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Related Articles Rapid discovery of absorbed constituents and metabolites in rat plasma after the oral administration of Zi Shen Wan using high-throughput UHPLC-MS with a multivariate analysis approach. J Sep Sci. 2016 Dec;39(24):4700-4711 Authors: Li XN, Zhang A, Sun H, Song Y, Zou D, Wang X Abstract Zi Shen Wan is a typical formula consisting of three herbs, Phellodendri Amurensis Cortex, Rhizoma Anemarrhenae, and Cortex Cinnamomi, and has been widely used for treating prostatitis and infection diseases. However, it lacks in-depth research of the constituents of Zi Shen Wan in vivo and in vitro. In this work, ultra high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry and MassLynx software was established to characterize the chemical compositions of Zi Shen Wan in vivo and in vitro. In total, 92 peaks were characterized in vitro and 33 peaks were characterized in vivo based on mass spectrometry and tandem mass spectrometry data. Among the 33 compounds characterized in rat plasma, 22 prototype components absorbed in rat serum and 11 metabolites were identified in vivo. This work was fully reports the chemical constituents of traditional Chinese formula of Zi Shen Wan, it demonstrated that ultra high performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry coupled to MassLynx software and multivariate data processing approach could be successfully applied for rapid screening and comprehensive analysis of chemical constituents in vitro and prototype components or metabolites in vivo of traditional Chinese medicine. PMID: 27778479 [PubMed - indexed for MEDLINE]

Related Articles Nonfasting for Routine Lipid Testing: From Evidence to Action. JAMA Intern Med. 2016 07 01;176(7):1005-6 Authors: Mora S PMID: 27119719 [PubMed - indexed for MEDLINE]

18 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 2018/03/06PubMed comprises more than millions of 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.

Comprehensive transcriptome analyses correlated with untargeted metabolome reveal differentially expressed pathways in response to cell wall alterations. Plant Mol Biol. 2018 Mar 03;: Authors: Reem NT, Chen HY, Hur M, Zhao X, Wurtele ES, Li X, Li L, Zabotina O Abstract KEY MESSAGE: This research provides new insights into plant response to cell wall perturbations through correlation of transcriptome and metabolome datasets obtained from transgenic plants expressing cell wall-modifying enzymes. Plants respond to changes in their cell walls in order to protect themselves from pathogens and other stresses. Cell wall modifications in Arabidopsis thaliana have profound effects on gene expression and defense response, but the cell signaling mechanisms underlying these responses are not well understood. Three transgenic Arabidopsis lines, two with reduced cell wall acetylation (AnAXE and AnRAE) and one with reduced feruloylation (AnFAE), were used in this study to investigate the plant responses to cell wall modifications. RNA-Seq in combination with untargeted metabolome was employed to assess differential gene expression and metabolite abundance. RNA-Seq results were correlated with metabolite abundances to determine the pathways involved in response to cell wall modifications introduced in each line. The resulting pathway enrichments revealed the deacetylation events in AnAXE and AnRAE plants induced similar responses, notably, upregulation of aromatic amino acid biosynthesis and changes in regulation of primary metabolic pathways that supply substrates to specialized metabolism, particularly those related to defense responses. In contrast, genes and metabolites of lipid biosynthetic pathways and peroxidases involved in lignin polymerization were downregulated in AnFAE plants. These results elucidate how primary metabolism responds to extracellular stimuli. Combining the transcriptomics and metabolomics datasets increased the power of pathway prediction, and demonstrated the complexity of pathways involved in cell wall-mediated signaling. PMID: 29502299 [PubMed - as supplied by publisher]

