PubMed

Related Articles Qualitative and spatial metabolite profiling of lichens by a LC-MS approach combined with optimised extraction. Phytochem Anal. 2015 Jan-Feb;26(1):23-33 Authors: Parrot D, Peresse T, Hitti E, Carrie D, Grube M, Tomasi S Abstract INTRODUCTION: Lichens are self-sustaining partnerships comprising fungi as shape-forming partners for their enclosed symbiotic algae. They produce a tremendous diversity of metabolites (1050 metabolites described so far). OBJECTIVES: A comparison of metabolic profiles in nine lichen species belonging to three genera (Lichina, Collema and Roccella) by using an optimised extraction protocol, determination of the fragmentation pathway and the in situ localisation for major compounds in Roccella species. METHODS: Chemical analysis was performed using a complementary study combining a Taguchi experimental design with qualitative analysis by high-performance liquid chromatography coupled with mass spectrometry techniques. RESULTS: Optimal conditions to obtain the best total extraction yield were determined as follows: mortar grinding to a fine powder, two successive extractions, solid:liquid ratio (2:60) and 700 rpm stirring. Qualitative analysis of the metabolite profiling of these nine species extracted with the optimised method was corroborated using MS and MS/MS approaches. Nine main compounds were identified: 1 β-orcinol, 2 orsellinic acid, 3 putative choline sulphate, 4 roccellic acid, 5 montagnetol, 6 lecanoric acid, 7 erythrin, 8 lepraric acid and 9 acetylportentol, and several other compounds were reported. Identification was performed using the m/z ratio, fragmentation pathway and/or after isolation by NMR analysis. The variation of the metabolite profile in differently organised parts of two Roccella species suggests a specific role of major compounds in developmental stages of this symbiotic association. CONCLUSION: Metabolic profiles represent specific chemical species and depend on the extraction conditions, the kind of the photobiont partner and the in situ localisation of major compounds. PMID: 25130294 [PubMed - indexed for MEDLINE]

Related Articles Eosinophils control the resolution of inflammation and draining lymph node hypertrophy through the proresolving mediators and CXCL13 pathway in mice. FASEB J. 2014 Sep;28(9):4036-43 Authors: Tani Y, Isobe Y, Imoto Y, Segi-Nishida E, Sugimoto Y, Arai H, Arita M Abstract Resolution of inflammation is critical to restoration of tissue function after an inflammatory response. We previously demonstrated that 12/15-lipoxygenase (12/15-LOX)-expressing eosinophils contribute to this process in murine zymosan-induced peritonitis. In this study, eosinophils promoted resolution by regulating expression of macrophage CXCL13. Microarray analysis revealed that eosinophils significantly increased (∼3-fold) the expression of macrophage CXCL13 by a 12/15-LOX-dependent mechanism. CXCL13 depletion caused a resolution defect, with the reduced appearance of phagocytes carrying engulfed zymosan in the draining lymph nodes. Inflamed lymph node hypertrophy, a critical feature of the resolution process, was reduced by ∼60% in eosinophil-deficient mice, and adoptive transfer of eosinophils or administration of CXCL13 corrected this defect. Administration of the 12/15-LOX-derived mediator lipoxin A4 (LXA4) increased the expression of CXCL13 and restored the defect of lymph node hypertrophy in eosinophil-deficient mice. These results demonstrate that eosinophils control the resolution of inflammation and draining lymph node hypertrophy through proresolving lipid mediators and the CXCL13 pathway in mice. PMID: 24891522 [PubMed - indexed for MEDLINE]

