Literature DB >> 20619249

Complexity and pitfalls of mass spectrometry-based targeted metabolomics in brain research.

Michael Urban1, David P Enot, Guido Dallmann, Lisa Körner, Verena Forcher, Peter Enoh, Therese Koal, Matthias Keller, Hans-Peter Deigner.   

Abstract

Current quantitative metabolomic research in brain tissue is challenged by several analytical issues. To compare data of metabolite pattern, ratios of individual metabolite concentrations and composed classifiers characterizing a distinct state, standardized workup conditions, and extraction medium are crucial. Differences in physicochemical properties of individual compounds and compound classes such as polarity determine extraction yields and, thus, ratios of compounds with varying properties. Also, variations in suppressive effects related to coextracted matrix components affect standards or references and their concentration-dependent responses.The selection of a common tissue extraction protocol is an ill-posed problem because it can be regarded as a multiple objective decision depending on factors such as sample handling practicability, measurement precision, control of matrix effects, and relevance of the chemical assay. This study systematically evaluates the impact of extraction solvents and the impact of the complex brain tissue on measured metabolite levels, taking into account ionization efficiency as well as challenges encountered in the trace-level quantification of the analytes in brain matrices. In comparison with previous studies that relied on nontargeted platforms, consequently emphasizing the global behavior of the metabolomic fingerprint, here we focus on several series of metabolites spanning over extensive polarity, concentration, and molecular mass ranges. Copyright 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20619249     DOI: 10.1016/j.ab.2010.07.002

Source DB:  PubMed          Journal:  Anal Biochem        ISSN: 0003-2697            Impact factor:   3.365


  8 in total

Review 1.  Methods for studying the metabolic basis of Drosophila development.

Authors:  Hongde Li; Jason M Tennessen
Journal:  Wiley Interdiscip Rev Dev Biol       Date:  2017-05-26       Impact factor: 5.814

Review 2.  Sum of the parts: mass spectrometry-based metabolomics.

Authors:  Stephen B Milne; Thomas P Mathews; David S Myers; Pavlina T Ivanova; H Alex Brown
Journal:  Biochemistry       Date:  2013-03-07       Impact factor: 3.162

3.  Analytical strategies for studying stem cell metabolism.

Authors:  James M Arnold; William T Choi; Arun Sreekumar; Mirjana Maletić-Savatić
Journal:  Front Biol (Beijing)       Date:  2015-04

4.  Targeted metabolomics highlights perturbed metabolism in the brain of autism spectrum disorder sufferers.

Authors:  Stewart F Graham; Onur Turkoglu; Ali Yilmaz; Ilyas Ustun; Zafer Ugur; Trent Bjorndhal; BeomSoo Han; Rupa Mandal; David Wishart; Ray O Bahado-Singh
Journal:  Metabolomics       Date:  2020-04-24       Impact factor: 4.290

5.  Metabolite profiles reveal energy failure and impaired beta-oxidation in liver of mice with complex III deficiency due to a BCS1L mutation.

Authors:  Heike Kotarsky; Matthias Keller; Mina Davoudi; Per Levéen; Riitta Karikoski; David P Enot; Vineta Fellman
Journal:  PLoS One       Date:  2012-07-19       Impact factor: 3.240

6.  Inflammatory-induced hibernation in the fetus: priming of fetal sheep metabolism correlates with developmental brain injury.

Authors:  Matthias Keller; David P Enot; Mark P Hodson; Emeka I Igwe; Hans-Peter Deigner; Justin Dean; Hayde Bolouri; Henrik Hagberg; Carina Mallard
Journal:  PLoS One       Date:  2011-12-29       Impact factor: 3.240

7.  High-throughput extraction and quantification method for targeted metabolomics in murine tissues.

Authors:  Sven Zukunft; Cornelia Prehn; Cornelia Röhring; Gabriele Möller; Martin Hrabě de Angelis; Jerzy Adamski; Janina Tokarz
Journal:  Metabolomics       Date:  2017-12-30       Impact factor: 4.290

8.  Metabolomic Profiling of Bile Acids in Clinical and Experimental Samples of Alzheimer's Disease.

Authors:  Xiaobei Pan; Christopher T Elliott; Bernadette McGuinness; Peter Passmore; Patrick G Kehoe; Christian Hölscher; Paula L McClean; Stewart F Graham; Brian D Green
Journal:  Metabolites       Date:  2017-06-17
  8 in total

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