Literature DB >> 15389842

Mass spectrometry in metabolome analysis.

Silas G Villas-Bôas1, Sandrine Mas, Mats Akesson, Jørn Smedsgaard, Jens Nielsen.   

Abstract

In the post-genomic era, increasing efforts have been made to describe the relationship between the genome and the phenotype in cells and organisms. It has become clear that even a complete understanding of the state of the genes, messages, and proteins in a living system does not reveal its phenotype. Therefore, researchers have started to study the metabolome (or the metabolic complement of functional genomics). Within this context, mass spectrometry (MS) has increasingly occupied a central position in the methodologies developed for determination of the metabolic state. This review is mainly focused on the status of MS in the metabolome field, trying to direct the reader to the main approaches for analysis of metabolites, reviewing basic methodologies in sample preparation, and the most recent MS techniques introduced. Apart from the description of the different methods, this review will try to state a general comparison between the several different techniques that involve MS and metabolite analysis, and will highlight their limitations and preferred applicability.

Mesh:

Year:  2005        PMID: 15389842     DOI: 10.1002/mas.20032

Source DB:  PubMed          Journal:  Mass Spectrom Rev        ISSN: 0277-7037            Impact factor:   10.946


  103 in total

1.  PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools.

Authors:  Sean O'Callaghan; David P De Souza; Andrew Isaac; Qiao Wang; Luke Hodkinson; Moshe Olshansky; Tim Erwin; Bill Appelbe; Dedreia L Tull; Ute Roessner; Antony Bacic; Malcolm J McConville; Vladimir A Likić
Journal:  BMC Bioinformatics       Date:  2012-05-30       Impact factor: 3.169

Review 2.  Metabolic engineering in the -omics era: elucidating and modulating regulatory networks.

Authors:  Goutham N Vemuri; Aristos A Aristidou
Journal:  Microbiol Mol Biol Rev       Date:  2005-06       Impact factor: 11.056

3.  Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum.

Authors:  Anders Nordström; Grace O'Maille; Chuan Qin; Gary Siuzdak
Journal:  Anal Chem       Date:  2006-05-15       Impact factor: 6.986

Review 4.  Expression profiling in granulomatous lung disease.

Authors:  Edward S Chen; David R Moller
Journal:  Proc Am Thorac Soc       Date:  2007-01

5.  Selective metabolite and peptide capture/mass detection using fluorous affinity tags.

Authors:  Eden P Go; Wilasinee Uritboonthai; Junefredo V Apon; Sunia A Trauger; Anders Nordstrom; Grace O'Maille; Scott M Brittain; Eric C Peters; Gary Siuzdak
Journal:  J Proteome Res       Date:  2007-03-08       Impact factor: 4.466

Review 6.  Database resources in metabolomics: an overview.

Authors:  Eden P Go
Journal:  J Neuroimmune Pharmacol       Date:  2009-05-07       Impact factor: 4.147

7.  Efficient denoising algorithms for large experimental datasets and their applications in Fourier transform ion cyclotron resonance mass spectrometry.

Authors:  Lionel Chiron; Maria A van Agthoven; Bruno Kieffer; Christian Rolando; Marc-André Delsuc
Journal:  Proc Natl Acad Sci U S A       Date:  2014-01-03       Impact factor: 11.205

Review 8.  Emerging applications of metabolomics in studying chemopreventive phytochemicals.

Authors:  Lei Wang; Chi Chen
Journal:  AAPS J       Date:  2013-06-22       Impact factor: 4.009

Review 9.  Metabolomic signature of brain cancer.

Authors:  Renu Pandey; Laura Caflisch; Alessia Lodi; Andrew J Brenner; Stefano Tiziani
Journal:  Mol Carcinog       Date:  2017-07-17       Impact factor: 4.784

10.  Phosphonium labeling for increasing metabolomic coverage of neutral lipids using electrospray ionization mass spectrometry.

Authors:  Hin-Koon Woo; Eden P Go; Linh Hoang; Sunia A Trauger; Benjamin Bowen; Gary Siuzdak; Trent R Northen
Journal:  Rapid Commun Mass Spectrom       Date:  2009-06       Impact factor: 2.419

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