16 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2015/08/25PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Ambient ionization MS for bioanalysis: recent developments and challenges. Bioanalysis. 2015 Aug;7(15):1901-1923 Authors: Takyi-Williams J, Liu CF, Tang K Abstract Ambient ionization MS has become very popular in analytical science and has now evolved as an effective analytical tool in metabolomics, biological tissue imaging, protein and small molecule drug analysis, where biological samples are probed in a rapid and direct fashion with minimal sample preparation at ambient conditions. However, certain inherent challenges continue to hinder the vibrant prospects of these methods for in situ analyses or to replace conventional methods in bioanalysis. This review provides an introduction to the field and its application in bioanalysis, with an emphasis on the most recent developments and applications. Furthermore, ongoing challenges or limitations related to quantitation, sensitivity, selectivity, instrumentation and mass range of these ambient methods will also be discussed. PMID: 26295990 [PubMed - as supplied by publisher]

Effects of Graphene Oxide and Oxidized Carbon Nanotubes on the Cellular Division, Microstructure, Uptake, Oxidative Stress and Metabolic Profiles. Environ Sci Technol. 2015 Aug 21; Authors: Hu X, Ouyang S, Mu L, An J, Zhou Q Abstract Nanomaterial oxides are common formations of nanomaterials in the natural environment. Herein, the nanotoxicology of typical graphene oxide (GO) and carboxyl single-walled carbon nanotubes (C-SWCNT) was compared. The results showed that cell division of Chlorella vulgaris was promoted at 24 h and then inhibited at 96 h after nanomaterial exposure. At 96 h, GO and C-SWCNT inhibited the rates of cell division by 0.08-15% and 0.8-28.3%, respectively. Both GO and C-SWCNT covered the cell surface, but the uptake percentage of C-SWCNT was 2-fold higher than that of GO. C-SWCNT induced stronger plasmolysis and mitochondrial membrane potential loss and decreased the cell viability to a greater extent than GO. Moreover, C-SWCNT-exposed cells exhibited more starch grains and lysosome formation and higher reactive oxygen species (ROS) levels than GO-exposed cells. Metabolomics analysis revealed significant differences in the metabolic profiles among the control, C-SWCNT and GO groups. The metabolisms of alkanes, lysine, octadecadienoic acid and valine was associated with ROS and could be considered as new biomarkers of ROS. The nanotoxicological mechanisms involved the inhibition of fatty acid, amino acid and small molecule acid metabolisms. These findings provide new insights into the effects of GO and C-SWCNT on cellular responses. PMID: 26295980 [PubMed - as supplied by publisher]

Organelle-Specific Initiation of Autophagy. Mol Cell. 2015 Aug 20;59(4):522-539 Authors: Sica V, Galluzzi L, Bravo-San Pedro JM, Izzo V, Maiuri MC, Kroemer G Abstract Autophagy constitutes a prominent mechanism through which eukaryotic cells preserve homeostasis in baseline conditions and in response to perturbations of the intracellular or extracellular microenvironment. Autophagic responses can be relatively non-selective or target a specific subcellular compartment. At least in part, this depends on the balance between the availability of autophagic substrates ("offer") and the cellular need of autophagic products or functions for adaptation ("demand"). Irrespective of cargo specificity, adaptive autophagy relies on a panel of sensors that detect potentially dangerous cues and convert them into signals that are ultimately relayed to the autophagic machinery. Here, we summarize the molecular systems through which specific subcellular compartments-including the nucleus, mitochondria, plasma membrane, reticular apparatus, and cytosol-convert homeostatic perturbations into an increased offer of autophagic substrates or an accrued cellular demand for autophagic products or functions. PMID: 26295960 [PubMed - as supplied by publisher]