The glycomic effect of N-acetylglucosaminyltransferase III overexpression in metastatic melanoma cells. GnT-III modifies highly branched N-glycans. Glycoconj J. 2018 Mar 03;: Authors: Link-Lenczowski P, Bubka M, Balog CIA, Koeleman CAM, Butters TD, Wuhrer M, Lityńska A Abstract N-acetylglucosaminyltransferase III (GnT-III) is known to catalyze N-glycan "bisection" and thereby modulate the formation of highly branched complex structures within the Golgi apparatus. While active, it inhibits the action of other GlcNAc transferases such as GnT-IV and GnT-V. Moreover, GnT-III is considered as an inhibitor of the metastatic potential of cancer cells both in vitro and in vivo. However, the effects of GnT-III may be more diverse and depend on the cellular context. We describe the detailed glycomic analysis of the effect of GnT-III overexpression in WM266-4-GnT-III metastatic melanoma cells. We used MALDI-TOF and ESI-ion-trap-MS/MS together with HILIC-HPLC of 2-AA labeled N-glycans to study the N-glycome of membrane-attached and secreted proteins. We found that the overexpression of GnT-III in melanoma leads to the modification of a broad range of N-glycan types by the introduction of the "bisecting" GlcNAc residue with highly branched complex structures among them. The presence of these unusual complex N-glycans resulted in stronger interactions of cellular glycoproteins with the PHA-L. Based on the data presented here we conclude that elevated activity of GnT-III in cancer cells does not necessarily lead to a total abrogation of the formation of highly branched glycans. In addition, the modification of pre-existing N-glycans by the introduction of "bisecting" GlcNAc can modulate their capacity to interact with carbohydrate-binding proteins such as plant lectins. Our results suggest further studies on the biological function of "bisected" oligosaccharides in cancer cell biology and their interactions with carbohydrate-binding proteins. PMID: 29502191 [PubMed - as supplied by publisher]

[Changes of cerebral cortical metabolomics in rats following benzo[a]pyrene exposure]. Nan Fang Yi Ke Da Xue Xue Bao. 2018 Feb 20;38(2):162-167 Authors: Wang J, Li CL, Bai LL, Tang QH, Zhang RY, Han TL, Guo YM, N Baker P, Xia YY, Tu BJ Abstract OBJECTIVE: To analyze the changes in endogenous small molecule metabolites after benzo[a]pyrene (B[a]P) exposure in rat cerebral cortex and explore the mechanism of B[a]P neurotoxicity. METHODS: Five-day-old SD rats were subjected to gavage administration of 2 mg/kg B[a]P for 7 consecutive weeks. After the exposure, the rats were assessed for spatial learning ability using Morris water maze test, ultrastructural changes of the cortical neurons under electron microscope, and metabolite profiles of the cortex using GC/MS. The differential metabolites between the exposed and control rats were identified with partial least squares discriminant analysis (PLS-DA) and the metabolic pathways related with the differential metabolites were analyzed using Cytoscape software. RESULTS: Compared with the control group, the rats exposed to B[a]P showed significantly increased escape latency (P<0.05) and decreased time spent in the target area (P<0.05). The exposed rats exhibited widened synaptic cleft, thickened endplate membrane and swollen cytoplasm compared with the control rats. Eighteen differential metabolites (VIP>1, P<0.05) in the cortex were identified between the two groups, and 9 pathways associated with B[a]P neurotoxicity were identified involving amino acid metabolism, tricarboxylic acid cycle and Vitamin B3 (niacin and nicotinamide) metabolism. CONCLUSION: B[a]P can cause disturbance in normal metabolisms and its neurotoxicity is possibly related with disorders in amino acid metabolism, tricarboxylic acid cycle and vitamin metabolism. PMID: 29502054 [PubMed - in process]

