussed their relevance to human IBD. The 16S rRNA gene was sequenced from fecal DNA of Winnie and C57BL/6 mice to define operational taxonomic units at ≥97% similarity threshold. Metabolomic profiling of the same fecal samples was performed by gas chromatography-mass spectrometry. Composition of the dominant microbiota was disturbed, and prominent differences were evident at all levels of the intestinal microbiome in fecal samples from Winnie mice, similar to observations in patients with IBD. Metabolomic profiling revealed that chronic colitis in Winnie mice upregulated production of metabolites and altered several metabolic pathways, mostly affecting amino acid synthesis and breakdown of monosaccharides to short chain fatty acids. Significant dysbiosis in the Winnie mouse gut replicates many changes observed in patients with IBD. These results provide justification for the suitability of this model to investigate mechanisms underlying the role of intestinal microbiota and metabolome in the pathophysiology of IBD.

New biomarkers of coffee consumption identified by the non-targeted metabolomic profiling of cohort study subjects.

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Joseph A Rothwell

Full Text Available Coffee contains various bioactives implicated with human health and disease risk. To accurately assess the effects of overall consumption upon health and disease, individual intake must be measured in large epidemiological studies. Metabolomics has emerged as a powerful approach to discover biomarkers of intake for a large range of foods. Here we report the profiling of the urinary metabolome of cohort study subjects to search for new biomarkers of coffee intake. Using repeated 24-hour dietary records and a food frequency questionnaire, 20 high coffee consumers (183-540 mL/d and 19 low consumers were selected from the French SU.VI.MAX2 cohort. Morning spot urine samples from each subject were profiled by high-resolution mass spectrometry. Partial least-square discriminant analysis of multidimensional liquid chromatography-mass spectrometry data clearly distinguished high consumers from low via 132 significant (p-value<0.05 discriminating features. Ion clusters whose intensities were most elevated in the high consumers were annotated using online and in-house databases and their identities checked using commercial standards and MS-MS fragmentation. The best discriminants, and thus potential markers of coffee consumption, were the glucuronide of the diterpenoid atractyligenin, the diketopiperazine cyclo(isoleucyl-prolyl, and the alkaloid trigonelline. Some caffeine metabolites, such as 1-methylxanthine, were also among the discriminants, however caffeine may be consumed from other sources and its metabolism is subject to inter-individual variation. Receiver operating characteristics curve analysis showed that the biomarkers identified could be used effectively in combination for increased sensitivity and specificity. Once validated in other cohorts or intervention studies, these specific single or combined biomarkers will become a valuable alternative to assessment of coffee intake by dietary survey and finally lead to a better understanding of

Enzymatically Modified Starch Ameliorates Postprandial Serum Triglycerides and Lipid Metabolome in Growing Pigs.

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Metzler-Zebeli, Barbara U; Eberspächer, Eva; Grüll, Dietmar; Kowalczyk, Lidia; Molnar, Timea; Zebeli, Qendrim

2015-01-01

Developing host digestion-resistant starches to promote human health is of great research interest. Chemically modified starches (CMS) are widely used in processed foods and although the modification of the starch molecule allows specific reduction in digestibility, the metabolic effects of CMS have been less well described. This short-term study evaluated the impact of enzymatically modified starch (EMS) on fasting and postprandial profiles of blood glucose, insulin and lipids, and serum metabolome in growing pigs. Eight jugular-vein catheterized pigs (initial body weight, 37.4 kg; 4 months of age) were fed 2 diets containing 72% purified starch (EMS or waxy corn starch (control)) in a cross-over design for 7 days. On day 8, an 8-hour meal tolerance test (MTT) was performed with serial blood samplings. Besides biochemical analysis, serum was analysed for 201 metabolites through targeted mass spectrometry-based metabolomic approaches. Pigs fed the EMS diet showed increased (Pmetabolome profiling identified characteristic changes in glycerophospholipid, lysophospholipids, sphingomyelins and amino acid metabolome profiles with EMS diet compared to control diet. Results showed rapid adaptations of blood metabolites to dietary starch shifts within 7 days. In conclusion, EMS ingestion showed potential to attenuate postprandial raise in serum lipids and suggested constant alteration in the synthesis or breakdown of sphingolipids and phospholipids which might be a health benefit of EMS consumption. Because serum insulin was not lowered, more research is warranted to reveal possible underlying mechanisms behind the observed changes in the profile of serum lipid metabolome in response to EMS consumption.

Specific Metabolome Profile of Exhaled Breath Condensate in Patients with Shock and Respiratory Failure: A Pilot Study

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Brice Fermier

2016-09-01

Full Text Available Background: Shock includes different pathophysiological mechanisms not fully understood and remains a challenge to manage. Exhaled breath condensate (EBC may contain relevant biomarkers that could help us make an early diagnosis or better understand the metabolic perturbations resulting from this pathological situation. Objective: we aimed to establish the metabolomics signature of EBC from patients in shock with acute respiratory failure in a pilot study. Material and methods: We explored the metabolic signature of EBC in 12 patients with shock compared to 14 controls using LC-HRMS. We used a non-targeted approach, and we performed a multivariate analysis based on Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA to differentiate between the two groups of patients. Results: We optimized the procedure of EBC collection and LC-HRMS detected more than 1000 ions in this fluid. The optimization of multivariate models led to an excellent model of differentiation for both groups (Q2 > 0.4 after inclusion of only 6 ions. Discussion and conclusion: We validated the procedure of EBC collection and we showed that the metabolome profile of EBC may be relevant in characterizing patients with shock. We performed well in distinguishing these patients from controls, and the identification of relevant compounds may be promising for ICC patients.

Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics

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Ping Zhang

2017-01-01

Full Text Available In this study, an integrative high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF based metabolomics approach was performed to evaluate the enantioselective metabolic perturbations in MCF-7 cells after treatment with R-metalaxyl and S-metalaxyl, respectively. Untargeted metabolomics profile, multivariate pattern recognition, metabolites identification, and pathway analysis were determined after metalaxyl enantiomer exposure. Principal component analysis (PCA and partitial least-squares discriminant analysis (PLS-DA directly reflected the enantioselective metabolic perturbations induced by metalaxyl enantiomers. On the basis of multivariate statistical results, a total of 49 metabolites including carbohydrates, amino acids, nucleotides, fatty acids, organic acids, phospholipids, indoles, derivatives, etc. were found to be the most significantly changed metabolites and metabolic fluctuations caused by the same concentration of R-metalaxyl and S-metalaxyl were enantioselective. Pathway analysis indicated that R-metalaxyl and S-metalaxyl mainly affected the 7 and 10 pathways in MCF-7 cells, respectively, implying the perturbed pathways induced by metalaxyl enantiomers were also enantioselective. Furthermore, the significantly perturbed metabolic pathways were highly related to energy metabolism, amino acid metabolism, lipid metabolism, and antioxidant defense. Such results provide more specific insights into the enantioselective metabolic effects of chiral pesticides in breast cancer progression, reveal the underlying mechanisms, and provide available data for the health risk assessments of chiral environmental pollutants at the molecular level.

Metabolome of human gut microbiome is predictive of host dysbiosis.

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Larsen, Peter E; Dai, Yang

2015-01-01

Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome's interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome-host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

Metabolomics as a tool in the identification of dietary biomarkers.

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Gibbons, Helena; Brennan, Lorraine

2017-02-01

Current dietary assessment methods including FFQ, 24-h recalls and weighed food diaries are associated with many measurement errors. In an attempt to overcome some of these errors, dietary biomarkers have emerged as a complementary approach to these traditional methods. Metabolomics has developed as a key technology for the identification of new dietary biomarkers and to date, metabolomic-based approaches have led to the identification of a number of putative biomarkers. The three approaches generally employed when using metabolomics in dietary biomarker discovery are: (i) acute interventions where participants consume specific amounts of a test food, (ii) cohort studies where metabolic profiles are compared between consumers and non-consumers of a specific food and (iii) the analysis of dietary patterns and metabolic profiles to identify nutritypes and biomarkers. The present review critiques the current literature in terms of the approaches used for dietary biomarker discovery and gives a detailed overview of the currently proposed biomarkers, highlighting steps needed for their full validation. Furthermore, the present review also evaluates areas such as current databases and software tools, which are needed to advance the interpretation of results and therefore enhance the utility of dietary biomarkers in nutrition research.

Alteration of metabolomic markers of amino-acid metabolism in piglets with in-feed antibiotics.

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Mu, Chunlong; Yang, Yuxiang; Yu, Kaifan; Yu, Miao; Zhang, Chuanjian; Su, Yong; Zhu, Weiyun

2017-04-01

In-feed antibiotics have been used to promote growth in piglets, but its impact on metabolomics profiles associated with host metabolism is largely unknown. In this study, to test the hypothesis that antibiotic treatment may affect metabolite composition both in the gut and host biofluids, metabolomics profiles were analyzed in antibiotic-treated piglets. Piglets were fed a corn-soy basal diet with or without in-feed antibiotics from postnatal day 7 to day 42. The serum biochemical parameters, metabolomics profiles of the serum, urine, and jejunal digesta, and indicators of microbial metabolism (short-chain fatty acids and biogenic amines) were analyzed. Compared to the control group, antibiotics treatment did not have significant effects on serum biochemical parameters except that it increased (P Antibiotics treatment increased the relative concentrations of metabolites involved in amino-acid metabolism in the serum, while decreased the relative concentrations of most amino acids in the jejunal content. Antibiotics reduced urinary 2-ketoisocaproate and hippurate. Furthermore, antibiotics decreased (P Antibiotics significantly affected the concentrations of biogenic amines, which are derived from microbial amino-acid metabolism. The three major amines, putrescine, cadaverine, and spermidine, were all increased (P antibiotics-treated piglets. These results identified the phenomena that in-feed antibiotics may have significant impact on the metabolomic markers of amino-acid metabolism in piglets.

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

DEFF Research Database (Denmark)

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...

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

International Nuclear Information System (INIS)

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

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

International Nuclear Information System (INIS)

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

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

Energy Technology Data Exchange (ETDEWEB)

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.

Serum metabolome profiles characterized by patients with hepatocellular carcinoma associated with hepatitis B and C.

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Saito, Takafumi; Sugimoto, Masahiro; Okumoto, Kazuo; Haga, Hiroaki; Katsumi, Tomohiro; Mizuno, Kei; Nishina, Taketo; Sato, Sonoko; Igarashi, Kaori; Maki, Hiroko; Tomita, Masaru; Ueno, Yoshiyuki; Soga, Tomoyoshi

2016-07-21

To clarify the characteristics of metabolite profiles in virus-related hepatocellular carcinoma (HCC) patients using serum metabolome analysis. The serum levels of low-molecular-weight metabolites in 68 patients with HCC were quantified using capillary electrophoresis chromatography and mass spectrometry. Thirty and 38 of the patients suffered from hepatitis B virus-related HCC (HCC-B) and hepatitis C virus-related HCC (HCC-C), respectively. The main metabolites characteristic of HCC were those associated with glutathione metabolism, notably 13 γ-glutamyl peptides, which are by-products of glutathione induction. Two major profiles, i.e., concentration patterns, of metabolites were identified in HCC patients, and these were classified into two groups: an HCC-B group and an HCC-C group including some of the HCC-B cases. The receiver operating characteristic curve for the multiple logistic regression model discriminating HCC-B from HCC-C incorporating the concentrations of glutamic acid, methionine and γ-glutamyl-glycine-glycine showed a highly significant area under the curve value of 0.94 (95%CI: 0.89-1.0, P < 0.0001). The serum levels of γ-glutamyl peptides, as well as their concentration patterns, contribute to the development of potential biomarkers for virus-related HCC. The difference in metabolite profiles between HCC-B and HCC-C may reflect the respective metabolic reactions that underlie the different pathogeneses of these two types of HCC.

Blood metabolome profiles of cattle colonized with Escherichia coli O157

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Metabolomics is being increasingly used for diagnosis of asymptomatic/difficult-to-diagnose diseases in humans including parasitic (i.e. protozoan, schistosomal), viral (i.e. cytomegalovirus), bacterial (i.e. cystic fibrosis caused by Pseudomonas), genetic (i.e. autism) and cancer (i.e. gastric canc...

A Plasma Metabolomic Signature of the Exfoliation Syndrome Involves Amino Acids, Acylcarnitines, and Polyamines.

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Leruez, Stéphanie; Bresson, Thomas; Chao de la Barca, Juan M; Marill, Alexandre; de Saint Martin, Grégoire; Buisset, Adrien; Muller, Jeanne; Tessier, Lydie; Gadras, Cédric; Verny, Christophe; Amati-Bonneau, Patrizia; Lenaers, Guy; Gohier, Philippe; Bonneau, Dominique; Simard, Gilles; Milea, Dan; Procaccio, Vincent; Reynier, Pascal

2018-02-01

To determine the plasma metabolomic signature of the exfoliative syndrome (XFS), the most common cause worldwide of secondary open-angle glaucoma. We performed a targeted metabolomic study, using the standardized p180 Biocrates Absolute IDQ p180 kit with a QTRAP 5500 mass spectrometer, to compare the metabolomic profiles of plasma from individuals with XFS (n = 16), and an age- and sex-matched control group with cataract (n = 18). A total of 151 metabolites were detected correctly, 16 of which allowed for construction of an OPLS-DA model with a good predictive capability (Q2cum = 0.51) associated with a low risk of over-fitting (permQ2 = -0.48, CV-ANOVA P-value <0.001). The metabolites contributing the most to the signature were octanoyl-carnitine (C8) and decanoyl-carnitine (C10), the branched-chain amino acids (i.e., isoleucine, leucine, and valine), and tyrosine, all of which were at higher concentrations in the XFS group, whereas spermine and spermidine, together with their precursor acetyl-ornithine, were at lower concentrations than in the control group. We identified a significant metabolomic signature in the plasma of individuals with XFS. Paradoxically, this signature, characterized by lower concentrations of the neuroprotective spermine and spermidine polyamines than in controls, partially overlaps the plasma metabolomic profile associated with insulin resistance, despite the absence of evidence of insulin resistance in XFS.

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

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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.

The effect of acyclic retinoid on the metabolomic profiles of hepatocytes and hepatocellular carcinoma cells.

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Xian-Yang Qin

Full Text Available BACKGROUND/PURPOSE: Acyclic retinoid (ACR is a promising chemopreventive agent for hepatocellular carcinoma (HCC that selectively inhibits the growth of HCC cells (JHH7 but not normal hepatic cells (Hc. To better understand the molecular basis of the selective anti-cancer effect of ACR, we performed nuclear magnetic resonance (NMR-based and capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS-based metabolome analyses in JHH7 and Hc cells after treatment with ACR. METHODOLOGY/PRINCIPAL FINDINGS: NMR-based metabolomics revealed a distinct metabolomic profile of JHH7 cells at 18 h after ACR treatment but not at 4 h after ACR treatment. CE-TOFMS analysis identified 88 principal metabolites in JHH7 and Hc cells after 24 h of treatment with ethanol (EtOH or ACR. The abundance of 71 of these metabolites was significantly different between EtOH-treated control JHH7 and Hc cells, and 49 of these metabolites were significantly down-regulated in the ACR-treated JHH7 cells compared to the EtOH-treated JHH7 cells. Of particular interest, the increase in adenosine-5'-triphosphate (ATP, the main cellular energy source, that was observed in the EtOH-treated control JHH7 cells was almost completely suppressed in the ACR-treated JHH7 cells; treatment with ACR restored ATP to the basal levels observed in both EtOH-control and ACR-treated Hc cells (0.72-fold compared to the EtOH control-treated JHH7 cells. Moreover, real-time PCR analyses revealed that ACR significantly increased the expression of pyruvate dehydrogenase kinases 4 (PDK4, a key regulator of ATP production, in JHH7 cells but not in Hc cells (3.06-fold and 1.20-fold compared to the EtOH control, respectively. CONCLUSIONS/SIGNIFICANCE: The results of the present study suggest that ACR may suppress the enhanced energy metabolism of JHH7 cells but not Hc cells; this occurs at least in part via the cancer-selective enhancement of PDK4 expression. The cancer-selective metabolic pathways

Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women

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Luan, Hemi; Meng, Nan; Liu, Ping

2015-01-01

Background: Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy.Findings: In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were...... collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy.Conclusions: As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data...

Transglycosylated Starch Improves Insulin Response and Alters Lipid and Amino Acid Metabolome in a Growing Pig Model.

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Newman, Monica A; Zebeli, Qendrim; Eberspächer, Eva; Grüll, Dietmar; Molnar, Timea; Metzler-Zebeli, Barbara U

2017-03-16

Due to the functional properties and physiological effects often associated with chemically modified starches, significant interest lies in their development for incorporation in processed foods. This study investigated the effect of transglycosylated cornstarch (TGS) on blood glucose, insulin, and serum metabolome in the pre- and postprandial phase in growing pigs. Eight jugular vein-catheterized barrows were fed two diets containing 72% purified starch (waxy cornstarch (CON) or TGS). A meal tolerance test (MTT) was performed with serial blood sampling for glucose, insulin, lipids, and metabolome profiling. TGS-fed pigs had reduced postprandial insulin ( p phosphatidylcholines and sphingomyelins were generally increased ( p phosphatidylcholines and lysophosphatidylcholines were decreased ( p insulin and glucose metabolism, which may have caused the alterations in serum amino acid and phospholipid metabolome profiles.

Metabolome of human gut microbiome is predictive of host dysbiosis

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Larsen, Peter E.; Dai, Yang

2015-09-14

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

Metabolomic Profiling of the Nectars of Aquilegia pubescens and A. Canadensis.

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Christos Noutsos

Full Text Available To date, variation in nectar chemistry of flowering plants has not been studied in detail. Such variation exerts considerable influence on pollinator-plant interactions, as well as on flower traits that play important roles in the selection of a plant for visitation by specific pollinators. Over the past 60 years the Aquilegia genus has been used as a key model for speciation studies. In this study, we defined the metabolomic profiles of flower samples of two Aquilegia species, A. Canadensis and A. pubescens. We identified a total of 75 metabolites that were classified into six main categories: organic acids, fatty acids, amino acids, esters, sugars, and unknowns. The mean abundances of 25 of these metabolites were significantly different between the two species, providing insights into interspecies variation in floral chemistry. Using the PlantSEED biochemistry database, we found that the majority of these metabolites are involved in biosynthetic pathways. Finally, we explored the annotated genome of A. coerulea, using the PlantSEED pipeline and reconstructed the metabolic network of Aquilegia. This network, which contains the metabolic pathways involved in generating the observed chemical variation, is now publicly available from the DOE Systems Biology Knowledge Base (KBase; http://kbase.us.

Metabolomics for laboratory diagnostics.

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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.

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

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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.

Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics

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Margaux Marie-Hélène, Olivia Luck

2015-07-01

Full Text Available Long-term endurance exercise severely affects metabolism in both human and animal athletes resulting in serious risk of metabolic disorders during or after competition. Young horses (up to 6 years old can compete in races up to 90 km despite limited scientific knowledge of energetic metabolism responses to long distance exercise in these animals. The hypothesis of this study was that there would be a strong effect of endurance exercise on the metabolomic profiles of young horses and that the energetic metabolism response in young horses would be different from that of more experienced horses. Metabolomic profiling is a powerful method that combines Nuclear magnetic resonance (NMR spectrometry with supervised orthogonal projection on latent structure (OPLS statistical analysis. 1H-NMR spectra were obtained from plasma samples drawn from young horses (before and after competition. The spectra obtained before and after the race from the same horse (92 samples were compared using OPLS. The statistical parameters showed the robustness of the model (R2Y=0.947, Q2Y=0.856 and CV-ANOVA p-value < 0.001. For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1. The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism. An OPLS model was calculated to compare spectra obtained on plasma taken after the race from 6-year-old horses and from experienced horses (cross-validated ANOVA p-value < 0.001. The comparison of metabolomic profiles in young horses to those from experienced horses showed that experienced horses maintained their glycemia with higher levels of lactate and a decrease of plasma lipids after the race.

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

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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.

Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins.

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Pallister, Tess; Jennings, Amy; Mohney, Robert P; Yarand, Darioush; Mangino, Massimo; Cassidy, Aedin; MacGregor, Alexander; Spector, Tim D; Menni, Cristina

2016-01-01

Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 adult female twins from the TwinsUK cohort. For each metabolite, linear regression analysis was undertaken in the discovery group (excluding MZ twin pairs discordant [≥1 SD apart] for food group intake) with each food group as a predictor adjusting for age, batch effects, BMI, family relatedness and multiple testing (1.17x10-6 = 0.05/[71 food groups x 601 detected metabolites]). Significant results were then replicated (non-targeted: Pfood groups (Pfood intake for potential use in nutritional epidemiological studies. We compiled our findings into the DietMetab database (http://www.twinsuk.ac.uk/dietmetab-data/), an online tool to investigate our top associations.

Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer

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Bertini, Ivano; Cacciatore, Stefano; Jensen, Benny V

2012-01-01

Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance ((1)H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist...... survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P = 1.33 × 10(-6)). A number of metabolites concurred with the (1)H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that (1)H-NMR profiling of patient serum can provide a strong metabolomic signature of m...

Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows.

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Imhasly, Sandro; Naegeli, Hanspeter; Baumann, Sven; von Bergen, Martin; Luch, Andreas; Jungnickel, Harald; Potratz, Sarah; Gerspach, Christian

2014-06-02

Hepatic lipidosis or fatty liver disease is a major metabolic disorder of high-producing dairy cows that compromises animal performance and, hence, causes heavy economic losses worldwide. This syndrome, occurring during the critical transition from gestation to early lactation, leads to an impaired health status, decreased milk yield, reduced fertility and shortened lifetime. Because the prevailing clinical chemistry parameters indicate advanced liver damage independently of the underlying disease, currently, hepatic lipidosis can only be ascertained by liver biopsy. We hypothesized that the condition of fatty liver disease may be accompanied by an altered profile of endogenous metabolites in the blood of affected animals. To identify potential small-molecule biomarkers as a novel diagnostic alternative, the serum samples of diseased dairy cows were subjected to a targeted metabolomics screen by triple quadrupole mass spectrometry. A subsequent multivariate test involving principal component and linear discriminant analyses yielded 29 metabolites (amino acids, phosphatidylcholines and sphingomyelines) that, in conjunction, were able to distinguish between dairy cows with no hepatic lipidosis and those displaying different stages of the disorder. This proof-of-concept study indicates that metabolomic profiles, including both amino acids and lipids, distinguish hepatic lipidosis from other peripartal disorders and, hence, provide a promising new tool for the diagnosis of hepatic lipidosis. By generating insights into the molecular pathogenesis of hepatic lipidosis, metabolomics studies may also facilitate the prevention of this syndrome.

Can NMR solve some significant challenges in metabolomics?

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Gowda, G.A. Nagana; Raftery, Daniel

2015-01-01

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact biospecimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. PMID:26476597

Can NMR solve some significant challenges in metabolomics?

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Nagana Gowda, G A; Raftery, Daniel

2015-11-01

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. Copyright © 2015 Elsevier Inc. All rights reserved.

Can NMR solve some significant challenges in metabolomics?

Science.gov (United States)

Nagana Gowda, G. A.; Raftery, Daniel

2015-11-01

The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

Global LC/MS Metabolomics Profiling of Calcium Stressed and Immunosuppressant Drug Treated Saccharomyces cerevisiae

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Stefan Jenkins

2013-12-01

Full Text Available Previous studies have shown that calcium stressed Saccharomyces cerevisiae, challenged with immunosuppressant drugs FK506 and Cyclosporin A, responds with comprehensive gene expression changes and attenuation of the generalized calcium stress response. Here, we describe a global metabolomics workflow for investigating the utility of tracking corresponding phenotypic changes. This was achieved by efficiently analyzing relative abundance differences between intracellular metabolite pools from wild-type and calcium stressed cultures, with and without prior immunosuppressant drugs exposure. We used pathway database content from WikiPathways and YeastCyc to facilitate the projection of our metabolomics profiling results onto biological pathways. A key challenge was to increase the coverage of the detected metabolites. This was achieved by applying both reverse phase (RP and aqueous normal phase (ANP chromatographic separations, as well as electrospray ionization (ESI and atmospheric pressure chemical ionization (APCI sources for detection in both ion polarities. Unsupervised principle component analysis (PCA and ANOVA results revealed differentiation between wild-type controls, calcium stressed and immunosuppressant/calcium challenged cells. Untargeted data mining resulted in 247 differentially expressed, annotated metabolites, across at least one pair of conditions. A separate, targeted data mining strategy identified 187 differential, annotated metabolites. All annotated metabolites were subsequently mapped onto curated pathways from YeastCyc and WikiPathways for interactive pathway analysis and visualization. Dozens of pathways showed differential responses to stress conditions based on one or more matches to the list of annotated metabolites or to metabolites that had been identified further by MS/MS. The purine salvage, pantothenate and sulfur amino acid pathways were flagged as being enriched, which is consistent with previously published

Targeted Metabolomics Approach To Detect the Misuse of Steroidal Aromatase Inhibitors in Equine Sports by Biomarker Profiling.

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Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming

2016-01-05

The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups

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

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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

Differential metabolic profiles associated to movement behaviour of stream-resident brown trout (Salmo trutta.

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Neus Oromi

Full Text Available The mechanisms that can contribute in the fish movement strategies and the associated behaviour can be complex and related to the physiology, genetic and ecology of each species. In the case of the brown trout (Salmo trutta, in recent research works, individual differences in mobility have been observed in a population living in a high mountain river reach (Pyrenees, NE Spain. The population is mostly sedentary but a small percentage of individuals exhibit a mobile behavior, mainly upstream movements. Metabolomics can reflect changes in the physiological process and can determine different profiles depending on behaviour. Here, a non-targeted metabolomics approach was used to find possible changes in the blood metabolomic profile of S. trutta related to its movement behaviour, using a minimally invasive sampling. Results showed a differentiation in the metabolomic profiles of the trouts and different level concentrations of some metabolites (e.g. cortisol according to the home range classification (pattern of movements: sedentary or mobile. The change in metabolomic profiles can generally occur during the upstream movement and probably reflects the changes in metabolite profile from the non-mobile season to mobile season. This study reveals the contribution of the metabolomic analyses to better understand the behaviour of organisms.

Differential metabolic profiles associated to movement behaviour of stream-resident brown trout (Salmo trutta).