Related Articles Appropriate models for novel osteoporosis drug discovery and future perspectives. Expert Opin Drug Discov. 2015 Aug 21;:1-16 Authors: Gennari L, Rotatori S, Bianciardi S, Gonnelli S, Nuti R, Merlotti D Abstract INTRODUCTION: Osteoporosis is a common skeletal disorder characterized by compromised bone strength and increased fracture risk. It is becoming a growing health-economic problem worldwide. Over the past two decades, there has been considerable progress in the availability of compounds with antiresorptive or anabolic activity on bone. However, existing therapeutic strategies still have limitations. Areas covered: In this review, the authors summarize past and current approaches for the development of antiresorptive and anabolic agents for osteoporosis together with their mechanisms of action. They also provide discussion on the application of new technologies for novel osteoporosis drug discovery. Expert opinion: Thanks to the recent advances in molecular biology over the past few years, novel therapeutic targets for antiresorptive or anabolic compounds have been discovered and several promising new drugs are in preclinical and clinical development. Despite these advances, the current understanding of the mechanisms regulating bone remodeling is far from complete, leaving significant drawbacks to the discovery and the clinical development of novel therapeutic agents. Hopefully, improvements in functional genomics and bioinformatics, along with new technological approaches such as RNA silencing, quantitative proteomics, metabolomics, and the use of mesenchymal stem cells, will address these issues and widen our options for treating several disorders of bone metabolism, including osteoporosis. PMID: 26292627 [PubMed - as supplied by publisher]

Related Articles Retention projection enables accurate calculation of liquid chromatographic retention times across labs and methods. J Chromatogr A. 2015 Aug 3; Authors: Abate-Pella D, Freund DM, Ma Y, Simón-Manso Y, Hollender J, Broeckling CD, Huhman DV, Krokhin OV, Stoll DR, Hegeman AD, Kind T, Fiehn O, Schymanski EL, Prenni JE, Sumner LW, Boswell PG Abstract Identification of small molecules by liquid chromatography-mass spectrometry (LC-MS) can be greatly improved if the chromatographic retention information is used along with mass spectral information to narrow down the lists of candidates. Linear retention indexing remains the standard for sharing retention data across labs, but it is unreliable because it cannot properly account for differences in the experimental conditions used by various labs, even when the differences are relatively small and unintentional. On the other hand, an approach called "retention projection" properly accounts for many intentional differences in experimental conditions, and when combined with a "back-calculation" methodology described recently, it also accounts for unintentional differences. In this study, the accuracy of this methodology is compared with linear retention indexing across eight different labs. When each lab ran a test mixture under a range of multi-segment gradients and flow rates they selected independently, retention projections averaged 22-fold more accurate for uncharged compounds because they properly accounted for these intentional differences, which were more pronounced in steep gradients. When each lab ran the test mixture under nominally the same conditions, which is the ideal situation to reproduce linear retention indices, retention projections still averaged 2-fold more accurate because they properly accounted for many unintentional differences between the LC systems. To the best of our knowledge, this is the most successful study to date aiming to calculate (or even just to reproduce) LC gradient retention across labs, and it is the only study in which retention was reliably calculated under various multi-segment gradients and flow rates chosen independently by labs. PMID: 26292625 [PubMed - as supplied by publisher]

Related Articles [Exploration on serum metabolic biomarkers of hepatitis B virus infected patients based on gas chromatography-mass spectrometry]. Se Pu. 2015 Apr;33(4):383-8 Authors: Hou Y, Zhu W, Chen C, Wang Y, Duan Z, Yan C Abstract Abstract: The difference of serum metabolome between hepatitis B virus (HBV) infected patients and healthy controls was explored for the potential metabolite biomarkers of HBV disease using serum metabolomics approach. Totally 30 HBV infected patients and 35 healthy controls were enrolled. Gas chromatography-time-of-flight mass spectrometry (GC-TOFMS), pattern recognition by principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied in each group. Several metabolites which were different between the two groups based on variable importance in projection (VIP) value, non-parametric test and screening in databases were identified. Ten variables that were significantly different were considered as the potential biomarkers, among which five variables (citric acid, aconitic acid, glutamine, N,N-dimethylglycine and malonic acid) showed good correlation with HBV patients. The area under the receiver operating characteristic curve was 0.975, with good specificity and sensitivity. A panel of metabolite markers composed of citric acid, aconitic acid, glutamine, N,N-dimethylglycine and malonic acid from GC-TOFMS were selected to discriminate HBV subjects from their healthy counterparts. These biochemical changes provide a novel molecular diagnostic approach which could be helpful to further understand the pathogenesis and identify the therapeutic target of HBV disease. PMID: 26292408 [PubMed - in process]