UPLC-G2Si-HDMS untargeted metabolomics for identification of metabolic targets of Yin-Chen-Hao-Tang used as a therapeutic agent of dampness-heat jaundice syndrome. J Chromatogr B Analyt Technol Biomed Life Sci. 2018 Feb 27;1081-1082:41-50 Authors: Sun H, Yang L, Li MX, Fang H, Zhang AH, Song Q, Liu XY, Su J, Yu MD, Makino T, Wang XJ Abstract Yin-Chen-Hao-Tang (YCHT), the classic formulae of traditional Chinese medicine (TCM), is widely used to treat dampness-heat jaundice syndrome (DHJS) and various liver diseases. However, the therapeutic mechanism of YCHT is yet to have an integrated biological interpretation. In this work, we used metabolomics technology to reveal the adjustment of small molecule metabolites in body during the treatment of YCHT. Aim to discover the serum biomarkers which are associated with the treatment of DHJS against YCHT. Pathological results and biochemical indicators showed that the hepatic injury and liver index abnormalities caused by DHJS was effectively improve after treatment with YCHT. On the basis of effective treatment, ultra-high performance liquid chromatography (UPLC-G2Si-HDMS) combined with the multivariate statistical analysis method was utilized to analyze the serum samples. Finally, 22 biomarkers were identified by using mass spectrometry and illuminated the correlative metabolic pathways which play a significant role and as therapeutic targets in the treatment of DHJS. This work demonstrated that mass spectrometry metabolomics provides a new insight to elucidate the action mechanism of formulae. PMID: 29502028 [PubMed - as supplied by publisher]

Multiple nucleobase transporters contribute to boscalid sensitivity in Aspergillus nidulans. Fungal Genet Biol. 2018 Feb 28;: Authors: Kalampokis IF, Kapetanakis GC, Aliferis KA, Diallinas G Abstract The development of fungicide-resistant fungal populations represents a major challenge for the agrochemical and agri-food sectors, which threatens food supply and security. The issue becomes complex for fungi that cause quantitative and qualitative losses due to mycotoxin biosynthesis. Nonetheless, currently, the molecular details underlying fungicide action and fungal resistance mechanisms are partially known. Here, we have investigated whether plasma membrane transporters contribute to specific fungicide uptake in the model fungus Aspergillus nidulans. Independent physiological tests and toxicity screening of selected fungicides provided evidence that the antifungal activity of Succinate Dehydrogenase Inhibitors (SDHIs) is associated with the expression of several nucleobase-related transporters. In particular, it was shown that a strain genetically inactivated in all seven nucleobase-related transporters is resistant to the fungicide boscalid, whereas none of the single null mutants exhibited significant resistance level. By constructing and testing isogenic strains that over-express each one of the seven transporters, we confirmed that five of them, namely, UapC, AzgA, FycB, CntA, and FurA, contribute to boscalid uptake. Additionally, by employing metabolomics we have examined the effect of boscalid on the metabolism of isogenic strains expressing or genetically lacking boscalid-related nucleobase transporters. The results confirmed the involvement of specific nucleobase transporters in fungicide uptake, leading to the discovery of corresponding metabolites-biomarkers. This work is the first report on the involvement of specific transporters in fungicide uptake and toxicity and their impact on fungal metabolism regulation and results might be further exploited towards the deeper understanding of fungal resistance to fungicides. PMID: 29501616 [PubMed - as supplied by publisher]

A review of nanoscale LC-ESI for metabolomics and its potential to enhance the metabolome coverage. Talanta. 2018 May 15;182:380-390 Authors: Chetwynd AJ, David A Abstract Liquid chromatography-electrospray ionisation-mass spectrometry (LC-ESI-MS) platforms are widely used to perform high throughput untargeted profiling of biological samples for metabolomics-based approaches. However, these LC-ESI platforms usually favour the detection of metabolites present at relatively high concentrations because of analytical limitations such as ion suppression, thus reducing overall sensitivity. To counter this issue of sensitivity, the latest in terms of analytical platforms can be adopted to enable a greater portion of the metabolome to be analysed in a single analytical run. Here, nanoflow liquid chromatography-nanoelectrospray ionisation (nLC-nESI), which has previously been utilised successfully in proteomics, is explored for use in metabolomic and exposomic research. As a discovery based field, the markedly increased sensitivity of these nLC-nESI platforms offer the potential to uncover the roles played by low abundant signalling metabolites (e.g. steroids, eicosanoids) in health and disease studies, and would also enable an improvement in the detection of xenobiotics present at trace levels in biological matrices to better characterise the chemical exposome. This review aims to give an insight into the advantages associated with nLC-nESI for metabolomics-based approaches. Initially we detail the source of improved sensitivity prior to reviewing the available approaches to achieving nanoflow rates and nanospray ionisation for metabolomics. The robustness of nLC-nESI platforms was then assessed using the literature available from a metabolomic viewpoint. We also discuss the challenging point of sample preparation which needs to be addressed to fully enjoy the benefits of these nLC-nESI platforms. Finally, we assess metabolomic analysis utilising nano scale platforms and look ahead to the future of metabolomics using these new highly sensitive platforms. PMID: 29501168 [PubMed - in process]

