Literature DB >> 24816495

After the feature presentation: technologies bridging untargeted metabolomics and biology.

Kevin Cho1, Nathaniel G Mahieu1, Stephen L Johnson2, Gary J Patti3.   

Abstract

Liquid chromatography/mass spectrometry-based untargeted metabolomics is now an established experimental approach that is being broadly applied by many laboratories worldwide. Interpreting untargeted metabolomic data, however, remains a challenge and limits the translation of results into biologically relevant conclusions. Here we review emerging technologies that can be applied after untargeted profiling to extend biological interpretation of metabolomic data. These technologies include advances in bioinformatic software that enable identification of isotopes and adducts, comprehensive pathway mapping, deconvolution of MS(2) data, and tracking of isotopically labeled compounds. There are also opportunities to gain additional biological insight by complementing the metabolomic analysis of homogenized samples with recently developed technologies for metabolite imaging of intact tissues. To maximize the value of these emerging technologies, a unified workflow is discussed that builds on the traditional untargeted metabolomic pipeline. Particularly when integrated together, the combination of the advances highlighted in this review helps transform lists of masses and fold changes characteristic of untargeted profiling results into structures, absolute concentrations, pathway fluxes, and localization patterns that are typically needed to understand biology.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 24816495      PMCID: PMC4111999          DOI: 10.1016/j.copbio.2014.04.006

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  50 in total

1.  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

2.  INCA: a computational platform for isotopically non-stationary metabolic flux analysis.

Authors:  Jamey D Young
Journal:  Bioinformatics       Date:  2014-01-11       Impact factor: 6.937

3.  Meta-analysis of global metabolomic data identifies metabolites associated with life-span extension.

Authors:  Gary J Patti; Ralf Tautenhahn; Darcy Johannsen; Ewa Kalisiak; Eric Ravussin; Jens C Brüning; Andrew Dillin; Gary Siuzdak
Journal:  Metabolomics       Date:  2014-08-01       Impact factor: 4.290

Review 4.  Mass spectrometry imaging and profiling of single cells.

Authors:  Eric J Lanni; Stanislav S Rubakhin; Jonathan V Sweedler
Journal:  J Proteomics       Date:  2012-03-29       Impact factor: 4.044

5.  An accelerated workflow for untargeted metabolomics using the METLIN database.

Authors:  Ralf Tautenhahn; Kevin Cho; Winnie Uritboonthai; Zhengjiang Zhu; Gary J Patti; Gary Siuzdak
Journal:  Nat Biotechnol       Date:  2012-09       Impact factor: 54.908

6.  Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in Arabidopsis.

Authors:  Christoph Böttcher; Edda von Roepenack-Lahaye; Jürgen Schmidt; Constanze Schmotz; Steffen Neumann; Dierk Scheel; Stephan Clemens
Journal:  Plant Physiol       Date:  2008-06-13       Impact factor: 8.340

7.  LMSD: LIPID MAPS structure database.

Authors:  Manish Sud; Eoin Fahy; Dawn Cotter; Alex Brown; Edward A Dennis; Christopher K Glass; Alfred H Merrill; Robert C Murphy; Christian R H Raetz; David W Russell; Shankar Subramaniam
Journal:  Nucleic Acids Res       Date:  2006-11-10       Impact factor: 16.971

8.  HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries.

Authors:  Jiarui Zhou; Ralf J M Weber; J William Allwood; Robert Mistrik; Zexuan Zhu; Zhen Ji; Siping Chen; Warwick B Dunn; Shan He; Mark R Viant
Journal:  Bioinformatics       Date:  2013-12-11       Impact factor: 6.937

9.  13CFLUX2--high-performance software suite for (13)C-metabolic flux analysis.

Authors:  Michael Weitzel; Katharina Nöh; Tolga Dalman; Sebastian Niedenführ; Birgit Stute; Wolfgang Wiechert
Journal:  Bioinformatics       Date:  2012-10-30       Impact factor: 6.937

10.  Predicting network activity from high throughput metabolomics.

Authors:  Shuzhao Li; Youngja Park; Sai Duraisingham; Frederick H Strobel; Nooruddin Khan; Quinlyn A Soltow; Dean P Jones; Bali Pulendran
Journal:  PLoS Comput Biol       Date:  2013-07-04       Impact factor: 4.475

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  21 in total

1.  Perspectives on Data Analysis in Metabolomics: Points of Agreement and Disagreement from the 2018 ASMS Fall Workshop.

Authors:  Erin S Baker; Gary J Patti
Journal:  J Am Soc Mass Spectrom       Date:  2019-08-22       Impact factor: 3.109

2.  Revealing disease-associated pathways by network integration of untargeted metabolomics.

Authors:  Leila Pirhaji; Pamela Milani; Mathias Leidl; Timothy Curran; Julian Avila-Pacheco; Clary B Clish; Forest M White; Alan Saghatelian; Ernest Fraenkel
Journal:  Nat Methods       Date:  2016-08-01       Impact factor: 28.547

Review 3.  Chemical Discovery in the Era of Metabolomics.

Authors:  Miriam Sindelar; Gary J Patti
Journal:  J Am Chem Soc       Date:  2020-05-11       Impact factor: 15.419

4.  Urinary Metabolites Diagnostic and Prognostic of Intrahepatic Cholangiocarcinoma.

Authors:  Christopher M Diehl; Amelia L Parker; Majda Haznadar; Kristopher W Krausz; Elise D Bowman; Siritida Rabibhadana; Marshonna Forgues; Vajarabhongsa Bhudhisawasdi; Frank J Gonzalez; Chulabhorn Mahidol; Anuradha Budhu; Xin W Wang; Mathuros Ruchirawat; Curtis C Harris
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-07-29       Impact factor: 4.254

5.  BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics.

Authors:  Dmitry M Avtonomov; Alexander Raskind; Alexey I Nesvizhskii
Journal:  J Proteome Res       Date:  2016-06-28       Impact factor: 4.466

Review 6.  Metabolomics applied to the pancreatic islet.

Authors:  Jessica R Gooding; Mette V Jensen; Christopher B Newgard
Journal:  Arch Biochem Biophys       Date:  2015-06-25       Impact factor: 4.013

7.  A Landscape of Metabolic Variation across Tumor Types.

Authors:  Ed Reznik; Augustin Luna; Bülent Arman Aksoy; Eric Minwei Liu; Konnor La; Irina Ostrovnaya; Chad J Creighton; A Ari Hakimi; Chris Sander
Journal:  Cell Syst       Date:  2018-01-27       Impact factor: 10.304

Review 8.  Computational Metabolomics: A Framework for the Million Metabolome.

Authors:  Karan Uppal; Douglas I Walker; Ken Liu; Shuzhao Li; Young-Mi Go; Dean P Jones
Journal:  Chem Res Toxicol       Date:  2016-10-12       Impact factor: 3.739

9.  A Protocol for Untargeted Metabolomic Analysis: From Sample Preparation to Data Processing.

Authors:  Amanda L Souza; Gary J Patti
Journal:  Methods Mol Biol       Date:  2021

10.  MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

Authors:  Pietro Franceschi; Roman Mylonas; Nir Shahaf; Matthias Scholz; Panagiotis Arapitsas; Domenico Masuero; Georg Weingart; Silvia Carlin; Urska Vrhovsek; Fulvio Mattivi; Ron Wehrens
Journal:  Front Bioeng Biotechnol       Date:  2014-12-16
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