Related Articles Precision high-throughput proton NMR spectroscopy of human urine, serum, and plasma for large-scale metabolic phenotyping. Anal Chem. 2014 Oct 7;86(19):9887-94 Authors: Dona AC, Jiménez B, Schäfer H, Humpfer E, Spraul M, Lewis MR, Pearce JT, Holmes E, Lindon JC, Nicholson JK Abstract Proton nuclear magnetic resonance (NMR)-based metabolic phenotyping of urine and blood plasma/serum samples provides important prognostic and diagnostic information and permits monitoring of disease progression in an objective manner. Much effort has been made in recent years to develop NMR instrumentation and technology to allow the acquisition of data in an effective, reproducible, and high-throughput approach that allows the study of general population samples from epidemiological collections for biomarkers of disease risk. The challenge remains to develop highly reproducible methods and standardized protocols that minimize technical or experimental bias, allowing realistic interlaboratory comparisons of subtle biomarker information. Here we present a detailed set of updated protocols that carefully consider major experimental conditions, including sample preparation, spectrometer parameters, NMR pulse sequences, throughput, reproducibility, quality control, and resolution. These results provide an experimental platform that facilitates NMR spectroscopy usage across different large cohorts of biofluid samples, enabling integration of global metabolic profiling that is a prerequisite for personalized healthcare. PMID: 25180432 [PubMed - indexed for MEDLINE]

Related Articles Comprehensive analyses of genomes, transcriptomes and metabolites of neem tree. PeerJ. 2015;3:e1066 Authors: Kuravadi NA, Yenagi V, Rangiah K, Mahesh HB, Rajamani A, Shirke MD, Russiachand H, Loganathan RM, Shankara Lingu C, Siddappa S, Ramamurthy A, Sathyanarayana BN, Gowda M Abstract Neem (Azadirachta indica A. Juss) is one of the most versatile tropical evergreen tree species known in India since the Vedic period (1500 BC-600 BC). Neem tree is a rich source of limonoids, having a wide spectrum of activity against insect pests and microbial pathogens. Complex tetranortriterpenoids such as azadirachtin, salanin and nimbin are the major active principles isolated from neem seed. Absolutely nothing is known about the biochemical pathways of these metabolites in neem tree. To identify genes and pathways in neem, we sequenced neem genomes and transcriptomes using next generation sequencing technologies. Assembly of Illumina and 454 sequencing reads resulted in 267 Mb, which accounts for 70% of estimated size of neem genome. We predicted 44,495 genes in the neem genome, of which 32,278 genes were expressed in neem tissues. Neem genome consists about 32.5% (87 Mb) of repetitive DNA elements. Neem tree is phylogenetically related to citrus, Citrus sinensis. Comparative analysis anchored 62% (161 Mb) of assembled neem genomic contigs onto citrus chromomes. Ultrahigh performance liquid chromatography-mass spectrometry-selected reaction monitoring (UHPLC-MS/SRM) method was used to quantify azadirachtin, nimbin, and salanin from neem tissues. Weighted Correlation Network Analysis (WCGNA) of expressed genes and metabolites resulted in identification of possible candidate genes involved in azadirachtin biosynthesis pathway. This study provides genomic, transcriptomic and quantity of top three neem metabolites resource, which will accelerate basic research in neem to understand biochemical pathways. PMID: 26290780 [PubMed]