Alcohol and substance use are associated with altered metabolome in the first trimester serum samples of pregnant mothers. Eur J Obstet Gynecol Reprod Biol. 2018 Feb 17;223:79-84 Authors: Lehikoinen AI, Kärkkäinen OK, Lehtonen MAS, Auriola SOK, Hanhineva KJ, Heinonen ST Abstract BACKGROUND: Although the effects of alcohol on metabolic processes in the body have been studied widely, there do not appear to be any previous reports clarifying how substance abuse changes metabolic profiles of pregnant women during the first trimester of pregnancy. OBJECTIVE: Our aim was to evaluate the effect of substance abuse, especially alcohol use, on the metabolic profile of pregnant women during the first trimester. STUDY DESIGN: We applied mass spectrometry based non-targeted metabolite profiling of serum collected during routine visit to the hospital between gestational weeks 9 + 0 to 11 + 6 from controls (n = 55), alcohol users (n = 19), drug users (n = 24) and tobacco smokers (n = 40). RESULTS: We observed statistically significantly differences among the study groups in serum levels of glutamate, glutamine, and serotonin (p-values ≤ 0.0001). The serum levels of glutamate were increased in alcohol and drug using mothers when compared to the controls, whereas levels of glutamine were decreased in alcohol and drug using mothers. In addition, serum levels of serotonin were decreased in alcohol using mothers when compared to the controls. CONCLUSION: The present study shows that alcohol and drug use were associated with increased glutamate, and decreased glutamine levels, and alcohol use is associated with decreased serotonin levels. This study serves as a proof-of-concept that the metabolite profile of human first trimester serum samples could be used to detect alcohol exposure during pregnancy. PMID: 29500949 [PubMed - as supplied by publisher]

Alterations in Gut Microbial Function Following Liver Transplant. Liver Transpl. 2018 Mar 03;: Authors: Bajaj JS, Kakiyama G, Cox IJ, Nittono H, Takei H, White M, Fagan A, Gavis EA, Heuman DM, Gilles HC, Hylemon P, Taylor-Robinson SD, Legido-Quigley C, Kim M, Xu J, Williams R, Sikaroodi M, Pandak WM, Gillevet PM Abstract Liver transplant (LT) improves daily function and ameliorates gut microbial composition. However, the effect of LT on microbial functionality, which can be related to overall patient benefit, is unclear and could affect the post-LT course. AIMS: To determine the effect of LT on gut microbial functionality focusing on endotoxemia, bile acid (BA), ammonia metabolism and lipidomics. METHOD: We enrolled outpatient cirrhotic patients on the LT list and followed them till 6 months post-LT. Microbiota composition (Shannon diversity and individual taxa) and function analysis (serum endotoxin, urinary metabolomics and serum lipidomics, and stool BA profile) and cognitive tests were performed at both visits. RESULTS: We enrolled 40 patients (56±7 years, MELD 23). They received LT 6±3 months after enrollment and were re-evaluated 7±3 months post-LT with a stable course. A significant improvement in cognition with increase in microbial diversity, increase in autochthonous and decrease in potentially pathogenic taxa and reduced endotoxemia were seen post-LT compared to baseline. Stool BAs increased significantly post-LT and there was evidence of greater bacterial action (higher secondary, oxo and iso-BAs) post-LT although the levels of conjugated BAs remained similar. There was a reduced serum ammonia and corresponding rise in urinary phenylacetylglutamine (PAG) post-LT. There was an increase in urinary trimethylamine-N-oxide (TMAO), which was correlated with specific changes in serum lipids related to cell membrane products. The ultimate post-LT lipidomic profile appeared beneficial compared to the pre-LT. CONCLUSIONS: LT improves gut microbiota diversity and dysbiosis which is accompanied by favorable changes in gut microbial functionality corresponding to bile acids, ammonia, endotoxemia, lipidomic and metabolomic profiles. This article is protected by copyright. All rights reserved. PMID: 29500907 [PubMed - as supplied by publisher]