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Oromi, Neus; Jové, Mariona; Pascual-Pons, Mariona; Royo, Jose Luis; Rocaspana, Rafel; Aparicio, Enric; Pamplona, Reinald; Palau, Antoni; Sanuy, Delfi; Fibla, Joan; Portero-Otin, Manuel

2017-01-01

The mechanisms that can contribute in the fish movement strategies and the associated behaviour can be complex and related to the physiology, genetic and ecology of each species. In the case of the brown trout (Salmo trutta), in recent research works, individual differences in mobility have been observed in a population living in a high mountain river reach (Pyrenees, NE Spain). The population is mostly sedentary but a small percentage of individuals exhibit a mobile behavior, mainly upstream movements. Metabolomics can reflect changes in the physiological process and can determine different profiles depending on behaviour. Here, a non-targeted metabolomics approach was used to find possible changes in the blood metabolomic profile of S. trutta related to its movement behaviour, using a minimally invasive sampling. Results showed a differentiation in the metabolomic profiles of the trouts and different level concentrations of some metabolites (e.g. cortisol) according to the home range classification (pattern of movements: sedentary or mobile). The change in metabolomic profiles can generally occur during the upstream movement and probably reflects the changes in metabolite profile from the non-mobile season to mobile season. This study reveals the contribution of the metabolomic analyses to better understand the behaviour of organisms.

Validation of Metabolomic, Diagnostic, and Prognostic Classifiers of Lung Cancer

Science.gov (United States)

2016-10-01

information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this...Additionally, global metabolomic profiling will allow us to interrogate whether the military have unique exposures that may be related to lung cancer

Radiation Metabolomics: Current Status and Future Directions

Directory of Open Access Journals (Sweden)

Smrithi eSugumaran Menon

2016-02-01

Full Text Available Human exposure to ionizing radiation disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms and peripheral lymphocyte counts are of limited value as organ and tissue specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic ionizing radiation. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure.

Targeted metabolomic profiling indicates structure-based perturbations in serum phospholipids in children with acetaminophen overdose

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Sudeepa Bhattacharyya

Full Text Available Phospholipids are an important class of lipids that act as building blocks of biological cell membranes and participate in a variety of vital cellular functions including cell signaling. Previous studies have reported alterations in phosphatidylcholine (PC and lysophosphatidylcholine (lysoPC metabolism in acetaminophen (APAP-treated animals or cell cultures. However, little is known about phospholipid perturbations in humans with APAP toxicity. In the current study, targeted metabolomic analysis of 180 different metabolites including 14 lysoPCs and 73 PCs was performed in serum samples from children and adolescents hospitalized for APAP overdose. Metabolite profiles in the overdose group were compared to those of healthy controls and hospitalized children receiving low dose APAP for treatment of pain or fever (therapeutic group. PCs and lysoPCs with very long chain fatty acids (VLCFAs were significantly decreased in the overdose group, while those with comparatively shorter chain lengths were increased in the overdose group compared to the therapeutic and control groups. All ether linked PCs were decreased in the overdose group compared to the controls. LysoPC-C26:1 was highly reduced in the overdose group and could discriminate between the overdose and control groups with 100% sensitivity and specificity. The PCs and lysoPCs with VLCFAs showed significant associations with changes in clinical indicators of drug metabolism (APAP protein adducts and liver injury (alanine aminotransferase, or ALT. Thus, a structure-dependent reduction in PCs and lysoPCs was observed in the APAP-overdose group, which may suggest a structure-activity relationship in inhibition of enzymes involved in phospholipid metabolism in APAP toxicity. Keywords: Metabolomics, Phospholipids, Acetaminophen, Hepatotoxicity, Drug

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

Directory of Open Access Journals (Sweden)

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.

Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome.

Science.gov (United States)

Chetwynd, Andrew J; David, Arthur; Hill, Elizabeth M; Abdul-Sada, Alaa

2014-10-01

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra-high-pressure liquid chromatography-nanoelectrospray ionization-time-of-flight MS (nUHPLC-nESI-TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC-ESI-TOFMS, nUHPLC-nESI-TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000-fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC-nESI-TOFMS, supporting implementation of this platform as a novel approach for high-throughput (xeno)metabolomics. Copyright © 2014 John Wiley & Sons, Ltd.

Data fusion in metabolomic cancer diagnostics

DEFF Research Database (Denmark)

Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco

2013-01-01

We have recently shown that fluorescence spectroscopy of plasma samples has promising abilities regarding early detection of colorectal cancer. In the present paper, these results were further developed by combining fluorescence with the biomarkers, CEA and TIMP-1 and traditional metabolomic meas...... measurements in the form of (1)H NMR spectroscopy. The results indicate that using an extensive profile established by combining such measurements together with the biomarkers is better than using single markers....

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis

OpenAIRE

Ahn, Joong Kyong; Kim, Sooah; Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

2015-01-01

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α...

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

Science.gov (United States)

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.

Metabolomics as an emerging strategy for the investigation of yogurt components

NARCIS (Netherlands)

Settachaimongkon, S.; Valenberg, van H.J.F.; Smid, E.J.

2017-01-01

The advanced development in metabolomics allows discovery of a wide range of metabolites in complex biological systems including food matrices. This analytical approach provides opportunities to attain a global metabolite profile and discover potential biomarkers and various chemical contaminants

Urinary metabolomic profiling in mice with diet-induced obesity and type 2 diabetes mellitus after treatment with metformin, vildagliptin and their combination.

Science.gov (United States)

Pelantová, Helena; Bugáňová, Martina; Holubová, Martina; Šedivá, Blanka; Zemenová, Jana; Sýkora, David; Kaválková, Petra; Haluzík, Martin; Železná, Blanka; Maletínská, Lenka; Kuneš, Jaroslav; Kuzma, Marek

2016-08-15

Metformin, vildagliptin and their combination are widely used for the treatment of diabetes, but little is known about the metabolic responses to these treatments. In the present study, NMR-based metabolomics was applied to detect changes in the urinary metabolomic profile of a mouse model of diet-induced obesity in response to these treatments. Additionally, standard biochemical parameters and the expression of enzymes involved in glucose and fat metabolism were monitored. Significant correlations were observed between several metabolites (e.g., N-carbamoyl-β-alanine, N1-methyl-4-pyridone-3-carboxamide, N1-methyl-2-pyridone-5-carboxamide, glucose, 3-indoxyl sulfate, dimethylglycine and several acylglycines) and the area under the curve of glucose concentrations during the oral glucose tolerance test. The present study is the first to present N-carbamoyl-β-alanine as a potential marker of type 2 diabetes mellitus and consequently to demonstrate the efficacies of the applied antidiabetic interventions. Moreover, the elevated acetate level observed after vildagliptin administration might reflect increased fatty acid oxidation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

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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

Transglycosylated Starch Improves Insulin Response and Alters Lipid and Amino Acid Metabolome in a Growing Pig Model

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Monica A. Newman

2017-03-01

Full Text Available Due to the functional properties and physiological effects often associated with chemically modified starches, significant interest lies in their development for incorporation in processed foods. This study investigated the effect of transglycosylated cornstarch (TGS on blood glucose, insulin, and serum metabolome in the pre- and postprandial phase in growing pigs. Eight jugular vein-catheterized barrows were fed two diets containing 72% purified starch (waxy cornstarch (CON or TGS. A meal tolerance test (MTT was performed with serial blood sampling for glucose, insulin, lipids, and metabolome profiling. TGS-fed pigs had reduced postprandial insulin (p < 0.05 and glucose (p < 0.10 peaks compared to CON-fed pigs. The MTT showed increased (p < 0.05 serum urea with TGS-fed pigs compared to CON, indicative of increased protein catabolism. Metabolome profiling showed reduced (p < 0.05 amino acids such as alanine and glutamine with TGS, suggesting increased gluconeogenesis compared to CON, probably due to a reduction in available glucose. Of all metabolites affected by dietary treatment, alkyl-acyl-phosphatidylcholines and sphingomyelins were generally increased (p < 0.05 preprandially, whereas diacyl-phosphatidylcholines and lysophosphatidylcholines were decreased (p < 0.05 postprandially in TGS-fed pigs compared to CON. In conclusion, TGS led to changes in postprandial insulin and glucose metabolism, which may have caused the alterations in serum amino acid and phospholipid metabolome profiles.

Metabolomic analysis of three Mollicute species.

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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.

Comparison of earthworm responses to petroleum hydrocarbon exposure in aged field contaminated soil using traditional ecotoxicity endpoints and 1H NMR-based metabolomics

International Nuclear Information System (INIS)

Whitfield Åslund, Melissa; Stephenson, Gladys L.; Simpson, André J.; Simpson, Myrna J.

2013-01-01

1 H NMR metabolomics and conventional ecotoxicity endpoints were used to examine the response of earthworms exposed to petroleum hydrocarbons (PHCs) in soil samples collected from a site that was contaminated with crude oil from a pipeline failure in the mid-1990s. The conventional ecotoxicity tests showed that the soils were not acutely toxic to earthworms (average survival ≥90%), but some soil samples impaired reproduction endpoints by >50% compared to the field control soil. Additionally, metabolomics revealed significant relationships between earthworm metabolic profiles (collected after 2 or 14 days of exposure) and soil properties including soil PHC concentration. Further comparisons by partial least squares regression revealed a significant relationship between the earthworm metabolomic data (collected after only 2 or 14 days) and the reproduction endpoints (measured after 63 days). Therefore, metabolomic responses measured after short exposure periods may be predictive of chronic, ecologically relevant toxicity endpoints for earthworms exposed to soil contaminants. -- Highlights: •Earthworm response to petroleum hydrocarbon exposure in soil is examined. •Metabolomics shows significant changes to metabolic profile after 2 days. •Significant relationships observed between metabolomic and reproduction endpoints. •Metabolomics may have value as a rapid screening tool for chronic toxicity. -- Earthworm metabolomic responses measured after 2 and 14 days are compared to traditional earthworm ecotoxicity endpoints (survival and reproduction) in petroleum hydrocarbon contaminated soil

NMR-based milk metabolomics

DEFF Research Database (Denmark)

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-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking...... compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining...

Hepatocyte MyD88 affects bile acids, gut microbiota and metabolome contributing to regulate glucose and lipid metabolism

DEFF Research Database (Denmark)

Duparc, Thibaut; Plovier, Hubert; Marrachelli, Vannina G

2017-01-01

performed microarrays and quantitative PCRs in the liver. In addition, we investigated the gut microbiota composition, bile acid profile and both liver and plasma metabolome. We analysed the expression pattern of genes in the liver of obese humans developing non-alcoholic steatohepatitis (NASH). RESULTS...... proliferator activator receptor-α, farnesoid X receptor (FXR), liver X receptors and STAT3) and bile acid profiles involved in glucose, lipid metabolism and inflammation. In addition to these alterations, the genetic deletion of MyD88 in hepatocytes changes the gut microbiota composition and their metabolomes...

Proteomic and metabolomic profiles of marine Vibrio sp. 010 in response to an antifoulant challenge

KAUST Repository

Chandramouli, Kondethimmanahalli; Dash, Swagatika; Zhang, Yu; Ravasi, Timothy; Qian, Peiyuan

2013-01-01

Vibrio spp. have the ability to form biofilms, which may contribute to the subsequent successful colonization by microfouling and macrofouling organisms. The effects of an antifouling compound, poly-ether B, on Vibrio sp. 010 were investigated using flow cytometry, proteomics, and metabolomics. A 2-D gel-based proteomic analysis was used to identify proteins responsive to poly-ether B treatment. The profiles of biofilm metabolites were analyzed by ultra-performance liquid chromatography-mass spectrometry. Poly-ether B caused a significant reduction in viability. The proteins affected by the treatment were related to nucleotide metabolism, the glyoxylate cycle, and stress responses. Metabolites such as tripeptides, fatty acids, and quorum-sensing molecules were regulated differentially. Down-regulation of proteins and metabolites potentially led to a loss in colonisation ability, thereby affecting the structure of the biofilm. These results suggest that the proteins and metabolites identified may serve as target molecules for potent antifouling compounds. © 2013 Copyright Taylor and Francis Group, LLC.

Proteomic and metabolomic profiles of marine Vibrio sp. 010 in response to an antifoulant challenge

KAUST Repository

Chandramouli, Kondethimmanahalli

2013-08-01

Vibrio spp. have the ability to form biofilms, which may contribute to the subsequent successful colonization by microfouling and macrofouling organisms. The effects of an antifouling compound, poly-ether B, on Vibrio sp. 010 were investigated using flow cytometry, proteomics, and metabolomics. A 2-D gel-based proteomic analysis was used to identify proteins responsive to poly-ether B treatment. The profiles of biofilm metabolites were analyzed by ultra-performance liquid chromatography-mass spectrometry. Poly-ether B caused a significant reduction in viability. The proteins affected by the treatment were related to nucleotide metabolism, the glyoxylate cycle, and stress responses. Metabolites such as tripeptides, fatty acids, and quorum-sensing molecules were regulated differentially. Down-regulation of proteins and metabolites potentially led to a loss in colonisation ability, thereby affecting the structure of the biofilm. These results suggest that the proteins and metabolites identified may serve as target molecules for potent antifouling compounds. © 2013 Copyright Taylor and Francis Group, LLC.

Nuclear magnetic resonance based metabolomics and liver diseases: Recent advances and future clinical applications.

Science.gov (United States)

Amathieu, Roland; Triba, Mohamed Nawfal; Goossens, Corentine; Bouchemal, Nadia; Nahon, Pierre; Savarin, Philippe; Le Moyec, Laurence

2016-01-07

Metabolomics is defined as the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification. It is an "omics" technique that is situated downstream of genomics, transcriptomics and proteomics. Metabolomics is recognized as a promising technique in the field of systems biology for the evaluation of global metabolic changes. During the last decade, metabolomics approaches have become widely used in the study of liver diseases for the detection of early biomarkers and altered metabolic pathways. It is a powerful technique to improve our pathophysiological knowledge of various liver diseases. It can be a useful tool to help clinicians in the diagnostic process especially to distinguish malignant and non-malignant liver disease as well as to determine the etiology or severity of the liver disease. It can also assess therapeutic response or predict drug induced liver injury. Nevertheless, the usefulness of metabolomics is often not understood by clinicians, especially the concept of metabolomics profiling or fingerprinting. In the present work, after a concise description of the different techniques and processes used in metabolomics, we will review the main research on this subject by focusing specifically on in vitro proton nuclear magnetic resonance spectroscopy based metabolomics approaches in human studies. We will first consider the clinical point of view enlighten physicians on this new approach and emphasis its future use in clinical "routine".

Phenotyping of Chronic Obstructive Pulmonary Disease Based on the Integration of Metabolomes and Clinical Characteristics

Directory of Open Access Journals (Sweden)

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.

Profiling of altered metabolomic states in Nicotiana tabacum cells induced by priming agents

CSIR Research Space (South Africa)

Mhlongo, MI

2016-10-01

Full Text Available tabacum cells. Identified biomarkers were then compared to responses induced by three phytohormones—abscisic acid, methyljasmonate, and salicylic acid. Altered metabolomes were studied using a metabolite fingerprinting approach based on liquid...

Metabolomics and Epidemiology Working Group

Science.gov (United States)

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.

Web-based resources for mass-spectrometry-based metabolomics: a user's guide.

Science.gov (United States)

Tohge, Takayuki; Fernie, Alisdair R

2009-03-01

In recent years, a plethora of web-based tools aimed at supporting mass-spectrometry-based metabolite profiling and metabolomics applications have appeared. Given the huge hurdles presented by the chemical diversity and dynamic range of the metabolites present in the plant kingdom, profiling the levels of a broad range of metabolites is highly challenging. Given the scale and costs involved in defining the plant metabolome, it is imperative that data are effectively shared between laboratories pursuing this goal. However, ensuring accurate comparison of samples run on the same machine within the same laboratory, let alone cross-machine and cross-laboratory comparisons, requires both careful experimentation and data interpretation. In this review, we present an overview of currently available software that aids either in peak identification or in the related field of peak alignment as well as those with utility in defining structural information of compounds and metabolic pathways.

Biomarker Discovery in Human Prostate Cancer: an Update in Metabolomics Studies

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Ana Rita Lima

2016-08-01

Full Text Available Prostate cancer (PCa is the most frequently diagnosed cancer and the second leading cause of cancer death among men in Western countries. Current screening techniques are based on the measurement of serum prostate specific antigen (PSA levels and digital rectal examination. A decisive diagnosis of PCa is based on prostate biopsies; however, this approach can lead to false-positive and false-negative results. Therefore, it is important to discover new biomarkers for the diagnosis of PCa, preferably noninvasive ones. Metabolomics is an approach that allows the analysis of the entire metabolic profile of a biological system. As neoplastic cells have a unique metabolic phenotype related to cancer development and progression, the identification of dysfunctional metabolic pathways using metabolomics can be used to discover cancer biomarkers and therapeutic targets. In this study, we review several metabolomics studies performed in prostatic fluid, blood plasma/serum, urine, tissues and immortalized cultured cell lines with the objective of discovering alterations in the metabolic phenotype of PCa and thus discovering new biomarkers for the diagnosis of PCa. Encouraging results using metabolomics have been reported for PCa, with sarcosine being one of the most promising biomarkers identified to date. However, the use of sarcosine as a PCa biomarker in the clinic remains a controversial issue within the scientific community. Beyond sarcosine, other metabolites are considered to be biomarkers for PCa, but they still need clinical validation. Despite the lack of metabolomics biomarkers reaching clinical practice, metabolomics proved to be a powerful tool in the discovery of new biomarkers for PCa detection.

Metabolic drift in the aging brain.

Science.gov (United States)

Ivanisevic, Julijana; Stauch, Kelly L; Petrascheck, Michael; Benton, H Paul; Epstein, Adrian A; Fang, Mingliang; Gorantla, Santhi; Tran, Minerva; Hoang, Linh; Kurczy, Michael E; Boska, Michael D; Gendelman, Howard E; Fox, Howard S; Siuzdak, Gary

2016-05-01

Brain function is highly dependent upon controlled energy metabolism whose loss heralds cognitive impairments. This is particularly notable in the aged individuals and in age-related neurodegenerative diseases. However, how metabolic homeostasis is disrupted in the aging brain is still poorly understood. Here we performed global, metabolomic and proteomic analyses across different anatomical regions of mouse brain at different stages of its adult lifespan. Interestingly, while severe proteomic imbalance was absent, global-untargeted metabolomics revealed an energymetabolic drift or significant imbalance in core metabolite levels in aged mouse brains. Metabolic imbalance was characterized by compromised cellular energy status (NAD decline, increased AMP/ATP, purine/pyrimidine accumulation) and significantly altered oxidative phosphorylation and nucleotide biosynthesis and degradation. The central energy metabolic drift suggests a failure of the cellular machinery to restore metabostasis (metabolite homeostasis) in the aged brain and therefore an inability to respond properly to external stimuli, likely driving the alterations in signaling activity and thus in neuronal function and communication.

Integration of metabolomics and transcriptomics in nanotoxicity studies.

Science.gov (United States)

Shin, Tae Hwan; Lee, Da Yeon; Lee, Hyeon-Seong; Park, Hyung Jin; Jin, Moon Suk; Paik, Man-Jeong; Manavalan, Balachandran; Mo, Jung-Soon; Lee, Gwang

2018-01-01

Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics". [BMB Reports 2018; 51(1): 14-20].

The Role of Mass Spectrometry-Based Metabolomics in Medical Countermeasures Against Radiation

Science.gov (United States)

Patterson, Andrew D.; Lanz, Christian; Gonzalez, Frank J.; Idle, Jeffrey R.

2013-01-01

Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry (CMCR) was established to develop field-deployable biodosimeters based, in principle, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter. PMID:19890938

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

Directory of Open Access Journals (Sweden)

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.

A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.

Science.gov (United States)

Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang

2014-04-15

Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.

Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate

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Misra, Biswapriya B.; de Armas, Evaldo; Tong, Zhaohui; Chen, Sixue

2015-01-01

Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs) are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs) represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus) to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3 -). Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3 - responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3 -. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids), and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids) as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage. PMID:26641455

Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study.

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Vijay R Varma

2018-01-01

Full Text Available The metabolic basis of Alzheimer disease (AD is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression.Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180 assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA (N = 44, mean age = 81.33, % female = 36.36 from AD (N = 15, control (CN; N = 14, and "asymptomatic Alzheimer's disease" (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15 participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes-sphingolipids and glycerophospholipids-that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer's Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63 and preclinical (BLSA (N = 207, mean age = 78.68, % female = 42.63 AD, in which we tested their associations with magnetic resonance imaging (MRI measures of AD-related brain atrophy, cerebrospinal fluid (CSF biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of

Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study

Science.gov (United States)

Oommen, Anup M.; Varma, Sudhir; Casanova, Ramon; An, Yang; O’Brien, Richard; Pletnikova, Olga; Kastenmueller, Gabi; Doraiswamy, P. Murali; Kaddurah-Daouk, Rima; Thambisetty, Madhav

2018-01-01

Background The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. Methods and findings Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and “asymptomatic Alzheimer’s disease” (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes—sphingolipids and glycerophospholipids—that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer’s Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that

The food metabolome

DEFF Research Database (Denmark)

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...

Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods

Energy Technology Data Exchange (ETDEWEB)

Bingol, Kerem

2018-04-18

Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome manual absolute quantitation step of metabolites in 1D 1H NMR spectra. This provides more consistency between inter-laboratory comparisons. Integration of 2D NMR metabolomics databases under a unified web server allowed very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry. These hybrid NMR/MS approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing to profile ever larger number of metabolites in application studies.

MicroRNA expression profiling of the porcine developing brain

DEFF Research Database (Denmark)

Podolska, Agnieszka; Kaczkowski, Bogumil; Busk, Peter Kamp

2011-01-01

MicroRNAs are small, non-coding RNA molecules that regulate gene expression at the post-transcriptional level and play an important role in the control of developmental and physiological processes. In particular, the developing brain contains an impressive diversity of microRNAs. Most micro...... and the growth curve when compared to humans. Considering these similarities, studies examining microRNA expression during porcine brain development could potentially be used to predict the expression profile and role of microRNAs in the human brain....

Quality assurance of metabolomics.

Science.gov (United States)

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.

Oxidative stress, metabolomics profiling, and mechanism of local anesthetic induced cell death in yeast

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Cory H.T. Boone

2017-08-01

glutathione to combat the oxidative cellular environment, glycolytic to PPP cycling of carbon generating NADPH, obstruction of carbon flow through the TCA cycle, decreased ATP generation, and metacaspase dependent apoptotic cell death. Keywords: Local anesthetic toxicity, Oxidative stress, Metabolomics profiling, Apoptotic cell death pathways, Flow cytometry, Mass spectrometry

Transcriptomic and metabolomic profiling of Zymomonas mobilis during aerobic and anaerobic fermentations

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Palumbo Anthony V

2009-01-01

Full Text Available Abstract Background Zymomonas mobilis ZM4 (ZM4 produces near theoretical yields of ethanol with high specific productivity and recombinant strains are able to ferment both C-5 and C-6 sugars. Z. mobilis performs best under anaerobic conditions, but is an aerotolerant organism. However, the genetic and physiological basis of ZM4's response to various stresses is understood poorly. Results In this study, transcriptomic and metabolomic profiles for ZM4 aerobic and anaerobic fermentations were elucidated by microarray analysis and by high-performance liquid chromatography (HPLC, gas chromatography (GC and gas chromatography-mass spectrometry (GC-MS analyses. In the absence of oxygen, ZM4 consumed glucose more rapidly, had a higher growth rate, and ethanol was the major end-product. Greater amounts of other end-products such as acetate, lactate, and acetoin were detected under aerobic conditions and at 26 h there was only 1.7% of the amount of ethanol present aerobically as there was anaerobically. In the early exponential growth phase, significant differences in gene expression were not observed between aerobic and anaerobic conditions via microarray analysis. HPLC and GC analyses revealed minor differences in extracellular metabolite profiles at the corresponding early exponential phase time point. Differences in extracellular metabolite profiles between conditions became greater as the fermentations progressed. GC-MS analysis of stationary phase intracellular metabolites indicated that ZM4 contained lower levels of amino acids such as alanine, valine and lysine, and other metabolites like lactate, ribitol, and 4-hydroxybutanoate under anaerobic conditions relative to aerobic conditions. Stationary phase microarray analysis revealed that 166 genes were significantly differentially expressed by more than two-fold. Transcripts for Entner-Doudoroff (ED pathway genes (glk, zwf, pgl, pgk, and eno and gene pdc, encoding a key enzyme leading to ethanol

The Emerging Field of Quantitative Blood Metabolomics for Biomarker Discovery in Critical Illnesses

Science.gov (United States)

Serkova, Natalie J.; Standiford, Theodore J.

2011-01-01

Metabolomics, a science of systems biology, is the global assessment of endogenous metabolites within a biologic system and represents a “snapshot” reading of gene function, enzyme activity, and the physiological landscape. Metabolite detection, either individual or grouped as a metabolomic profile, is usually performed in cells, tissues, or biofluids by either nuclear magnetic resonance spectroscopy or mass spectrometry followed by sophisticated multivariate data analysis. Because loss of metabolic homeostasis is common in critical illness, the metabolome could have many applications, including biomarker and drug target identification. Metabolomics could also significantly advance our understanding of the complex pathophysiology of acute illnesses, such as sepsis and acute lung injury/acute respiratory distress syndrome. Despite this potential, the clinical community is largely unfamiliar with the field of metabolomics, including the methodologies involved, technical challenges, and, most importantly, clinical uses. Although there is evidence of successful preclinical applications, the clinical usefulness and application of metabolomics in critical illness is just beginning to emerge, the advancement of which hinges on linking metabolite data to known and validated clinically relevant indices. In addition, other important aspects, such as patient selection, sample collection, and processing, as well as the needed multivariate data analysis, have to be taken into consideration before this innovative approach to biomarker discovery can become a reliable tool in the intensive care unit. The purpose of this review is to begin to familiarize clinicians with the field of metabolomics and its application for biomarker discovery in critical illnesses such as sepsis. PMID:21680948

Women with preterm birth have a distinct cervicovaginal metabolome.

Science.gov (United States)

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.

Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

Science.gov (United States)

Zhang, Aihua; Sun, Hui; Yan, Guangli; Wang, Ping; Wang, Xijun

2016-01-01

Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

Experimental Chagas disease-induced perturbations of the fecal microbiome and metabolome.

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McCall, Laura-Isobel; Tripathi, Anupriya; Vargas, Fernando; Knight, Rob; Dorrestein, Pieter C; Siqueira-Neto, Jair L

2018-03-01

Trypanosoma cruzi parasites are the causative agents of Chagas disease. These parasites infect cardiac and gastrointestinal tissues, leading to local inflammation and tissue damage. Digestive Chagas disease is associated with perturbations in food absorption, intestinal traffic and defecation. However, the impact of T. cruzi infection on the gut microbiota and metabolome have yet to be characterized. In this study, we applied mass spectrometry-based metabolomics and 16S rRNA sequencing to profile infection-associated alterations in fecal bacterial composition and fecal metabolome through the acute-stage and into the chronic stage of infection, in a murine model of Chagas disease. We observed joint microbial and chemical perturbations associated with T. cruzi infection. These included alterations in conjugated linoleic acid (CLA) derivatives and in specific members of families Ruminococcaceae and Lachnospiraceae, as well as alterations in secondary bile acids and members of order Clostridiales. These results highlight the importance of multi-'omics' and poly-microbial studies in understanding parasitic diseases in general, and Chagas disease in particular.

Characterizing Blood Metabolomics Profiles Associated with Self-Reported Food Intakes in Female Twins.

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Tess Pallister

Full Text Available Using dietary biomarkers in nutritional epidemiological studies may better capture exposure and improve the level at which diet-disease associations can be established and explored. Here, we aimed to identify and evaluate reproducibility of novel biomarkers of reported habitual food intake using targeted and non-targeted metabolomic blood profiling in a large twin cohort. Reported intakes of 71 food groups, determined by FFQ, were assessed against 601 fasting blood metabolites in over 3500 adult female twins from the TwinsUK cohort. For each metabolite, linear regression analysis was undertaken in the discovery group (excluding MZ twin pairs discordant [≥1 SD apart] for food group intake with each food group as a predictor adjusting for age, batch effects, BMI, family relatedness and multiple testing (1.17x10-6 = 0.05/[71 food groups x 601 detected metabolites]. Significant results were then replicated (non-targeted: P<0.05; targeted: same direction in the MZ discordant twin group and results from both analyses meta-analyzed. We identified and replicated 180 significant associations with 39 food groups (P<1.17x10-6, overall consisting of 106 different metabolites (74 known and 32 unknown, including 73 novel associations. In particular we identified trans-4-hydroxyproline as a potential marker of red meat intake (0.075[0.009]; P = 1.08x10-17, ergothioneine as a marker of mushroom consumption (0.181[0.019]; P = 5.93x10-22, and three potential markers of fruit consumption (top association: apple and pears: including metabolites derived from gut bacterial transformation of phenolic compounds, 3-phenylpropionate (0.024[0.004]; P = 1.24x10-8 and indolepropionate (0.026[0.004]; P = 2.39x10-9, and threitol (0.033[0.003]; P = 1.69x10-21. With the largest nutritional metabolomics dataset to date, we have identified 73 novel candidate biomarkers of food intake for potential use in nutritional epidemiological studies. We compiled our findings into the

Metabolome strategy against Edwardsiella tarda infection through glucose-enhanced metabolic modulation in tilapias.

Science.gov (United States)

Peng, Bo; Ma, Yan-Mei; Zhang, Jian-Ying; Li, Hui

2015-08-01

Edwardsiella tarda causes fish disease and great economic loss. However, metabolic strategy against the pathogen remains unexplored. In the present study, GC-MS based metabolomics was used to investigate the metabolic profile from tilapias infected by sublethal dose of E. tarda. The metabolic differences between the dying group and survival group allow the identification of key pathways and crucial metabolites during infections. More importantly, those metabolites may modulate the survival-related metabolome to enhance the anti-infective ability. Our data showed that tilapias generated two different strategies, survival-metabolome and death-metabolome, to encounter EIB202 infection, leading to differential outputs of the survival and dying. Glucose was the most crucial biomarker, which was upregulated and downregulated in the survival and dying groups, respectively. Exogenous glucose by injection or oral administration enhanced hosts' ability against EIB202 infection and increased the chances of survival. These findings highlight that host mounts the metabolic strategy to cope with bacterial infection, from which crucial biomarkers may be identified to enhance the metabolic strategy. Copyright © 2015 Elsevier Ltd. All rights reserved.

A metabolomic profile is associated with the risk of incident coronary heart disease

NARCIS (Netherlands)

Vaarhorst, A.A.M.; Verhoeven, A.; Weller, C.M.; Böhringer, S.; Göraler, S.; Meissner, A.; Deelder, A.M.; Henneman, P.; Gorgels, A.P.M.; van den Brandt, P.A.; Schouten, L.J.; van Greevenbroek, M.M.; Merry, A.H.H.; Verschuren, W.M.M.; van den Maagdenberg, A.M.J.M.; Willems van Dijk, K.; Isaacs, A.; Boomsma, D.I.; Oostra, B.A.; van Duijn, C.M.; Jukema, J.W.; Boer, J.M.A.; Feskens, E.; Heijmans, B.T.; Slagboom, P.E.

2014-01-01

Background Metabolomics, defined as the comprehensive identification and quantification of low-molecular-weight metabolites to be found in a biological sample, has been put forward as a potential tool for classifying individuals according to their risk of coronary heart disease (CHD). Here, we

Nanoparticle-Assisted Metabolomics

Directory of Open Access Journals (Sweden)

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.

Metabolomic Studies in Drosophila.

Science.gov (United States)

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.

Variable selection methods in PLS regression - a comparison study on metabolomics data

DEFF Research Database (Denmark)

Karaman, İbrahim; Hedemann, Mette Skou; Knudsen, Knud Erik Bach

. 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 LC-MS based metabolomic approach. References 1. Lê Cao KA, Rossouw D, Robert-Granié C, Besse P: A Sparse PLS for Variable Selection when...... integrated approach. Due to the high number of variables in data sets (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. Variable selection (or removal of irrelevant...... different strategies for variable selection on PLSR method were considered and compared with respect to selected subset of variables and the possibility for biological validation. Sparse PLSR [1] as well as PLSR with Jack-knifing [2] was applied to data in order to achieve variable selection prior...

A functional genomics approach using metabolomics and in silico pathway analysis

DEFF Research Database (Denmark)

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...

The future of metabolomics in ELIXIR

Science.gov (United States)

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

The future of metabolomics in ELIXIR.

Science.gov (United States)

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.

Feasibility Study of NMR Based Serum Metabolomic Profiling to Animal Health Monitoring: A Case Study on Iron Storage Disease in Captive Sumatran Rhinoceros (Dicerorhinus sumatrensis).

Science.gov (United States)

Watanabe, Miki; Roth, Terri L; Bauer, Stuart J; Lane, Adam; Romick-Rosendale, Lindsey E

2016-01-01

A variety of wildlife species maintained in captivity are susceptible to iron storage disease (ISD), or hemochromatosis, a disease resulting from the deposition of excess iron into insoluble iron clusters in soft tissue. Sumatran rhinoceros (Dicerorhinus sumatrensis) is one of the rhinoceros species that has evolutionarily adapted to a low-iron diet and is susceptible to iron overload. Hemosiderosis is reported at necropsy in many African black and Sumatran rhinoceroses but only a small number of animals reportedly die from hemochromatosis. The underlying cause and reasons for differences in susceptibility to hemochromatosis within the taxon remains unclear. Although serum ferritin concentrations have been useful in monitoring the progression of ISD in many species, there is some question regarding their value in diagnosing hemochromatosis in the Sumatran rhino. To investigate the metabolic changes during the development of hemochromatosis and possibly increase our understanding of its progression and individual susceptibility differences, the serum metabolome from a Sumatran rhinoceros was investigated by nuclear magnetic resonance (NMR)-based metabolomics. The study involved samples from female rhinoceros at the Cincinnati Zoo (n = 3), including two animals that died from liver failure caused by ISD, and the Sungai Dusun Rhinoceros Conservation Centre in Peninsular Malaysia (n = 4). Principal component analysis was performed to visually and statistically compare the metabolic profiles of the healthy animals. The results indicated that significant differences were present between the animals at the zoo and the animals in the conservation center. A comparison of the 43 serum metabolomes of three zoo rhinoceros showed two distinct groupings, healthy (n = 30) and unhealthy (n = 13). A total of eighteen altered metabolites were identified in healthy versus unhealthy samples. Results strongly suggest that NMR-based metabolomics is a valuable tool for animal health

Feasibility Study of NMR Based Serum Metabolomic Profiling to Animal Health Monitoring: A Case Study on Iron Storage Disease in Captive Sumatran Rhinoceros (Dicerorhinus sumatrensis.

Directory of Open Access Journals (Sweden)

Miki Watanabe

Full Text Available A variety of wildlife species maintained in captivity are susceptible to iron storage disease (ISD, or hemochromatosis, a disease resulting from the deposition of excess iron into insoluble iron clusters in soft tissue. Sumatran rhinoceros (Dicerorhinus sumatrensis is one of the rhinoceros species that has evolutionarily adapted to a low-iron diet and is susceptible to iron overload. Hemosiderosis is reported at necropsy in many African black and Sumatran rhinoceroses but only a small number of animals reportedly die from hemochromatosis. The underlying cause and reasons for differences in susceptibility to hemochromatosis within the taxon remains unclear. Although serum ferritin concentrations have been useful in monitoring the progression of ISD in many species, there is some question regarding their value in diagnosing hemochromatosis in the Sumatran rhino. To investigate the metabolic changes during the development of hemochromatosis and possibly increase our understanding of its progression and individual susceptibility differences, the serum metabolome from a Sumatran rhinoceros was investigated by nuclear magnetic resonance (NMR-based metabolomics. The study involved samples from female rhinoceros at the Cincinnati Zoo (n = 3, including two animals that died from liver failure caused by ISD, and the Sungai Dusun Rhinoceros Conservation Centre in Peninsular Malaysia (n = 4. Principal component analysis was performed to visually and statistically compare the metabolic profiles of the healthy animals. The results indicated that significant differences were present between the animals at the zoo and the animals in the conservation center. A comparison of the 43 serum metabolomes of three zoo rhinoceros showed two distinct groupings, healthy (n = 30 and unhealthy (n = 13. A total of eighteen altered metabolites were identified in healthy versus unhealthy samples. Results strongly suggest that NMR-based metabolomics is a valuable tool for

Changes in the Metabolome in Response to Low-Dose Exposure to Environmental Chemicals Used in Personal Care Products during Different Windows of Susceptibility.

Science.gov (United States)

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.

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context.

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Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens; Gobbo-Neto, Leonardo

2018-01-01

Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

Monitoring Metabolite Profiles of Cannabis sativa L. Trichomes during Flowering Period Using 1H NMR-Based Metabolomics and Real-Time PCR.

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Happyana, Nizar; Kayser, Oliver

2016-08-01

Cannabis sativa trichomes are glandular structures predominantly responsible for the biosynthesis of cannabinoids, the biologically active compounds unique to this plant. To the best of our knowledge, most metabolomic works on C. sativa that have been reported previously focused their investigations on the flowers and leaves of this plant. In this study, (1)H NMR-based metabolomics and real-time PCR analysis were applied for monitoring the metabolite profiles of C. sativa trichomes, variety Bediol, during the last 4 weeks of the flowering period. Partial least squares discriminant analysis models successfully classified metabolites of the trichomes based on the harvest time. Δ (9)-Tetrahydrocannabinolic acid (1) and cannabidiolic acid (2) constituted the vital differential components of the organic preparations, while asparagine, glutamine, fructose, and glucose proved to be their water-extracted counterparts. According to RT-PCR analysis, gene expression levels of olivetol synthase and olivetolic acid cyclase influenced the accumulation of cannabinoids in the Cannabis trichomes during the monitoring time. Moreover, quantitative (1)H NMR and RT-PCR analysis of the Cannabis trichomes suggested that the gene regulation of cannabinoid biosynthesis in the C. sativa variety Bediol is unique when compared with other C. sativa varieties. Georg Thieme Verlag KG Stuttgart · New York.

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

Science.gov (United States)

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.

Pre-analytic evaluation of volumetric absorptive microsampling and integration in a mass spectrometry-based metabolomics workflow.

Science.gov (United States)

Volani, Chiara; Caprioli, Giulia; Calderisi, Giovanni; Sigurdsson, Baldur B; Rainer, Johannes; Gentilini, Ivo; Hicks, Andrew A; Pramstaller, Peter P; Weiss, Guenter; Smarason, Sigurdur V; Paglia, Giuseppe

2017-10-01

Volumetric absorptive microsampling (VAMS) is a novel approach that allows single-drop (10 μL) blood collection. Integration of VAMS with mass spectrometry (MS)-based untargeted metabolomics is an attractive solution for both human and animal studies. However, to boost the use of VAMS in metabolomics, key pre-analytical questions need to be addressed. Therefore, in this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. We first evaluated the best extraction procedure for the polar metabolome and found that the highest number and amount of metabolites were recovered upon extraction with acetonitrile/water (70:30). In contrast, basic conditions (pH 9) resulted in divergent metabolite profiles mainly resulting from the extraction of intracellular metabolites originating from red blood cells. In addition, the prolonged storage of blood samples at room temperature caused significant changes in metabolome composition, but once the VAMS devices were stored at - 80 °C, the metabolome remained stable for up to 6 months. The time used for drying the sample did also affect the metabolome. In fact, some metabolites were rapidly degraded or accumulated in the sample during the first 48 h at room temperature, indicating that a longer drying step will significantly change the concentration in the sample. Graphical abstract Volumetric absorptive microsampling (VAMS) is a novel technology that allows single-drop blood collection and, in combination with mass spectrometry (MS)-based untargeted metabolomics, represents an attractive solution for both human and animal studies. In this work, we integrated VAMS in a MS-based untargeted metabolomics workflow and investigated pre-analytical strategies such as sample extraction procedures and metabolome stability at different storage conditions. The latter revealed that

Proteomics and Metabolomics: two emerging areas for legume improvement

Directory of Open Access Journals (Sweden)

Abirami eRamalingam

2015-12-01

Full Text Available The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important source of nutrition and contribute to a significant amount of biological nitrogen fixation (>20 million tons of fixed nitrogen in agriculture. However, the production of legumes is constrained due to abiotic and biotic stresses. It is therefore imperative to understand the molecular mechanisms of plant response to different stresses and identify key candidate genes regulating tolerance which can be deployed in breeding programs. The information obtained from transcriptomics has facilitated the identification of candidate genes for the given trait of interest and utilizing them in crop breeding programs to improve stress tolerance. However, the mechanisms of stress tolerance are complex due to the influence of multi-genes and post-transcriptional regulations. Furthermore, stress conditions greatly affect gene expression which in turn causes modifications in the composition of plant proteomes and metabolomes. Therefore, functional genomics involving various proteomics and metabolomics approaches have been obligatory for understanding plant stress tolerance. These approaches have also been found useful to unravel different pathways related to plant and seed development as well as symbiosis. Proteome and metabolome profiling using high-throughput based systems have been extensively applied in the model legume species Medicago truncatula and Lotus japonicus, as well as in the model crop legume, soybean, to examine stress signalling pathways, cellular and developmental processes and nodule symbiosis. Moreover, the availability of protein reference maps as well as proteomics and metabolomics databases greatly support research and understanding of various biological processes in legumes. Protein-protein interaction techniques, particularly the yeast two-hybrid system have been advantageous for studying symbiosis and stress signalling in legumes. In

Serum metabolomic profiles suggest influence of sex and oral contraceptive use

OpenAIRE

Ruoppolo, Margherita; Campesi, Ilaria; Scolamiero, Emanuela; Pecce, Rita; Caterino, Marianna; Cherchi, Sara; Mercuro, Giuseppe; Tonolo, Giancarlo; Franconi, Flavia

2014-01-01

Aim: Considering that the effects of sex and oral contraceptives (OCs) on blood metabolites have been scarcely studied and the fact that protocol designs for clinical trials emphasise the use of contraception for women of childbearing potential, we examined if OCs and sex affect the serum levels of the physiologically relevant amino acids, carnitine and acylcarnitines, using metabolomics approaches. Methods: Healthy adult men and women were enrolled. They were drug free with the exception of ...

Metabolomic profiles of arsenic (+3 oxidation state) methyltransferase knockout mice: Effect of sex and arsenic exposure

Science.gov (United States)

Huang, Madelyn C.; Douillet, Christelle; Su, Mingming; Zhou, Kejun; Wu, Tao; Chen, Wenlian; Galanko, Joseph A.; Drobná, Zuzana; Saunders, R. Jesse; Martin, Elizabeth; Fry, Rebecca C.; Jia, Wei; Stýblo, Miroslav

2016-01-01

Arsenic (+3 oxidation state) methyltransferase (As3mt) is the key enzyme in the pathway for methylation of inorganic arsenic (iAs). Altered As3mt expression and AS3MT polymorphism have been linked to changes in iAs metabolism and in susceptibility to iAs toxicity in laboratory models and in humans. As3mt-knockout mice have been used to study the association between iAs metabolism and adverse effects of iAs exposure. However, little is known about systemic changes in metabolism of these mice and how these changes lead to their increased susceptibility to iAs toxicity. Here, we compared plasma and urinary metabolomes of male and female wild-type (WT) and As3mt-KO (KO) C57BL6 mice and examined metabolomic shifts associated with iAs exposure in drinking water. Surprisingly, exposure to 1 ppm As elicited only small changes in the metabolite profiles of either WT or KO mice. In contrast, comparisons of KO mice with WT mice revealed significant differences in plasma and urinary metabolites associated with lipid (phosphatidylcholines, cytidine, acyl-carnitine), amino acid (hippuric acid, acetylglycine, urea), and carbohydrate (L-sorbose, galactonic acid, gluconic acid) metabolism. Notably, most of these differences were sex-specific. Sex-specific differences were also found between WT and KO mice in plasma triglyceride and lipoprotein cholesterol levels. Some of the differentially changed metabolites (phosphatidylcholines, carnosine, and sarcosine) are substrates or products of reactions catalyzed by other methyltransferases. These results suggest that As3mt KO alters major metabolic pathways in a sex-specific manner, independent of iAs treatment, and that As3mt may be involved in other cellular processes beyond iAs methylation. PMID:26883664

Disruption of TCA Cycle and Glutamate Metabolism Identified by Metabolomics in an In Vitro Model of Amyotrophic Lateral Sclerosis.

Science.gov (United States)

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.

Development of chemical isotope labeling liquid chromatography mass spectrometry for silkworm hemolymph metabolomics

International Nuclear Information System (INIS)

Shen, Weifeng; Han, Wei; Li, Yunong; Meng, Zhiqi; Cai, Leiming; Li, Liang

2016-01-01

Silkworm (Bombyx mori) is a very useful target insect for evaluation of endocrine disruptor chemicals (EDCs) due to mature breeding techniques, complete endocrine system and broad basic knowledge on developmental biology. Comparative metabolomics of silkworms with and without EDC exposure offers another dimension of studying EDCs. In this work, we report a workflow on metabolomic profiling of silkworm hemolymph based on high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) and demonstrate its application in studying the metabolic changes associated with the pesticide dichlorodiphenyltrichloroethane (DDT) exposure in silkworm. Hemolymph samples were taken from mature silkworms after growing on diet that contained DDT at four different concentrations (1, 0.1, 0.01, 0.001 ppm) as well as on diet without DDT as controls. They were subjected to differential "1"2C-/"1"3C-dansyl labeling of the amine/phenol submetabolome, LC-UV quantification of the total amount of labeled metabolites for sample normalization, and LC-MS detection and relative quantification of individual metabolites in comparative samples. The total concentration of labeled metabolites did not show any significant change between four DDT-treatment groups and one control group. Multivariate statistical analysis of the metabolome data set showed that there was a distinct metabolomic separation between the five groups. Out of the 2044 detected peak pairs, 338 and 1471 metabolites have been putatively identified against the HMDB database and the EML library, respectively. 65 metabolites were identified by the dansyl library searching based on the accurate mass and retention time. Among the 65 identified metabolites, 33 positive metabolites had changes of greater than 1.20-fold or less than 0.83-fold in one or more groups with p-value of smaller than 0.05. Several useful biomarkers including serine, methionine, tryptophan, asymmetric dimethylarginine, N

Development of chemical isotope labeling liquid chromatography mass spectrometry for silkworm hemolymph metabolomics

Energy Technology Data Exchange (ETDEWEB)

Shen, Weifeng [Key Laboratory of Detection for Pesticide Residues, Ministry of Agriculture (China); Sericultural Research Institute, Zhejiang Academy of Agricultural Sciences, Hangzhou (China); Han, Wei; Li, Yunong [Department of Chemistry, University of Alberta, Edmonton, Alberta (Canada); Meng, Zhiqi [Sericultural Research Institute, Zhejiang Academy of Agricultural Sciences, Hangzhou (China); Cai, Leiming, E-mail: cailm@mail.zaas.ac.cn [Institute of Quality and Standard for Agro-products, Zhejiang Academy of Agricultural Sciences, Hangzhou (China); Li, Liang, E-mail: Liang.Li@ualberta.ca [Department of Chemistry, University of Alberta, Edmonton, Alberta (Canada)

2016-10-26

Silkworm (Bombyx mori) is a very useful target insect for evaluation of endocrine disruptor chemicals (EDCs) due to mature breeding techniques, complete endocrine system and broad basic knowledge on developmental biology. Comparative metabolomics of silkworms with and without EDC exposure offers another dimension of studying EDCs. In this work, we report a workflow on metabolomic profiling of silkworm hemolymph based on high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) and demonstrate its application in studying the metabolic changes associated with the pesticide dichlorodiphenyltrichloroethane (DDT) exposure in silkworm. Hemolymph samples were taken from mature silkworms after growing on diet that contained DDT at four different concentrations (1, 0.1, 0.01, 0.001 ppm) as well as on diet without DDT as controls. They were subjected to differential {sup 12}C-/{sup 13}C-dansyl labeling of the amine/phenol submetabolome, LC-UV quantification of the total amount of labeled metabolites for sample normalization, and LC-MS detection and relative quantification of individual metabolites in comparative samples. The total concentration of labeled metabolites did not show any significant change between four DDT-treatment groups and one control group. Multivariate statistical analysis of the metabolome data set showed that there was a distinct metabolomic separation between the five groups. Out of the 2044 detected peak pairs, 338 and 1471 metabolites have been putatively identified against the HMDB database and the EML library, respectively. 65 metabolites were identified by the dansyl library searching based on the accurate mass and retention time. Among the 65 identified metabolites, 33 positive metabolites had changes of greater than 1.20-fold or less than 0.83-fold in one or more groups with p-value of smaller than 0.05. Several useful biomarkers including serine, methionine, tryptophan, asymmetric dimethylarginine, N

A chronological expression profile of gene activity during embryonic mouse brain development.

Science.gov (United States)

Goggolidou, P; Soneji, S; Powles-Glover, N; Williams, D; Sethi, S; Baban, D; Simon, M M; Ragoussis, I; Norris, D P

2013-12-01

The brain is a functionally complex organ, the patterning and development of which are key to adult health. To help elucidate the genetic networks underlying mammalian brain patterning, we conducted detailed transcriptional profiling during embryonic development of the mouse brain. A total of 2,400 genes were identified as showing differential expression between three developmental stages. Analysis of the data identified nine gene clusters to demonstrate analogous expression profiles. A significant group of novel genes of as yet undiscovered biological function were detected as being potentially relevant to brain development and function, in addition to genes that have previously identified roles in the brain. Furthermore, analysis for genes that display asymmetric expression between the left and right brain hemispheres during development revealed 35 genes as putatively asymmetric from a combined data set. Our data constitute a valuable new resource for neuroscience and neurodevelopment, exposing possible functional associations between genes, including novel loci, and encouraging their further investigation in human neurological and behavioural disorders.

Haystack, a web-based tool for metabolomics research.

Science.gov (United States)

Grace, Stephen C; Embry, Stephen; Luo, Heng

2014-01-01

Liquid chromatography coupled to mass spectrometry (LCMS) has become a widely used technique in metabolomics research for differential profiling, the broad screening of biomolecular constituents across multiple samples to diagnose phenotypic differences and elucidate relevant features. However, a significant limitation in LCMS-based metabolomics is the high-throughput data processing required for robust statistical analysis and data modeling for large numbers of samples with hundreds of unique chemical species. To address this problem, we developed Haystack, a web-based tool designed to visualize, parse, filter, and extract significant features from LCMS datasets rapidly and efficiently. Haystack runs in a browser environment with an intuitive graphical user interface that provides both display and data processing options. Total ion chromatograms (TICs) and base peak chromatograms (BPCs) are automatically displayed, along with time-resolved mass spectra and extracted ion chromatograms (EICs) over any mass range. Output files in the common .csv format can be saved for further statistical analysis or customized graphing. Haystack's core function is a flexible binning procedure that converts the mass dimension of the chromatogram into a set of interval variables that can uniquely identify a sample. Binned mass data can be analyzed by exploratory methods such as principal component analysis (PCA) to model class assignment and identify discriminatory features. The validity of this approach is demonstrated by comparison of a dataset from plants grown at two light conditions with manual and automated peak detection methods. Haystack successfully predicted class assignment based on PCA and cluster analysis, and identified discriminatory features based on analysis of EICs of significant bins. Haystack, a new online tool for rapid processing and analysis of LCMS-based metabolomics data is described. It offers users a range of data visualization options and supports non

The next wave in metabolome analysis

DEFF Research Database (Denmark)

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...

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

Science.gov (United States)

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

Metabolomic studies in pulmonology

Directory of Open Access Journals (Sweden)

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.

NMR-based metabolomics applications

DEFF Research Database (Denmark)

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...

Role of metabolomics in TBI research

Science.gov (United States)

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

ECMDB: The E. coli Metabolome Database

OpenAIRE

Guo, An Chi; Jewison, Timothy; Wilson, Michael; Liu, Yifeng; Knox, Craig; Djoumbou, Yannick; Lo, Patrick; Mandal, Rupasri; Krishnamurthy, Ram; Wishart, David S.