Related Articles The ABRF Metabolomics Research Group 2013 Study: Investigation of Spiked Compound Differences in a Human Plasma Matrix. J Biomol Tech. 2015 Sep;26(3):83-9 Authors: Cheema AK, Asara JM, Wang Y, Neubert TA, Tolstikov V, Turck CW Abstract Metabolomics is an emerging field that involves qualitative and quantitative measurements of small molecule metabolites in a biological system. These measurements can be useful for developing biomarkers for diagnosis, prognosis, or predicting response to therapy. Currently, a wide variety of metabolomics approaches, including nontargeted and targeted profiling, are used across laboratories on a routine basis. A diverse set of analytical platforms, such as NMR, gas chromatography-mass spectrometry, Orbitrap mass spectrometry, and time-of-flight-mass spectrometry, which use various chromatographic and ionization techniques, are used for resolution, detection, identification, and quantitation of metabolites from various biological matrices. However, few attempts have been made to standardize experimental methodologies or comparative analyses across different laboratories. The Metabolomics Research Group of the Association of Biomolecular Resource Facilities organized a "round-robin" experiment type of interlaboratory study, wherein human plasma samples were spiked with different amounts of metabolite standards in 2 groups of biologic samples (A and B). The goal was a study that resembles a typical metabolomics analysis. Here, we report our efforts and discuss challenges that create bottlenecks for the field. Finally, we discuss benchmarks that could be used by laboratories to compare their methodologies. PMID: 26290656 [PubMed - in process]

Related Articles Metabolic profiling in human exposome studies. Mutagenesis. 2015 Aug 18; Authors: Athersuch TJ, Keun HC Abstract The human metabolome-the complement of small molecule metabolites present in biofluids and tissues-represents a significant part of the internal chemical milieu and is therefore an important aspect of the human exposome. Metabolic profiling approaches, commonly referred to as metabonomics or metabolomics, permit detailed and efficient characterisation of human biospecimens; application to population studies holds great promise for uncovering new associations and causal relationships between environmental factors and chronic disease. In addition to the insight metabolic information can provide, metabolic phenotypes anchor other molecular readouts and help formulate a systems-level interpretation of biological phenomena. In this commentary, we discuss the general approach for applying metabolic profiling in exposome studies, alongside recent exemplars. We also comment on the complexity and dynamism of the metabolome and highlight both the limitations such properties impart and the requirements for dealing with such issues in real-world phenotyping studies. Given that several large-scale exposome studies are now underway, we offer a perspective on current and future challenges that will need to be addressed to maximise their utility in environmental health research. PMID: 26290610 [PubMed - as supplied by publisher]

Related Articles Phenylphenalenones protect banana plants from infection by Mycosphaerella fijiensis and are deactivated by metabolic conversion. Plant Cell Environ. 2015 Aug 20; Authors: Hidalgo W, Chandran JN, Menezes RC, Otálvaro F, Schneider B Abstract Phenylphenalenones, polycyclic aromatic natural products from some monocotyledonous plants, are known as phytoalexins in banana (Musa spp.). In this study, (1) H NMR-based metabolomics along with liquid chromatography and mass spectrometry were used to explore the chemical responses of the susceptible 'Williams' and the resistant 'Khai Thong Ruang' Musa varieties to the ascomycete fungus Mycosphaerella fijiensis, the agent of the Black Leaf Sigatoka Disease. Principal component analysis discriminated strongly between infected and non-infected plant tissue, mainly due to specialized metabolism induced in response to the fungus. Phenylphenalenones are among the major induced compounds, and the resistance level of the plants was correlated with the progress of the disease. However, a virulent strain of M. fijiensis was able to overcome plant resistance by converting phenylphenalenones to sulfate conjugates. Here we report the first metabolic detoxification of fungitoxic phenylphenalenones to evade the chemical defense of Musa plants. PMID: 26290378 [PubMed - as supplied by publisher]

