Literature DB >> 23711563

Untargeted metabolomics from biological sources using ultraperformance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS).

Nathaniel W Snyder1, Maya Khezam, Clementina A Mesaros, Andrew Worth, Ian A Blair.   

Abstract

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.

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Year:  2013        PMID: 23711563      PMCID: PMC3711276          DOI: 10.3791/50433

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  29 in total

1.  KEGG: kyoto encyclopedia of genes and genomes.

Authors:  M Kanehisa; S Goto
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  Global metabolic profiling procedures for urine using UPLC-MS.

Authors:  Elizabeth J Want; Ian D Wilson; Helen Gika; Georgios Theodoridis; Robert S Plumb; John Shockcor; Elaine Holmes; Jeremy K Nicholson
Journal:  Nat Protoc       Date:  2010-06       Impact factor: 13.491

3.  XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification.

Authors:  Colin A Smith; Elizabeth J Want; Grace O'Maille; Ruben Abagyan; Gary Siuzdak
Journal:  Anal Chem       Date:  2006-02-01       Impact factor: 6.986

4.  Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry.

Authors:  Warwick B Dunn; David Broadhurst; Paul Begley; Eva Zelena; Sue Francis-McIntyre; Nadine Anderson; Marie Brown; Joshau D Knowles; Antony Halsall; John N Haselden; Andrew W Nicholls; Ian D Wilson; Douglas B Kell; Royston Goodacre
Journal:  Nat Protoc       Date:  2011-06-30       Impact factor: 13.491

5.  Metabolic profiling of the fission yeast S. pombe: quantification of compounds under different temperatures and genetic perturbation.

Authors:  Tomás Pluskal; Takahiro Nakamura; Alejandro Villar-Briones; Mitsuhiro Yanagida
Journal:  Mol Biosyst       Date:  2009-09-04

6.  MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data.

Authors:  Tomás Pluskal; Sandra Castillo; Alejandro Villar-Briones; Matej Oresic
Journal:  BMC Bioinformatics       Date:  2010-07-23       Impact factor: 3.169

7.  Dichloromethane as a solvent for lipid extraction and assessment of lipid classes and fatty acids from samples of different natures.

Authors:  Elena Cequier-Sánchez; Covadonga Rodríguez; Angel G Ravelo; Rafael Zárate
Journal:  J Agric Food Chem       Date:  2008-05-28       Impact factor: 5.279

8.  Processing methods for differential analysis of LC/MS profile data.

Authors:  Mikko Katajamaa; Matej Oresic
Journal:  BMC Bioinformatics       Date:  2005-07-18       Impact factor: 3.169

9.  PubChem: a public information system for analyzing bioactivities of small molecules.

Authors:  Yanli Wang; Jewen Xiao; Tugba O Suzek; Jian Zhang; Jiyao Wang; Stephen H Bryant
Journal:  Nucleic Acids Res       Date:  2009-06-04       Impact factor: 16.971

10.  Highly sensitive feature detection for high resolution LC/MS.

Authors:  Ralf Tautenhahn; Christoph Böttcher; Steffen Neumann
Journal:  BMC Bioinformatics       Date:  2008-11-28       Impact factor: 3.169

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  18 in total

Review 1.  Bioanalytical techniques for detecting biomarkers of response to human asbestos exposure.

Authors:  Clementina Mesaros; Andrew J Worth; Nathaniel W Snyder; Melpo Christofidou-Solomidou; Anil Vachani; Steven M Albelda; Ian A Blair
Journal:  Bioanalysis       Date:  2015       Impact factor: 2.681

2.  Hyper response to ovarian stimulation affects the follicular fluid metabolomic profile of women undergoing IVF similarly to polycystic ovary syndrome.

Authors:  Fernanda Bertuccez Cordeiro; Thaís Regiani Cataldi; Beatriz Zappellini de Souza; Raquel Cellin Rochetti; Renato Fraietta; Carlos Alberto Labate; Edson Guimarães Lo Turco
Journal:  Metabolomics       Date:  2018-03-16       Impact factor: 4.290

3.  Inhibition of neuronal cell mitochondrial complex I with rotenone increases lipid β-oxidation, supporting acetyl-coenzyme A levels.

Authors:  Andrew J Worth; Sankha S Basu; Nathaniel W Snyder; Clementina Mesaros; Ian A Blair
Journal:  J Biol Chem       Date:  2014-08-12       Impact factor: 5.157

Review 4.  The use of mass spectrometry for analysing metabolite biomarkers in epidemiology: methodological and statistical considerations for application to large numbers of biological samples.

Authors:  Mads V Lind; Otto I Savolainen; Alastair B Ross
Journal:  Eur J Epidemiol       Date:  2016-05-26       Impact factor: 8.082

5.  Cytotoxic 1-deoxysphingolipids are metabolized by a cytochrome P450-dependent pathway.

Authors:  Irina Alecu; Alaa Othman; Anke Penno; Essa M Saied; Christoph Arenz; Arnold von Eckardstein; Thorsten Hornemann
Journal:  J Lipid Res       Date:  2016-11-21       Impact factor: 5.922

6.  Differences in testosterone and its precursors by sex of the offspring in meconium.

Authors:  Alexander J Frey; Bo Y Park; Emily R Schriver; Daniel R Feldman; Samuel Parry; Lisa A Croen; Daniele M Fallin; Irva Hertz-Picciotto; Craig J Newschaffer; Nathaniel W Snyder
Journal:  J Steroid Biochem Mol Biol       Date:  2016-11-18       Impact factor: 4.292

7.  Comparison of statistical methods for detection of serum lipid biomarkers for mesothelioma and asbestos exposure.

Authors:  Rengyi Xu; Clementina Mesaros; Liwei Weng; Nathaniel W Snyder; Anil Vachani; Ian A Blair; Wei-Ting Hwang
Journal:  Biomark Med       Date:  2017-05-23       Impact factor: 2.851

8.  Metabolism of propionic acid to a novel acyl-coenzyme A thioester by mammalian cell lines and platelets.

Authors:  Nathaniel W Snyder; Sankha S Basu; Andrew J Worth; Clementina Mesaros; Ian A Blair
Journal:  J Lipid Res       Date:  2014-11-25       Impact factor: 5.922

Review 9.  Translational metabolomics in cancer research.

Authors:  Nathaniel W Snyder; Clementina Mesaros; Ian A Blair
Journal:  Biomark Med       Date:  2015-09-01       Impact factor: 2.851

10.  A strategy for sensitive, large scale quantitative metabolomics.

Authors:  Xiaojing Liu; Zheng Ser; Ahmad A Cluntun; Samantha J Mentch; Jason W Locasale
Journal:  J Vis Exp       Date:  2014-05-27       Impact factor: 1.355

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