2012-01-01

The Escherichia coli Metabolome Database (ECMDB, http://www.ecmdb.ca) is a comprehensively annotated metabolomic database containing detailed information about the metabolome of E. coli (K-12). Modelled closely on the Human and Yeast Metabolome Databases, the ECMDB contains >2600 metabolites with links to ?1500 different genes and proteins, including enzymes and transporters. The information in the ECMDB has been collected from dozens of textbooks, journal articles and electronic databases. E...

Metabolites as Biomarkers of Adverse Reactions Following Vaccination: A Pilot Study using Nuclear Magnetic Resonance Metabolomics

Science.gov (United States)

McClenathan, Bruce M.; Stewart, Delisha A.; Spooner, Christina E.; Pathmasiri, Wimal W.; Burgess, Jason P.; McRitchie, Susan L.; Choi, Y. Sammy; Sumner, Susan C.J.

2017-01-01

An Adverse Event Following Immunization (AEFI) is an adverse reaction to a vaccination that goes above and beyond the usual side effects associated with vaccinations. One serious AEFI related to the smallpox vaccine is myopericarditis. Metabolomics involves the study of the low molecular weight metabolite profile of cells, tissues, and biological fluids, and provides a functional readout of the phenotype. Metabolomics may help identify a particular metabolic signature in serum of subjects who are predisposed to developing AEFIs. The goal of this study was to identify metabolic markers that may predict the development of adverse events following smallpox vaccination. Serum samples were collected from military personnel prior to and following receipt of smallpox vaccine. The study population included five subjects who were clinically diagnosed with myopericarditis, 30 subjects with asymptomatic elevation of troponins, and 31 subjects with systemic symptoms following immunization, and 34 subjects with no AEFI, serving as controls. Two-hundred pre- and post-smallpox vaccination sera were analyzed by untargeted metabolomics using 1H nuclear magnetic resonance (NMR) spectroscopy. Baseline (pre-) and post-vaccination samples from individuals who experienced clinically verified myocarditis or asymptomatic elevation of troponins were more metabolically distinguishable pre- and post-vaccination compared to individuals who only experienced systemic symptoms, or controls. Metabolomics profiles pre- and post-receipt of vaccine differed substantially when an AEFI resulted. This study is the first to describe pre- and post-vaccination metabolic profiles of subjects who developed an adverse event following immunization. The study demonstrates the promise of metabolites for determining mechanisms associated with subjects who develop AEFI and the potential to develop predictive biomarkers. PMID:28169076

Inhaled ozone (O3)-induces changes in serum metabolomic and liver transcriptomic profiles in rats

International Nuclear Information System (INIS)

Miller, Desinia B.; Karoly, Edward D.; Jones, Jan C.; Ward, William O.; Vallanat, Beena D.; Andrews, Debora L.; Schladweiler, Mette C.; Snow, Samantha J.; Bass, Virginia L.; Richards, Judy E.; Ghio, Andrew J.; Cascio, Wayne E.; Ledbetter, Allen D.; Kodavanti, Urmila P.

2015-01-01

Air pollution has been linked to increased incidence of diabetes. Recently, we showed that ozone (O 3 ) induces glucose intolerance, and increases serum leptin and epinephrine in Brown Norway rats. In this study, we hypothesized that O 3 exposure will cause systemic changes in metabolic homeostasis and that serum metabolomic and liver transcriptomic profiling will provide mechanistic insights. In the first experiment, male Wistar Kyoto (WKY) rats were exposed to filtered air (FA) or O 3 at 0.25, 0.50, or 1.0 ppm, 6 h/day for two days to establish concentration-related effects on glucose tolerance and lung injury. In a second experiment, rats were exposed to FA or 1.0 ppm O 3 , 6 h/day for either one or two consecutive days, and systemic metabolic responses were determined immediately after or 18 h post-exposure. O 3 increased serum glucose and leptin on day 1. Glucose intolerance persisted through two days of exposure but reversed 18 h-post second exposure. O 3 increased circulating metabolites of glycolysis, long-chain free fatty acids, branched-chain amino acids and cholesterol, while 1,5-anhydroglucitol, bile acids and metabolites of TCA cycle were decreased, indicating impaired glycemic control, proteolysis and lipolysis. Liver gene expression increased for markers of glycolysis, TCA cycle and gluconeogenesis, and decreased for markers of steroid and fat biosynthesis. Genes involved in apoptosis and mitochondrial function were also impacted by O 3 . In conclusion, short-term O 3 exposure induces global metabolic derangement involving glucose, lipid, and amino acid metabolism, typical of a stress–response. It remains to be examined if these alterations contribute to insulin resistance upon chronic exposure. - Highlights: • Ozone, an ubiquitous air pollutant induces acute systemic metabolic derangement. • Serum metabolomic approach provides novel insights in ozone-induced changes. • Ozone exposure induces leptinemia, hyperglycemia, and glucose intolerance

A targeted metabolomics approach for clinical diagnosis of inborn errors of metabolism.

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Jacob, Minnie; Malkawi, Abeer; Albast, Nour; Al Bougha, Salam; Lopata, Andreas; Dasouki, Majed; Abdel Rahman, Anas M

2018-09-26

Metabolome, the ultimate functional product of the genome, can be studied through identification and quantification of small molecules. The global metabolome influences the individual phenotype through clinical and environmental interventions. Metabolomics has become an integral part of clinical research and allowed for another dimension of better understanding of disease pathophysiology and mechanism. More than 95% of the clinical biochemistry laboratory routine workload is based on small molecular identification, which can potentially be analyzed through metabolomics. However, multiple challenges in clinical metabolomics impact the entire workflow and data quality, thus the biological interpretation needs to be standardized for a reproducible outcome. Herein, we introduce the establishment of a comprehensive targeted metabolomics method for a panel of 220 clinically relevant metabolites using Liquid chromatography-tandem mass spectrometry (LC-MS/MS) standardized for clinical research. The sensitivity, reproducibility and molecular stability of each targeted metabolite (amino acids, organic acids, acylcarnitines, sugars, bile acids, neurotransmitters, polyamines, and hormones) were assessed under multiple experimental conditions. The metabolic tissue distribution was determined in various rat organs. Furthermore, the method was validated in dry blood spot (DBS) samples collected from patients known to have various inborn errors of metabolism (IEMs). Using this approach, our panel appears to be sensitive and robust as it demonstrated differential and unique metabolic profiles in various rat tissues. Also, as a prospective screening method, this panel of diverse metabolites has the ability to identify patients with a wide range of IEMs who otherwise may need multiple, time-consuming and expensive biochemical assays causing a delay in clinical management. Copyright © 2018 Elsevier B.V. All rights reserved.

Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

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Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

2016-07-01

Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas

Normalization method for metabolomics data using optimal selection of multiple internal standards

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Yetukuri Laxman

2007-03-01

Full Text Available Abstract Background Success of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task. Results With the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS. We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization by l2 norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization. Conclusion Depending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.

Metabolomics in Toxicology and Preclinical Research

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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

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae in a phylogenetic context.

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Maria Elvira Poleti Martucci

Full Text Available Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus. Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

Food metabolomics: from farm to human.

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Kim, Sooah; Kim, Jungyeon; Yun, Eun Ju; Kim, Kyoung Heon

2016-02-01

Metabolomics, one of the latest components in the suite of systems biology, has been used to understand the metabolism and physiology of living systems, including microorganisms, plants, animals and humans. Food metabolomics can be defined as the application of metabolomics in food systems, including food resources, food processing and diet for humans. The study of food metabolomics has increased gradually in the recent years, because food systems are directly related to nutrition and human health. This review describes the recent trends and applications of metabolomics to food systems, from farm to human, including food resource production, industrial food processing and food intake by humans. Copyright © 2015 Elsevier Ltd. All rights reserved.

Metabolite profiling, antioxidant, and α-glucosidase inhibitory activities of germinated rice: nuclear-magnetic-resonance-based metabolomics study

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Phaiwan Pramai

2018-01-01

Full Text Available In an attempt to profile the metabolites of three different varieties of germinated rice, specifically black (GBR, red, and white rice, a 1H-nuclear-magnetic-resonance-based metabolomics approach was conducted. Multivariate data analysis was applied to discriminate between the three different varieties using a partial least squares discriminant analysis (PLS-DA model. The PLS model was used to evaluate the relationship between chemicals and biological activities of germinated rice. The PLS-DA score plot exhibited a noticeable separation between the three rice varieties into three clusters by PC1 and PC2. The PLS model indicated that α-linolenic acid, γ-oryzanol, α-tocopherol, γ-aminobutyric acid, 3-hydroxybutyric acid, fumaric acid, fatty acids, threonine, tryptophan, and vanillic acid were significantly correlated with the higher bioactivities demonstrated by GBR that was extracted in 100% ethanol. Subsequently, the proposed biosynthetic pathway analysis revealed that the increased quantities of secondary metabolites found in GBR may contribute to its nutritional value and health benefits.

Global mass spectrometry based metabolomics profiling of erythrocytes infected with Plasmodium falciparum.

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Theodore R Sana

Full Text Available Malaria is a global infectious disease that threatens the lives of millions of people. Transcriptomics, proteomics and functional genomics studies, as well as sequencing of the Plasmodium falciparum and Homo sapiens genomes, have shed new light on this host-parasite relationship. Recent advances in accurate mass measurement mass spectrometry, sophisticated data analysis software, and availability of biological pathway databases, have converged to facilitate our global, untargeted biochemical profiling study of in vitro P. falciparum-infected (IRBC and uninfected (NRBC erythrocytes. In order to expand the number of detectable metabolites, several key analytical steps in our workflows were optimized. Untargeted and targeted data mining resulted in detection of over one thousand features or chemical entities. Untargeted features were annotated via matching to the METLIN metabolite database. For targeted data mining, we queried the data using a compound database derived from a metabolic reconstruction of the P. falciparum genome. In total, over one hundred and fifty differential annotated metabolites were observed. To corroborate the representation of known biochemical pathways from our data, an inferential pathway analysis strategy was used to map annotated metabolites onto the BioCyc pathway collection. This hypothesis-generating approach resulted in over-representation of many metabolites onto several IRBC pathways, most prominently glycolysis. In addition, components of the "branched" TCA cycle, partial urea cycle, and nucleotide, amino acid, chorismate, sphingolipid and fatty acid metabolism were found to be altered in IRBCs. Interestingly, we detected and confirmed elevated levels for cyclic ADP ribose and phosphoribosyl AMP in IRBCs, a novel observation. These metabolites may play a role in regulating the release of intracellular Ca(2+ during P. falciparum infection. Our results support a strategy of global metabolite profiling by untargeted

Metabolomics er fremtiden

DEFF Research Database (Denmark)

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...

Metabolic Mechanism for l-Leucine-Induced Metabolome To Eliminate Streptococcus iniae.

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Du, Chao-Chao; Yang, Man-Jun; Li, Min-Yi; Yang, Jun; Peng, Bo; Li, Hui; Peng, Xuan-Xian

2017-05-05

Crucial metabolites that modulate hosts' metabolome to eliminate bacterial pathogens have been documented, but the metabolic mechanisms are largely unknown. The present study explores the metabolic mechanism for l-leucine-induced metabolome to eliminate Streptococcus iniae in tilapia. GC-MS-based metabolomics was used to investigate the tilapia liver metabolic profile in the presence of exogenous l-leucine. Thirty-seven metabolites of differential abundance were determined, and 11 metabolic pathways were enriched. Pattern recognition analysis identified serine and proline as crucial metabolites, which are the two metabolites identified in survived tilapias during S. iniae infection, suggesting that the two metabolites play crucial roles in l-leucine-induced elimination of the pathogen by the host. Exogenous l-serine reduces the mortality of tilapias infected by S. iniae, providing a robust proof supporting the conclusion. Furthermore, exogenous l-serine elevates expression of genes IL-1β and IL-8 in tilapia spleen, but not TNFα, CXCR4 and Mx, suggesting that the metabolite promotes a phagocytosis role of macrophages, which is consistent with the finding that l-leucine promotes macrophages to kill both Gram-positive and Gram-negative bacterial pathogens. Therefore, the ability of phagocytosis enhanced by exogenous l-leucine is partly attributed to elevation of l-serine. These results demonstrate a metabolic mechanism by which exogenous l-leucine modulates tilapias' metabolome to enhance innate immunity and eliminate pathogens.

Stoichiometric Correlation Analysis: Principles of Metabolic Functionality from Metabolomics Data

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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.

Metabolomics and bioactive substances in plants

DEFF Research Database (Denmark)

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...

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

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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.

Topsoil depth substantially influences the responses to drought of the foliar metabolomes of Mediterranean forests

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Rivas-Ubach, Albert; Barbeta, Adrià; Sardans, Jordi; Guenther, Alex; Ogaya, Romà; Oravec, Michal; Urban, Otmar; Peñuelas, Josep

2016-08-01

Soils provide physical support, water, and nutrients to terrestrial plants. Upper soil layers are crucial for forest dynamics, especially under drought conditions, because many biological processes occur there and provide support, water and nutrients to terrestrial plants. We postulated that tree size and overall plant function manifested in the metabolome composition, the total set of metabolites, were dependent on the depth of upper soil layers and on water availability. We sampled leaves for stoichiometric and metabolomic analyses once per season from differently sized Quercus ilex trees under natural and experimental drought conditions as projected for the coming decades. Different sized trees had different metabolomes and plots with shallower soils had smaller trees. Soil moisture of the upper soil did not explain the tree size and smaller trees did not show higher concentrations of biomarker metabolites related to drought stress. However, the impact of drought treatment on metabolomes was higher in smaller trees in shallower soils. Our results suggested that tree size was more dependent on the depth of the upper soil layers, which indirectly affect the metabolomes of the trees, than on the moisture content of the upper soil layers. Metabolomic profiling of Q. ilex supported the premise that water availability in the upper soil layers was not necessarily correlated with tree size. The higher impact of drought on trees growing in shallower soils nevertheless indicates a higher vulnerability of small trees to the future increase in frequency, intensity, and duration of drought projected for the Mediterranean Basin and other areas. Metabolomics has proven to be an excellent tool detecting significant metabolic changes among differently sized individuals of the same species and it improves our understanding of the connection between plant metabolomes and environmental variables such as soil depth and moisture content.

Clinical Metabolomics and Glaucoma.

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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.

NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

International Nuclear Information System (INIS)

Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M.C.; Wijmenga, Sybren S.

2012-01-01

Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

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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.

Current metabolomics: technological advances.

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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.

Infrared biospectroscopy for a fast qualitative evaluation of sample preparation in metabolomics.

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Kuligowski, Julia; Pérez-Guaita, David; Escobar, Javier; Lliso, Isabel; de la Guardia, Miguel; Lendl, Bernhard; Vento, Máximo; Quintás, Guillermo

2014-09-01

Liquid chromatography-mass spectrometry (LC-MS) has been increasingly used in biomedicine to study the dynamic metabolomic responses of biological systems under different physiological or pathological conditions. To obtain an integrated snapshot of the system, metabolomic methods in biomedicine typically analyze biofluids (e.g. plasma) that require clean-up before being injected into LC-MS systems. However, high resolution LC-MS is costly in terms of resources required for sample and data analysis and care must be taken to prevent chemical (e.g. ion suppression) or statistical artifacts. Because of that, the effect of sample preparation on the metabolomic profile during metabolomic method development is often overlooked. This work combines an Attenuated Total Reflectance-Fourier transform infrared (ATR-FTIR) and a multivariate exploratory data analysis for a cost-effective qualitative evaluation of major changes in sample composition during sample preparation. ATR-FTIR and LC-time of flight mass spectrometry (TOFMS) data from the analysis of a set of plasma samples precipitated using acetonitrile, methanol and acetone performed in parallel were used as a model example. Biochemical information obtained from the analysis of the ATR-FTIR and LC-TOFMS data was thoroughly compared to evaluate the strengths and shortcomings of FTIR biospectroscopy for assessing sample preparation in metabolomics studies. Results obtained show the feasibility of ATR-FTIR for the evaluation of major trends in the plasma composition changes among different sample pretreatments, providing information in terms of e.g., amino acids, proteins, lipids and carbohydrates overall contents comparable to those found by LC-TOFMS. Copyright © 2014 Elsevier B.V. All rights reserved.

A Metabolomic Perspective on Coeliac Disease

Science.gov (United States)

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

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling.

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Castagné, Raphaële; Boulangé, Claire Laurence; Karaman, Ibrahim; Campanella, Gianluca; Santos Ferreira, Diana L; Kaluarachchi, Manuja R; Lehne, Benjamin; Moayyeri, Alireza; Lewis, Matthew R; Spagou, Konstantina; Dona, Anthony C; Evangelos, Vangelis; Tracy, Russell; Greenland, Philip; Lindon, John C; Herrington, David; Ebbels, Timothy M D; Elliott, Paul; Tzoulaki, Ioanna; Chadeau-Hyam, Marc

2017-10-06

1 H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1 H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

Metabolite Profiling of the Microalgal Diatom Chaetoceros Calcitrans and Correlation with Antioxidant and Nitric Oxide Inhibitory Activities via 1H NMR-Based Metabolomics

Directory of Open Access Journals (Sweden)

Awanis Azizan

2018-05-01

Full Text Available Microalgae are promising candidate resources from marine ecology for health-improving effects. Metabolite profiling of the microalgal diatom, Chaetoceros calcitrans was conducted by using robust metabolomics tools, namely 1H nuclear magnetic resonance (NMR spectroscopy coupled with multivariate data analysis (MVDA. The unsupervised data analysis, using principal component analysis (PCA, resolved the five types of extracts made by solvents ranging from polar to non-polar into five different clusters. Collectively, with various extraction solvents, 11 amino acids, cholesterol, 6 fatty acids, 2 sugars, 1 osmolyte, 6 carotenoids and 2 chlorophyll pigments were identified. The fatty acids and both carotenoid pigments as well as chlorophyll, were observed in the extracts made from medium polar (acetone, chloroform and non-polar (hexane solvents. It is suggested that the compounds were the characteristic markers that influenced the separation between the clusters. Based on partial least square (PLS analysis, fucoxanthin, astaxanthin, violaxanthin, zeaxanthin, canthaxanthin, and lutein displayed strong correlation to 2,2-diphenyl-1-picrylhydrazyl (DPPH free radical scavenging and nitric oxide (NO inhibitory activity. This metabolomics study showed that solvent extractions are one of the main bottlenecks for the maximum recovery of bioactive microalgal compounds and could be a better source of natural antioxidants due to a high value of metabolites.

Bridging the gap: basic metabolomics methods for natural product chemistry.

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Jones, Oliver A H; Hügel, Helmut M

2013-01-01

Natural products and their derivatives often have potent physiological activities and therefore play important roles as both frontline treatments for many diseases and as the inspiration for chemically synthesized therapeutics. However, the detection and synthesis of new therapeutic compounds derived from, or inspired by natural compounds has declined in recent years due to the increased difficulty of identifying and isolating novel active compounds. A new strategy is therefore necessary to jumpstart this field of research. Metabolomics, including both targeted and global metabolite profiling strategies, has the potential to be instrumental in this effort since it allows a systematic study of complex mixtures (such as plant extracts) without the need for prior isolation of active ingredients (or mixtures thereof). Here we describe the basic steps for conducting metabolomics experiments and analyzing the results using some of the more commonly used analytical and statistical methodologies.

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis.

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Joong Kyong Ahn

Full Text Available Rheumatoid arthritis (RA is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3, which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin. Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA.

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis.

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Ahn, Joong Kyong; Kim, Sooah; Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

2015-01-01

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA.

Serial Metabolome Changes in a Prospective Cohort of Subjects with Influenza Viral Infection and Comparison with Dengue Fever.

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Cui, Liang; Fang, Jinling; Ooi, Eng Eong; Lee, Yie Hou

2017-07-07

Influenza virus infection (IVI) and dengue virus infection (DVI) are major public health threats. Between IVI and DVI, clinical symptoms can be overlapping yet infection-specific, but host metabolome changes are not well-described. Untargeted metabolomics and targeted oxylipinomic analyses were performed on sera serially collected at three phases of infection from a prospective cohort study of adult subjects with either H3N2 influenza infection or dengue fever. Untargeted metabolomics identified 26 differential metabolites, and major perturbed pathways included purine metabolism, fatty acid biosynthesis and β-oxidation, tryptophan metabolism, phospholipid catabolism, and steroid hormone pathway. Alterations in eight oxylipins were associated with the early symptomatic phase of H3N2 flu infection, were mostly arachidonic acid-derived, and were enriched in the lipoxygenase pathway. There was significant overlap in metabolome profiles in both infections. However, differences specific to IVI and DVI were observed. DVI specifically attenuated metabolites including serotonin, bile acids and biliverdin. Additionally, metabolome changes were more persistent in IVI in which metabolites such as hypoxanthine, inosine, and xanthine of the purine metabolism pathway remained significantly elevated at 21-27 days after fever onset. This study revealed the dynamic metabolome changes in IVI subjects and provided biochemical insights on host physiological similarities and differences between IVI and DVI.

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

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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

Bio-effectors from waste materials as growth promoters, an agronomic and metabolomic study

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Alwanney, Deaa; Chami, Ziad Al; Angelica De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

2014-05-01

Nowadays, improving plant performance by providing growth promoters is a main concern of the organic agriculture. As a consequence of increased food demands, more efficient and alternatives of the current plant nutrition strategies are becoming urgent. Recently, a novel concept "bio-effectors" raised on to describe a group of products that are able to improve plant performance and do not belong to fertilizers or pesticides. Agro-Food processing residues are promising materials as bio-effector. Three plant-derived materials: brewers' spent grain (BSG), fennel processing residues (FPR) and lemon processing residues (LPR) were chosen as bio-effector candidates. Plant-derived materials were characterized in term of total macro and micronutrients content. Green extraction methodology and solvent choice (aqueous; ethanol; and aqueous: ethanol mixture 1:1) was based on the extraction yield as main factor. Optimum extracts, to be used on the tomato test plant, were determined using phytotoxicity test (seed germination test) as main constraint. Thereafter, selected extracts were characterized and secondary metabolites profiling were detected by NMR technique. Selected extracts were applied on tomato in a growth chamber at different doses in comparison to humic-like substances as positive control (Ctrl+) and to a Hoagland solution as negative control (Ctrl-). At the end of the experiment, agronomical parameters were determined and NMR-metabolomic profiling were conducted on tomato seedlings. Results are summarized as follow: (i) raw showed an interesting content, either at nutritional or biological level; (ii) aqueous extraction resulted higher yield than other used solvent; (iii) at high extraction ratio (1:25 for BSG; 1:100 for FPR; and 1:200 for LPR) aqueous extracts were not phytotoxic on the tomato test plant; (iv) all aqueous extract are differently rich in nutrients, aminoacids, sugars and low molecular weight molecules; (v) all extract exhibited a growth promotion at

Heritable IUGR and adult metabolic syndrome are reversible and associated with alterations in the metabolome following dietary supplementation of 1-carbon intermediates.

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Seferovic, Maxim D; Goodspeed, Danielle M; Chu, Derrick M; Krannich, Laura A; Gonzalez-Rodriguez, Pablo J; Cox, James E; Aagaard, Kjersti M

2015-06-01

Metabolic syndrome (MetS), following intrauterine growth restriction (IUGR), is epigenetically heritable. Recently, we abrogated the F2 adult phenotype with essential nutrient supplementation (ENS) of intermediates along the 1-carbon pathway. With the use of the same grandparental uterine artery ligation model, we profiled the F2 serum metabolome at weaning [postnatal day (d)21; n = 76] and adulthood (d160; n = 12) to test if MetS is preceded by alterations in the metabolome. Indicative of developmentally programmed MetS, adult F2, formerly IUGR rats, were obese (621 vs. 461 g; P metabolome at weaning (randomForest analysis; class error metabolome accompany heritable IUGR, precede adult-onset MetS, and are partially amenable to dietary intervention. © FASEB.

Inhaled ozone (O{sub 3})-induces changes in serum metabolomic and liver transcriptomic profiles in rats

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Miller, Desinia B. [Curriculum in Toxicology, University of North Carolina-Chapel Hill, Chapel Hill, NC (United States); Karoly, Edward D.; Jones, Jan C. [Metabolon Incorporation, Durham, NC (United States); Ward, William O.; Vallanat, Beena D.; Andrews, Debora L. [Research Cores Unit, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC (United States); Schladweiler, Mette C.; Snow, Samantha J. [Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC (United States); Bass, Virginia L. [Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC (United States); Richards, Judy E.; Ghio, Andrew J.; Cascio, Wayne E.; Ledbetter, Allen D. [Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC (United States); Kodavanti, Urmila P., E-mail: kodavanti.urmila@epa.gov [Environmental Public Health Division, National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, NC (United States)

2015-07-15

Air pollution has been linked to increased incidence of diabetes. Recently, we showed that ozone (O{sub 3}) induces glucose intolerance, and increases serum leptin and epinephrine in Brown Norway rats. In this study, we hypothesized that O{sub 3} exposure will cause systemic changes in metabolic homeostasis and that serum metabolomic and liver transcriptomic profiling will provide mechanistic insights. In the first experiment, male Wistar Kyoto (WKY) rats were exposed to filtered air (FA) or O{sub 3} at 0.25, 0.50, or 1.0 ppm, 6 h/day for two days to establish concentration-related effects on glucose tolerance and lung injury. In a second experiment, rats were exposed to FA or 1.0 ppm O{sub 3}, 6 h/day for either one or two consecutive days, and systemic metabolic responses were determined immediately after or 18 h post-exposure. O{sub 3} increased serum glucose and leptin on day 1. Glucose intolerance persisted through two days of exposure but reversed 18 h-post second exposure. O{sub 3} increased circulating metabolites of glycolysis, long-chain free fatty acids, branched-chain amino acids and cholesterol, while 1,5-anhydroglucitol, bile acids and metabolites of TCA cycle were decreased, indicating impaired glycemic control, proteolysis and lipolysis. Liver gene expression increased for markers of glycolysis, TCA cycle and gluconeogenesis, and decreased for markers of steroid and fat biosynthesis. Genes involved in apoptosis and mitochondrial function were also impacted by O{sub 3}. In conclusion, short-term O{sub 3} exposure induces global metabolic derangement involving glucose, lipid, and amino acid metabolism, typical of a stress–response. It remains to be examined if these alterations contribute to insulin resistance upon chronic exposure. - Highlights: • Ozone, an ubiquitous air pollutant induces acute systemic metabolic derangement. • Serum metabolomic approach provides novel insights in ozone-induced changes. • Ozone exposure induces leptinemia

Metabolic profiles are principally different between cancers of the liver, pancreas and breast.