Related Articles Dipeptide species regulate p38MAPK-Smad3 signalling to maintain chronic myelogenous leukaemia stem cells. Nat Commun. 2015;6:8039 Authors: Naka K, Jomen Y, Ishihara K, Kim J, Ishimoto T, Bae EJ, Mohney RP, Stirdivant SM, Oshima H, Oshima M, Kim DW, Nakauchi H, Takihara Y, Kato Y, Ooshima A, Kim SJ Abstract Understanding the specific survival of the rare chronic myelogenous leukaemia (CML) stem cell population could provide a target for therapeutics aimed at eradicating these cells. However, little is known about how survival signalling is regulated in CML stem cells. In this study, we survey global metabolic differences between murine normal haematopoietic stem cells (HSCs) and CML stem cells using metabolomics techniques. Strikingly, we show that CML stem cells accumulate significantly higher levels of certain dipeptide species than normal HSCs. Once internalized, these dipeptide species activate amino-acid signalling via a pathway involving p38MAPK and the stemness transcription factor Smad3, which promotes CML stem cell maintenance. Importantly, pharmacological inhibition of dipeptide uptake inhibits CML stem cell activity in vivo. Our results demonstrate that dipeptide species support CML stem cell maintenance by activating p38MAPK-Smad3 signalling in vivo, and thus point towards a potential therapeutic target for CML treatment. PMID: 26289811 [PubMed - in process]

Related Articles Enzymatic passaging of human embryonic stem cells alters central carbon metabolism and glycan abundance. Biotechnol J. 2015 Aug 18; Authors: Badur MG, Zhang H, Metallo CM Abstract To realize the potential of human embryonic stem cells (hESCs) in regenerative medicine and drug discovery applications, large numbers of cells that accurately recapitulate cell and tissue function must be robustly produced. Previous studies have suggested that genetic instability and epigenetic changes occur as a consequence of enzymatic passaging; however, the potential impacts of such passaging methods on the metabolism of hESCs have not been described. Using stable isotope tracing and mass spectrometry-based metabolomics, we have explored how different passaging reagents impact hESC metabolism. Enzymatic passaging caused significant decreases in glucose utilization throughout central carbon metabolism along with attenuated de novo lipogenesis. In addition, we developed and validated a method for rapidly quantifying glycan abundance and isotopic labeling in hydrolyzed biomass. Enzymatic passaging reagents significantly altered levels of glycans immediately after digestion but surprisingly glucose contribution to glycans was not affected. These results demonstrate that there is an immediate effect on hESC metabolism after enzymatic passaging in both central carbon metabolism and biosynthesis. HESCs subjected to enzymatic passaging are routinely placed in a state requiring re-synthesis of biomass components, subtly influencing their metabolic needs in a manner that may impact cell performance in regenerative medicine applications. PMID: 26289220 [PubMed - as supplied by publisher]

Related Articles Tracking hippo in the cancer jungle. Chem Biol. 2014 Jul 17;21(7):803-4 Authors: Suh JH, Saba JD Abstract Signaling through the Hippo pathway controls major aspects of cell growth and proliferation. Focusing on the metabolic consequences of Hippo signaling, Mulvihill and colleagues in this issue of Chemistry & Biology employ a large scale, integrative approach and uncover downstream reorganization of cellular metabolism when the effector TAZ is upregulated, identifying new connections to lipid metabolism. PMID: 25036773 [PubMed - indexed for MEDLINE]