Metabolomics profiles of hepatocellular carcinoma in a Korean prospective cohort: the Korean Cancer Prevention Study-II. Cancer Prev Res (Phila). 2018 Mar 02;: Authors: Jee SH, Kim M, Kim M, Yoo HJ, Kim H, Jung KJ, Hong S, Lee JH Abstract In the prospective Korean Cancer Prevention Study-II (KCPS-II), we investigated the application of metabolomics to differentiate subjects with incident hepatocellular carcinoma (HCC group) from subjects who remained free of cancer (control group) during a mean follow-up period of 7 years with the aim of identifying valuable metabolic biomarkers for HCC. We used baseline serum samples from 75 subjects with incident HCC and 134 age- and gender-matched cancer-free subjects. Serum metabolic profiles associated with HCC incidence were investigated via metabolomics analysis. Compared to the control group, the HCC group showed significantly higher serum levels of aspartate aminotransferase (AST), alanine aminotransferase, and gamma-glutamyl transpeptidase. At baseline, compared to the control group, the HCC group showed significantly higher levels of 9 metabolites, including leucine, 5-hydroxyhexanoic acid, phenylalanine, tyrosine, arachidonic acid, and tauroursodeoxycholic acid (TUDCA), but lower levels of 28 metabolites, including oleamide, androsterone sulfate, L-palmitoylcarnitine, lysophosphatidic acid (LPA) 16:0, LPA 18:1, and lysophosphatidylcholines (lysoPCs). Multiple linear regression revealed that the incidence of HCC was associated with the levels of tyrosine, AST, lysoPCs (16:1, 20:3), oleamide, 5-hydroxyhexanoic acid, androsterone sulfate, and TUDCA (adjusted R2=0.514, P=0.036). This study showed the clinical relevance of the dysregulation of not only branched amino acids, aromatic amino acids, and lysoPCs but also bile acid biosynthesis and linoleic acid, arachidonic acid and fatty acid metabolism. Additionally, tyrosine, AST, lysoPCs (16:1, 20:3), oleamide, 5-hydroxyhexanoic acid, androsterone sulfate, and TUDCA were identified as independent variables associated with the incidence of HCC. PMID: 29500188 [PubMed - as supplied by publisher]

Development of an analytical method for polycyclic aromatic hydrocarbons in coffee beverages and dark beer using novel high-sensitivity technique of supercritical fluid chromatography/mass spectrometry. J Biosci Bioeng. 2018 Feb 28;: Authors: Yoshioka T, Nagatomi Y, Harayama K, Bamba T Abstract Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic substances that are mainly generated during heating in food; therefore, the European Union (EU) has regulated the amount of benzo[a]pyrene and PAH4 in various types of food. In addition, the Scientific Committee on Food of the EU and the Joint Food and Agriculture Organization/World Health Organization Expert Committee on Food Additives have recommended that 16 PAHs should be monitored. Since coffee beverages and dark beer are roasted during manufacture, monitoring these 16 PAHs is of great importance. On the other hand, supercritical fluid chromatography (SFC) is a separation method that has garnered attention in recent years as a complement for liquid and gas chromatography. Therefore, we developed a rapid high-sensitivity analytical method for the above-mentioned 16 PAHs in coffee beverages and dark beer involving supercritical fluid chromatography/atmospheric pressure chemical ionization-mass spectrometry (SFC/APCI-MS) and simple sample preparation. In this study, we developed a novel analytical technique that increased the sensitivity of MS detection by varying the back-pressure in SFC depending on the elution of PAHs. In addition, analysis of commercially available coffee and dark beer samples in Japan showed that the risk of containing the 16 PAHs may be low. PMID: 29499993 [PubMed - as supplied by publisher]