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Budhu, Anuradha; Terunuma, Atsushi; Zhang, Geng; Hussain, S Perwez; Ambs, Stefan; Wang, Xin Wei

2014-01-01

Molecular profiling of primary tumors may facilitate the classification of patients with cancer into more homogenous biological groups to aid clinical management. Metabolomic profiling has been shown to be a powerful tool in characterizing the biological mechanisms underlying a disease but has not been evaluated for its ability to classify cancers by their tissue of origin. Thus, we assessed metabolomic profiling as a novel tool for multiclass cancer characterization. Global metabolic profiling was employed to identify metabolites in paired tumor and non-tumor liver (n=60), breast (n=130) and pancreatic (n=76) tissue specimens. Unsupervised principal component analysis showed that metabolites are principally unique to each tissue and cancer type. Such a difference can also be observed even among early stage cancers, suggesting a significant and unique alteration of global metabolic pathways associated with each cancer type. Our global high-throughput metabolomic profiling study shows that specific biochemical alterations distinguish liver, pancreatic and breast cancer and could be applied as cancer classification tools to differentiate tumors based on tissue of origin.

Biomarkers of Morbid Obesity and Prediabetes by Metabolomic Profiling of Human Discordant Phenotypes.

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Tulipani, Sara; Palau-Rodriguez, Magali; Miñarro Alonso, Antonio; Cardona, Fernando; Marco-Ramell, Anna; Zonja, Bozo; Lopez de Alda, Miren; Muñoz-Garach, Araceli; Sanchez-Pla, Alejandro; Tinahones, Francisco J; Andres-Lacueva, Cristina

2016-12-01

Metabolomic studies aimed to dissect the connection between the development of type 2 diabetes and obesity are still scarce. In the present study, fasting serum from sixty-four adult individuals classified into four sex-matched groups by their BMI [non-obese versus morbid obese] and the increased risk of developing diabetes [prediabetic insulin resistant state versus non-prediabetic non-insulin resistant] was analyzed by LC- and FIA-ESI-MS/MS-driven metabolomic approaches. Altered levels of [lyso]glycerophospholipids was the most specific metabolic trait associated to morbid obesity, particularly lysophosphatidylcholines acylated with margaric, oleic and linoleic acids [lysoPC C17:0: R=-0.56, p=0.0003; lysoPC C18:1: R=-0.61, p=0.0001; lysoPC C18:2 R=-0.64, pprediabetes and insulin resistance in a BMI-independent manner [fasting insulin: R=0.37, p=0.0479; HOMA-IR: R=0.37, p=0.0468]. Minority sphingolipids including specific [dihydro]ceramides and sphingomyelins also associated with the prediabetic insulin resistant state, hence deserving attention as potential targets for early diagnosis or therapeutic intervention. Copyright © 2016 Elsevier B.V. All rights reserved.

Investigation of the effect of genotype and agronomic conditions on metabolomic profiles of selected strawberry cultivars with different sensitivity to environmental stress.

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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.

Metabolomic profile of umbilical cord blood plasma from early and late intrauterine growth restricted (IUGR neonates with and without signs of brain vasodilation.

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Magdalena Sanz-Cortés

Full Text Available OBJECTIVES: To characterize via NMR spectroscopy the full spectrum of metabolic changes in umbilical vein blood plasma of newborns diagnosed with different clinical forms of intrauterine growth restriction (IUGR. METHODS: 23 early IUGR cases and matched 23 adequate-for-gestational-age (AGA controls and 56 late IUGR cases with 56 matched AGAs were included in this study. Early IUGR was defined as a birth weight 35 weeks. This group was subdivided in 18 vasodilated (VD and 38 non-VD late IUGR fetuses. All AGA patients had a birth weight >10(th centile. (1H nuclear magnetic resonance (NMR metabolomics of the blood samples collected from the umbilical vein at delivery was obtained. Multivariate statistical analysis identified several metabolites that allowed the discrimination between the different IUGR subgroups, and their comparative levels were quantified from the NMR data. RESULTS: The NMR-based analysis showed increased unsaturated lipids and VLDL levels in both early and late IUGR samples, decreased glucose and increased acetone levels in early IUGR. Non-significant trends for decreased glucose and increased acetone levels were present in late IUGR, which followed a severity gradient when the VD and non-VD subgroups were considered. Regarding amino acids and derivatives, early IUGR showed significantly increased glutamine and creatine levels, whereas the amounts of phenylalanine and tyrosine were decreased in early and late-VD IUGR samples. Valine and leucine were decreased in late IUGR samples. Choline levels were decreased in all clinical subforms of IUGR. CONCLUSIONS: IUGR is not associated with a unique metabolic profile, but important changes are present in different clinical subsets used in research and clinical practice. These results may help in characterizing comprehensively specific alterations underlying different IUGR subsets.

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

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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

Metabolomics to unveil and understand phenotypic diversity between pathogen populations.

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Ruben t'Kindt

Full Text Available Leishmaniasis is a debilitating disease caused by the parasite Leishmania. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study Leishmania donovani parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for L. donovani to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant L. donovani isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured in vitro and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of Leishmania and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical Leishmania isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.

From models to crop species: caveats and solutions for translational metabolomics

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Takayuki eTohge

2011-10-01

Full Text Available Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa that illustrate how such dangers can be detected and circumvented.

Impact of a western diet on the ovarian and serum metabolome.

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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.

Metabolomic markers of fatigue: Association between circulating metabolome and fatigue in women with chronic widespread pain.

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Freidin, Maxim B; Wells, Helena R R; Potter, Tilly; Livshits, Gregory; Menni, Cristina; Williams, Frances M K

2018-02-01

Fatigue is a sensation of unbearable tiredness that frequently accompanies chronic widespread musculoskeletal pain (CWP) and inflammatory joint disease. Its mechanisms are poorly understood and there is a lack of effective biomarkers for diagnosis and onset prediction. We studied the circulating metabolome in a population sample characterised for CWP to identify biomarkers showing specificity for fatigue. Untargeted metabolomic profiling was conducted on fasting plasma and serum samples of 1106 females with and without CWP from the TwinsUK cohort. Linear mixed-effects models accounting for covariates were used to determine relationships between fatigue and metabolites. Receiver operating curve (ROC)-analysis was used to determine predictive value of metabolites for fatigue. While no association between fatigue and metabolites was identified in twins without CWP (n=711), in participants with CWP (n=395), levels of eicosapentaenoate (EPA) ω-3 fatty acid were significantly reduced in those with fatigue (β=-0.452±0.116; p=1.2×10 -4 ). A significant association between fatigue and two other metabolites also emerged when BMI was excluded from the model: 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF), and C-glycosyltryptophan (p=1.5×10 -4 and p=3.1×10 -4 , respectively). ROC analysis has identified a combination of 15 circulating metabolites with good predictive potential for fatigue in CWP (AUC=75%; 95% CI 69-80%). The results of this agnostic metabolomics screening show that fatigue is metabolically distinct from CWP, and is associated with a decrease in circulating levels of EPA. Our panel of circulating metabolites provides the starting point for a diagnostic test for fatigue in CWP. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Metabolomics Society’s International Affiliations

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Roessner, U.; Rolin, D.; Rijswijk, van M.E.C.; Hall, R.D.; Hankemeier, T.

2015-01-01

In 2012 the Metabolomics Society established a more formal system for national and regional metabolomics initiatives, interest groups, societies and networks to become an International Affiliate of the Society. A number of groups (http://metabolomicssociety.org/international-affilia

Metabolomics: the chemistry between ecology and genetics

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Macel, M.; Van Dam, N.M.; Keurentjes, J.J.B.

2010-01-01

Metabolomics is a fast developing field of comprehensive untargeted chemical analyses. It has many applications and can in principle be used on any organism without prior knowledge of the metabolome or genome. The amount of functional information that is acquired with metabolomics largely depends on

NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

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Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

2012-10-31

Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

The effects of age and dietary restriction on the tissue-specific metabolome of Drosophila.

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Laye, Matthew J; Tran, ViLinh; Jones, Dean P; Kapahi, Pankaj; Promislow, Daniel E L

2015-10-01

Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age-related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease-associated phenotypes. Here, we use high-resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient-rich ad libitum (AL) or nutrient-restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age-related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age. © 2015 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.

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

Science.gov (United States)

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.

A phytochemical comparison of saw palmetto products using gas chromatography and 1H nuclear magnetic resonance spectroscopy metabolomic profiling

Science.gov (United States)

Booker, Anthony; Suter, Andy; Krnjic, Ana; Strassel, Brigitte; Zloh, Mire; Said, Mazlina; Heinrich, Michael

2014-01-01

Objectives Preparations containing saw palmetto berries are used in the treatment of benign prostatic hyperplasia (BPH). There are many products on the market, and relatively little is known about their chemical variability and specifically the composition and quality of different saw palmetto products notwithstanding that in 2000, an international consultation paper from the major urological associations from the five continents on treatments for BPH demanded further research on this topic. Here, we compare two analytical approaches and characterise 57 different saw palmetto products. Methods An established method – gas chromatography – was used for the quantification of nine fatty acids, while a novel approach of metabolomic profiling using 1H nuclear magnetic resonance (NMR) spectroscopy was used as a fingerprinting tool to assess the overall composition of the extracts. Key findings The phytochemical analysis determining the fatty acids showed a high level of heterogeneity of the different products in the total amount and of nine single fatty acids. A robust and reproducible 1H NMR spectroscopy method was established, and the results showed that it was possible to statistically differentiate between saw palmetto products that had been extracted under different conditions but not between products that used a similar extraction method. Principal component analysis was able to determine those products that had significantly different metabolites. Conclusions The metabolomic approach developed offers novel opportunities for quality control along the value chain of saw palmetto and needs to be followed further, as with this method, the complexity of a herbal extract can be better assessed than with the analysis of a single group of constituents. PMID:24417505

A phytochemical comparison of saw palmetto products using gas chromatography and (1) H nuclear magnetic resonance spectroscopy metabolomic profiling.

Science.gov (United States)

Booker, Anthony; Suter, Andy; Krnjic, Ana; Strassel, Brigitte; Zloh, Mire; Said, Mazlina; Heinrich, Michael

2014-06-01

Preparations containing saw palmetto berries are used in the treatment of benign prostatic hyperplasia (BPH). There are many products on the market, and relatively little is known about their chemical variability and specifically the composition and quality of different saw palmetto products notwithstanding that in 2000, an international consultation paper from the major urological associations from the five continents on treatments for BPH demanded further research on this topic. Here, we compare two analytical approaches and characterise 57 different saw palmetto products. An established method - gas chromatography - was used for the quantification of nine fatty acids, while a novel approach of metabolomic profiling using (1) H nuclear magnetic resonance (NMR) spectroscopy was used as a fingerprinting tool to assess the overall composition of the extracts. The phytochemical analysis determining the fatty acids showed a high level of heterogeneity of the different products in the total amount and of nine single fatty acids. A robust and reproducible (1) H NMR spectroscopy method was established, and the results showed that it was possible to statistically differentiate between saw palmetto products that had been extracted under different conditions but not between products that used a similar extraction method. Principal component analysis was able to determine those products that had significantly different metabolites. The metabolomic approach developed offers novel opportunities for quality control along the value chain of saw palmetto and needs to be followed further, as with this method, the complexity of a herbal extract can be better assessed than with the analysis of a single group of constituents. © 2014 The Authors. Journal of Pharmacy and Pharmacology published by John Wiley & Sons Ltd on behalf of Royal Pharmaceutical Society.

Metabolomics of Genetically Modified Crops

Science.gov (United States)

Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

2014-01-01

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064

Metabolomics of Genetically Modified Crops

Directory of Open Access Journals (Sweden)

Carolina Simó

2014-10-01

Full Text Available Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

Poplar trees reconfigure the transcriptome and metabolome in response to drought in a genotype- and time-of-day-dependent manner.

Science.gov (United States)

Hamanishi, Erin T; Barchet, Genoa L H; Dauwe, Rebecca; Mansfield, Shawn D; Campbell, Malcolm M

2015-04-21

Drought has a major impact on tree growth and survival. Understanding tree responses to this stress can have important application in both conservation of forest health, and in production forestry. Trees of the genus Populus provide an excellent opportunity to explore the mechanistic underpinnings of forest tree drought responses, given the growing molecular resources that are available for this taxon. Here, foliar tissue of six water-deficit stressed P. balsamifera genotypes was analysed for variation in the metabolome in response to drought and time of day by using an untargeted metabolite profiling technique, gas chromatography/mass-spectrometry (GC/MS). Significant variation in the metabolome was observed in response the imposition of water-deficit stress. Notably, organic acid intermediates such as succinic and malic acid had lower concentrations in leaves exposed to drought, whereas galactinol and raffinose were found in increased concentrations. A number of metabolites with significant difference in accumulation under water-deficit conditions exhibited intraspecific variation in metabolite accumulation. Large magnitude fold-change accumulation was observed in three of the six genotypes. In order to understand the interaction between the transcriptome and metabolome, an integrated analysis of the drought-responsive transcriptome and the metabolome was performed. One P. balsamifera genotype, AP-1006, demonstrated a lack of congruence between the magnitude of the drought transcriptome response and the magnitude of the metabolome response. More specifically, metabolite profiles in AP-1006 demonstrated the smallest changes in response to water-deficit conditions. Pathway analysis of the transcriptome and metabolome revealed specific genotypic responses with respect to primary sugar accumulation, citric acid metabolism, and raffinose family oligosaccharide biosynthesis. The intraspecific variation in the molecular strategies that underpin the responses to drought

Demographic profile of severe traumatic brain injury admissions to ...

African Journals Online (AJOL)

Background. Paediatric traumatic brain injury (PTBI) is a major public health problem. However, recent epidemiological data for PTBI in South Africa (SA) are lacking. Objectives. To establish a demographic profile of severe PTBI admissions to the Red Cross War Memorial Children's Hospital (RCWMCH) over a 5-year ...

The impact of ambient air pollution on the human blood metabolome.

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Vlaanderen, J J; Janssen, N A; Hoek, G; Keski-Rahkonen, P; Barupal, D K; Cassee, F R; Gosens, I; Strak, M; Steenhof, M; Lan, Q; Brunekreef, B; Scalbert, A; Vermeulen, R C H

2017-07-01

Biological perturbations caused by air pollution might be reflected in the compounds present in blood originating from air pollutants and endogenous metabolites influenced by air pollution (defined here as part of the blood metabolome). We aimed to assess the perturbation of the blood metabolome in response to short term exposure to air pollution. We exposed 31 healthy volunteers to ambient air pollution for 5h. We measured exposure to particulate matter, particle number concentrations, absorbance, elemental/organic carbon, trace metals, secondary inorganic components, endotoxin content, gaseous pollutants, and particulate matter oxidative potential. We collected blood from the participants 2h before and 2 and 18h after exposure. We employed untargeted metabolite profiling to monitor 3873 metabolic features in 493 blood samples from these volunteers. We assessed lung function using spirometry and six acute phase proteins in peripheral blood. We assessed the association of the metabolic features with the measured air pollutants and with health markers that we previously observed to be associated with air pollution in this study. We observed 89 robust associations between air pollutants and metabolic features two hours after exposure and 118 robust associations 18h after exposure. Some of the metabolic features that were associated with air pollutants were also associated with acute health effects, especially changes in forced expiratory volume in 1s. We successfully identified tyrosine, guanosine, and hypoxanthine among the associated features. Bioinformatics approach Mummichog predicted enriched pathway activity in eight pathways, among which tyrosine metabolism. This study demonstrates for the first time the application of untargeted metabolite profiling to assess the impact of air pollution on the blood metabolome. Copyright © 2017 Elsevier Inc. All rights reserved.

Metabolomics Application in Maternal-Fetal Medicine

OpenAIRE

Fanos, Vassilios; Atzori, Luigi; Makarenko, Karina; Melis, Gian Benedetto; Ferrazzi, Enrico

2013-01-01

Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, prete...

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

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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.

Fusion of mass spectrometry-based metabolomics data

NARCIS (Netherlands)

Smilde, Age K.; van der Werf, Mariët J.; Bijlsma, Sabina; van der Werff-van der Vat, Bianca J. C.; Jellema, Renger H.

2005-01-01

A general method is presented for combining mass spectrometry-based metabolomics data. Such data are becoming more and more abundant, and proper tools for fusing these types of data sets are needed. Fusion of metabolomics data leads to a comprehensive view on the metabolome of an organism or

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

International Nuclear Information System (INIS)

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

Metabolomics enables precision medicine: "A White Paper, Community Perspective".

Science.gov (United States)

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

Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and

Metabolomics Application in Maternal-Fetal Medicine

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Vassilios Fanos

2013-01-01

Full Text Available Metabolomics in maternal-fetal medicine is still an “embryonic” science. However, there is already an increasing interest in metabolome of normal and complicated pregnancies, and neonatal outcomes. Tissues used for metabolomics interrogations of pregnant women, fetuses and newborns are amniotic fluid, blood, plasma, cord blood, placenta, urine, and vaginal secretions. All published papers highlight the strong correlation between biomarkers found in these tissues and fetal malformations, preterm delivery, premature rupture of membranes, gestational diabetes mellitus, preeclampsia, neonatal asphyxia, and hypoxic-ischemic encephalopathy. The aim of this review is to summarize and comment on original data available in relevant published works in order to emphasize the clinical potential of metabolomics in obstetrics in the immediate future.

Towards Polypharmacokinetics: Pharmacokinetics of Multicomponent Drugs and Herbal Medicines Using a Metabolomics Approach

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Ke Lan

2013-01-01

Full Text Available Determination of pharmacokinetics (PKs of multicomponent pharmaceuticals and/or nutraceuticals (polypharmacokinetics, poly-PKs is difficult due to the vast number of compounds present in natural products, their various concentrations across a wide range, complexity of their interactions, as well as their complex degradation dynamics in vivo. Metabolomics coupled with multivariate statistical tools that focus on the comprehensive analysis of small molecules in biofluids is a viable approach to address the challenges of poly-PK. This paper discusses recent advances in the characterization of poly-PK and the metabolism of multicomponent xenobiotic agents, such as compound drugs, dietary supplements, and herbal medicines, using metabolomics strategy. We propose a research framework that integrates the dynamic concentration profile of bioavailable xenobiotic molecules that result from in vivo absorption and hepatic and gut bacterial metabolism, as well as the human metabolic response profile. This framework will address the bottleneck problem in the pharmacological evaluation of multicomponent pharmaceuticals and nutraceuticals, leading to the direct elucidation of the pharmacological and molecular mechanisms of these compounds.

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

OpenAIRE

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 ...

A pilot study of the metabolomic profiles of saliva from female orthodontic patients with external apical root resorption.

Science.gov (United States)

Zhou, Jinglin; Hu, Huimin; Huang, Renhuan

2018-03-01

Orthodontically induced external apical root resorption (OIEARR) is one of the most severe complications of orthodontic treatment, which is hard to diagnose at early stage by merely radiographic examination. This study aimed to identify salivary metabolic products using unbiased metabolic profiling in order to discover biomarkers that may indicate OIEARR. Unstimulated saliva samples were analyzed from 19 healthy orthodontic patients with EARR (n=8) and non-EARR (n=11). Metabolite profiling was performed using 1 H Nuclear Magnetic Resonance (NMR) spectroscopy. A total of 187 metabolites were found in saliva samples. With supervised partial least squares discriminant analysis and regression analysis, samples from 2 groups were well separated, attributed by a series of metabolites of interest, including butyrate, propane-1,2-diol, α-linolenic acid (Ala), α-glucose, urea, fumarate, formate, guanosine, purine, etc. Indicating the increased inflammatory responses in the periodontal tissues possibly associated with energy metabolism and oxidative stress. The effective separation capacity of 1 H NMR based metabolomics suggested potential feasibility of clinical application in monitoring periodontal and apical condition in orthodontic patients during treatment and make early diagnosis of OIEARR. Metabolites detected in this study need further validation to identify exact biomarkers of OIEARR. Saliva biomarkers may assist in diagnosis and monitoring of this disease. Copyright © 2018 Elsevier B.V. All rights reserved.

Using NMR metabolomics to identify responses of an environmental estrogen in blood plasma of fish

International Nuclear Information System (INIS)

Samuelsson, Linda M.; Foerlin, Lars; Karlsson, Goeran; Adolfsson-Erici, Margaretha; Larsson, D.G. Joakim

2006-01-01

Nuclear magnetic resonance (NMR) based metabolomics in combination with multivariate data analysis may become valuable tools to study environmental effects of pharmaceuticals and other chemicals in aquatic organisms. To explore the usefulness of this approach in fish, we have used 1 H NMR metabolomics to compare blood plasma and plasma lipid extracts from rainbow trout exposed to the synthetic contraceptive estrogen ethinylestradiol (EE 2 ) with plasma from control fish. The plasma metabolite profile was affected in fish exposed to 10 ng/L but not 0.87 ng/L of EE 2 , which was in agreement with an induced vitellogenin synthesis in the high dose group only, as measured by ELISA. The main affected metabolites were vitellogenin, alanine, phospholipids and cholesterol. The responses identified by this discovery-driven method could be put in context with previous knowledge of the effects of estrogens on fish. This adds confidence to the approach of using NMR metabolomics to identify environmental effects of pharmaceuticals and other contaminants

Functional metabolomics reveals novel active products in the DHA metabolome

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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.

NMR metabolomics for assessment of exercise effects with mouse biofluids

Energy Technology Data Exchange (ETDEWEB)

Le Moyec, Laurence; Mille-Hamard, Laurence; Breuneval, Carole; Petot, Helene; Billat, Veronique L. [Universite Evry Val d' Essonne, UBIAE INSERM U902, Evry Cedex (France); Triba, Mohamed N. [Universite Paris 13, CSPBAT UMR 7244, Bobigny (France)

2012-08-15

Exercise modulates the metabolome in urine or blood as demonstrated previously for humans and animal models. Using nuclear magnetic resonance (NMR) metabolomics, the present study compares the metabolic consequences of an exhaustive exercise at peak velocity (Vp) and at critical velocity (Vc) on mice. Since small-volume samples (blood and urine) were collected, dilution was necessary to acquire NMR spectra. Consequently, specific processing methods were applied before statistical analysis. According to the type of exercise (control group, Vp group and Vc group), 26 male mice were divided into three groups. Mice were sacrificed 2 h after the end of exercise, and urine and blood samples were drawn from each mouse. Proton NMR spectra were acquired with urine and deproteinized blood. The NMR data were aligned with the icoshift method and normalised using the probabilistic quotient method. Finally, data were analysed with the orthogonal projection of latent-structure analysis. The spectra obtained with deproteinized blood can neither discriminate the control mice from exercised mice nor discriminate according to the duration of the exercise. With urine samples, a significant statistical model can be estimated when comparing the control mice to both groups, Vc and Vp. The best model is obtained according to the exercise duration with all mice. Taking into account the spectral regions having the highest correlations, the discriminant metabolites are allantoin, inosine and branched-chain amino acids. In conclusion, metabolomic profiles assessed with NMR are highly dependent on the exercise. These results show that urine samples are more informative than blood samples and that the duration of the exercise is a more important parameter to influence the metabolomic status than the exercise velocity. (orig.)

Symbiosis of chemometrics and metabolomics: past, present, and future

NARCIS (Netherlands)

van der Greef, J.; Smilde, A. K.

2005-01-01

Metabolomics is a growing area in the field of systems biology. Metabolomics has already a long history and also the connection of metabolomics with chemometrics goes back some time. This review discusses the symbiosis of metabolomics and chemometrics with emphasis on the medical domain, puts the

Metabolomic and Transcriptomic Comparison of Solid-State and Submerged Fermentation of Penicillium expansum KACC 40815.

Science.gov (United States)

Kim, Hyang Yeon; Heo, Do Yeon; Park, Hye Min; Singh, Digar; Lee, Choong Hwan

2016-01-01

Penicillium spp. are known to harbor a wide array of secondary metabolites with cryptic bioactivities. However, the metabolomics of these species is not well-understood in terms of different fermentation models and conditions. The present study involved metabolomics profiling and transcriptomic analysis of Penicillium expansum 40815 under solid-state fermentation (SSF) and submerged fermentation (SmF). Metabolite profiling was carried out using ultra-performance liquid chromatography quadruple time-of-flight mass spectrometry with multivariate analysis, followed by transcriptomic analyses of differentially expressed genes. In principal component analysis, the metabolite profiling data was studied under different experimental sets, including SSF and SmF. The significantly different metabolites such as polyketide metabolites (agonodepside B, rotiorin, verrucosidin, and ochrephilone) and corresponding gene transcripts (polyketide synthase, aromatic prenyltransferase, and terpenoid synthase) were primarily detected under SmF conditions. In contrast, the meroterpenoid compounds (andrastin A and C) and their genes transcripts were exclusively detected under SSF conditions. We demonstrated that the metabolite production and its corresponding gene expression levels in P. expansum 40815 were significantly influenced by the varying growth parameters and the immediate environment. This study further provides a foundation to produce specific metabolites by regulating fermentation conditions.

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

Directory of Open Access Journals (Sweden)

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

Metabolomic Effects of Xylitol and Fluoride on Plaque Biofilm in Vivo

Science.gov (United States)

Takahashi, N.; Washio, J.

2011-01-01

Dental caries is initiated by demineralization of the tooth surface through acid production from sugar by plaque biofilm. Fluoride and xylitol have been used worldwide as caries-preventive reagents, based on in vitro-proven inhibitory mechanisms on bacterial acid production. We attempted to confirm the inhibitory mechanisms of fluoride and xylitol in vivo by performing metabolome analysis on the central carbon metabolism in supragingival plaque using the combination of capillary electrophoresis and a time-of-flight mass spectrometer. Fluoride (225 and 900 ppm F−) inhibited lactate production from 10% glucose by 34% and 46%, respectively, along with the increase in 3-phosphoglycerate and the decrease in phosphoenolpyruvate in the EMP pathway in supragingival plaque. These results confirmed that fluoride inhibited bacterial enolase in the EMP pathway and subsequently repressed acid production in vivo. In contrast, 10% xylitol had no effect on acid production and the metabolome profile in supragingival plaque, although xylitol 5-phosphate was produced. These results suggest that xylitol is not an inhibitor of plaque acid production but rather a non-fermentative sugar alcohol. Metabolome analyses of plaque biofilm can be applied for monitoring the efficacy of dietary components and medicines for plaque biofilm, leading to the development of effective plaque control. PMID:21940519

Metabolomic effects of xylitol and fluoride on plaque biofilm in vivo.