Metabolomic and Lipidomic Analysis of Serum Samples following Curcuma longa Extract Supplementation in High-Fructose and Saturated Fat Fed Rats. PLoS One. 2015;10(8):e0135948 Authors: Tranchida F, Shintu L, Rakotoniaina Z, Tchiakpe L, Deyris V, Hiol A, Caldarelli S Abstract We explored, using nuclear magnetic resonance (NMR) metabolomics and fatty acids profiling, the effects of a common nutritional complement, Curcuma longa, at a nutritionally relevant dose with human use, administered in conjunction with an unbalanced diet. Indeed, traditional food supplements have been long used to counter metabolic impairments induced by unbalanced diets. Here, rats were fed either a standard diet, a high level of fructose and saturated fatty acid (HFS) diet, a diet common to western countries and that certainly contributes to the epidemic of insulin resistance (IR) syndrome, or a HFS diet with a Curcuma longa extract (1% of curcuminoids in the extract) for ten weeks. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) on the serum NMR profiles and fatty acid composition (determined by GC/MS) showed a clear discrimination between HFS groups and controls. This discrimination involved metabolites such as glucose, amino acids, pyruvate, creatine, phosphocholine/glycerophosphocholine, ketone bodies and glycoproteins as well as an increase of monounsaturated fatty acids (MUFAs) and a decrease of n-6 and n-3 polyunsaturated fatty acids (PUFAs). Although the administration of Curcuma longa did not prevent the observed increase of glucose, triglycerides, cholesterol and insulin levels, discriminating metabolites were observed between groups fed HFS alone or with addition of a Curcuma longa extract, namely some MUFA and n-3 PUFA, glycoproteins, glutamine, and methanol, suggesting that curcuminoids may act respectively on the fatty acid metabolism, the hexosamine biosynthesis pathway and alcohol oxidation. Curcuma longa extract supplementation appears to be beneficial in these metabolic pathways in rats. This metabolomic approach highlights important serum metabolites that could help in understanding further the metabolic mechanisms leading to IR. PMID: 26288372 [PubMed - as supplied by publisher]

Analysis of Metabolomics Datasets with High-Performance Computing and Metabolite Atlases. Metabolites. 2015;5(3):431-442 Authors: Yao Y, Sun T, Wang T, Ruebel O, Northen T, Bowen BP Abstract Even with the widespread use of liquid chromatography mass spectrometry (LC/MS) based metabolomics, there are still a number of challenges facing this promising technique. Many, diverse experimental workflows exist; yet there is a lack of infrastructure and systems for tracking and sharing of information. Here, we describe the Metabolite Atlas framework and interface that provides highly-efficient, web-based access to raw mass spectrometry data in concert with assertions about chemicals detected to help address some of these challenges. This integration, by design, enables experimentalists to explore their raw data, specify and refine features annotations such that they can be leveraged for future experiments. Fast queries of the data through the web using SciDB, a parallelized database for high performance computing, make this process operate quickly. By using scripting containers, such as IPython or Jupyter, to analyze the data, scientists can utilize a wide variety of freely available graphing, statistics, and information management resources. In addition, the interfaces facilitate integration with systems biology tools to ultimately link metabolomics data with biological models. PMID: 26287255 [PubMed - as supplied by publisher]

Related Articles Topologically inferring pathway activity toward precise cancer classification via integrating genomic and metabolomic data: prostate cancer as a case. Sci Rep. 2015;5:13192 Authors: Liu W, Bai X, Liu Y, Wang W, Han J, Wang Q, Xu Y, Zhang C, Zhang S, Li X, Ren Z, Zhang J, Li C Abstract Precise cancer classification is a central challenge in clinical cancer research such as diagnosis, prognosis and metastasis prediction. Most existing cancer classification methods based on gene or metabolite biomarkers were limited to single genomics or metabolomics, and lacked integration and utilization of multiple 'omics' data. The accuracy and robustness of these methods when applied to independent cohorts of patients must be improved. In this study, we propose a directed random walk-based method to evaluate the topological importance of each gene in a reconstructed gene-metabolite graph by integrating information from matched gene expression profiles and metabolomic profiles. The joint use of gene and metabolite information contributes to accurate evaluation of the topological importance of genes and reproducible pathway activities. We constructed classifiers using reproducible pathway activities for precise cancer classification and risk metabolic pathway identification. We applied the proposed method to the classification of prostate cancer. Within-dataset experiments and cross-dataset experiments on three independent datasets demonstrated that the proposed method achieved a more accurate and robust overall performance compared to several existing classification methods. The resulting risk pathways and topologically important differential genes and metabolites provide biologically informative models for prostate cancer prognosis and therapeutic strategies development. PMID: 26286638 [PubMed - in process]