Estimated Glomerular Filtration Rate From a Panel of Filtration Markers-Hope for Increased Accuracy Beyond Measured Glomerular Filtration Rate? Adv Chronic Kidney Dis. 2018 Jan;25(1):67-75 Authors: Inker LA, Levey AS, Coresh J Abstract The recent Kidney Disease Improving Global Outcomes 2012 CKD guidelines recommend estimating GFR from serum creatinine (eGFRcr) as a first-line test to assess kidney function and using cystatin C or measured glomerular filtration rate (GFR) as confirmatory tests. eGFRcr may be inaccurate in people with variation in muscle mass or diet, and eGFRcys is not more accurate than eGFRcr. eGFRcrcys is more accurate than either, but it is not independent of eGFRcr. Measured GFR is not practical and is susceptible to error due to variation in clearance methods and in the behavior of exogenous filtration markers. Over the past few years, we have hypothesized, and begun to test the hypothesis, that a panel of filtration markers (panel eGFR) from a single blood draw would require fewer demographic or clinical variables and could estimate GFR as accurately as measured GFR. In this article, we describe the conceptual background and rationale for this hypothesis and summarize our work thus far including evaluation of novel low-molecular-weight proteins and metabolites and then outline how we envision that such a panel could be used in clinical practice, research, and public health. PMID: 29499889 [PubMed - in process]

Metabolomics reveal optimal grain pre-processing (milling) toward rice koji fermentation. J Agric Food Chem. 2018 Mar 02;: Authors: Lee S, Lee DE, Singh D, Lee CH Abstract A time-correlated mass spectrometry (MS) based metabolic profiling was performed for rice koji made using the substrates with varying degrees of milling (DOM). Overall, 67 primary and secondary metabolites were observed as significantly discriminant among different samples. Notably, a higher abundance of carbohydrate (sugars, sugar alcohols, organic acids, phenolic acids) and lipid (fatty acids, lysophospholipids) derived metabolites with enhanced hydrolytic enzyme activities were observed for koji made with substrate's DOM 5-7, at 36 h. The antioxidant secondary metabolites (flavonoids and phenolic acid) were relatively higher in koji with substrate's DOM 0, followed by DOM 5 > 7 > 9 and 11, at 96 h. Hence, we conjecture that the rice substrate pre-processing between DOM 5-7 was potentially optimal toward koji fermentation with end-product being rich in distinctive organoleptic, nutritional, and functional metabolites. The study rationalizes the substrate pre-processing steps vital for commercial koji making. PMID: 29499610 [PubMed - as supplied by publisher]

20 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 2018/03/03PubMed comprises more than millions of 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.

Related Articles speaq 2.0: A complete workflow for high-throughput 1D NMR spectra processing and quantification. PLoS Comput Biol. 2018 Mar 01;14(3):e1006018 Authors: Beirnaert C, Meysman P, Vu TN, Hermans N, Apers S, Pieters L, Covaci A, Laukens K Abstract Nuclear Magnetic Resonance (NMR) spectroscopy is, together with liquid chromatography-mass spectrometry (LC-MS), the most established platform to perform metabolomics. In contrast to LC-MS however, NMR data is predominantly being processed with commercial software. Meanwhile its data processing remains tedious and dependent on user interventions. As a follow-up to speaq, a previously released workflow for NMR spectral alignment and quantitation, we present speaq 2.0. This completely revised framework to automatically analyze 1D NMR spectra uses wavelets to efficiently summarize the raw spectra with minimal information loss or user interaction. The tool offers a fast and easy workflow that starts with the common approach of peak-picking, followed by grouping, thus avoiding the binning step. This yields a matrix consisting of features, samples and peak values that can be conveniently processed either by using included multivariate statistical functions or by using many other recently developed methods for NMR data analysis. speaq 2.0 facilitates robust and high-throughput metabolomics based on 1D NMR but is also compatible with other NMR frameworks or complementary LC-MS workflows. The methods are benchmarked using a simulated dataset and two publicly available datasets. speaq 2.0 is distributed through the existing speaq R package to provide a complete solution for NMR data processing. The package and the code for the presented case studies are freely available on CRAN (https://cran.r-project.org/package=speaq) and GitHub (https://github.com/beirnaert/speaq). PMID: 29494588 [PubMed - as supplied by publisher]