Science.gov (United States)

Takahashi, N; Washio, J

2011-12-01

Dental caries is initiated by demineralization of the tooth surface through acid production from sugar by plaque biofilm. Fluoride and xylitol have been used worldwide as caries-preventive reagents, based on in vitro-proven inhibitory mechanisms on bacterial acid production. We attempted to confirm the inhibitory mechanisms of fluoride and xylitol in vivo by performing metabolome analysis on the central carbon metabolism in supragingival plaque using the combination of capillary electrophoresis and a time-of-flight mass spectrometer. Fluoride (225 and 900 ppm F(-)) inhibited lactate production from 10% glucose by 34% and 46%, respectively, along with the increase in 3-phosphoglycerate and the decrease in phosphoenolpyruvate in the EMP pathway in supragingival plaque. These results confirmed that fluoride inhibited bacterial enolase in the EMP pathway and subsequently repressed acid production in vivo. In contrast, 10% xylitol had no effect on acid production and the metabolome profile in supragingival plaque, although xylitol 5-phosphate was produced. These results suggest that xylitol is not an inhibitor of plaque acid production but rather a non-fermentative sugar alcohol. Metabolome analyses of plaque biofilm can be applied for monitoring the efficacy of dietary components and medicines for plaque biofilm, leading to the development of effective plaque control.

Application of Metabolomics to Quality Control of Natural Product Derived Medicines.

Science.gov (United States)

Lee, Kyung-Min; Jeon, Jun-Yeong; Lee, Byeong-Ju; Lee, Hwanhui; Choi, Hyung-Kyoon

2017-11-01

Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. Veregen ® (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

Metabolomics as a promising tool for early osteoarthritis diagnosis

Directory of Open Access Journals (Sweden)

E.B. de Sousa

2017-09-01

Full Text Available Osteoarthritis (OA is the main cause of disability worldwide, due to progressive articular cartilage loss and degeneration. According to recent research, OA is more than just a degenerative disease due to some metabolic components associated to its pathogenesis. However, no biomarker has been identified to detect this disease at early stages or to track its development. Metabolomics is an emerging field and has the potential to detect many metabolites in a single spectrum using high resolution nuclear magnetic resonance (NMR techniques or mass spectrometry (MS. NMR is a reproducible and reliable non-destructive analytical method. On the other hand, MS has a lower detection limit and is more destructive, but it is more sensitive. NMR and MS are useful for biological fluids, such as urine, blood plasma, serum, or synovial fluid, and have been used for metabolic profiling in dogs, mice, sheep, and humans. Thus, many metabolites have been listed as possibly associated to OA pathogenesis. The goal of this review is to provide an overview of the studies in animal models and humans, regarding the use of metabolomics as a tool for early osteoarthritis diagnosis. The concept of osteoarthritis as a metabolic disease and the importance of detecting a biomarker for its early diagnosis are highlighted. Then, some studies in plasma and synovial tissues are shown, and finally the application of metabolomics in the evaluation of synovial fluid is described.

Metabolomics of the aqueous humor in the rat glaucoma model induced by a series of intracamerular sodium hyaluronate injection.

Science.gov (United States)

Mayordomo-Febrer, A; López-Murcia, M; Morales-Tatay, J M; Monleón-Salvado, D; Pinazo-Durán, M D

2015-02-01

Glaucoma models are helpful to study disease characteristics and to design new therapeutic options. Metabolomic profiling approach have been used to elucidating the molecular characteristics of the aqueous humor. Juvenile male Wistar rats experimental (n = 15) and controls (n = 6) were used for these studies. Experimental rats received weekly intracamerular injection of 25 µl of sodium hyaluronate in the left eye and sterile saline solution in the right eye, consecutively for ten weeks. Rats were subjected to anterior/posterior eye segment examinations, intraocular pressure (IOP), and flash electroretinograms (ERG). The aqueous humor was collected at endpoints and analyzed by Nuclear Magnetic Resonance. Elevated IOP and significant reduction of a, b waves and amplitude of oscillatory potential was observed in the left eyes compared to control eyes. The aqueous humor metabolomic profile from control and the experimental eyes were compared. Concentrations of metabolites (amino acids, lipids and carbohydrates) significantly changed after the sodium hyaluronate injections series, compared to the sham-operated eyes. Metabolic changes in the hypertensive eyes correlated with the impaired retinal function. Observed metabolomic changes in aqueous humor in hypertensive state may play a significant role in glaucoma pathogenesis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome.

Science.gov (United States)

Naser, Fuad J; Mahieu, Nathaniel G; Wang, Lingjue; Spalding, Jonathan L; Johnson, Stephen L; Patti, Gary J

2018-02-01

Although it is common in untargeted metabolomics to apply reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) methods that have been systematically optimized for lipids and central carbon metabolites, here we show that these established protocols provide poor coverage of semipolar metabolites because of inadequate retention. Our objective was to develop an RPLC approach that improved detection of these metabolites without sacrificing lipid coverage. We initially evaluated columns recently released by Waters under the CORTECS line by analyzing 47 small-molecule standards that evenly span the nonpolar and semipolar ranges. An RPLC method commonly used in untargeted metabolomics was considered a benchmarking reference. We found that highly nonpolar and semipolar metabolites cannot be reliably profiled with any single method because of retention and solubility limitations of the injection solvent. Instead, we optimized a multiplexed approach using the CORTECS T3 column to analyze semipolar compounds and the CORTECS C 8 column to analyze lipids. Strikingly, we determined that combining these methods allowed detection of 41 of the total 47 standards, whereas our reference RPLC method detected only 10 of the 47 standards. We then applied credentialing to compare method performance at the comprehensive scale. The tandem method showed more than a fivefold increase in credentialing coverage relative to our RPLC benchmark. Our results demonstrate that comprehensive coverage of metabolites amenable to reversed-phase separation necessitates two reconstitution solvents and chromatographic methods. Thus, we suggest complementing HILIC methods with a dual T3 and C 8 RPLC approach to increase coverage of semipolar metabolites and lipids for untargeted metabolomics. Graphical abstract Analysis of semipolar and nonpolar metabolites necessitates two reversed-phase chromatography (RPLC) methods, which extend metabolome coverage more

FODMAPs alter symptoms and the metabolome of patients with IBS: a randomised controlled trial.

Science.gov (United States)

McIntosh, Keith; Reed, David E; Schneider, Theresa; Dang, Frances; Keshteli, Ammar H; De Palma, Giada; Madsen, Karen; Bercik, Premysl; Vanner, Stephen

2017-07-01

To gain mechanistic insights, we compared effects of low fermentable oligosaccharides, disaccharides and monosaccharides and polyols (FODMAP) and high FODMAP diets on symptoms, the metabolome and the microbiome of patients with IBS. We performed a controlled, single blind study of patients with IBS (Rome III criteria) randomised to a low (n=20) or high (n=20) FODMAP diet for 3 weeks. Symptoms were assessed using the IBS symptom severity scoring (IBS-SSS). The metabolome was evaluated using the lactulose breath test (LBT) and metabolic profiling in urine using mass spectrometry. Stool microbiota composition was analysed by 16S rRNA gene profiling. Thirty-seven patients (19 low FODMAP; 18 high FODMAP) completed the 3-week diet. The IBS-SSS was reduced in the low FODMAP diet group (pmetabolome. In subsets of patients, FODMAPs modulate histamine levels and the microbiota, both of which could alter symptoms. NCT01829932. 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/.

Of monkeys and men: A metabolomic analysis of static and dynamic urinary metabolic phenotypes in two species

NARCIS (Netherlands)

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

Of Monkeys and Men: A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

NARCIS (Netherlands)

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

Of Monkeys and Men : A Metabolomic Analysis of Static and Dynamic Urinary Metabolic Phenotypes in Two Species

NARCIS (Netherlands)

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

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

Energy Technology Data Exchange (ETDEWEB)

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

Mass spectrometry-based metabolomics for tuberculosis meningitis.

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Zhang, Peixu; Zhang, Weiguanliu; Lang, Yue; Qu, Yan; Chu, Fengna; Chen, Jiafeng; Cui, Li

2018-04-18

Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described. Copyright © 2018. Published by Elsevier B.V.

Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments

Science.gov (United States)

Valkenborg, Dirk; Baggerman, Geert; Vanaerschot, Manu; Witters, Erwin; Dujardin, Jean-Claude; Burzykowski, Tomasz; Berg, Maya

2013-01-01

Abstract Combining liquid chromatography-mass spectrometry (LC-MS)-based metabolomics experiments that were collected over a long period of time remains problematic due to systematic variability between LC-MS measurements. Until now, most normalization methods for LC-MS data are model-driven, based on internal standards or intermediate quality control runs, where an external model is extrapolated to the dataset of interest. In the first part of this article, we evaluate several existing data-driven normalization approaches on LC-MS metabolomics experiments, which do not require the use of internal standards. According to variability measures, each normalization method performs relatively well, showing that the use of any normalization method will greatly improve data-analysis originating from multiple experimental runs. In the second part, we apply cyclic-Loess normalization to a Leishmania sample. This normalization method allows the removal of systematic variability between two measurement blocks over time and maintains the differential metabolites. In conclusion, normalization allows for pooling datasets from different measurement blocks over time and increases the statistical power of the analysis, hence paving the way to increase the scale of LC-MS metabolomics experiments. From our investigation, we recommend data-driven normalization methods over model-driven normalization methods, if only a few internal standards were used. Moreover, data-driven normalization methods are the best option to normalize datasets from untargeted LC-MS experiments. PMID:23808607

Metabolomic profiling and sensorial quality of 'Golden Delicious', 'Liberty', 'Santana', and 'Topaz' apples grown using organic and integrated production systems.

Science.gov (United States)

Vanzo, Andreja; Jenko, Mojca; Vrhovsek, Urska; Stopar, Matej

2013-07-03

Apple quality was investigated in the scab-resistant 'Liberty', 'Santana', and 'Topaz' cultivars and the scab-susceptible 'Golden Delicious' cultivar. Trees subjected to the same crop load were cultivated using either an organic (ORG) or an integrated production (IP) system. Physicochemical properties, phenolic content, and sensorial quality of fruit from both systems were compared. There were no significant differences in fruit mass, starch, and total soluble solid content (the latter was higher in ORG 'Liberty') between ORG and IP fruit, whereas significantly higher flesh firmness was found in ORG fruit (except no difference in 'Golden Delicious'). Significantly higher total phenolic content in ORG fruit was found in 'Golden Delicious', whereas differences in other cultivars were not significant. Targeted metabolomic profiling of multiple classes of phenolics confirmed the impact of the production system on the 'Golden Delicious' phenolic profile as higher levels of 4-hydroxybenzoic acid, neo- and chlorogenic acids, phloridzin, procyanidin B2+B4, -3-O-glucoside and -3-O-galactoside of quercetin, kaempferol-3-O-rutinoside, and rutin being found in ORG fruit. The results obtained suggested that scab resistance influenced the phenolic biosynthesis in relation to the agricultural system. Sensorial evaluation indicated significantly better flavor (except for 'Topaz') and better appearance of IP fruit.

Endocrinology Meets Metabolomics: Achievements, Pitfalls, and Challenges.

Science.gov (United States)

Tokarz, Janina; Haid, Mark; Cecil, Alexander; Prehn, Cornelia; Artati, Anna; Möller, Gabriele; Adamski, Jerzy

2017-10-01

The metabolome, although very dynamic, is sufficiently stable to provide specific quantitative traits related to health and disease. Metabolomics requires balanced use of state-of-the-art study design, chemical analytics, biostatistics, and bioinformatics to deliver meaningful answers to contemporary questions in human disease research. The technology is now frequently employed for biomarker discovery and for elucidating the mechanisms underlying endocrine-related diseases. Metabolomics has also enriched genome-wide association studies (GWAS) in this area by providing functional data. The contributions of rare genetic variants to metabolome variance and to the human phenotype have been underestimated until now. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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.

Metabolomic variation of brassica rapa var. rapa (var. raapstelen) and raphanus sativus l. at different developmental stages

International Nuclear Information System (INIS)

Jahangir, M.; Farid, I.B.A.

2014-01-01

Brassica rapa (var. raapstelen) and Raphanus sativus (red radish) are being used as food and fodder while also known as model in recent plant research due to the diversity of metabolites as well as genetic resemblance to Arabidopsis. This study explains the change in metabolites (amino acids, organic acids, chlorophyll, carotenoids, tocopherols, ascorbic acid, sucrose, phenylpropanoids and glucosinolates) during plant development. In present study the metabolomic variation in relation to plant growth has been evaluated, for Brassica rapa (var. raapstelen) and red radish (Raphanus sativus) at three different developmental stages. A non-targeted and targeted metabolomic approach by NMR and HPLC in combination with Principal component analysis (PCA) of the data was used to identify phytochemicals being influenced by plant growth. The results lead to the better understanding of metabolic changes during plant development and show the importance of plant age with respect to the metabolomic profile of vegetables. (author)

Effect of pharmacologic resuscitation on the brain gene expression profiles in a swine model of traumatic brain injury and hemorrhage

DEFF Research Database (Denmark)

Dekker, Simone E; Bambakidis, Ted; Sillesen, Martin

2014-01-01

BACKGROUND: We have previously shown that addition of valproic acid (VPA; a histone deacetylase inhibitor) to hetastarch (Hextend [HEX]) resuscitation significantly decreases lesion size in a swine model of traumatic brain injury (TBI) and hemorrhagic shock (HS). However, the precise mechanisms...... have not been well defined. As VPA is a transcriptional modulator, the aim of this study was to investigate its effect on brain gene expression profiles. METHODS: Swine were subjected to controlled TBI and HS (40% blood volume), kept in shock for 2 hours, and resuscitated with HEX or HEX + VPA (n = 5...... per group). Following 6 hours of observation, brain RNA was isolated, and gene expression profiles were measured using a Porcine Gene ST 1.1 microarray (Affymetrix, Santa Clara, CA). Pathway analysis was done using network analysis tools Gene Ontology, Ingenuity Pathway Analysis, and Parametric Gene...

Towards a scientific interpretation of the terroir concept: plasticity of the grape berry metabolome.

Science.gov (United States)

Anesi, Andrea; Stocchero, Matteo; Dal Santo, Silvia; Commisso, Mauro; Zenoni, Sara; Ceoldo, Stefania; Tornielli, Giovanni Battista; Siebert, Tracey E; Herderich, Markus; Pezzotti, Mario; Guzzo, Flavia

2015-08-07

The definition of the terroir concept is one of the most debated issues in oenology and viticulture. The dynamic interaction among diverse factors including the environment, the grapevine plant and the imposed viticultural techniques means that the wine produced in a given terroir is unique. However, there is an increasing interest to define and quantify the contribution of individual factors to a specific terroir objectively. Here, we characterized the metabolome and transcriptome of berries from a single clone of the Corvina variety cultivated in seven different vineyards, located in three macrozones, over a 3-year trial period. To overcome the anticipated strong vintage effect, we developed statistical tools that allowed us to identify distinct terroir signatures in the metabolic composition of berries from each macrozone, and from different vineyards within each macrozone. We also identified non-volatile and volatile components of the metabolome which are more plastic and therefore respond differently to terroir diversity. We observed some relationships between the plasticity of the metabolome and transcriptome, allowing a multifaceted scientific interpretation of the terroir concept. Our experiments with a single Corvina clone in different vineyards have revealed the existence of a clear terroir-specific effect on the transcriptome and metabolome which persists over several vintages and allows each vineyard to be characterized by the unique profile of specific metabolites.

Metabolomics data normalization with EigenMS.

Directory of Open Access Journals (Sweden)

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.

Sample normalization methods in quantitative metabolomics.

Science.gov (United States)

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.

Characterization of the concurrent metabolic changes in brain and plasma during insulin-induced moderate hypoglycemia using 1H NMR spectroscopy in juvenile rats.

Science.gov (United States)

Ennis, Kathleen; Lusczek, Elizabeth; Rao, Raghavendra

2017-07-13

Treatment of hypoglycemia in children is currently based on plasma glucose measurements. This approach may not ensure neuroprotection since plasma glucose does not reflect the dynamic state of cerebral energy metabolism. To determine whether cerebral metabolic changes during hypoglycemia could be better characterized using plasma metabolomic analysis, insulin-induced acute hypoglycemia was induced in 4-week-old rats. Brain tissue and concurrent plasma samples were collected from hypoglycemic (N=7) and control (N=7) rats after focused microwave fixation to prevent post-mortem metabolic changes. The concentration of 29 metabolites in brain and 34 metabolites in plasma were determined using 1 H NMR spectroscopy at 700MHz and examined using partial least squares-discriminant analysis. The sensitivity of plasma glucose for detecting cerebral energy failure was assessed by determining its relationship to brain phosphocreatine. The brain and plasma metabolite profiles of the hypoglycemia group were distinct from the control group (brain: R 2 =0.92, Q 2 =0.31; plasma: R 2 =0.95, Q 2 =0.74). Concentration differences in glucose, ketone bodies and amino acids were responsible for the intergroup separation. There was 45% concordance between the brain and plasma metabolite profiles. Brain phosphocreatine correlated with brain glucose (control group: R 2 =0.86; hypoglycemia group: R 2 =0.59; pplasma glucose. The results confirm that plasma glucose is an insensitive biomarker of cerebral energy changes during hypoglycemia and suggest that a plasma metabolite profile is superior for monitoring cerebral metabolism. Copyright © 2017 Elsevier B.V. All rights reserved.

Probabilistic Principal Component Analysis for Metabolomic Data.

LENUS (Irish Health Repository)

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.

Human Plasma Metabolomics Study across All Stages of Age-Related Macular Degeneration Identifies Potential Lipid Biomarkers.

Science.gov (United States)

Laíns, Inês; Kelly, Rachel S; Miller, John B; Silva, Rufino; Vavvas, Demetrios G; Kim, Ivana K; Murta, Joaquim N; Lasky-Su, Jessica; Miller, Joan W; Husain, Deeba

2018-02-01

To characterize the plasma metabolomic profile of patients with age-related macular degeneration (AMD) using mass spectrometry (MS). Cross-sectional observational study. We prospectively recruited participants with a diagnosis of AMD and a control group (>50 years of age) without any vitreoretinal disease. All participants underwent color fundus photography, used for AMD diagnosis and staging, according to the Age-Related Eye Disease Study classification scheme. Fasting blood samples were collected and plasma was analyzed by Metabolon, Inc. (Durham, NC), using ultrahigh-performance liquid chromatography (UPLC) and high-resolution MS. Metabolon's hardware and software were used to identify peaks and control quality. Principal component analysis and multivariate regression were performed to assess differences in the metabolomic profiles of AMD patients versus controls, while controlling for potential confounders. For biological interpretation, pathway enrichment analysis of significant metabolites was performed using MetaboAnalyst. The primary outcome measures were levels of plasma metabolites in participants with AMD compared with controls and among different AMD severity stages. We included 90 participants with AMD (30 with early AMD, 30 with intermediate AMD, and 30 with late AMD) and 30 controls. Using UPLC and MS, 878 biochemicals were identified. Multivariate logistic regression identified 87 metabolites with levels that differed significantly between AMD patients and controls. Most of these metabolites (82.8%; n = 72), including the most significant metabolites, belonged to the lipid pathways. Analysis of variance revealed that of the 87 metabolites, 48 (55.2%) also were significantly different across the different stages of AMD. A significant enrichment of the glycerophospholipids pathway was identified (P = 4.7 × 10 -9 ) among these metabolites. Participants with AMD have altered plasma metabolomic profiles compared with controls. Our data suggest

Mathematical Modeling Approaches in Plant Metabolomics.

Science.gov (United States)

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.

An explorative study of the effect of apple and apple products on the human plasma metabolome investigated by LC–MS profiling

DEFF Research Database (Denmark)

Rago, Daniela; Gürdeniz, Gözde; Ravn-Haren, Gitte

2015-01-01

Apple is one of the most commonly consumed fruits worldwide and it has been associated with several health effects, especially on plasma cholesterol and risk of cardiovascular disease both in human and animal studies. By using an untargeted metabolomics approach we wanted to investigate whether...... supplementation of whole apple or processed apple products affect the human plasma metabolome. Therefore, 24 healthy volunteers were recruited for a comprehensive 5 × 4 weeks dietary crossover study and receiving supplement of whole apples (550 g/day), clear and cloudy apple juices (500 ml/day), dried apple...... metabolome than the other apple products. We observed an effect on branched-chain amino acids and aromatic amino acids degradation, and a decreased use of lipid fuels indicating an improvement in glucose utilisation. A reduced level of plasma bile acids after apple consumption may indicate less re...

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

Science.gov (United States)

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

Updates in metabolomics tools and resources: 2014-2015.

Science.gov (United States)

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.

New tools and resources in metabolomics: 2016-2017.

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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.

Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies.

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Zaitsu, Kei; Hayashi, Yumi; Kusano, Maiko; Tsuchihashi, Hitoshi; Ishii, Akira

2016-02-01

Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided. Copyright © 2015 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

Metabolomic profiling in cattle experimentally infected with Mycobacterium avium subsp. paratuberculosis.

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Jeroen De Buck

Full Text Available The sensitivity of current diagnostics for Johne's disease, a slow, progressing enteritis in ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP, is too low to reliably detect all infected animals in the subclinical stage. The objective was to identify individual metabolites or metabolite profiles that could be used as biomarkers of early MAP infection in ruminants. In a monthly follow-up for 17 months, calves infected at 2 weeks of age were compared with aged-matched controls. Sera from all animals were analyzed by 1H nuclear magnetic resonance spectrometry. Spectra were acquired, processed, and quantified for analysis. The concentration of many metabolites changed over time in all calves, but some metabolites only changed over time in either infected or non-infected groups and the change in others was impacted by the infection. Hierarchical multivariate statistical analysis achieved best separation between groups between 300 and 400 days after infection. Therefore, a cross-sectional comparison between 1-year-old calves experimentally infected at various ages with either a high- or a low-dose and age-matched non-infected controls was performed. Orthogonal Projection to Latent Structures Discriminant Analysis (OPLS DA yielded distinct separation of non-infected from infected cattle, regardless of dose and time (3, 6, 9 or 12 months after infection. Receiver Operating Curves demonstrated that constructed models were high quality. Increased isobutyrate in the infected cattle was the most important agreement between the longitudinal and cross-sectional analysis. In general, high- and low-dose cattle responded similarly to infection. Differences in acetone, citrate, glycerol and iso-butyrate concentrations indicated energy shortages and increased fat metabolism in infected cattle, whereas changes in urea and several amino acids (AA, including the branched chain AA, indicated increased protein turnover. In conclusion, metabolomics

Metabolomics through the lens of precision cardiovascular medicine.

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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.

Metabolomics applied to the pancreatic islet.

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Gooding, Jessica R; Jensen, Mette V; Newgard, Christopher B

2016-01-01

Metabolomics, the characterization of the set of small molecules in a biological system, is advancing research in multiple areas of islet biology. Measuring a breadth of metabolites simultaneously provides a broad perspective on metabolic changes as the islets respond dynamically to metabolic fuels, hormones, or environmental stressors. As a result, metabolomics has the potential to provide new mechanistic insights into islet physiology and pathophysiology. Here we summarize advances in our understanding of islet physiology and the etiologies of type-1 and type-2 diabetes gained from metabolomics studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Developmental Research in Space: Predicting Adult Neurobehavioral Phenotypes via Metabolomic Imaging

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Schorn, Julia M.; Moyer, Eric L.; Lowe, Moniece M.; Morgan, Jonathan; Tulbert, Christina D.; Olson, John; Olson, John; Horita, David A.; Kleven, Gale A.

2017-01-01

As human habitation and eventual colonization of space becomes an inevitable reality, there is a necessity to understand how organisms develop over the life span in the space environment. Microgravity, altered CO2, radiation and psychological stress are some of the key factors that could affect mammalian reproduction and development in space, however there is a paucity of information on this topic. Here we combine early (neonatal) in vivo spectroscopic imaging with an adult emotionality assay following a common obstetric complication (prenatal asphyxia) likely to occur during gestation in space. The neural metabolome is sensitive to alteration by degenerative changes and developmental disorders, thus we hypothesized that that early neonatal neurometabolite profiles can predict adult response to novelty. Late gestation fetal rats were exposed to moderate asphyxia by occluding the blood supply feeding one of the rats pair uterine horns for 15min. Blood supply to the opposite horn was not occluded (within-litter cesarean control). Further comparisons were made with vaginal (natural) birth controls. In one-week old neonates, we measured neurometabolites in three brain areas (i.e., striatum, prefrontal cortex, and hippocampus). Adult perinatally-asphyxiated offspring exhibited greater anxiety-like behavioral phenotypes (as measured the composite neurobehavioral assay involving open field activity, responses to novel object, quantification of fecal droppings, and resident-intruder tests of social behavior). Further, early neurometabolite profiles predicted adult responses. Non-invasive MRS screening of mammalian offspring is likely to advance ground-based space analogue studies informing mammalian reproduction in space, and achieving high-priority.

Metabolomics applied to diabetes-lessons from human population studies.

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Liggi, Sonia; Griffin, Julian L

2017-12-01

The 'classical' distribution of type 2 diabetes (T2D) across the globe is rapidly changing and it is no longer predominantly a disease of middle-aged/elderly adults of western countries, but it is becoming more common through Asia and the Middle East, as well as increasingly found in younger individuals. This global altered incidence of T2D is most likely associated with the spread of western diets and sedentary lifestyles, although there is still much debate as to whether the increased incidence rates are due to an overconsumption of fats, sugars or more generally high-calorie foods. In this context, understanding the interactions between genes of risk and diet and how they influence the incidence of T2D will help define the causative pathways of the disease. This review focuses on the use of metabolomics in large cohort studies to follow the incidence of type 2 diabetes in different populations. Such approaches have been used to identify new biomarkers of pre-diabetes, such as branch chain amino acids, and associate metabolomic profiles with genes of known risk in T2D from large scale GWAS studies. As the field develops, there are also examples of meta-analysis across metabolomics cohort studies and cross-comparisons with different populations to allow us to understand how genes and diet contribute to disease risk. Such approaches demonstrate that insulin resistance and T2D have far reaching metabolic effects beyond raised blood glucose and how the disease impacts systemic metabolism. Copyright © 2017 Elsevier Ltd. All rights reserved.

Serum metabolomics differentiating pancreatic cancer from new-onset diabetes

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He, Xiangyi; Zhong, Jie; Wang, Shuwei; Zhou, Yufen; Wang, Lei; Zhang, Yongping; Yuan, Yaozong

2017-01-01

To establish a screening strategy for pancreatic cancer (PC) based on new-onset diabetic mellitus (NO-DM), serum metabolomics analysis and a search for the metabolic pathways associated with PC related DM were performed. Serum samples from patients with NO-DM (n = 30) and patients with pancreatic cancer and NO-DM were examined by liquid chromatography-mass spectrometry. Data were analyzed using principal components analysis (PCA) and orthogonal projection to latent structures (OPLS) of the most significant metabolites. The diagnostic model was constructed using logistic regression analysis. Metabolic pathways were analyzed using the web-based tool MetPA. PC patients with NO-DM were older and had a lower BMI and shorter duration of DM than those with NO-DM. The metabolomic profiles of patients with PC and NO-DM were significantly different from those of patients with NO-DM in the PCA and OPLS models. Sixty two differential metabolites were identified by the OPLS model. The logistic regression model using a panel of two metabolites including N_Succinyl_L_diaminopimelic_acid and PE (18:2) had high sensitivity (93.3%) and specificity (93.1%) for PC. The top three metabolic pathways associated with PC related DM were valine, leucine and isoleucine biosynthesis and degradation, primary bile acid biosynthesis, and sphingolipid metabolism. In conclusion, screening for PC based on NO-DM using serum metabolomics in combination with clinic characteristics and CA19-9 is a potential useful strategy. Several metabolic pathways differed between PC related DM and type 2 DM. PMID:28418859

Comprehensive metabolomics identified lipid peroxidation as a prominent feature in human plasma of patients with coronary heart diseases

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Jianhong Lu

2017-08-01

Full Text Available Coronary heart disease (CHD is a complex human disease associated with inflammation and oxidative stress. The underlying mechanisms and diagnostic biomarkers for the different types of CHD remain poorly defined. Metabolomics has been increasingly recognized as an enabling technique with the potential to identify key metabolomic features in an attempt to understand the pathophysiology and differentiate different stages of CHD. We performed comprehensive metabolomic analysis in human plasma from 28 human subjects with stable angina (SA, myocardial infarction (MI, and healthy control (HC. Subsequent analysis demonstrated a uniquely altered metabolic profile in these CHD: a total of 18, 37 and 36 differential metabolites were identified to distinguish SA from HC, MI from SA, and MI from HC groups respectively. Among these metabolites, glycerophospholipid (GPL metabolism emerged as the most significantly disturbed pathway. Next, we used a targeted metabolomic approach to systematically analyze GPL, oxidized phospholipid (oxPL, and downstream metabolites derived from polyunsaturated fatty acids (PUFAs, such as arachidonic acid and linoleic acid. Surprisingly, lipids associated with lipid peroxidation (LPO pathways including oxidized PL and isoprostanes, isomers of prostaglandins, were significantly elevated in plasma of MI patients comparing to HC and SA, consistent with the notion that oxidative stress-induced LPO is a prominent feature in CHD. Our studies using the state-of-the-art metabolomics help to understand the underlying biological mechanisms involved in the pathogenesis of CHD; LPO metabolites may serve as potential biomarkers to differentiation MI from SA and HC. Keywords: Metabolomics, Lipid peroxidation, Lipidomics, Myocardial infarction, Isoprostanes, Coronary heart disease (CHD

Protein profiles of serum, brain regions and hypophyses of pubertal ...

African Journals Online (AJOL)

The effects of dietary fumonisin B1 (FB1 ), a toxin produced mainly by Fusarium verticillioides and F. proliferatum that grow on maize worldwide, on protein profiles of serum, brain regions and hypophyses were studied in 24 male Large White weanling pigs randomly divided into four groups (n = 6). In a completely ...

Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe.

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Lamichhane, Santosh; Sen, Partho; Dickens, Alex M; Orešič, Matej; Bertram, Hanne Christine

2018-04-30

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 of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted. Copyright © 2018 Elsevier Inc. All rights reserved.

Systematic Applications of Metabolomics in Metabolic Engineering

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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.

Tools for the functional interpretation of metabolomic experiments.

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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.

Microbial metabolomics in open microscale platforms

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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

Prediction of Clinically Relevant Safety Signals of Nephrotoxicity through Plasma Metabolite Profiling

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W. B. Mattes

2013-01-01

Full Text Available Addressing safety concerns such as drug-induced kidney injury (DIKI early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC. The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound’s well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity, not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

YMDB: the Yeast Metabolome Database

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Jewison, Timothy; Knox, Craig; Neveu, Vanessa; Djoumbou, Yannick; Guo, An Chi; Lee, Jacqueline; Liu, Philip; Mandal, Rupasri; Krishnamurthy, Ram; Sinelnikov, Igor; Wilson, Michael; Wishart, David S.

2012-01-01

The Yeast Metabolome Database (YMDB, http://www.ymdb.ca) is a richly annotated ‘metabolomic’ database containing detailed information about the metabolome of Saccharomyces cerevisiae. Modeled closely after the Human Metabolome Database, the YMDB contains >2000 metabolites with links to 995 different genes/proteins, including enzymes and transporters. The information in YMDB has been gathered from hundreds of books, journal articles and electronic databases. In addition to its comprehensive literature-derived data, the YMDB also contains an extensive collection of experimental intracellular and extracellular metabolite concentration data compiled from detailed Mass Spectrometry (MS) and Nuclear Magnetic Resonance (NMR) metabolomic analyses performed in our lab. This is further supplemented with thousands of NMR and MS spectra collected on pure, reference yeast metabolites. Each metabolite entry in the YMDB contains an average of 80 separate data fields including comprehensive compound description, names and synonyms, structural information, physico-chemical data, reference NMR and MS spectra, intracellular/extracellular concentrations, growth conditions and substrates, pathway information, enzyme data, gene/protein sequence data, as well as numerous hyperlinks to images, references and other public databases. Extensive searching, relational querying and data browsing tools are also provided that support text, chemical structure, spectral, molecular weight and gene/protein sequence queries. Because of S. cervesiae's importance as a model organism for biologists and as a biofactory for industry, we believe this kind of database could have considerable appeal not only to metabolomics researchers, but also to yeast biologists, systems biologists, the industrial fermentation industry, as well as the beer, wine and spirit industry. PMID:22064855

Metabolite profiles and the risk of developing diabetes

OpenAIRE

2011-01-01

Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines, and other polar metabolites were profiled in baseline specimens using liquid chromatography-tandem mass spectrometry. Cases and controls were matched for age, body mass index and fasting g...

Comparison of two GM maize varieties with a near-isogenic non-GM variety using transcriptomics, proteomics and metabolomics

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Barros, E.; Lezar, S.; Anttonen, M.J.; Dijk, van J.P.; Rohlig, R.M.; Kok, E.J.; Engel, K.H.

2010-01-01

P>The aim of this study was to evaluate the use of four nontargeted analytical methodologies in the detection of unintended effects that could be derived during genetic manipulation of crops. Three profiling technologies were used to compare the transcriptome, proteome and metabolome of two

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

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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.

A New Method of Area under the Absorbance-Wavelength Curve for Rats Total Metabolomic Pharmacokinetics from Yangxue Injection with Multicomponents

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Lihong Zhang

2013-01-01

Full Text Available To bridge the convergence between traditional Chinese medicine (TCM and modern medicine originated from the West, a new method of area under the absorbance-wavelength curve (AUAWC by spectrophotometer scanning was investigated and compared with HPLC method to explore metabolomic pharmacokinetics in rats. AUAWC and drug total concentration were obtained after Yangxue was injected to rats. Meanwhile, individual concentrations of sodium ferulate, tetramethylpyrazine hydrochloride, tanshinol sodium, and sodium tanshinone IIA sulfonate in plasma were determined by HPLC. Metabolomic profile of multicomponents plasma concentration time from AUAWC and that of individual components from HPLC were compared. The data from AUAWC had one-compartment model with mean area under concentration versus time (AUC of 9370.58 min·μg/mL and mean elimination half-life (t1/2 of 12.92 min. The results by HPLC demonstrated that sodium ferulate and tetramethylpyrazine hydrochloride had one-compartment model with AUC of 6075.50 and 876.94 min·μg/mL, t1/2 of 10.85 and 20.57 min, respectively. Tanshinol sodium and sodium tanshinone IIA sulfonate showed two-compartment model, and AUC was 29.58 and 201.46 with t1/2β of 1.76 and 16.90, respectively. The profiles indicated that method of AUAWC can be used to study pharmacokinetics of TCM with multicomponents and to improve its development of active theory and application in clinic combined with in vivo metabolomic profile of HPLC.

Application of NMR-based metabolomics for environmental assessment in the Great Lakes using zebra mussel (Dreissena polymorpha).

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Watanabe, Miki; Meyer, Kathryn A; Jackson, Tyler M; Schock, Tracey B; Johnson, W Edward; Bearden, Daniel W

Zebra mussel, Dreissena polymorpha , in the Great Lakes is being monitored as a bio-indicator organism for environmental health effects by the National Oceanic and Atmospheric Administration's Mussel Watch program. In order to monitor the environmental effects of industrial pollution on the ecosystem, invasive zebra mussels were collected from four stations-three inner harbor sites (LMMB4, LMMB1, and LMMB) in Milwaukee Estuary, and one reference site (LMMB5) in Lake Michigan, Wisconsin. Nuclear magnetic resonance (NMR)-based metabolomics was used to evaluate the metabolic profiles of the mussels from these four sites. The objective was to observe whether there were differences in metabolite profiles between impacted sites and the reference site; and if there were metabolic profile differences among the impacted sites. Principal component analyses indicated there was no significant difference between two impacted sites: north Milwaukee harbor (LMMB and LMMB4) and the LMMB5 reference site. However, significant metabolic differences were observed between the impacted site on the south Milwaukee harbor (LMMB1) and the LMMB5 reference site, a finding that correlates with preliminary sediment toxicity results. A total of 26 altered metabolites (including two unidentified peaks) were successfully identified in a comparison of zebra mussels from the LMMB1 site and LMMB5 reference site. The application of both uni- and multivariate analysis not only confirmed the variability of altered metabolites but also ensured that these metabolites were identified via unbiased analysis. This study has demonstrated the feasibility of the NMR-based metabolomics approach to assess whole-body metabolomics of zebra mussels to study the physiological impact of toxicant exposure at field sites.

Global metabolic profiling procedures for urine using UPLC-MS.

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Want, Elizabeth J; Wilson, Ian D; Gika, Helen; Theodoridis, Georgios; Plumb, Robert S; Shockcor, John; Holmes, Elaine; Nicholson, Jeremy K

2010-06-01

The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.

The food metabolome: a window over dietary exposure.

Science.gov (United States)

Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine; Andres-Lacueva, Cristina; Dragsted, Lars O; Draper, John; Rappaport, Stephen M; van der Hooft, Justin J J; Wishart, David S

2014-06-01

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 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 compositions by using hypothesis-driven approaches. However, the rapid development of metabolomics resulting from the development of highly sensitive modern analytic instruments, the availability of metabolite databases, and progress in (bio)informatics has made agnostic approaches more attractive as shown 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 face hurdles, which slow progress and need to be resolved to bring this emerging field of research to maturity. These limits were discussed during the First International Workshop on the Food Metabolome held in Glasgow. Key recommendations made during the workshop included more coordination of efforts; development of new databases, software tools, and chemical libraries for the food metabolome; and shared repositories of metabolomic data. Once achieved, major progress can be expected toward a better understanding of the complex interactions between diet and human health. © 2014 American Society for Nutrition.

Dietary salecan reverts partially the metabolic gene expressions and NMR-based metabolomic profiles from high-fat-diet-induced obese rats.

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Sun, Qi; Li, Minghui; Yang, Xiao; Xu, Xi; Wang, Junsong; Zhang, Jianfa

2017-09-01

Previous studies suggest that dietary salecan (a water-soluble β-glucan) effectively reduces high-fat-diet-induced adiposity through disturbing bile-acid-promoted emulsification in mice. However, the effects of salecan on metabolic genes and metabolites involved in lipid accumulation are mostly unknown. Here, we confirmed that dietary 3% and 6% salecan for 4 weeks markedly decreased fat accumulation in liver and adipose tissue in high-fat-diet rats, displaying a decrease in mRNA levels of SREBP1-C, FAS, SCD1 and ACC1 involved in de novo lipogenesis and a reduction of levels of GPAT1, DGAT1 and DGAT2 related to triglyceride synthesis. Dietary salecan also increased the mRNA levels of PPARα and CYP7A1, which are related to fatty acid oxidation and cholesterol decomposition, respectively. In the 1 H nuclear magnetic resonance metabolomic analysis, both the serum and liver metabolite profiles differed among the control groups, and the metabolic profiles of the salecan groups were shifted toward that of the low-fat-diet group. Metabolites analysis showed that salecan significantly increased hepatic glutathione and betaine levels which are related to regulation of cellular reactive oxygen species. These data demonstrate that dietary salecan not only disturbed fat digestion and absorption but also influenced lipid accumulation and metabolism in diet-induced obesity. Copyright © 2017 Elsevier Inc. All rights reserved.

The Human Urine Metabolome

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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

Intra- and inter-metabolite correlation spectroscopy of tomato metabolomics data obtained by liquid chromatography-mass spectrometry and nuclear magnetic resonance

NARCIS (Netherlands)

Moco, S.I.A.; Forshed, J.; Vos, de C.H.; Bino, R.J.; Vervoort, J.J.M.

2008-01-01

Nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LCMS) are frequently used as technological platforms for metabolomics applications. In this study, the metabolic profiles of ripe fruits from 50 different tomato cultivars, including beef, cherry and round types, were

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

Science.gov (United States)

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

Urinary Metabolomic Profiling to Identify Potential Biomarkers for the Diagnosis of Behcet’s Disease by Gas Chromatography/Time-of-Flight−Mass Spectrometry

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Joong Kyong Ahn

2017-11-01

Full Text Available Diagnosing Behcet’s disease (BD is challenging because of the lack of a diagnostic biomarker. The purposes of this study were to investigate distinctive metabolic changes in urine samples of BD patients and to identify urinary metabolic biomarkers for diagnosis of BD using gas chromatography/time-of-flight–mass spectrometry (GC/TOF−MS. Metabolomic profiling of urine samples from 44 BD patients and 41 healthy controls (HC were assessed using GC/TOF−MS, in conjunction with multivariate statistical analysis. A total of 110 urinary metabolites were identified. The urine metabolite profiles obtained from GC/TOF−MS analysis could distinguish BD patients from the HC group in the discovery set. The parameter values of the orthogonal partial least squared-discrimination analysis (OPLS-DA model were R2X of 0.231, R2Y of 0.804, and Q2 of 0.598. A biomarker panel composed of guanine, pyrrole-2-carboxylate, 3-hydroxypyridine, mannose, l-citrulline, galactonate, isothreonate, sedoheptuloses, hypoxanthine, and gluconic acid lactone were selected and adequately validated as putative biomarkers of BD (sensitivity 96.7%, specificity 93.3%, area under the curve 0.974. OPLS-DA showed clear discrimination of BD and HC groups by a biomarker panel of ten metabolites in the independent set (accuracy 88%. We demonstrated characteristic urinary metabolic profiles and potential urinary metabolite biomarkers that have clinical value in the diagnosis of BD using GC/TOF−MS.

Gut microbiome composition and metabolomic profiles/nof wild western lowland gorillas (Gorilla gorilla gorilla)/nreflect host ecology

Czech Academy of Sciences Publication Activity Database

Gomez, A.; Petrželková, Klára Judita; Yeoman, C. J.; Vlčková, K.; Mrázek, J.; Koppova, I.; Carbonero, F.; Ulanov, A.; Modrý, David; Todd, A.; Torralba, M.; Nelson, K. E.; Gaskins, H. R.; Wilson, B.; Stumpf, R. M.; White, B. A.; Leigh, S. R.

2015-01-01

Roč. 24, č. 10 (2015), s. 2551-2565 ISSN 0962-1083 R&D Projects: GA ČR GA206/09/0927 Institutional support: RVO:60077344 Keywords : anthropogenic interactions * foraging ecology * metabolomics * microbiome * western lowland gorillas Subject RIV: EG - Zoology Impact factor: 5.947, year: 2015

The same microbiota and a potentially discriminant metabolome in the saliva of omnivore, ovo-lacto-vegetarian and Vegan individuals.

Science.gov (United States)

De Filippis, Francesca; Vannini, Lucia; La Storia, Antonietta; Laghi, Luca; Piombino, Paola; Stellato, Giuseppina; Serrazanetti, Diana I; Gozzi, Giorgia; Turroni, Silvia; Ferrocino, Ilario; Lazzi, Camilla; Di Cagno, Raffaella; Gobbetti, Marco; Ercolini, Danilo

2014-01-01

The salivary microbiota has been linked to both oral and non-oral diseases. Scant knowledge is available on the effect of environmental factors such as long-term dietary choices on the salivary microbiota and metabolome. This study analyzed the microbial diversity and metabolomic profiles of the saliva of 161 healthy individuals who followed an omnivore or ovo-lacto-vegetarian or vegan diet. A large core microbiota was identified, including 12 bacterial genera, found in >98% of the individuals. The subjects could be stratified into three "salivary types" that differed on the basis of the relative abundance of the core genera Prevotella, Streptococcus/Gemella and Fusobacterium/Neisseria. Statistical analysis indicated no effect of dietary habit on the salivary microbiota. Phylogenetic beta-diversity analysis consistently showed no differences between omnivore, ovo-lacto-vegetarian and vegan individuals. Metabolomic profiling of saliva using (1)H-NMR and GC-MS/SPME identified diet-related biomarkers that enabled a significant discrimination between the 3 groups of individuals on the basis of their diet. Formate, urea, uridine and 5-methyl-3-hexanone could discriminate samples from omnivores, whereas 1-propanol, hexanoic acid and proline were characteristic of non-omnivore diets. Although the salivary metabolome can be discriminating for diet, the microbiota has a remarkable inter-individual stability and did not vary with dietary habits. Microbial homeostasis might be perturbed with sub-standard oral hygiene or other environmental factors, but there is no current indication that a choice of an omnivore, ovo-lacto-vegetarian or vegan diet can lead to a specific composition of the oral microbiota with consequences on the oral homeostasis.

The same microbiota and a potentially discriminant metabolome in the saliva of omnivore, ovo-lacto-vegetarian and Vegan individuals.

Directory of Open Access Journals (Sweden)

Francesca De Filippis

Full Text Available The salivary microbiota has been linked to both oral and non-oral diseases. Scant knowledge is available on the effect of environmental factors such as long-term dietary choices on the salivary microbiota and metabolome. This study analyzed the microbial diversity and metabolomic profiles of the saliva of 161 healthy individuals who followed an omnivore or ovo-lacto-vegetarian or vegan diet. A large core microbiota was identified, including 12 bacterial genera, found in >98% of the individuals. The subjects could be stratified into three "salivary types" that differed on the basis of the relative abundance of the core genera Prevotella, Streptococcus/Gemella and Fusobacterium/Neisseria. Statistical analysis indicated no effect of dietary habit on the salivary microbiota. Phylogenetic beta-diversity analysis consistently showed no differences between omnivore, ovo-lacto-vegetarian and vegan individuals. Metabolomic profiling of saliva using (1H-NMR and GC-MS/SPME identified diet-related biomarkers that enabled a significant discrimination between the 3 groups of individuals on the basis of their diet. Formate, urea, uridine and 5-methyl-3-hexanone could discriminate samples from omnivores, whereas 1-propanol, hexanoic acid and proline were characteristic of non-omnivore diets. Although the salivary metabolome can be discriminating for diet, the microbiota has a remarkable inter-individual stability and did not vary with dietary habits. Microbial homeostasis might be perturbed with sub-standard oral hygiene or other environmental factors, but there is no current indication that a choice of an omnivore, ovo-lacto-vegetarian or vegan diet can lead to a specific composition of the oral microbiota with consequences on the oral homeostasis.

Potential of human saliva for nuclear magnetic resonance-based metabolomics and for health-related biomarker identification

DEFF Research Database (Denmark)

Bertram, Hanne Christine; Eggers, Nina; Eller, Nanna

2009-01-01

In the present study, the ability of (1)H nuclear magnetic resonance (NMR) for metabolic profiling of human saliva samples was investigated. High-resolution (1)H NMR spectra were obtained, and signals were assigned to various metabolites mainly representing small organic acids and amino acids...... in intensities of several metabolites including trimethylamine oxide (TMAO), choline, propionate, alanine, methanol, and N-acetyl groups. No effects of gender and body mass index (BMI) on the salivary metabolite profile were detected. The relationships between the salivary metabolome and glycated hemoglobin...

The Development of Metabolomic Sampling Procedures for Pichia pastoris, and Baseline Metabolome Data

Science.gov (United States)

Tredwell, Gregory D.; Edwards-Jones, Bryn; Leak, David J.; Bundy, Jacob G.

2011-01-01

Metabolic profiling is increasingly being used to investigate a diverse range of biological questions. Due to the rapid turnover of intracellular metabolites it is important to have reliable, reproducible techniques for sampling and sample treatment. Through the use of non-targeted analytical techniques such as NMR and GC-MS we have performed a comprehensive quantitative investigation of sampling techniques for Pichia pastoris. It was clear that quenching metabolism using solutions based on the standard cold methanol protocol caused some metabolite losses from P. pastoris cells. However, these were at a low level, with the NMR results indicating metabolite increases in the quenching solution below 5% of their intracellular level for 75% of metabolites identified; while the GC-MS results suggest a slightly higher level with increases below 15% of their intracellular values. There were subtle differences between the four quenching solutions investigated but broadly, they all gave similar results. Total culture extraction of cells + broth using high cell density cultures typical of P. pastoris fermentations, was an efficient sampling technique for NMR analysis and provided a gold standard of intracellular metabolite levels; however, salts in the media affected the GC-MS analysis. Furthermore, there was no benefit in including an additional washing step in the quenching process, as the results were essentially identical to those obtained just by a single centrifugation step. We have identified the major high-concentration metabolites found in both the extra- and intracellular locations of P. pastoris cultures by NMR spectroscopy and GC-MS. This has provided us with a baseline metabolome for P. pastoris for future studies. The P. pastoris metabolome is significantly different from that of Saccharomyces cerevisiae, with the most notable difference being the production of high concentrations of arabitol by P. pastoris. PMID:21283710

Compliance with minimum information guidelines in public metabolomics repositories.

Science.gov (United States)

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.

Metabolomics in transfusion medicine.

Science.gov (United States)

Nemkov, Travis; Hansen, Kirk C; Dumont, Larry J; D'Alessandro, Angelo

2016-04-01

Biochemical investigations on the regulatory mechanisms of red blood cell (RBC) and platelet (PLT) metabolism have fostered a century of advances in the field of transfusion medicine. Owing to these advances, storage of RBCs and PLT concentrates has become a lifesaving practice in clinical and military settings. There, however, remains room for improvement, especially with regard to the introduction of novel storage and/or rejuvenation solutions, alternative cell processing strategies (e.g., pathogen inactivation technologies), and quality testing (e.g., evaluation of novel containers with alternative plasticizers). Recent advancements in mass spectrometry-based metabolomics and systems biology, the bioinformatics integration of omics data, promise to speed up the design and testing of innovative storage strategies developed to improve the quality, safety, and effectiveness of blood products. Here we review the currently available metabolomics technologies and briefly describe the routine workflow for transfusion medicine-relevant studies. The goal is to provide transfusion medicine experts with adequate tools to navigate through the otherwise overwhelming amount of metabolomics data burgeoning in the field during the past few years. Descriptive metabolomics data have represented the first step omics researchers have taken into the field of transfusion medicine. However, to up the ante, clinical and omics experts will need to merge their expertise to investigate correlative and mechanistic relationships among metabolic variables and transfusion-relevant variables, such as 24-hour in vivo recovery for transfused RBCs. Integration with systems biology models will potentially allow for in silico prediction of metabolic phenotypes, thus streamlining the design and testing of alternative storage strategies and/or solutions. © 2015 AABB.

Ultrasound: a subexploited tool for sample preparation in metabolomics.

Science.gov (United States)

Luque de Castro, M D; Delgado-Povedano, M M

2014-01-02

Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

NMR metabolomics of thrips (Frankliniella occidentalis) resistance in Senecio hybrids.

Science.gov (United States)

Leiss, Kirsten A; Choi, Young H; Abdel-Farid, Ibrahim B; Verpoorte, Robert; Klinkhamer, Peter G L

2009-02-01

Western flower thrips (Frankliniella occidentalis) has become a key insect pest of agricultural and horticultural crops worldwide. Little is known about host plant resistance to thrips. In this study, we investigated thrips resistance in F (2) hybrids of Senecio jacobaea and Senecio aquaticus. We identified thrips-resistant hybrids applying three different bioassays. Subsequently, we compared the metabolomic profiles of these hybrids applying nuclear magnetic resonance spectroscopy (NMR). The new developments of NMR facilitate a wide range coverage of the metabolome. This makes NMR especially suitable if there is no a priori knowledge of the compounds related to herbivore resistance and allows a holistic approach analyzing different chemical compounds simultaneously. We show that the metabolomes of thrips-resistant and -susceptible hybrids differed considerably. Thrips-resistant hybrids contained higher amounts of the pyrrolizidine alkaloids (PA), jacobine, and jaconine, especially in younger leaves. Also, a flavanoid, kaempferol glucoside, accumulated in the resistant plants. Both PAs and kaempferol are known for their inhibitory effect on herbivores. In resistant and susceptible F (2) hybrids, young leaves showed less thrips damage than old leaves. Consistent with the optimal plant defense theory, young leaves contained increased levels of primary metabolites such as sucrose, raffinose, and stachyose, but also accumulated jacaranone as a secondary plant defense compound. Our results prove NMR as a promising tool to identify different metabolites involved in herbivore resistance. It constitutes a significant advance in the study of plant-insect relationships, providing key information on the implementation of herbivore resistance breeding strategies in plants.