Related Articles An evolutionary learning and network approach to identifying key metabolites for osteoarthritis. PLoS Comput Biol. 2018 Mar 01;14(3):e1005986 Authors: Hu T, Oksanen K, Zhang W, Randell E, Furey A, Sun G, Zhai G Abstract Metabolomics studies use quantitative analyses of metabolites from body fluids or tissues in order to investigate a sequence of cellular processes and biological systems in response to genetic and environmental influences. This promises an immense potential for a better understanding of the pathogenesis of complex diseases. Most conventional metabolomics analysis methods exam one metabolite at a time and may overlook the synergistic effect of combining multiple metabolites. In this article, we proposed a new bioinformatics framework that infers the non-linear synergy among multiple metabolites using a symbolic model and subsequently, identify key metabolites using network analysis. Such a symbolic model is able to represent a complex non-linear relationship among a set of metabolites associated with osteoarthritis (OA) and is automatically learned using an evolutionary algorithm. Applied to the Newfoundland Osteoarthritis Study (NFOAS) dataset, our methodology was able to identify nine key metabolites including some known osteoarthritis-associated metabolites and some novel metabolic markers that have never been reported before. The results demonstrate the effectiveness of our methodology and more importantly, with further investigations, propose new hypotheses that can help better understand the OA disease. PMID: 29494586 [PubMed - as supplied by publisher]

Related Articles Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online. Nat Protoc. 2018 Apr;13(4):633-651 Authors: Forsberg EM, Huan T, Rinehart D, Benton HP, Warth B, Hilmers B, Siuzdak G Abstract Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min. PMID: 29494574 [PubMed - in process]

Related Articles MycoKey Round Table Discussions of Future Directions in Research on Chemical Detection Methods, Genetics and Biodiversity of Mycotoxins. Toxins (Basel). 2018 Mar 01;10(3): Authors: Leslie JF, Lattanzio V, Audenaert K, Battilani P, Cary J, Chulze SN, De Saeger S, Gerardino A, Karlovsky P, Liao YC, Maragos CM, Meca G, Medina A, Moretti A, Munkvold G, Mulè G, Njobeh P, Pecorelli I, Perrone G, Pietri A, Palazzini JM, Proctor RH, Rahayu ES, Ramírez ML, Samson R, Stroka J, Sulyok M, Sumarah M, Waalwijk C, Zhang Q, Zhang H, Logrieco AF Abstract MycoKey, an EU-funded Horizon 2020 project, includes a series of "Roundtable Discussions" to gather information on trending research areas in the field of mycotoxicology. This paper includes summaries of the Roundtable Discussions on Chemical Detection and Monitoring of mycotoxins and on the role of genetics and biodiversity in mycotoxin production. Discussions were managed by using the nominal group discussion technique, which generates numerous ideas and provides a ranking for those identified as the most important. Four questions were posed for each research area, as well as two questions that were common to both discussions. Test kits, usually antibody based, were one major focus of the discussions at the Chemical Detection and Monitoring roundtable because of their many favorable features, e.g., cost, speed and ease of use. The second area of focus for this roundtable was multi-mycotoxin detection protocols and the challenges still to be met to enable these protocols to become methods of choice for regulated mycotoxins. For the genetic and biodiversity group, both the depth and the breadth of trending research areas were notable. For some areas, e.g., microbiome studies, the suggested research questions were primarily of a descriptive nature. In other areas, multiple experimental approaches, e.g., transcriptomics, proteomics, RNAi and gene deletions, are needed to understand the regulation of toxin production and mechanisms underlying successful biological controls. Answers to the research questions will provide starting points for developing acceptable prevention and remediation processes. Forging a partnership between scientists and appropriately-placed communications experts was recognized by both groups as an essential step to communicating risks, while retaining overall confidence in the safety of the food supply and the integrity of the food production chain. PMID: 29494529 [PubMed - in process]