Proteomic and metabolomic approaches to biomarker discovery

CERN Document Server

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...

Neuronal DNA Methylation Profiling of Blast-Related Traumatic Brain Injury.

Science.gov (United States)

Haghighi, Fatemeh; Ge, Yongchao; Chen, Sean; Xin, Yurong; Umali, Michelle U; De Gasperi, Rita; Gama Sosa, Miguel A; Ahlers, Stephen T; Elder, Gregory A

2015-08-15

Long-term molecular changes in the brain resulting from blast exposure may be mediated by epigenetic changes, such as deoxyribonucleic acid (DNA) methylation, that regulate gene expression. Aberrant regulation of gene expression is associated with behavioral abnormalities, where DNA methylation bridges environmental signals to sustained changes in gene expression. We assessed DNA methylation changes in the brains of rats exposed to three 74.5 kPa blast overpressure events, conditions that have been associated with long-term anxiogenic manifestations weeks or months following the initial exposures. Rat frontal cortex eight months post-exposure was used for cell sorting of whole brain tissue into neurons and glia. We interrogated DNA methylation profiles in these cells using Expanded Reduced Representation Bisulfite Sequencing. We obtained data for millions of cytosines, showing distinct methylation profiles for neurons and glia and an increase in global methylation in neuronal versus glial cells (pDNA methylation perturbations in blast overpressure-exposed animals, compared with sham blast controls, within 458 and 379 genes in neurons and glia, respectively. Differentially methylated neuronal genes showed enrichment in cell death and survival and nervous system development and function, including genes involved in transforming growth factor β and nitric oxide signaling. Functional validation via gene expression analysis of 30 differentially methylated neuronal and glial genes showed a 1.2 fold change in gene expression of the serotonin N-acetyltransferase gene (Aanat) in blast animals (pDNA methylation induced in response to multiple blast overpressure exposures. In particular, increased methylation and decreased gene expression were observed in the Aanat gene, which is involved in converting serotonin to the circadian hormone melatonin and is implicated in sleep disturbance and depression associated with traumatic brain injury.

Induced pluripotent stem cells show metabolomic differences to embryonic stem cells in polyunsaturated phosphatidylcholines and primary metabolism.

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John K Meissen

Full Text Available Induced pluripotent stem cells are different from embryonic stem cells as shown by epigenetic and genomics analyses. Depending on cell types and culture conditions, such genetic alterations can lead to different metabolic phenotypes which may impact replication rates, membrane properties and cell differentiation. We here applied a comprehensive metabolomics strategy incorporating nanoelectrospray ion trap mass spectrometry (MS, gas chromatography-time of flight MS, and hydrophilic interaction- and reversed phase-liquid chromatography-quadrupole time-of-flight MS to examine the metabolome of induced pluripotent stem cells (iPSCs compared to parental fibroblasts as well as to reference embryonic stem cells (ESCs. With over 250 identified metabolites and a range of structurally unknown compounds, quantitative and statistical metabolome data were mapped onto a metabolite networks describing the metabolic state of iPSCs relative to other cell types. Overall iPSCs exhibited a striking shift metabolically away from parental fibroblasts and toward ESCs, suggestive of near complete metabolic reprogramming. Differences between pluripotent cell types were not observed in carbohydrate or hydroxyl acid metabolism, pentose phosphate pathway metabolites, or free fatty acids. However, significant differences between iPSCs and ESCs were evident in phosphatidylcholine and phosphatidylethanolamine lipid structures, essential and non-essential amino acids, and metabolites involved in polyamine biosynthesis. Together our findings demonstrate that during cellular reprogramming, the metabolome of fibroblasts is also reprogrammed to take on an ESC-like profile, but there are select unique differences apparent in iPSCs. The identified metabolomics signatures of iPSCs and ESCs may have important implications for functional regulation of maintenance and induction of pluripotency.

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

Science.gov (United States)

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

Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain.

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Krienen, Fenna M; Yeo, B T Thomas; Ge, Tian; Buckner, Randy L; Sherwood, Chet C

2016-01-26

The human brain is patterned with disproportionately large, distributed cerebral networks that connect multiple association zones in the frontal, temporal, and parietal lobes. The expansion of the cortical surface, along with the emergence of long-range connectivity networks, may be reflected in changes to the underlying molecular architecture. Using the Allen Institute's human brain transcriptional atlas, we demonstrate that genes particularly enriched in supragranular layers of the human cerebral cortex relative to mouse distinguish major cortical classes. The topography of transcriptional expression reflects large-scale brain network organization consistent with estimates from functional connectivity MRI and anatomical tracing in nonhuman primates. Microarray expression data for genes preferentially expressed in human upper layers (II/III), but enriched only in lower layers (V/VI) of mouse, were cross-correlated to identify molecular profiles across the cerebral cortex of postmortem human brains (n = 6). Unimodal sensory and motor zones have similar molecular profiles, despite being distributed across the cortical mantle. Sensory/motor profiles were anticorrelated with paralimbic and certain distributed association network profiles. Tests of alternative gene sets did not consistently distinguish sensory and motor regions from paralimbic and association regions: (i) genes enriched in supragranular layers in both humans and mice, (ii) genes cortically enriched in humans relative to nonhuman primates, (iii) genes related to connectivity in rodents, (iv) genes associated with human and mouse connectivity, and (v) 1,454 gene sets curated from known gene ontologies. Molecular innovations of upper cortical layers may be an important component in the evolution of long-range corticocortical projections.

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

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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.

Metabolomics for functional genomics, systems biology, and biotechnology.

Science.gov (United States)

Saito, Kazuki; Matsuda, Fumio

2010-01-01

Metabolomics now plays a significant role in fundamental plant biology and applied biotechnology. Plants collectively produce a huge array of chemicals, far more than are produced by most other organisms; hence, metabolomics is of great importance in plant biology. Although substantial improvements have been made in the field of metabolomics, the uniform annotation of metabolite signals in databases and informatics through international standardization efforts remains a challenge, as does the development of new fields such as fluxome analysis and single cell analysis. The principle of transcript and metabolite cooccurrence, particularly transcriptome coexpression network analysis, is a powerful tool for decoding the function of genes in Arabidopsis thaliana. This strategy can now be used for the identification of genes involved in specific pathways in crops and medicinal plants. Metabolomics has gained importance in biotechnology applications, as exemplified by quantitative loci analysis, prediction of food quality, and evaluation of genetically modified crops. Systems biology driven by metabolome data will aid in deciphering the secrets of plant cell systems and their application to biotechnology.

Gut microbiota, metabolome and immune signatures in patients with uncomplicated diverticular disease.

Science.gov (United States)

Barbara, Giovanni; Scaioli, Eleonora; Barbaro, Maria Raffaella; Biagi, Elena; Laghi, Luca; Cremon, Cesare; Marasco, Giovanni; Colecchia, Antonio; Picone, Gianfranco; Salfi, Nunzio; Capozzi, Francesco; Brigidi, Patrizia; Festi, Davide

2017-07-01

The engagement of the gut microbiota in the development of symptoms and complications of diverticular disease has been frequently hypothesised. Our aim was to explore colonic immunocytes, gut microbiota and the metabolome in patients with diverticular disease in a descriptive, cross-sectional, pilot study. Following colonoscopy with biopsy and questionnaire phenotyping, patients were classified into diverticulosis or symptomatic uncomplicated diverticular disease; asymptomatic subjects served as controls. Mucosal immunocytes, in the diverticular region and in unaffected sites, were quantified with immunohistochemistry. Mucosa and faecal microbiota were analysed by the phylogenetic platform high taxonomic fingerprint (HTF)-Microbi.Array, while the metabolome was assessed by 1 H nuclear magnetic resonance. Compared with controls, patients with diverticula, regardless of symptoms, had a >70% increase in colonic macrophages. Their faecal microbiota showed depletion of Clostridium cluster IV. Clostridium cluster IX, Fusobacterium and Lactobacillaceae were reduced in symptomatic versus asymptomatic patients. A negative correlation was found between macrophages and mucosal Clostridium cluster IV and Akkermansia . Urinary and faecal metabolome changes in diverticular disease involved the hippurate and kynurenine pathways. Six urinary molecules allowed to discriminate diverticular disease and control groups with >95% accuracy. Patients with colonic diverticular disease show depletion of microbiota members with anti-inflammatory activity associated with mucosal macrophage infiltration. Metabolome profiles were linked to inflammatory pathways and gut neuromotor dysfunction and showed the ability to discriminate diverticular subgroups and controls. These data pave the way for further large-scale studies specifically aimed at identifying microbiota signatures with a potential diagnostic value in patients with diverticular disease. Published by the BMJ Publishing Group Limited

Metabolomic method: UPLC-q-ToF polar and non-polar metabolites in the healthy rat cerebellum using an in-vial dual extraction.

Directory of Open Access Journals (Sweden)

Amera A Ebshiana

Full Text Available Unbiased metabolomic analysis of biological samples is a powerful and increasingly commonly utilised tool, especially for the analysis of bio-fluids to identify candidate biomarkers. To date however only a small number of metabolomic studies have been applied to studying the metabolite composition of tissue samples, this is due, in part to a number of technical challenges including scarcity of material and difficulty in extracting metabolites. The aim of this study was to develop a method for maximising the biological information obtained from small tissue samples by optimising sample preparation, LC-MS analysis and metabolite identification. Here we describe an in-vial dual extraction (IVDE method, with reversed phase and hydrophilic liquid interaction chromatography (HILIC which reproducibly measured over 4,000 metabolite features from as little as 3mg of brain tissue. The aqueous phase was analysed in positive and negative modes following HILIC separation in which 2,838 metabolite features were consistently measured including amino acids, sugars and purine bases. The non-aqueous phase was also analysed in positive and negative modes following reversed phase separation gradients respectively from which 1,183 metabolite features were consistently measured representing metabolites such as phosphatidylcholines, sphingolipids and triacylglycerides. The described metabolomics method includes a database for 200 metabolites, retention time, mass and relative intensity, and presents the basal metabolite composition for brain tissue in the healthy rat cerebellum.

Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

Science.gov (United States)

Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

2016-01-01

Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

A Rough Guide to Metabolite Identification Using High Resolution Liquid Chromatography Mass Spectrometry in Metabolomic Profiling in Metazoans

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David G Watson

2013-01-01

Full Text Available Compound identification in mass spectrometry based metabolomics can be a problem but sometimes the problem seems to be presented in an over complicated way. The current review focuses on metazoans where the range of metabolites is more restricted than for example in plants. The focus is on liquid chromatography with high resolution mass spectrometry where it is proposed that most of the problems in compound identification relate to structural isomers rather than to isobaric compounds. Thus many of the problems faced relate to separation of isomers, which is usually required even if fragmentation is used to support structural identification. Many papers report the use of MS/MS or MS2 as an adjunct to the identification of known metabolites but there a few examples in metabolomics studies of metazoans of complete structure elucidation of novel metabolites or metabolites where no authentic standards are available for comparison.

Gut microbiome composition and metabolomic profiles of wild western lowland gorillas (Gorilla gorilla gorilla) reflect host ecology

Czech Academy of Sciences Publication Activity Database

Gomez, A.; Petrželková, Klára Judita; Yeoman, C. J.; Vlčková, K.; Mrázek, Jakub; Koppová, Ingrid; Carbonero, F.; Ulanov, A.; Modrý, D.; Todd, A.; Torralba, M.; Nelson, K.; Gaskins, H. R.; Wilson, B.; Stumpf, R. M.; White, B. A.; Leigh, S. R.

2015-01-01

Roč. 24, č. 10 (2015), s. 2551-2565 ISSN 0962-1083 R&D Projects: GA ČR GA206/09/0927 Institutional support: RVO:68081766 ; RVO:67985904 Keywords : western lowland gorillas * microbiome * metabolomics * foraging ecology * anthropogenic interactions Subject RIV: GJ - Animal Vermins ; Diseases, Veterinary Medicine Impact factor: 5.947, year: 2015

Comparative metabolomics of drought acclimation in model and forage legumes.

Science.gov (United States)

Sanchez, Diego H; Schwabe, Franziska; Erban, Alexander; Udvardi, Michael K; Kopka, Joachim

2012-01-01

Water limitation has become a major concern for agriculture. Such constraints reinforce the urgent need to understand mechanisms by which plants cope with water deprivation. We used a non-targeted metabolomic approach to explore plastic systems responses to non-lethal drought in model and forage legume species of the Lotus genus. In the model legume Lotus. japonicus, increased water stress caused gradual increases of most of the soluble small molecules profiled, reflecting a global and progressive reprogramming of metabolic pathways. The comparative metabolomic approach between Lotus species revealed conserved and unique metabolic responses to drought stress. Importantly, only few drought-responsive metabolites were conserved among all species. Thus we highlight a potential impediment to translational approaches that aim to engineer traits linked to the accumulation of compatible solutes. Finally, a broad comparison of the metabolic changes elicited by drought and salt acclimation revealed partial conservation of these metabolic stress responses within each of the Lotus species, but only few salt- and drought-responsive metabolites were shared between all. The implications of these results are discussed with regard to the current insights into legume water stress physiology. © 2011 Blackwell Publishing Ltd.

Structured plant metabolomics for the simultaneous exploration of multiple factors.

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Vasilev, Nikolay; Boccard, Julien; Lang, Gerhard; Grömping, Ulrike; Fischer, Rainer; Goepfert, Simon; Rudaz, Serge; Schillberg, Stefan

2016-11-17

Multiple factors act simultaneously on plants to establish complex interaction networks involving nutrients, elicitors and metabolites. Metabolomics offers a better understanding of complex biological systems, but evaluating the simultaneous impact of different parameters on metabolic pathways that have many components is a challenging task. We therefore developed a novel approach that combines experimental design, untargeted metabolic profiling based on multiple chromatography systems and ionization modes, and multiblock data analysis, facilitating the systematic analysis of metabolic changes in plants caused by different factors acting at the same time. Using this method, target geraniol compounds produced in transgenic tobacco cell cultures were grouped into clusters based on their response to different factors. We hypothesized that our novel approach may provide more robust data for process optimization in plant cell cultures producing any target secondary metabolite, based on the simultaneous exploration of multiple factors rather than varying one factor each time. The suitability of our approach was verified by confirming several previously reported examples of elicitor-metabolite crosstalk. However, unravelling all factor-metabolite networks remains challenging because it requires the identification of all biochemically significant metabolites in the metabolomics dataset.

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

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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.

Exo-metabolome of some fungal isolates growing on cork-based medium

DEFF Research Database (Denmark)

Barreto, M. C.; Frisvad, Jens Christian; Larsen, Thomas Ostenfeld

2011-01-01

are produced by the studied fungal species, both in cork medium or in cork medium added with C. sitophila extracts. However, the addition of C. sitophila extract to the cork medium enhanced the growth of the other studied fungal isolates and altered the respective exo-metabolome profile, leading...... they can be dependent of the remains of former colonizers. In fact, the production of the exo-metabolites by the studied fungal isolates suggests that, under the used experimental conditions, they appear to play an important role in fungal interactions amongst the cork mycoflora....

Mass spectrometry data of metabolomics analysis of Nepenthes pitchers

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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.

Gut microbiome and serum metabolome alterations in obesity and after weight-loss intervention

DEFF Research Database (Denmark)

Liu, Ruixin; Hong, Jie; Xu, Xiaoqiang

2017-01-01

Emerging evidence has linked the gut microbiome to human obesity. We performed a metagenome-wide association study and serum metabolomics profiling in a cohort of lean and obese, young, Chinese individuals. We identified obesity-associated gut microbial species linked to changes in circulating...... metabolites. The abundance of Bacteroides thetaiotaomicron, a glutamate-fermenting commensal, was markedly decreased in obese individuals and was inversely correlated with serum glutamate concentration. Consistently, gavage with B. thetaiotaomicron reduced plasma glutamate concentration and alleviated diet...

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

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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.

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

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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

Urinary Biomarkers of Brain Diseases

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Manxia An

2015-12-01

Full Text Available Biomarkers are the measurable changes associated with a physiological or pathophysiological process. Unlike blood, urine is not subject to homeostatic mechanisms. Therefore, greater fluctuations could occur in urine than in blood, better reflecting the changes in human body. The roadmap of urine biomarker era was proposed. Although urine analysis has been attempted for clinical diagnosis, and urine has been monitored during the progression of many diseases, particularly urinary system diseases, whether urine can reflect brain disease status remains uncertain. As some biomarkers of brain diseases can be detected in the body fluids such as cerebrospinal fluid and blood, there is a possibility that urine also contain biomarkers of brain diseases. This review summarizes the clues of brain diseases reflected in the urine proteome and metabolome.

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

NARCIS (Netherlands)

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

Metabolomics in Sepsis and Its Impact on Public Health.

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Evangelatos, Nikolaos; Bauer, Pia; Reumann, Matthias; Satyamoorthy, Kapaettu; Lehrach, Hans; Brand, Angela

2017-01-01

Sepsis, with its often devastating consequences for patients and their families, remains a major public health concern that poses an increasing financial burden. Early resuscitation together with the elucidation of the biological pathways and pathophysiological mechanisms with the use of "-omics" technologies have started changing the clinical and research landscape in sepsis. Metabolomics (i.e., the study of the metabolome), an "-omics" technology further down in the "-omics" cascade between the genome and the phenome, could be particularly fruitful in sepsis research with the potential to alter the clinical practice. Apart from its benefit for the individual patient, metabolomics has an impact on public health that extends beyond its applications in medicine. In this review, we present recent developments in metabolomics research in sepsis, with a focus on pneumonia, and we discuss the impact of metabolomics on public health, with a focus on free/libre open source software. © 2018 S. Karger AG, Basel.

A window into extreme longevity; the circulating metabolomic signature of the naked mole-rat, a mammal that shows negligible senescence.

Science.gov (United States)

Lewis, Kaitlyn N; Rubinstein, Nimrod D; Buffenstein, Rochelle

2018-04-20

Mouse-sized naked mole-rats (Heterocephalus glaber), unlike other mammals, do not conform to Gompertzian laws of age-related mortality; adults show no age-related change in mortality risk. Moreover, we observe negligible hallmarks of aging with well-maintained physiological and molecular functions, commonly altered with age in other species. We questioned whether naked mole-rats, living an order of magnitude longer than laboratory mice, exhibit different plasma metabolite profiles, which could then highlight novel mechanisms or targets involved in disease and longevity. Using a comprehensive, unbiased metabolomics screen, we observe striking inter-species differences in amino acid, peptide, and lipid metabolites. Low circulating levels of specific amino acids, particularly those linked to the methionine pathway, resemble those observed during the fasting period at late torpor in hibernating ground squirrels and those seen in longer-lived methionine-restricted rats. These data also concur with metabolome reports on long-lived mutant mice, including the Ames dwarf mice and calorically restricted mice, as well as fruit flies, and even show similarities to circulating metabolite differences observed in young human adults when compared to older humans. During evolution, some of these beneficial nutrient/stress response pathways may have been positively selected in the naked mole-rat. These observations suggest that interventions that modify the aging metabolomic profile to a more youthful one may enable people to lead healthier and longer lives.

SECIMTools: a suite of metabolomics data analysis tools.

Science.gov (United States)

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.

Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

Science.gov (United States)

Blasco, H; Patin, F; Madji Hounoum, B; Gordon, P H; Vourc'h, P; Andres, C R; Corcia, P

2016-03-01

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs. © 2016 EAN.

Introduction to metabolomics and its applications in ophthalmology

Science.gov (United States)

Tan, S Z; Begley, P; Mullard, G; Hollywood, K A; Bishop, P N

2016-01-01

Metabolomics is the study of endogenous and exogenous metabolites in biological systems, which aims to provide comparative semi-quantitative information about all metabolites in the system. Metabolomics is an emerging and potentially powerful tool in ophthalmology research. It is therefore important for health professionals and researchers involved in the speciality to understand the basic principles of metabolomics experiments. This article provides an overview of the experimental workflow and examples of its use in ophthalmology research from the study of disease metabolism and pathogenesis to identification of biomarkers. PMID:26987591

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

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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.

Metabolome Integrated Analysis of High-Temperature Response in Pinus radiata

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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.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

Science.gov (United States)

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments

Directory of Open Access Journals (Sweden)

Anthony C. Dona

2016-01-01

Full Text Available Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR spectroscopy and mass spectrometry (MS, the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC, in a configuration known as LC–MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

Linking metabolomics data to underlying metabolic regulation

Directory of Open Access Journals (Sweden)

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

MetaboLights: An Open-Access Database Repository for Metabolomics Data.

Science.gov (United States)

Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

2016-03-24

MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

Metabolomics in the fight against malaria

Directory of Open Access Journals (Sweden)

Jorge L Salinas

2014-08-01

Full Text Available Metabolomics uses high-resolution mass spectrometry to provide a chemical fingerprint of thousands of metabolites present in cells, tissues or body fluids. Such metabolic phenotyping has been successfully used to study various biologic processes and disease states. High-resolution metabolomics can shed new light on the intricacies of host-parasite interactions in each stage of the Plasmodium life cycle and the downstream ramifications on the host’s metabolism, pathogenesis and disease. Such data can become integrated with other large datasets generated using top-down systems biology approaches and be utilised by computational biologists to develop and enhance models of malaria pathogenesis relevant for identifying new drug targets or intervention strategies. Here, we focus on the promise of metabolomics to complement systems biology approaches in the quest for novel interventions in the fight against malaria. We introduce the Malaria Host-Pathogen Interaction Center (MaHPIC, a new systems biology research coalition. A primary goal of the MaHPIC is to generate systems biology datasets relating to human and non-human primate (NHP malaria parasites and their hosts making these openly available from an online relational database. Metabolomic data from NHP infections and clinical malaria infections from around the world will comprise a unique global resource.

1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

International Nuclear Information System (INIS)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D.

2011-01-01

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in 1 H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

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

Science.gov (United States)

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.

Metabolomic characteristics of arsenic-associated diabetes in a prospective cohort in Chihuahua, Mexico.

Science.gov (United States)

Martin, Elizabeth; González-Horta, Carmen; Rager, Julia; Bailey, Kathryn A; Sánchez-Ramírez, Blanca; Ballinas-Casarrubias, Lourdes; Ishida, María C; Gutiérrez-Torres, Daniela S; Hernández Cerón, Roberto; Viniegra Morales, Damián; Baeza Terrazas, Francisco A; Saunders, R Jesse; Drobná, Zuzana; Mendez, Michelle A; Buse, John B; Loomis, Dana; Jia, Wei; García-Vargas, Gonzalo G; Del Razo, Luz M; Stýblo, Miroslav; Fry, Rebecca

2015-04-01

Chronic exposure to inorganic arsenic (iAs) has been linked to an increased risk of diabetes, yet the specific disease phenotype and underlying mechanisms are poorly understood. In the present study we set out to identify iAs exposure-associated metabolites with altered abundance in nondiabetic and diabetic individuals in an effort to understand the relationship between exposure, metabolomic response, and disease status. A nested study design was used to profile metabolomic shifts in urine and plasma collected from 90 diabetic and 86 nondiabetic individuals matched for varying iAs concentrations in drinking water, body mass index, age, and sex. Diabetes diagnosis was based on measures of fasting plasma glucose and 2-h blood glucose. Multivariable models were used to identify metabolites with altered abundance associated with iAs exposure among diabetic and nondiabetic individuals. A total of 132 metabolites were identified to shift in urine or plasma in response to iAs exposure characterized by the sum of iAs metabolites in urine (U-tAs). Although many metabolites were altered in both diabetic and nondiabetic 35 subjects, diabetic individuals displayed a unique response to iAs exposure with 59 altered metabolites including those that play a role in tricarboxylic acid cycle and amino acid metabolism. Taken together, these data highlight the broad impact of iAs exposure on the human metabolome, and demonstrate some specificity of the metabolomic response between diabetic and nondiabetic individuals. These data may provide novel insights into the mechanisms and phenotype of diabetes associated with iAs exposure. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Gas chromatography mass spectrometry : key technology in metabolomics

NARCIS (Netherlands)

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

Metabolomics to study functional consequences in peroxisomal disorders

NARCIS (Netherlands)

Herzog, K.

2017-01-01

This thesis focusses on metabolomics approaches performed in cultured cells and blood samples from patients with peroxisomal disorders. By applying both targeted and untargeted metabolomics, the aim of these approaches was to study the functional consequences of the primary genetic defects causing

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

Science.gov (United States)

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

Changes in the Metabolome in Response to Low-Dose Exposure to Environmental Chemicals Used in Personal Care Products during Different Windows of Susceptibility

NARCIS (Netherlands)

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

Metabolomic Profiles of Dinophysis acuminata and Dinophysis acuta Using Non-Targeted High-Resolution Mass Spectrometry

DEFF Research Database (Denmark)

García-Portela, María; Reguera, Beatriz; Sibat, Manoella

2018-01-01

Photosynthetic species of the genus Dinophysis are obligate mixotrophs with temporary plastids (kleptoplastids) that are acquired from the ciliate Mesodinium rubrum, which feeds on cryptophytes of the Teleaulax-Plagioselmis-Geminigera clade. A metabolomic study of the three-species food chain Din...

Application of Fourier-transform ion cyclotron resonance mass spectrometry to metabolic profiling and metabolite identification.

Science.gov (United States)

Ohta, Daisaku; Kanaya, Shigehiko; Suzuki, Hideyuki

2010-02-01

Metabolomics, as an essential part of genomics studies, intends holistic understanding of metabolic networks through simultaneous analysis of a myriad of both known and unknown metabolites occurring in living organisms. The initial stage of metabolomics was designed for the reproducible analyses of known metabolites based on their comparison to available authentic compounds. Such metabolomics platforms were mostly based on mass spectrometry (MS) technologies enabled by a combination of different ionization methods together with a variety of separation steps including LC, GC, and CE. Among these, Fourier-transform ion cyclotron resonance MS (FT-ICR/MS) is distinguished from other MS technologies by its ultrahigh resolution power in mass to charge ratio (m/z). The potential of FT-ICR/MS as a distinctive metabolomics tool has been demonstrated in nontargeted metabolic profiling and functional characterization of novel genes. Here, we discuss both the advantages and difficulties encountered in the FT-ICR/MS metabolomics studies.